papers.yaml

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# This YAML file contains information about all the papers published by the Chodera lab in human- and machine-readable format
#
# Publications can be viewed at multiple sources:
#
# Chodera lab webpage : http://www.choderalab.org/publications/
#   Note that subsequent pages may need to use this URL http://www.choderalab.org/publications/?page=2
#   where subsequent pages are ?page=3 and so on
#
# Google Scholar : https://scholar.google.com/citations?hl=en&user=nnEg7_8AAAAJ&view_op=list_works&authuser=2&sortby=pubdate

#### Added 2025-01-10

  # Title should have only initial letter capitalized
  - title: "Fine-tuning molecular mechanics force fields to free energies"
    authors: # Use same name in publication
    - Dominic Rufa
    - Joshua Fass
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/content/10.1101/2025.01.06.631610v1
      date: 2025-01-08
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Code used in this study
        short: GitHub
        description: Timemachine fork and scripts used in this study
        url: https://github.com/choderalab/timemachine_hydration_paper
    # Thumbnail image URL
    thumbnail: fine-tuning-hydration-free-energies
    # Two newlines are needed after the description
    funding:
    - id: NIH R35 GM152017
      rationale: >
        This work demonstrates how to fine-tune a molecular mechanics force field using experimental free energy measurements
        to consistently improve performance on related free energy tasks. This work introduces a novel one-shot fine-tuning approach 
        that enbales rapid fine-tuning of the electrostatics model for the espaloma graph convolutional molecular mechanics force field 
        without the need for additional simulation. While we demonstrate this approach in the context of hydration free energies because 
        of the ease of ensuring these calculations are converged to high precision, this approach can be applied to well-converged 
        free energy calculations of other properties such as binding free energies. To our knowledge, this is the first illustration
        of the fine-tuning of a foundation molecular mechanics simulation model using experimental free energy measurements to produce a
        fine-tuned model with improved accuracy in predicting experimental free energies tasks of interest.
    - id: NIH R01 GM132386
      rationale: >
        This work demonstrates how to fine-tune a molecular mechanics force field using experimental free energy measurements
        to consistently improve performance on related free energy tasks. This work introduces a novel one-shot fine-tuning approach 
        that enbales rapid fine-tuning of the electrostatics model for the espaloma graph convolutional molecular mechanics force field 
        without the need for additional simulation. While we demonstrate this approach in the context of hydration free energies because 
        of the ease of ensuring these calculations are converged to high precision, this approach can be applied to well-converged 
        free energy calculations of other properties such as binding free energies. To our knowledge, this is the first illustration
        of the fine-tuning of a foundation molecular mechanics simulation model using experimental free energy measurements to produce a
        fine-tuned model with improved accuracy in predicting experimental free energies tasks of interest.
    - id: NIH P30 CA008748
      rationale: >
        This work demonstrates how to fine-tune a molecular mechanics force field using experimental free energy measurements
        to consistently improve performance on related free energy tasks. This work introduces a novel one-shot fine-tuning approach 
        that enbales rapid fine-tuning of the electrostatics model for the espaloma graph convolutional molecular mechanics force field 
        without the need for additional simulation. While we demonstrate this approach in the context of hydration free energies because 
        of the ease of ensuring these calculations are converged to high precision, this approach can be applied to well-converged 
        free energy calculations of other properties such as binding free energies. To our knowledge, this is the first illustration
        of the fine-tuning of a foundation molecular mechanics simulation model using experimental free energy measurements to produce a
        fine-tuned model with improved accuracy in predicting experimental free energies tasks of interest.

#### Added 2024-12-24

  # Title should have only initial letter capitalized
  - title: "EspalomaCharge: Machine learning-enabled ultrafast partial charge assignment"
    authors: # Use same name in publication
    - Yuanqing Wang
    - Iván Pulido
    - Kenichiro Takaba
    - Benjamin Kaminow
    - Jenke Scheen
    - Lily Wang
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Yuanqing Wang
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://arxiv.org/abs/2302.06758
      date: 2023-02-16
    published:
      doi: https://doi.org/10.1021/acs.jpca.4c01287
      journal: Journal of Chemical Physics
      volume: 128
      page: 4160 # just first page
      year: 2024
      dates:
        submitted: 2024-02-27
        accepted: 2024-04-17
        published: 2024-05-08
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Code used in this study
        short: GitHub
        description: The EspalomaCharge fast graph convolutional charge model, useful as a drop-in replacement for AM1-BCC
        url: https://github.com/choderalab/espaloma_charge
    # Thumbnail image URL
    thumbnail: espaloma-charge
    # Two newlines are needed after the description
    funding:
    - id: NIH R01 GM132386
      rationale: >
        We developed EspalomaCharge, a graph convolutional charge model, as a drop-in replacement for generating AM1-BCC ELF10 charges.
        The approach produces scalable, self-consistent charges and is orders of magnitude faster than AM1-BCC while providing lower error
        than differences between standard AM1-BCC implementations.
    - id: NIH R01 GM140090
      rationale: >
        We developed EspalomaCharge, a graph convolutional charge model, as a drop-in replacement for generating AM1-BCC ELF10 charges.
        The approach produces scalable, self-consistent charges and is orders of magnitude faster than AM1-BCC while providing lower error
        than differences between standard AM1-BCC implementations.


  # Title should have only initial letter capitalized
  - title: "DrugGym: A testbed for the economics of autonomous drug discovery"
    authors: # Use same name in publication
    - Michael Retchin
    - Yuanqing Wang
    - Kenichiro Takaba
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/content/10.1101/2024.05.28.596296v1.abstract
      date: 2024-06-02
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Code used in this study
        short: GitHub
        description: DrugGym codebase and scripts used in this study
        url: https://github.com/choderalab/drug-gym/
    # Thumbnail image URL
    thumbnail: drug-gym
    # Two newlines are needed after the description
    funding:
    - id: NIH R35 GM152017
      rationale: >
        We present DrugGym, a sandbox for exploring reinforcement learning strategies and evaluating the economics of decisionmaking strategies and predictive models
        on small molecule discovery. We use this tool to quantify the value of predictive model accuracy on hit-to-lead programs.
    - id: NIH P30 CA008748
      rationale: >
        We present DrugGym, a sandbox for exploring reinforcement learning strategies and evaluating the economics of decisionmaking strategies and predictive models
        on small molecule discovery. We use this tool to quantify the value of predictive model accuracy on hit-to-lead programs.


  # Title should have only initial letter capitalized
  - title: "Enhancing protein–ligand binding affinity predictions using neural network potentials"
    authors: # Use same name in publication
    - Francesc Sabanés Zariquiey
    - Raimondas Galvelis
    - Emilio Gallicchio
    - John D. Chodera
    - Thomas E. Markland
    - Gianni de Fabritiis
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Gianni de Fabritiis
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://arxiv.org/abs/2401.16062
      date: 2024-02-14
    published:
      doi: https://doi.org/10.1021/acs.jcim.3c02031
      journal: Journal of Chemical Information and Modeling
      volume: 64
      page: 1481 # just first page
      year: 2024
      dates:
        submitted: 2023-12-18
        accepted: 2024-02-14
        published: 2024-02-20
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Code used in this study
        short: GitHub
        description: The calculated free energy values and ligand and proteinstructures, as well as preparation scripts
        url: https://github.com/compsciencelab/ATM_benchmark/tree/main/ATM_With_NNPs
    # Thumbnail image URL
    thumbnail: de-fabritiis-nnp-free-energy
    # Two newlines are needed after the description
    funding:
    - id: NIH R01 GM140090
      rationale: >
        We show that hybrid neural network / molecular mechanics potentials can significantly improve accuracy over molecular
        mechanics potentials alone in predicting protein-ligand binding affinities.
    - id: NIH P30 CA008748
      rationale: >
        We show that hybrid neural network / molecular mechanics potentials can significantly improve accuracy over molecular
        mechanics potentials alone in predicting protein-ligand binding affinities.


  # Title should have only initial letter capitalized
  - title: "Prospective evaluation of structure-based simulations reveal their ability to predict the impact of kinase mutations on inhibitor binding"
    authors: # Use same name in publication
    - Sukrit Singh
    - Vytautas Gapsys
    - Matteo Aldeghi
    - David Schaller
    - Aziz M Rangwala
    - Jessica B White
    - Joseph P Bluck
    - Jenke Scheen
    - William G Glass
    - Jiaye Guo
    - Sikander Hayat
    - Bert L de Groot
    - Andrea Volkamer
    - Clara D Christ
    - Markus A Seeliger
    - John D Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Sukrit Singh
    - John D Chodera
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/content/10.1101/2024.11.15.623861v1
      date: 2024-11-17
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Code used in this study
        short: GitHub
        description: Generated structures and scripts for structure preparation are available on github 
        url: https://github.com/openkinome/study-abl-resistance
    # Thumbnail image URL
    thumbnail: prospective-kinase-mutations
    # Two newlines are needed after the description
    funding:
    - id: NIH R35 GM152017
      rationale: >
        We show that alchemical free energy calculations have the potential to prospectively predict the impact of clinical kinase mutations on targeted kinase inhibitor binding.
        Using a new NanoBRET approach to quantifying kinase inhibitor binding affinities on clinical kinase mutations observed in patients at MSKCC, we evaluated multiple
        strategies for alchemical free energy calculations---along with fast structure-based ROSETTA and machine learning methods---to assess their utility in predicting the
        impact of clinical kinase mutations on inhihbitor affinity for imatinib and dasatinib in a prospective fashion. We find that alchemical free energy calculations show
        significant promise in prospectively predicting resistance or sensitive mutations for kinase inhibitor therapy.
    - id: NIH P30 CA008748
      rationale: >
        We show that alchemical free energy calculations have the potential to prospectively predict the impact of clinical kinase mutations on targeted kinase inhibitor binding.
        Using a new NanoBRET approach to quantifying kinase inhibitor binding affinities on clinical kinase mutations observed in patients at MSKCC, we evaluated multiple
        strategies for alchemical free energy calculations---along with fast structure-based ROSETTA and machine learning methods---to assess their utility in predicting the
        impact of clinical kinase mutations on inhihbitor affinity for imatinib and dasatinib in a prospective fashion. We find that alchemical free energy calculations show
        significant promise in prospectively predicting resistance or sensitive mutations for kinase inhibitor therapy.

  # Title should have only initial letter capitalized
  - title: "Benchmarking Cross-Docking Strategies in Kinase Drug Discovery"
    authors: # Use same name in publication
    - David A. Schaller
    - Clara D. Christ
    - John D Chodera
    - Andrea Volkamer
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D Chodera
    - Andrea Volkamer
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://doi.org/10.1101/2023.09.11.557138
      date: 2023-09-14
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Code used in this study
        short: GitHub
        description: Scripts and modules used for docking benchmark
        url: https://github.com/openkinome/kinase-docking-benchmark
    published:
      doi: https://doi.org/10.1021/acs.jcim.4c00905
      journal: Journal of Chemical Information and Modeling
      volume: 64
      page: 1481 # just first page
      year: 2024
      dates:
        submitted: 2024-05-24
        accepted: 2024-11-04
        published: 2024-11-19
    # Thumbnail image URL
    thumbnail: kinase-docking-benchmark
    # Two newlines are needed after the description
    funding:
    - id: NIH R01 GM121505
      rationale: >
        We show that alchemical free energy calculations have the potential to prospectively predict the impact of clinical kinase mutations on targeted kinase inhibitor binding.
    - id: NIH P30 CA008748
      rationale: >
        We show that alchemical free energy calculations have the potential to prospectively predict the impact of clinical kinase mutations on targeted kinase inhibitor binding.


  # Title should have only initial letter capitalized
  - title: "Nutmeg and SPICE: Models and data for biomolecular machine learning"
    authors: # Use same name in publication
    - Peter Eastman
    - Benjamin P. Pritchard
    - John D. Chodera
    - Thomas E. Markland
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Peter Eastman
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://arxiv.org/abs/2406.13112
      date: 2023-09-14
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Code used in this study
        short: GitHub
        description: The SPICE quantum chemical dataset and scripts used to generate the dataset
        url: https://github.com/openmm/spice-dataset
    published:
      doi: https://doi.org/10.1021/acs.jctc.4c00794
      journal: Journal of Chemical Theory and Computation
      volume: 20
      page: 8583 # just first page
      year: 2024
      dates:
        submitted: 2024-06-18
        accepted: 2024-09-16
        published: 2024-09-25
    # Thumbnail image URL
    thumbnail: nutmeg-spice
    # Two newlines are needed after the description
    funding:
    - id: NIH R35 GM152017
      rationale: >
        We present a significant expansion of the SPICE dataset, a large-scale quantum chemical dataset for training machine learning potentials, and show how it can be used to build extremely accurate machine learning potentials.
        This dataset will provide a useful foundation for building highly accurate molecular mechanics and machine learning potentials for tasks such as computing protein:ligand binding free energy calculations.
    - id: NIH P30 CA008748
      rationale: >
        We present a significant expansion of the SPICE dataset, a large-scale quantum chemical dataset for training machine learning potentials, and show how it can be used to build extremely accurate machine learning potentials.
        This dataset will provide a useful foundation for building highly accurate molecular mechanics and machine learning potentials for tasks such as computing protein:ligand binding free energy calculations.


  # Title should have only initial letter capitalized
  - title: "Lessons learned during the journey of data: from experiment to model for predicting kinase affinity, selectivity, polypharmacology, and resistance"
    authors: # Use same name in publication
    - Raquel López-Ríos de Castro
    - Jaime Rodríguez-Guerra Pedregal
    - David Schaller
    - Talia B. Kimber
    - Corey Taylor
    - Jessica B. White
    - Michael Backenköhler
    - Alexander Payne
    - Ben Kaminow
    - Iván Pulido
    - Sukrit Singh
    - Paula Linh Kramer
    - Guillermo Pérez-Hernández
    - Andrea Volkamer
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Andrea Volkamer
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/content/10.1101/2024.09.10.612176v1
      date: 2024-09-10
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Code used in this study
        short: GitHub
        description: KinoML machine learning code package
        url: https://github.com/openkinome/kinoml
      - action: Machine learning ready kinase data
        short: GitHub
        description: KinoData machine learning ready dataset of kinase:ligand affinities
        url: https://github.com/openkinome/kinodata
    # Thumbnail image URL
    thumbnail: kinoml
    # Two newlines are needed after the description
    funding:
    - id: NIH R01 GM121505
      rationale: >
        This best practices paper describes considerations relevant to the use of experimental datasets in structure-based machine learning, using kinase:small molecule interactions as a model system.
    - id: NIH P30 CA008748
      rationale: >
        This best practices paper describes considerations relevant to the use of experimental datasets in structure-based machine learning, using kinase:small molecule interactions as a model system.


  # Title should have only initial letter capitalized
  - title: "Machine-learned molecular mechanics force fields from large-scale quantum chemical data"
    authors: # Use same name in publication
    - Kenichiro Takaba
    - Anika J Friedman
    - Chapin E Cavender
    - Pavan Kumar Behara
    - Iván Pulido
    - Michael M Henry
    - Hugo MacDermott-Opeskin
    - Christopher R Iacovella
    - Arnav M Nagle
    - Alexander Matthew Payne
    - Michael R Shirts
    - David L Mobley
    - John D Chodera
    - Yuanqing Wang
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Kenichiro Takaba
    - John D Chodera
    - Yuanqing Wang
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://arxiv.org/abs/2307.07085
      date: 2023-12-08
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: https://doi.org/10.1039/D4SC00690A
      journal: Chemical Science
      volume: 15
      page: 12861 # just first page
      year: 2024
      dates:
        submitted: 2024-01-29
        accepted: 2024-06-17
        published: 2024-06-26   
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Code used in this study
        short: GitHub
        description: Python code associated with this manuscript        
        url: https://github.com/choderalab/espaloma-0.3.0-manuscript
    # Thumbnail image URL
    thumbnail: espaloma-0.3
    # Two newlines are needed after the description
    funding:
    - id: NIH R01 GM132386
      rationale: >
        We present a new machine-learned molecular mechanics force field, espaloma, that is trained on a large-scale quantum chemical dataset and show that it outperforms traditional force fields in predicting quantum mechanical properties.
    - id: NIH R01 GM121505
      rationale: >
        We present a new machine-learned molecular mechanics force field, espaloma, that is trained on a large-scale quantum chemical dataset and show that it outperforms traditional force fields in predicting quantum mechanical properties.
    - id: NIH P30 CA008748
      rationale: >
        We present a new machine-learned molecular mechanics force field, espaloma, that is trained on a large-scale quantum chemical dataset and show that it outperforms traditional force fields in predicting quantum mechanical properties.


  # Title should have only initial letter capitalized
  - title: "OpenMM 8: molecular dynamics simulation with machine learning potentials"
    authors: # Use same name in publication
    - Peter Eastman
    - Raimondas Galvelis
    - Raúl P Peláez
    - Charlles RA Abreu
    - Stephen E Farr
    - Emilio Gallicchio
    - Anton Gorenko
    - Michael M Henry
    - Frank Hu
    - Jing Huang
    - Andreas Krämer
    - Julien Michel
    - Joshua A Mitchell
    - Vijay S Pande
    - João PGLM Rodrigues
    - Jaime Rodriguez-Guerra
    - Andrew C Simmonett
    - Sukrit Singh
    - Jason Swails
    - Philip Turner
    - Yuanqing Wang
    - Ivy Zhang
    - John D Chodera
    - Gianni De Fabritiis
    - Thomas E Markland
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Peter Eastman
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://arxiv.org/abs/2310.03121
      date: 2023-11-29
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: https://doi.org/10.1021/acs.jpcb.3c06662
      journal: Journal of Physical Chemistry B
      volume: 128
      page: 109 # just first page
      year: 2023
      dates:
        submitted: 2023-10-06
        accepted: 2023-12-06
        published: 2023-12-28
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: OpenMM 8 code
        short: GitHub
        description: OpenMM 8 code
        url: http://openmm.org
    # Thumbnail image URL
    thumbnail: openmm-logo
    # Two newlines are needed after the description
    funding:
    - id: NIH R01 GM140090
      rationale: >
        We present OpenMM 8, which includes GPU-accelerated support for simulating hybrid ML/MM systems that use machine learning (ML) potentials to achieve high accuracy with minimal loss in speed.
    - id: NIH P30 CA008748
      rationale: >
        We present OpenMM 8, which includes GPU-accelerated support for simulating hybrid ML/MM systems that use machine learning (ML) potentials to achieve high accuracy with minimal loss in speed.


  ##############################################

  # Title should have only initial letter capitalized
  - title: MEN1 mutations mediate clinical resistance to Menin inhibition
    authors: # Use same name in publication
    - Florian Perner
    - Eytan Stein
    - Sukrit Singh
    - Daniela Wenge
    - Athina Apazidis
    - Homa Rahnamoun
    - Disha Anand
    - Jeonghyeon Kim
    - Christian Marinaccio
    - Charles Hatton
    - Yanhe Wen
    - David Schaller
    - Shoron Mowla
    - Wenbin Xiao
    - Holly Gamlen
    - Aaron Stonestrom
    - Sonali Persaud
    - Elizabeth Ener
    - Jevon Cutler
    - John Doench
    - Gerard McGeehan
    - Andrea Volkamer
    - Radosław Nowak
    - Eric Fischer
    - John D. Chodera
    - Ross Levine
    - Sheng Cai
    - Richard Stone
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Scott Armstrong
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: 
      journal: Nature
      volume: in press
      page:  # just first page
      year: 
      dates:
        submitted: 2022-03-07
        accepted: 2022-11-30
    # Add these other fields are optional; fill in as much information as is available
    # Thumbnail image URL
    thumbnail: menin-mutations
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download simulation scripts
        short: GitHub
        description: Scripts for structure preparation, docking, and simulation of MEN1 mutants interacting with inhibitors
        url: https://github.com/choderalab/men1
      - action: Download the datasets
        short: OSF
        description: Data from free energy calculations, Folding@home trajectories, and Markov state models of MEN1 mutants
        url: https://osf.io/uge5j/
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
      rationale: >
        This work reports the use of computational methods developed for predicting the impact of clinical mutations
        in kinases on therapeutic response to another target of cancer therapy, the chromatin adapter protein Menin.
        To understand observed clinical resistance mutations that arose in a phase I clinical trial in response to 
        therapy with the Menin inhibitor revumineb, we probe the biophysical origin of the emergence of resistance to therapy.
    - id: NIH R01 GM121505
      rationale: >
        This work reports the use of computational methods developed for predicting the impact of clinical mutations
        in kinases on therapeutic response to another target of cancer therapy, the chromatin adapter protein Menin.
        To understand observed clinical resistance mutations that arose in a phase I clinical trial in response to 
        therapy with the Menin inhibitor revumineb, we probe the biophysical origin of the emergence of resistance to therapy.


  # Title should have only initial letter capitalized
  - title: "Death by a thousand cuts---combining kinase inhibitors for selective target inhibition and rational polypharmacology"
    authors: # Use same name in publication
    - Ian R. Outhwaite
    - Sukrit Singh
    - Benedict-Tilman Berger
    - Stefan Knapp
    - John D. Chodera
    - Markus A. Seeliger
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Markus A. Seeliger
    # Add these other fields are optional; fill in as much information as is available
    #preprint:
    #  url: https://www.biorxiv.org/content/10.1101/2021.08.24.457513v1.abstract
    #  date: 2021-08-26
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Code, datasets, and results used in this study
        short: GitHub
        description: Multi-inhibitor, multi-target (MMS) methodology code and data for designing kinase inhibitor mixtures to achieve high selectivity
        url: https://github.com/iouthwaite/inhibitor_combinations
    # Thumbnail image URL
    thumbnail: inhibitor-combinations
    # Two newlines are needed after the description
    funding:
    - id: NIH R01 GM121505
      rationale: >
        This work reports a new paradigm and approach for achieving selective kinase inhibition through use of combinations of
        kinase inhibitors with imperfect selectivities in a manner that minimizes off-target inhibition while maximizing on-target
        potency. The proposed method is validated with experimental data using NanoBRET measurements of kinase inhibition in cells.

  # Title should have only initial letter capitalized
  - title: "Development and benchmarking of Open Force Field 2.0.0---the Sage small molecule force field"
    authors: # Use same name in publication
    - Simon Boothroyd
    - Pavan Kumar Behara
    - Owen C. Madin
    - David F. Hahn
    - Hyesu Jang
    - Vytautas Gapsys
    - Jeffrey R. Wagner
    - Joshua T. Horton
    - David L. Dotson
    - Matthew W. Thompson
    - Jessica Maat
    - Trevor Gokey
    - Lee-Ping Wang
    - Daniel J. Cole
    - Michael K. Gilson
    - John D. Chodera
    - Christopher I. Bayly
    - Michael R. Shirts
    - David L. Mobley
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Michael K. Gilson
    - John D. Chodera
    - Michael R. Shirts
    - David L. Mobley
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://chemrxiv.org/engage/chemrxiv/article-details/637938cbe70b0a110aa33b8b
      date: 2022-11-21
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download the code to reproduce training
        short: GitHub
        description: Code and data for training the OpenFF 2.0.0 ("Sage") small molecule force field
        url: https://github.com/openforcefield/openff-sage
      - action: OpenFF 2.0.0 ("Sage") force field parameters in SMIRNOFF format
        short: GitHub
        description: The OpenFF 2.0.0 ("Sage") small molecule force field
        url: https://github.com/openforcefield/openff-forcefields/releases/tag/2.0.0
    # Thumbnail image URL
    thumbnail: openff-2.0.0
    # Two newlines are needed after the description
    funding:
    - id: NIH R01 GM132386
      rationale: >
        This work describes an improved molecular mechanics force field for organic matter that is fit to
        both quantum chemical and experimental solution phase data. It represents a considerable step toward
        a general force field capable of simulating heterogeneous biomolecular systems.
    - id: NSF CHE-1738975
      rationale: >
        This work describes the automated fitting of a molecular mechanics force field fit to
        both quantum chemical and experimental solution phase data. It represents a considerable step toward
        a general force field capable of simulating heterogeneous biomolecular systems.


  # Title should have only initial letter capitalized
  - title: "Open Force Field BespokeFit: Automating bespoke torsion parametrization at scale"
    authors: # Use same name in publication
    - Joshua T Horton
    - Simon Boothroyd
    - Jeffrey Wagner
    - Joshua A Mitchell
    - Trevor Gokey
    - David L Dotson
    - Pavan Kumar Behara
    - Venkata Krishnan Ramaswamy
    - Mark Mackey
    - John D Chodera
    - Jamshed Anwar
    - David L Mobley
    - Daniel J Cole
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Daniel J Cole
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://chemrxiv.org/engage/chemrxiv/article-details/631a10083940c20533f81566
      date: 2022-09-09
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Code to reproduce training and results
        short: GitHub
        description: OpenFF BespokeFit source code and installation instructions
        url: https://github.com/openforcefield/openff-bespokefit
      - action: Read the BespokeFit documentation
        short: Docs
        description: OpenFF BespokeFit documentation
        url: https://docs.openforcefield.org/projects/bespokefit
      - action: Download the data from the paper
        short: Data
        description: Raw data and analysis notebooks for the BespokeFit paper
        url: https://zenodo.org/record/7062336
    # Thumbnail image URL
    thumbnail: bespokefit
    # Two newlines are needed after the description
    funding:
    - id: NIH R01 GM132386
      rationale: >
        This work describes a methodology and generally useful tool for generating high-quality tailored parameters for specific
        small molecules via quantum chemical or machine learning potentials trained with quantum chemical data.

  # Title should have only initial letter capitalized
  - title: "NNP/MM: Fast molecular dynamics simulations with machine learning potentials and molecular mechanics"
    authors: # Use same name in publication
    - Raimondas Galvelis
    - Alejandro Varela-Rial
    - Stefan Doerr
    - Roberto Fino
    - Peter Eastman
    - Thomas E. Markland
    - John D. Chodera
    - Gianni De Fabritiis
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Gianni De Fabritiis
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://arxiv.org/abs/2201.08110
      date: 2022-01-20
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download the OpenMM pytorch plugin
        short: GitHub
        description: Source code for the OpenMM pytorch plugin
        url: https://github.com/openmm/openmm-torch
      - action: Download the NNPOps GPU-accelerated ML potential library
        short: GitHub
        description: Source code for the NNPOps GPU-accelerated ML potential library
        url: https://github.com/openmm/nnpops
    # Thumbnail image URL
    thumbnail: openmm
    # Two newlines are needed after the description
    funding:
    - id: NIH R01 GM140090
      rationale: >
        A major objective of this grant is to develop highly optimized, easy-to-use functionality for deploying machine learning
        (ML) potential energy functions within the OpenMM ecosystem. This paper demonstrates how we have achieved this with a
        fast, conda-installable plugin architecture that allows users to simulate hybrid ML/MM biomolecular systems with
        unprecedented performance.
    description: >
      We present the GPU-accelerated NNPOps library for accelerating hybrid machine learning / molecular mechanics (ML/MM)
      molecular simulations within OpenMM, and demonstrate how protein:ligand ML/MM simulations with the ANI ML potential 
      used to treat the ligand with high accuracy can reach within 5x of GPU-accelerated pure MM simulation speeds.

  # Title should have only initial letter capitalized
  - title: "SPICE, a dataset of drug-like molecules and peptides for training machine learning potentials"
    authors: # Use same name in publication
    - Peter Eastman
    - Pavan Kumar Behara
    - David L. Dotson
    - Raimondas Galvelis
    - John E. Herr
    - Josh T. Horton
    - Yuezhi Mao
    - John D. Chodera
    - Benjamin P. Pritchard
    - Yuanqing Wang
    - Gianni De Fabritiis
    - Thomas E. Markland
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Peter Eastman
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://arxiv.org/abs/2209.10702
      date: 2022-11-23
    published:
      doi: https://doi.org/10.1038/s41597-022-01882-6
      journal: Scientific Data
      volume: 10
      page: 11 # just first page
      year: 2023
      dates:         
        received: 2022-10-05
        accepted: 2022-12-01
        published: 2023-01-04
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download the dataset
        short: GitHub release
        description: SPICE quantum chemical dataset
        url: https://github.com/openmm/spice-dataset/releases/tag/1.1.2
      - action: Download the dataset generation code
        short: GitHub
        description: Source code for curating and generating the SPICE quantum chemical dataset
        url: https://github.com/openmm/spice-dataset
      - action: Download machine learning potential models
        short: Models
        description: Equivariant Transformer machine learning potential energy models built from the SPICE quantum chemical dataset
        url: https://github.com/openmm/spice-models
    # Thumbnail image URL
    thumbnail: spice-dataset
    # Two newlines are needed after the description
    funding:
    - id: NIH R01 GM132386
      rationale: >
        To remedy the lack of large, open quantum chemical datasets for training accurate general machine learning 
        potentials and molecular mechanics force fields for druglike small molecules and biomolecules, we produced 
        the open SPICE dataset, and show how it can be used to build extremely accurate machine learning potentials.
    - id: NIH R01 GM140090
      rationale: >
        To remedy the lack of large, open quantum chemical datasets for training accurate general machine learning 
        potentials for druglike small molecules and biomolecules, we produced the open SPICE dataset, and show how it 
        can be used to build extremely accurate machine learning potentials.

  # Title should have only initial letter capitalized
  - title: "Improving force field accuracy by training against condensed phase mixture properties"
    authors: # Use same name in publication
    - Simon Boothroyd
    - Owen C. Madin
    - David L. Mobley
    - Lee-Ping Wang
    - John D. Chodera
    - Michael R. Shirts
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Michael R. Shirts
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://chemrxiv.org/engage/chemrxiv/article-details/62587928ebac3a4647d513f7
      date: 2022-04-15
    published:
      doi: https://doi.org/10.1021/acs.jctc.1c01268
      journal: Journal of Chemical Theory and Computation
      volume: 18
      page: 3577 # just first page
      year: 2022
      dates:
        received: 2021-12-16
        published: 2022-05-09
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download the scripts to reproduce the study
        short: GitHub
        description: Scripts to assess and improve molecular mechanics force fields with condensed phase mixture simulations
        url: https://github.com/SimonBoothroyd/binary-mixture-publication
    # Thumbnail image URL
    thumbnail: openff-evaluator
    # Two newlines are needed after the description
    funding:
    - id: NIH R01 GM132386
      rationale: >
        We use a new automated framework for physical property evaluation and fitting to show how molecular mechanics 
        force fields can be systematically improved by fitting to condensed phase properties.


  # Title should have only initial letter capitalized
  - title: "The Open Force Field Evaluator: An automated, efficient, and scalable framework for the estimation of physical properties from molecular simulation"
    authors: # Use same name in publication
    - Simon Boothroyd
    - Lee-Ping Wang
    - David L Mobley
    - John D Chodera
    - Michael R Shirts
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Michael R. Shirts
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://chemrxiv.org/engage/chemrxiv/article-details/610ad0ed45805d722f80e4de
      date: 2021-08-05
    published:
      doi: https://doi.org/10.1021/acs.jctc.1c01111
      journal: Journal of Chemical Theory and Computation
      volume: 18
      page: 3566 # just first page
      year: 2022
      dates:
        received: 2021-11-04
        published: 2022-05-04
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download the OpenFF Evaluator
        short: GitHub
        description: Source code for the OpenFF Evaluator
        url: https://github.com/openforcefield/openff-evaluator
      - action: Read the documentation
        short: Docs
        description: Documentation for the OpenFF Evaluator
        url: https://docs.openforcefield.org/projects/evaluator/en/stable/
    # Thumbnail image URL
    thumbnail: openff-evaluator
    # Two newlines are needed after the description
    funding:
    - id: NIH R01 GM132386
      rationale: >
        We describe a new software framework for automated evaluation of physical properties for the benchmarking
        and optimization of small molecule force fields according to best practices.
    - id: NIH P30 CA008748
      rationale: >
        This work reports the development of a new software framework for automated evaluation of physical properties 
        for the benchmarking and optimization of small molecule force fields according to best practices. These tools
        can be used to systematically improvable predictions of protein:ligand interactions and binding affinities, enabling us
        to systematically increase the accuracy of our predictions of kinase:inhibitor affinities to accelerate the
        design of targeted cancer therapies.
        
  # Title should have only initial letter capitalized
  - title: "SAMPL7 protein-ligand challenge: A community-wide evaluation of computational methods against fragment screening and pose-prediction"
    authors: # Use same name in publication
    - Harold Grosjean
    - Mehtap Işık
    - Anthony Aimon
    - David Mobley
    - John Chodera
    - Frank von Delft
    - Philip C Biggin
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Philip C Biggin
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: https://doi.org/10.1007/s10822-022-00452-7
      journal: Journal of Computer Aided Molecular Design
      volume: 36
      page: 291 # just first page
      year: 2022
      dates:
        received: 2021-11-02
        accepted: 2022-03-22
        published: 2022-04-15
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download data
        short: GitHub
        description: All the experimental data, participant submissions, analysis, and codes for the SAMPL7 PHIPA protein-ligand challenge
        url: https://github.com/samplchallenges/SAMPL7/tree/master/protein_ligand
    # Thumbnail image URL
    thumbnail: sampl7-phip2
    # Two newlines are needed after the description
    funding:
    - id: NIH R01 GM124270
      rationale: >
        This work reports the results of a blind predictive modeling challenge assessing how well current generation computational
        chemistry approaches can predict the bound poses of small molecules against PHIPA, a target with no known chemical matter
        previously reported.
        
        
  # Title should have only initial letter capitalized
  - title: "CACHE (Critical Assessment of Computational Hit-finding Experiments): A public-private partnership benchmarking initiative to enable the development of computational methods for hit-finding"
    authors: # Use same name in publication
    - Harold Grosjean
    - Mehtap Işık
    - Anthony Aimon
    - David Mobley
    - John Chodera
    - Frank von Delft
    - Philip C Biggin
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Philip C Biggin
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://chemrxiv.org/engage/chemrxiv/article-details/6168ba62f718dfc39bdee0db
      date: 2021-10-22
    published:
      doi: https://doi.org/10.1038/s41570-022-00363-z
      journal: Nature Reviews Chemistry
      volume: 6
      page: 287 # just first page
      year: 2022
      dates:
        accepted: 2022-01-21
        published: 2022-02-15
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Visit the CACHE Challenges website
        short: Website
        description: The CACHE Challenges website
        url: https://cache-challenge.org/
    # Thumbnail image URL
    thumbnail: sampl7-phip2
    # Two newlines are needed after the description
    funding:
    - id: NIH R01 GM124270
      rationale: >
        We describe CACHE: A new public-private partnership that aims to transform computer-aided drug discovery 
        much the way that CASP transformed protein structure prediction into a reproducible, accurate engineering discipline.
        These blind predictive challenges will assess the accuracy of current generation machine learning and computational
        chemistry tools in identifying new hits for protein targets.

        
  # Title should have only initial letter capitalized
  - title: "Bayesian inference-driven model parameterization and model selection for 2CLJQ fluid models"
    authors: # Use same name in publication
    - Owen C. Madin
    - Simon Boothroyd
    - Richard A. Messerly
    - Josh Fass
    - John D. Chodera
    - Michael R. Shirts
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Michael R. Shirts
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://arxiv.org/abs/2105.07863
      date: 2021-09-13
    published:
      doi: https://doi.org/10.1021/acs.jcim.1c00829
      journal: Journal of Chemical Informatics and Modeling
      volume: 62
      page: 874 # just first page
      year: 2022
      dates:
        received: 2021-09-21
        published: 2022-02-07
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download code and data
        short: GitHub
        description: Data sets and code used to generate the results shown in this study
        url: https://github.com/SimonBoothroyd/bayesiantesting/tree/combined_run
    # Thumbnail image URL
    thumbnail: 2CLJQ
    # Two newlines are needed after the description
    funding:
    - id: NIH R01 GM132386
      rationale: >
        Here, we show how Bayesian inference can be used to automatically perform model selection and fit parameters for a molecular mechanics force field.


  # Title should have only initial letter capitalized
  - title: "GCN2 kinase activation by ATP-competitive kinase inhibitors"
    authors: # Use same name in publication
    - Colin P. Tang
    - Owen Clark
    - John R. Ferrarone
    - Carl Campos
    - Alshad S. Lalani
    - John D. Chodera
    - Andrew M. Intlekofer
    - Olivier Elemento
    - Ingo K. Mellinghoff
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Ingo K. Mellinghoff
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: https://doi.org/10.1038/s41589-021-00947-8
      journal: Nature Chemical Biology
      volume: 18
      page: 207 # just first page
      year: 2022
      dates:
        received: 2021-06-15
        accepted: 2021-10-28
        published: 2021-12-23
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download analysis scripts
        short: GitHub
        description: All scripts for downstream analysis of the CRISPR screen and RNA-seq data for assessing GCN2 kinase activation
        url: https://github.com/cot2005/Tang_et_al_2021
    # Thumbnail image URL
    thumbnail: gcn2-activation
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
      rationale: >
        We describe paradoxical activation of GCN2 kinase activity by the kinase inhibitor neratinib, 
        and propose a model for how inhibitor-induced dimerization might cause this unusual activity.
        This work helps us better understand the subtleties of how kinase inhibitors can modulate
        kinase conformational populations and how modulating these populations can impact kinase activity.
    - id: NIH R01 GM121505
      rationale: >
        We describe paradoxical activation of GCN2 kinase activity by the kinase inhibitor neratinib, 
        and propose a model for how inhibitor-induced dimerization might cause this unusual activity.
        This work helps us better understand the subtleties of how kinase inhibitors can modulate
        kinase conformational populations and how modulating these populations can impact kinase activity.


  # Title should have only initial letter capitalized
  - title: "INK4 Tumor Suppressor Proteins Mediate Resistance to CDK4/6 Kinase Inhibitors"
    authors: # Use same name in publication
    - Qing Li
    - Baishan Jiang
    - Jiaye Guo
    - Hong Shao
    - Isabella S. Del Priore
    - Qing Chang
    - Rei Kudo
    - Zhiqiang Li
    - Pedram Razavi
    - Bo Liu
    - Andrew S. Boghossian
    - Matthew G. Rees
    - Melissa M. Ronan
    - Jennifer A. Roth
    - Katherine A. Donovan
    - Marta Palafox
    - Jorge S. Reis-Filho
    - Elisa de Stanchina
    - Eric S. Fischer
    - Neal Rosen 
    - Violeta Serra 
    - Andrew Koff
    - John D. Chodera 
    - Nathanael S. Gray
    - Sarat Chandarlapaty
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Sarat Chandarlapaty
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: https://doi.org/10.1158/2159-8290.CD-20-1726
      journal: Cancer Discovery
      volume: 12
      page: 356 # just first page
      year: 2022
      dates:
        received: 2020-12-01
        accepted: 2021-09-15
        published: 2021-09-20
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download models and docking results
        short: GitHub
        description: Models and docking results for binding partners of human kinases (e.g. p27 for CDK4, p18 for CDK6) affect the binding of ATP, small-molecule kinase inhibitors (e.g. palbociclib), as well as proteolysis-targeting chimeras (PROTACs).
        url: https://github.com/choderalab/CDK_PROTAC
    # Thumbnail image URL
    thumbnail: ink4-cdk4
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
      rationale: >
        We demonstrate CDK6 causes drug resistance by binding INK4 proteins, 
        and develop bifunctional degraders conjugating palbociclib with E3 ligands to overcome this mechanism of resistance
        by exploiting advanced modeling of relevant conformations of CDK6.
    - id: NIH R01 GM121505
      rationale: >
        We demonstrate CDK6 causes drug resistance by binding INK4 proteins, 
        and develop bifunctional degraders conjugating palbociclib with E3 ligands to overcome this mechanism of resistance
        by exploiting advanced modeling of relevant conformations of CDK6.


  # Title should have only initial letter capitalized
  - title: "Capturing non-local through-bond effects in molecular mechanics force fields: II. Using fractional bond orders to fit torsion parameters"
    authors: # Use same name in publication
    - Chaya D. Stern
    - Jessica Maat
    - David L. Dotson
    - Christopher I. Bayly
    - Daniel G. A. Smith
    - David L. Mobley
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/content/10.1101/2022.01.17.476653v1.abstract
      date: 2022-01-18
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download kinase inhibitor dataset
        short: Kinase inhibitor dataset
        description: Scripts and data used to generate and analyze the kinase inhibitor dataset
        url: https://github.com/choderalab/fragmenter_data/tree/master/wbo-manuscript-figures/kinase_inhibitors_wbos
      - action: Download substituted phenyl dataset
        short: Substituted phenyl dataset
        description: Scripts and data used to generate and analyze the substituted phenyl dataset
        url: https://github.com/choderalab/fragmenter_data/tree/master/phenyl_benchmark
      - action: Download scripts used to generate figures
        short: GitHub
        description: Scripts used to generate figures for assessing non-local effects in molecular mechanics force fields via Wiberg bond order
        url: https://github.com/choderalab/fragmenter_data/tree/master/wbo-manuscript-figures
    # Thumbnail image URL
    thumbnail: biphenyl-wbo
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
      rationale: >
        We show how the Wiberg Bond Order (WBO) can be used to accurately interpolate torsional profiles for
        molecular mechanics force fields, which holts the potential for drastically reducing the complexity 
        of these force fields while increasing their ability to generalize and accurately treat complex 
        druglike molecules such as kinase inhibitors.
    - id: NIH R01 GM132386
      rationale: >
        We show how the Wiberg Bond Order (WBO) can be used to accurately interpolate torsional profiles for
        molecular mechanics force fields, which holts the potential for drastically reducing the complexity 
        of these force fields while increasing their ability to generalize and accurately treat complex 
        druglike molecules such as kinase inhibitors.
    - id: NIH R01 GM121505
      rationale: >
        We show how the Wiberg Bond Order (WBO) can be used to accurately interpolate torsional profiles for
        molecular mechanics force fields, which holts the potential for drastically reducing the complexity 
        of these force fields while increasing their ability to generalize and accurately treat complex 
        druglike molecules such as kinase inhibitors.
    - id: Open Force Field Consortium
      rationale: >
        We show how the Wiberg Bond Order (WBO) can be used to accurately interpolate torsional profiles for
        molecular mechanics force fields, which holts the potential for drastically reducing the complexity 
        of these force fields while increasing their ability to generalize and accurately treat complex 
        druglike molecules such as kinase inhibitors.
    description: >
      We show how the Wiberg Bond Order (WBO) can be used to accurately interpolate torsional profiles for
      molecular mechanics force fields, which holts the potential for drastically reducing the complexity 
      of these force fields while increasing their ability to generalize and accurately treat complex 
      druglike molecules such as kinase inhibitors.


  # Title should have only initial letter capitalized
  - title: "Teaching free energy calculations to learn from experimental data"
    authors: # Use same name in publication
    - Marcus Wieder
    - Josh Fass
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/content/10.1101/2021.08.24.457513v1.abstract
      date: 2021-08-26
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download source code
        short: GitHub
        description: neutromeratio
        url: https://github.com/choderalab/neutromeratio
      - action: Download data used in this study
        short: Zenodo
        description: data
        url: https://zenodo.org/record/5245934
    # Thumbnail image URL
    thumbnail: qml-explicit-free-energy
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
      rationale: >
        This work reports the development of a new generation of alchemical free energy calculations that can learn from 
        experimental free energy data collected for related molecules, such as a lead series under investigation, to produce
        systematically improvable predictions of protein:ligand interactions and binding affinities, enabling us
        to systematically increase the accuracy of our predictions of kinase:inhibitor affinities to accelerate the
        design of targeted cancer therapies.
    - id: NIH R01 GM121505
      rationale: >
        This work reports the development of a new generation of alchemical free energy calculations that can learn from 
        experimental free energy data collected for related molecules, such as a lead series under investigation, to produce
        systematically improvable predictions of protein:ligand interactions and binding affinities that will enable us
        to systematically increase the accuracy of our predictions of kinase:inhibitor affinities to accelerate the
        design of targeted kinase inhibitors.       
    - id: NIH R01 GM132386
      rationale: >
        This work describes a new strategy for systematically improving next-generation molecular mechanics potentials based on
        quantum chemical data by leveraging experimental measurements---including free energies---to produce substantially improved
        potential energy functions for biomolecular simulation. In this case, a quantum machine learning potential was used to simulate
        an entire solvated system, and alchemical free energy calculations were used to systematically improve prediction accuracy
        of tautomer ratios using a small amount of experimental free energy data.
    - id: NSF CHE 1738979
      rationale: >
        This work describes an automated approach to optimization of a fully machine learned force field that can be systematically
        improved using both quantum chemical data and experimental free energy data, an obligate first step to fully Bayesian force 
        field parameterization.



  # Title should have only initial letter capitalized
  - title: "The Open Force Field Evaluator: An automated, efficient, and scalable framework for the estimation of physical properties from molecular simulation"
    authors: # Use same name in publication
    - Simon Boothroyd
    - Lee-Ping Wang
    - David Mobley
    - John D. Chodera
    - Michael R. Shirts
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Michael R. Shirts
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://chemrxiv.org/engage/chemrxiv/article-details/610ad0ed45805d722f80e4de
      date: 2021-08-05
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download force field
        short: GitHub
        description: Open Force Field Evaluator
        url: https://github.com/openforcefield/openff-evaluator
    # Thumbnail image URL
    thumbnail: openff-evaluator
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
      rationale: >
        This work reports the development of a new generation of small molecule force fields that aim to deliver
        systematically improvable predictions of protein:ligand interactions and binding affinities, enabling us
        to systematically increase the accuracy of our predictions of kinase:inhibitor affinities to accelerate the
        design of targeted cancer therapies.
    - id: NIH R01 GM132386
      rationale: >
        This work is the first release of a new generation of biomolecular force fields funded by this effort,
        illustrating how our scalable infrastructure for force field parameterization can be applied to systematically
        expanded datasets.
    - id: NSF CHE 1738979
      rationale: >
        This work describes an automated approach to force field parameterization using a loss function formulation,
        which is the first step toward a fully Bayesian force field parameterization scheme.
    - id: Open Force Field Consortium        
    description: >
      We present a new, modern small molecule force field for molecular design from the Open Force Field Initiative,
      a large industry-academic collaboration that focuses on open science, open data, and modern open source infrastructure.


  # Title should have only initial letter capitalized
  - title: "Development and benchmarking of Open Force Field v1.0.0, the Parsley small molecule force field"
    authors: # Use same name in publication
    - Yudong Qiu
    - Daniel Smith
    - Simon Boothroyd
    - Hyesu Jang
    - Jeffrey Wagner
    - Caitlin C Bannan
    - Trevor Gokey
    - Victoria T. Lim
    - Chaya Stern
    - Andrea Rizzi
    - Xavier Lucas
    - Bryon Tjanaka
    - Michael R. Shirts
    - Michael Gilson
    - John D. Chodera
    - Christopher I. Bayly
    - David Mobley
    - Lee-Ping Wang
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Lee-Ping Wang
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://chemrxiv.org/engage/chemrxiv/article-details/60c7528bf96a0045df288276
      date: 2020-11-24
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download force field
        short: GitHub
        description: Open Force Field 1.0 ("Parsley") small molecule force fields and code needed to reproduce automated parameterization
        url: https://github.com/openforcefield/openff-forcefields
    # Thumbnail image URL
    thumbnail: parsley
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
      rationale: >
        This work reports the development of a new generation of small molecule force fields that aim to deliver
        systematically improvable predictions of protein:ligand interactions and binding affinities, enabling us
        to systematically increase the accuracy of our predictions of kinase:inhibitor affinities to accelerate the
        design of targeted cancer therapies.
    - id: NIH R01 GM121505
      rationale: >
        This work reports the development of a new generation of small molecule force fields that aim to deliver
        systematically improvable predictions of protein:ligand interactions and binding affinities, enabling us
        to systematically increase the accuracy of our predictions of kinase:inhibitor affinities.
    - id: NIH R01 GM132386
      rationale: >
        This work is the first release of a new generation of biomolecular force fields funded by this effort,
        illustrating how our scalable infrastructure for force field parameterization can be applied to systematically
        expanded datasets.
    - id: NSF CHE 1738979
      rationale: >
        This work describes an automated approach to force field parameterization using a loss function formulation,
        which is the first step toward a fully Bayesian force field parameterization scheme.
    description: >
      We present a new, modern small molecule force field for molecular design from the Open Force Field Initiative,
      a large industry-academic collaboration that focuses on open science, open data, and modern open source infrastructure.


  # Title should have only initial letter capitalized
  - title: "Fitting quantum machine learning potentials to experimental free energy data: Predicting tautomer ratios in solution"
    authors: # Use same name in publication
    - Marcus Wieder
    - Josh Fass
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/content/10.1101/2020.10.24.353318v4.abstract
      date: 2021-02-26
    #published:
    #  doi: none
    #  journal: Chemical Science
    #  volume: none
    #  page: in press # just first page
    #  year: 2021
    #  dates:
    #    accepted: 2021-07-05
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download code
        short: GitHub
        description: Python code for fitting quantum machine learning potentials to experimental free energy data for tautomer ratio prediction
        url: https://github.com/choderalab/neutromeratio
    # Thumbnail image URL
    thumbnail: neutromeratio-vacuum
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
    - id: NIH R01 GM121505
      rationale: >
        Accurately predicting aqueous populations of protonation and tautomeric states is essential for the accurate prediction
        of kinase:inhibitor binding free energies. This work is a critical step toward the accurate prediction of these quantities
        in a manner that can be systematically improved based on experimental data. In addition, this is a simplified demonstration of
        how more complex kinase:inhibitor binding free energies might be systematically improved by fitting flexible quantum machine learning
        potentials---which offer significant accuracy improvements beyond molecular mechanics potentials---to free energies of binding.
    - id: NIH R01 GM132386
      rationale: >
        Quantum machine learning (QML) force fields represent an enormous leap in next-generation force fields for molecular simulation
        since they are highly flexible and can be trained to accurately reproduce quantum chemical data. This work demonstrates a key
        advance in this area, showing how these flexible QML potentials can also be fit to reproduce experimental measurements
        such as free energies.
    - id: NSF CHE 1738979
      rationale: >
        Quantum machine learning (QML) force fields represent an enormous leap in next-generation force fields for molecular simulation
        since they are highly flexible and can be trained to accurately reproduce quantum chemical data. This work demonstrates a key
        advance in this area, showing how these flexible QML potentials can also be fit to reproduce experimental measurements
        such as free energies, as a first step toward fully Bayesian inference of flexible QML potentials.
    description: >
      We demonstrate, for the first time, how alchemical free energy calculations can performed on systems simulated entirely
      with quantum machine learning potentials and how these potentials can be retrained on experimental free energies to
      generalize to new molecules from limited training data. We apply this approach to a difficult problem in small
      molecule drug discovery: Predicting accurate tautomer ratios in solution.


  - title: "SARS-CoV-2 RBD antibodies that maximize breadth and resistance to escape"
    authors: # Use same name in publication
    - Tyler N. Starr
    - Nadine Czudnochowski
    - Fabrizia Zatta
    - Young-Jun Park
    - Zhuoming Liu
    - Amin Addetia
    - Dora Pinto
    - Martina Beltramello
    - Patrick Hernandez
    - Allison J. Greaney
    - Roberta Marzi
    - William G. Glass
    - Ivy Zhang
    - Adam S. Dingens
    - John E. Bowen
    - Jason A. Wojcechowskyj
    - Anna De Marco
    - Laura E. Rosen
    - Jiayi Zhou
    - Martin Montiel-Ruiz
    - Hannah Kaiser
    - Heather Tucker
    - Michael P. Housley
    - Julia di Iulio
    - Gloria Lombardo
    - Maria Agostini
    - Nicole Sprugasci
    - Katja Culap
    - Stefano Jaoni
    - Marcel Meury
    - Exequiel Dellota
    - Elisabetta Cameroni
    - Tristan I. Croll
    - Jay C. Nix
    - Colin Havenar-Daughton
    - Amalio Telenti
    - Florian A. Lempp
    - Matteo S. Pizzuto
    - John D. Chodera
    - Christy M. Hebner
    - Sean P. J. Whelan
    - Herbert W. Virgin
    - David Veesler
    - Davide Corti
    - Jesse D. Bloom
    - Gyorgy Snell
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Davide Corti
    - Jesse D. Bloom
    - Gyorgy Snell
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/content/10.1101/2021.04.06.438709v1.abstract
      date: 2021-04-08
    published:
      doi: 10.1038/s41586-021-03807-6
      journal: Nature
      volume: 597
      page: 97 # just first page
      year: 2021
      dates:
        submitted: 2021-03-29
        accepted: 2021-07-06
        published: 2021-07-14
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download code and analysis from GitHub
        short: GitHub
        description: SARS-CoV-2 receptor binding domain (RBD)
        url: https://github.com/choderalab/rbd-ab-contact-analysis
      # TODO: Check this is the correct link
      - action: Download Folding@home simulation trajectories
        short: MolSSI COVID Hub
        description: Folding@home simulation trajectories
        url: https://covid.molssi.org//simulations/#foldinghome-simulations-of-the-sars-cov-2-spike-rbd-bound-to-human-ace2
    # Thumbnail image URL
    thumbnail: vir-antibodies-escape
    # List funding, or none
    funding:
    - id: NIH P30 CA008748
    - id: NIH R01 GM121505
      rationale: >
        This work explores massively parallel distributed simulation and analysis algorithms in SARS-CoV-2 RBD:ACE2 interactions
        as a timely and relevant model system for the study of long-timescale kinase conformational dynamics and interactions.
    - id: NIH R01 GM132386
      rationale: >
        This work explores massively parallel distributed simulation and analysis algorithms in SARS-CoV-2 RBD:ACE2 interactions
        as a timely and relevant quantitative benchmark for glycosylated protein interaction affinity prediction.
    # Two newlines are needed after the description
    description: >
      We comprehensively characterize escape, breadth, and potency across a panel of SARS-CoV-2 antibodies
      targeting the receptor binding domain, including the parent antibody of the recently approved Vir
      antibody drug (Sotrovimab), illuminating escape mutations with structural and dynamic insight into
      their mechanism of action.


  - title: "Discovery of SARS-CoV-2 main protease inhibitors using a synthesis-directed de novo design model"
    authors: # Use same name in publication
    - Aaron Morris
    - William McCorkindale
    - The COVID Moonshot Consortium
    - Nir Drayman
    - John D. Chodera
    - Savaş Tay
    - Nir London
    - Alpha A. Lee
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Alpha A. Lee
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: https://doi.org/10.1007/s10822-020-00362-6
      journal: Journal of Computer-Aided Molecular Design
      volume: 35
      page: 131 # just first page
      year: 2021
      dates:
        received: 2021-01-05
        accepted: 2021-05-04
        published: 2021-05-06
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Try Manifold
        short: Manifold
        description: PostEra's Manifold online CRO synthetic route recommender, used by the COVID Moonshot
        url: https://postera.ai/manifold
      - action: Get the COVID Moonshot data
        short: COVID Moonshot data
        description: Biochemical inhibition data for the SARS-CoV-2 main viral protease (Mpro) for all compounds synthesized by the COVID Moonshot
        url: http://www.postera.ai/covid
    # Thumbnail image URL
    thumbnail: postera-ml-model
    # List funding, or none
    funding:
    - id: NIH P30 CA008748
    - id: NIH R01 GM124270
      rationale: >
        This work reports the development and generation of biophysical protein:ligand affinity and X-ray datasets for
        a large number of newly synthesized compounds against a model protein system of high interest to drug discovery---the main viral protease.
        This data can be used to retrospectively benchmark predictive models, and new data can be generated to field blind
        predictive challenges on a target with high relevance to human health.
    # Two newlines are needed after the description
    description: >
      We show how a machine learning models of ligand affinity can be coupled to synthetic enumeration models
      to rapidly generate potent inhibitors of the SARS-CoV-2 main viral protease.


  - title: "Mutation in Abl kinase with altered drug binding kinetics indicates a novel mechanism of imatinib resistance"
    authors: # Use same name in publication
    - Agatha Lyczek
    - Benedict Tilman Berger
    - Aziz M. Rangwala
    - YiTing Paung
    - Jessica Tom
    - Hannah Philipose
    - Jiaye Guo
    - Steven K. Albanese
    - Matthew B. Robers
    - Stefan Knapp
    - John D. Chodera
    - Markus A. Seeliger
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    - Markus A. Seeliger
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/node/1585452.full
      date: 2021-06-28
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: https://doi.org/10.1073/pnas.2111451118
      journal: Proceedings of the National Academy of Science
      volume: 118
      page: e2111451118 # just first page
      year: 2021
      dates:
        received: 2021-06-24
        accepted: 2021-09-28
        published: 2021-11-08
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download code from GitHub
        short: GitHub
        description: Code for conducting SAMS simulations accelerating activation loop sampling for Abl kinase to examine the impact of the N368S mutation on conformational populations
        url: https://github.com/choderalab/Abl_kinase_N368S
    # Thumbnail image URL
    thumbnail: abl-mutant-resistance
    # List funding, or none
    funding:
    - id: NIH P30 CA008748
    - id: NIH R01 GM121505
      rationale: >
        This work represents the first major use of NanoBRET to experimentally measure the impact of clinical cancer mutations
        associated with resistance to clinical kinase inhibitors on the binding affinity and kinetics of these
        inhibitors. The data collected here provides an incredibly valuable benchmark set for computational approaches
        to predicting the impact of resistance mutations for kinase inhibitors, and will allow us to continue to refine
        our computational approaches to mechanism-based prediction of the impact of clinical cancer mutations.
    - id: NIH R01 GM124270
      rationale: >
        This work represents the first major use of NanoBRET to experimentally measure the impact of point mutations
        on the binding affinity for druglike molecules in an important target class, kinases. Future datasets collected
        using this approach will be useful for fielding blind predictive challenges.
    # Two newlines are needed after the description
    description: >
      Here, we characterize the biophysical mechanisms underlying mutants of Abl kinase associated with clinical
      drug resistance to targeted cancer therapies. We uncover a surprising novel mechanism of mutational
      resistance to kinase inhibitor therapy in which the off-rate for inhibitor unbinding is increased
      without affecting inhibitor affinity.


  - title: "Overview of the SAMPL6 pKa challenge: evaluating small molecule microscopic and macroscopic pKa predictions"
    authors: # Use same name in publication
    - Mehtap Işık
    - Ariën S. Rustenburg
    - Andrea Rizzi
    - Marilyn R. Gunner
    - David L. Mobley
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Mehtap Işık
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/node/1585452.full
      date: 2020-10-15
    published:
      doi: https://doi.org/10.1007/s10822-020-00362-6
      journal: Journal of Computer-Aided Molecular Design
      volume: 35
      page: 131 # just first page
      year: 2021
      dates:
        received: 2020-10-16
        accepted: 2020-11-17
        published: 2021-01-04
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download SAMPL6 challenge data from GitHub
        short: GitHub
        description: The SAMPL6 Challenge blind predictive challenge instructions and datasets
        url: https://github.com/samplchallenges/SAMPL6
      - action: Download the manuscript and figure sources
        short: GitHub
        description: The SAMPL6 pKa Challenge manuscript and figure sources and analysis scripts
        url: https://github.com/choderalab/sampl6-pKa-challenge-manuscript
    # Thumbnail image URL
    thumbnail: sampl6-pka-assessment
    # List funding, or none
    funding:
    - id: NIH P30 CA008748
    - id: NIH R01 GM121505
      rationale: >
        Identification of dominant protonation and tautomer states and accurate prediction of their populations
        in solution is critical to accurate modeling of kinase:inhibitor binding affinities. This effort assessed the
        accuracy of a wide variety of quantitative pKa prediction tools at predicting microscopic and macroscopic
        pKas and state populations for many chemotypes commonly found in kinase inhibitors, providing an assessment
        of which tools lead to the best current accuracy for kinase:inhibitor interaction modeling.
    - id: NIH R01 GM124270
      rationale: >
        Accurate modeling of protonation and tautomeric states is a significant limiting factor in current-generation
        predictive modeling tools for structure-enabled drug discovery. This SAMPL blind challenge focused the community
        on this important accuracy-limiting challenge to predictive modeling, and provided a benchmark of the current state
        of the art. As this was our first pKa challenge, we describe a number of the lessons we learned from this exercise,
        providing a blueprint for future pKa challenges that aim to systematically advance the field toward more accurate modeling.
    # Two newlines are needed after the description
    description: >
      The SAMPL6 pKa challenge assessed the ability of the computational chemistry community to predict macroscopic
      and microscopic pKas for a set of druglike molecules resembling kinase inhibitors. This paper reports on the
      overall performance and lessons learned, including the surprising finding that many tools predict reasonably
      accurate macroscopic pKas corresponding to the wrong microscopic protonation sites.


  # Title should have only initial letter capitalized
  - title: "Circulating SARS-CoV-2 spike N439K variants maintain fitness while evading antibody-mediated immunity"
    authors: # Use same name in publication
    - Emma C. Thomson
    - Laura E. Rosen
    - James G. Shepherd
    - Roberto Spreafico
    - Ana da Silva Filipe
    - Jason A Wojcechowskyj
    - Chris Davis
    - Luca Piccoli
    - David J Pascall
    - Josh Dillen
    - Spyros Lytras
    - Nadine Czudnochowski
    - Rajiv Shah
    - Marcel Meury
    - Natasha Jesudason
    - Anna De Marco
    - Kathy Li
    - Jessica Bassi
    - Aine O’Toole
    - Dora Pinto
    - Rachel M. Colquhoun
    - Katja Culap
    - Ben Jackson
    - Fabrizia Zatta
    - Andrew Rambaut
    - Stefano Jaconi
    - Vattipally B. Sreenu
    - Jay Nix
    - Ivy Zhang
    - Ruth F. Jarrett
    - William G Glass
    - Martina Beltramello
    - Kyriaki Nomikou
    - Matteo Pizzuto
    - Lily Tong
    - Elisabetta Cameroni
    - Tristan I. Croll
    - Natasha Johnson
    - Julia Di Iulio
    - Arthur Wickenhagen
    - Alessandro Ceschi
    - Aoife M. Harbison
    - Daniel Mair
    - Paolo Ferrari
    - Katherine Smollett
    - Federica Sallusto
    - Stephen Carmichael
    - Christian Garzoni
    - Jenna Nichols
    - Massimo Galli
    - Joseph Hughes
    - Agostino Riva
    - Antonia Ho
    - Marco Schiuma
    - Malcolm G Semple
    - Peter JM Openshaw
    - Elisa Fadda
    - J. Kenneth Baillie
    - John D. Chodera
    - Suzannah J. Rihn
    - Samantha J. Lycett
    - Herbert W. Virgin
    - Amalio Telenti
    - Davide Corti
    - David L. Robertson
    - Gyorgy Snell
    - ISARIC4C Investigators
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Gyorgy Snell
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/content/10.1101/2020.11.04.355842v1
      date: 2020-11-05
    published:
      doi: https://doi.org/10.1016/j.cell.2021.01.037
      journal: Cell
      volume: 184
      page: 1171 # just first page
      year: 2021
      dates:
        published: 2021-03-04
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download supplementary data from Mendeley Data
        short: Mendeley Data
        description: 'Supplementary data for "Circulating SARS-CoV-2 spike N439K variants maintain fitness while evading antibody-mediated immunity'
        url: https://data.mendeley.com/datasets/2wrgws3545
      - action: Download Folding@home data
        short: Folding@home
        description: Folding@home simulation datasets of SARS-CoV-2 RBD:ACE2 interactions, including N439K variants
        url: https://covid.molssi.org//simulations/#foldinghome-simulations-of-the-sars-cov-2-spike-rbd-bound-to-human-ace2
    # Thumbnail image URL
    thumbnail: vir-cell-xray
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
    - id: NIH R01 GM121505
      rationale: >
        This work explores massively parallel distributed simulation and analysis algorithms in SARS-CoV-2 RBD:ACE2 interactions
        as a timely and relevant model system for the study of long-timescale kinase conformational dynamics and interactions.
    - id: Sloan Kettering Institute
    - id: Cycle for Survival
    description: >
      New mutations that enhance the affinity of SARS-CoV-2 spike protein for human ACE2—and potentially pose threats to
      antibody-based therapeutics and vaccines for COVID-19—are already emerging in the wild. We characterize and describe
      sentinel mutations of SARS-CoV-2 in the wild that herald challenges for combatting COVID-19, and use simulations of
      the RBD-ACE2 interface on Folding@home to biophysically characterize why these mutations can lead to enhanced affinity.


  # Title should have only initial letter capitalized
  - title: "What Markov State Models can and cannot do: Correlation versus path-based observables in protein-folding models"
    authors: # Use same name in publication
    - Ernesto Suárez
    - Rafal P. Wiewiora
    - Chris Wehmeyer
    - Frank Noé
    - John D. Chodera
    - Daniel M. Zuckerman
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    - Daniel M. Zuckerman
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/node/1626539.full
      date: 2020-11-09
    published:
      doi: https://doi.org/10.1021/acs.jctc.0c01154
      journal: Journal of Chemical Theory and Computation
      volume: 17
      page: 3119 # just first page
      year: 2021
      dates:
        published: 2021-04-27
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download code from GitHub
        short: GitHub
        description: 'Reference code for analysis and figure generation for "What Markov State Models can and cannot do: Correlation versus path-based observables in protein-folding models"'
        url: https://github.com/choderalab/msm-mfpt
    # Thumbnail image URL
    thumbnail: what-can-msms-do
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
    - id: NIH R01 GM121505
      rationale: >
        Markov state models are a key methodology for mapping the conformations accessible to kinases
        via massively distributed simulation. This work seeks to understand the limitations of these models
        in accurately describing conformational dynamics and populations using thoroughly-sampled datasets.
    description: >
      Markov state models are now well-established for describing the long-time conformational dynamics
      of proteins. Here, we take a critical look of what properties can reliably be extracted from
      these coarse-grained models.


  # Title should have only initial letter capitalized
  - title: "Best practices for constructing, preparing, and evaluating protein-ligand binding affinity benchmarks"
    authors: # Use same name in publication
    - David F. Hahn
    - Christopher I. Bayly
    - Hannah E. Bruce Macdonald
    - John D. Chodera
    - Antonia S. J. S. Mey
    - David L. Mobley
    - Laura Perez Benito
    - Christina E. M. Schindler
    - Gary Tresadern
    - Gregory L. Warren
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - David F. Hahn
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://arxiv.org/abs/2105.06222
      date: 2021-05-13
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Raise an issue on the manuscript source repository
        short: GitHub
        description: 'Living best practices manuscript GitHub repository for "Best practices for constructing, preparing, and evaluating protein-ligand binding affinity benchmarks"'
        url: https://github.com/openforcefield/FE-Benchmarks-Best-Practices
    # Thumbnail image URL
    thumbnail: affinity-benchmark-best-practices
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
    - id: NIH R01 GM132386
      rationale: >
        This work is a critical part of establishing best practices for benchmarking the accuracy
        of molecular mechanics force fields for predicting protein:ligand binding affinities.
    description: >
      This living best practices paper for the Living Journal of Computational Molecular Sciences
      describes the current community consensus in how to curate experimental benchmark data for
      assessing predictive affinity models for drug discovery, how to prepare these systems for
      affinity calculations, and how to assess the results to compare performance.


  # Title should have only initial letter capitalized
  - title: "Bayesian inference-driven model parameterization and model selection for 2CLJQ fluid models"
    authors: # Use same name in publication
    - Owen C. Madin
    - Simon Boothroyd
    - Richard A. Messerly
    - John D. Chodera
    - Josh Fass
    - Michael R. Shirts
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Michael R. Shirts
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://arxiv.org/abs/2105.07863
      date: 2020-05-14
    # Thumbnail image URL
    thumbnail: 2CLJQ
    # Two newlines are needed after the description
    funding:
    - id: NSF CHE-1738975
      rationale: >
        This work demonstrates how reversible-jump Monte Carlo can be used to automate the data-driven
        selection of appropriate functional forms for molecular mechanics force fields using Bayesian inference
        methods.
    - id: NIH R01 GM132386
      rationale: >
        This work shows how an automated, statistically motivated, data-driven method can be used to identify appropriate
        functional forms for molecular mechanics force field parameterization.
    - id: Open Force Field Consortium
    description: >
      Here, we show how Bayesian inference can be used to automatically perform model
      selection and fit parameters for a molecular mechanics force field.


  # Title should have only initial letter capitalized
  - title: "A white-knuckle ride of open COVID drug discovery"
    authors: # Use same name in publication
    - Frank von Delft
    - Mark Calmiano
    - John D. Chodera
    - Ed Griffen
    - Alpha Lee
    - Nir London
    - Tatiana Matviuk
    - Ben Perry
    - Matt Robinson
    - Annette von Delft
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Frank von Delft
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: https://doi.org/10.1038/d41586-021-01571-1
      journal: Nature
      volume: 594
      page: 330 # just first page
      year: 2021
      dates:
        published: 2021-06-17
    links:
      - action: Get the COVID Moonshot data
        short: COVID Moonshot data
        description: Biochemical inhibition data for the SARS-CoV-2 main viral protease (Mpro) for all compounds synthesized by the COVID Moonshot
        url: http://www.postera.ai/covid
    # Thumbnail image URL
    thumbnail: covid-moonshot-nature-commentary.jpg
    # Two newlines are needed after the description
    description: >
      The COVID Moonshot is an open science effort to discover a direct-acting SARS-CoV-2 oral antiviral.
      Here, we share lessons from this effort, including the missed opportunity to develop a phase 2 ready
      drug more than a decade ago that could have halted the COVID-19 pandemic in its tracks.


  # Title should have only initial letter capitalized
  - title: "End-to-end differentiable molecular mechanics force field construction"
    authors: # Use same name in publication
    - Yuanqing Wang
    - Josh Fass
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://arxiv.org/abs/2010.01196
      date: 2020-10-02
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download code
        short: GitHub
        description: Espaloma, an end-to-end differentiable infrastructure for modular molecular mechanics force field construction
        url: https://github.com/choderalab/espaloma
    # Thumbnail image URL
    thumbnail: espaloma
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
    - id: NIH R01 GM121505
      rationale: >
        This paper describes a new approach to end-to-end parameterization of small molecules that
        we believe will lead to systematically improvable force fields for predicting kinase:inhibitor
        binding affinities. Future extensions of this method will also allow us to model post-translational
        modifications of kinases in a self-consistent manner with ligand parameters.
    - id: NIH R01 GM132386
      rationale: >
        This paper describes a new approach to the data-driven parameterization of molecular mechanics
        force fields, breaking free of discrete atom or force types and instead providing an end-to-end
        differentiable scheme for optimizing force field parameter assignment directly in a modular,
        extensible fashion.
    - id: NSF CHE 1738979
      rationale: >
        This paper describes a new approach to the data-driven parameterization of molecular mechanics
        force fields, breaking free of discrete atom or force types and instead providing an end-to-end
        differentiable scheme for optimizing force field parameter assignment directly in a modular,
        extensible fashion.
    - id: Open Force Field Consortium
    description: >
      Molecular mechanics force fields have been a workhorse for computational chemistry and drug discovery.
      Here, we propose a new approach to force field parameterization in which graph convolutional networks
      are used to perceive chemical environments and assign molecular mechanics (MM) force field parameters.
      The entire process of chemical perception and parameter assignment is differentiable end-to-end with
      respect to model parameters, allowing new force fields to be easily constructed from MM or QM force fields,
      extended, and applied to arbitrary biomolecules.


  # Title should have only initial letter capitalized
  - title: "Capturing non-local through-bond effects when fragmenting molecules for quantum chemical torsion scans"
    authors: # Use same name in publication
    - Chaya D. Stern
    - Christopher I. Bayly
    - Daniel G. A. Smith
    - Josh Fass
    - Lee-Ping Wang
    - David L. Mobley
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/content/10.1101/2020.08.27.270934v1
      date: 2020-08-29
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download code
        short: GitHub
        url: https://github.com/openforcefield/fragmenter
        description: Fragmenter, an automated tool for fragmenting small molecules in a manner that preserves chemical environments for quantum chemical torsion scans
      - action: Download data
        short: GitHub
        description: Quantum chemical datasets for validating small molecule fragmentation schemes for torsion scans
        url: https://github.com/choderalab/fragmenter_data
      - action: Download dataset provenance
        short: GitHub
        description: Provenance data for quantum chemical datasets submitted to QCArchive from the Open Force Field Initiative
        url: https://github.com/openforcefield/qca-dataset-submission
      - action: Download dataset
        short: Open Science Framework
        description: 'Small molecule cheminformatic datasets used in "Capturing non-local through-bond effects when fragmenting molecules for quantum chemical torsion scans"'
        url: https://doi.org/gg8w5d
    # Thumbnail image URL
    thumbnail: fragmenter
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
    - id: NIH R01 GM132386
      rationale: >
        This manuscript describes the development of the small molecule fragmentation scheme that is currently used by the
        Open Force Field Initiative for generating small molecules for quantum chemical torsion scans to use
        in force field parameterization.
    - id: NSF GRFP DGE-1257284
    - id: Open Force Field Consortium
    description: >
      We show how the Wiberg Bond Order (WBO) can be used to construct small molecule fragmentation
      schemes that will avoid disrupting the chemical environment around torsions. The resulting
      fragmentation scheme powers the Open Force Field Initiative QCSubmit tool used to fragment and
      inject small molecule datasets into the QCFractal computation pipeline for deposition
      into the QCArchive quantum chemistry archive the Open Force Field Initiative uses for constructing
      force fields, as well as powering bespoke torsion refitting for individual molecules.


  # Title should have only initial letter capitalized
  - title: "Best practices for alchemical free energy calculations"
    authors: # Use same name in publication
    - Antonia S. J. S. Mey
    - Bryce Allen
    - Hannah E. Bruce Macdonald
    - John D. Chodera
    - Maximilian Kuhn
    - Julien Michel
    - David L. Mobley
    - Levi N. Naden
    - Samarjeet Prasad
    - Andrea Rizzi
    - Jenke Scheen
    - Michael R. Shirts
    - Gary Tresadern
    - Huafeng Xu
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Antonia S. J. S. Mey
    - John D. Chodera
    - David L. Mobley
    - Michael R. Shirts
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://arxiv.org/abs/2008.03067
      date: 2020-08-21
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Raise an issue on the manuscript source repository
        short: GitHub
        description: 'Living best practices GitHub manuscript repository for "Best practices for alchemical free energy calculations"'
        url: https://github.com/michellab/alchemical-best-practices
    # Thumbnail image URL
    thumbnail: alchemical-best-practices
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
    - id: NIH R01 GM121505
      rationale: >
        This living best practices paper describes our current understanding of the best practices for conducting
        alchemical free energy calculations of protein:ligand binding free energies, which are essential to assessing
        the accuracy of molecular mechanics force fields for predicting kinase:inhibitor affinity and selectivity.
    - id: NIH R01 GM132386
      rationale: >
        This living best practices paper describes our current understanding of the best practices for conducting
        alchemical free energy calculations of protein:ligand binding free energies, which are essential to assessing
        the accuracy of molecular mechanics force fields for biomolecular simulation.
    description: >
      This living best practices review for the Living Journal of Computational Molecular Sciences
      (LiveCoMS) covers the essential considerations for running alchemical free
      energy calculations for rational molecular design for drug discovery.


  # Title should have only initial letter capitalized
  - title: "Towards chemical accuracy for alchemical free energy calculations with hybrid physics-based machine learning / molecular mechanics potentials"
    authors: # Use same name in publication
    - Dominic A. Rufa
    - Hannah E. Bruce Macdonald
    - Josh Fass
    - Marcus Wieder
    - Patrick A. Grinaway
    - Adrian E. Rotiberg
    - Olexandr Isayev
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/content/10.1101/2020.07.29.227959v1
      date: 2020-07-30
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download code and data
        short: GitHub
        description: qmlify, code for computing corrections to molecular mechanics (MM) free energy calculations to obtain hybrid quantum machine learning / molecular mechanics (QML/MM) accuracy
        url: https://github.com/choderalab/qmlify
    # Thumbnail image URL
    thumbnail: hybrid-qm-mm
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
    - id: NIH R01 GM121505
      rationale: >
        This manuscript describes a new generation of hybrid quantum machine learning /
        molecular mechanics (QML/MM) potentials deliver enormous increases in accuracy
        in computing kinase:inhibitor binding free energies at minimal additional expense.
        Currently, this is performed as a correction calculation that can be performed in
        parallel with kinase:inhibitor binding free energy calculations. This accuracy
        increase could have an enormous impact on the design of new selective kinase inhibitors.
    - id: NIH R01 GM132386
      rationale: >
        This manuscript describes a new generation of hybrid quantum machine learning /
        molecular mechanics (QML/MM) potentials that can achieve significantly better
        accuracy in reproducing quantum chemical and physical property data. These QML/MM
        force fields will ultimately become a new standard for biomolecular simulation
        as hardware and software technologies advance to close the performance gap with
        pure MM simulations.
    description: >
      In this first use of hybrid machine learning / molecular mechanics (ML/MM) potentials
      for alchemical free energy calculations, we demonstrate how the improved modeling of
      intramolecular ligand energetics offered by the quantum machine learning potential
      ANI-2x can significantly improve the accuracy in predicting kinase inhibitor binding
      free energy by reducing the error from 0.97~kcal/mol to 0.47~kcal/mol, which could
      drastically reduce the number of compounds that must be synthesized in lead
      optimization campaigns for minimal additional computational cost.


# Here is an illustrative entry for papers
  # Title should have only initial letter capitalized
  - title: "Is structure based drug design ready for selectivity optimization?"
    authors: # Use same name in publication
    - Steven K. Albanese
    - John D. Chodera
    - Andrea Volkamer
    - Simon Keng
    - Robert Abel
    - Lingle Wang
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Lingle Wang
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/content/10.1101/2020.07.02.185132v1
      date: 2020-07-03
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download code and data
        short: GitHub
        description: 'Code to perform analyses and generate figures for "Is structure based drug design ready for selectivity optimization?"'
        url: https://github.com/choderalab/selectivity
    # Thumbnail image URL
    thumbnail: kinase-selectivity-paper
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
    - id: NIH R01 GM121505
      rationale: >
        Surprisingly, though selectivity is critical to selective kinase inhibitor discovery,
        there has been little work on how accurately free energy calculations can predict
        selectivity among similar kinase ATP-binding sites. Here, we show that free energy calculations
        (perhaps nonintuitively) can predict selectivity more accurately than affinity.
        We also examine how this phenomenon depends on similarity of kinase ATP-binding sites.
    description: >
      We asked whether the similarity of binding sites in related kinases might result
      in a fortuitous cancellation of errors in using alchemical free energy calculations
      to predict kinase inhibitor selectivities. Surprisingly, we find that even distantly
      related kinases have sufficient correlation in their errors that predicting changes in selectivity
      can be much more accurate than predicting changes in potency due to this effect, and
      show how this could lead to large reductions in the number of molecules that must
      be synthesized to achieve a desired selectivity goal.


  # Title should have only initial letter capitalized
  - title: "SARS-CoV-2 simulations go exascale to predict dramatic spike opening and cryptic pockets across the proteome"
    authors: # Use same name in publication
    - Maxwell I. Zimmerman
    - Justin R. Porter
    - Michael D. Ward
    - Sukrit Singh
    - Neha Vithani
    - Artur Meller
    - Upasana L. Mallimadugula
    - Catherine E. Kuhn
    - Jonathan H. Borowsky
    - Rafal P. Wiewiora
    - Matthew F. D. Hurley
    - Aoife M Harbison
    - Carl A Fogarty
    - Joseph E. Coffland
    - Elisa Fadda
    - Vincent A. Voelz
    - John D. Chodera
    - Gregory R. Bowman
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Gregory R. Bowman
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/content/10.1101/2020.06.27.175430v1
      date: 2020-06-30
    published:
      doi: https://doi.org/10.1038/s41557-021-00707-0
      journal: Nature Chemistry
      volume: 13
      page: 651 # just first page
      year: 2021
      dates:
        published: 2021-05-24
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download data through the Open Science Framework
        short: OSF
        description: Molecular simulation datasets for SARS-CoV-2 cryptic pockets from Folding@home
        url: https://osf.io/fs2yv/
      - action: Browse datasets on the MolSSI COVID-19 Molecular Structure and Therapeutics Hub
        short: MolSSI COVID-19 Hub
        description: Index of molecular simulation datasets for SARS-CoV-2 from Folding@home
        url: http://covid.molssi.org
    # Thumbnail image URL
    thumbnail: foldingathome-covid-cryptic-pockets
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
    - id: NIH R01 GM121505
      rationale: >
        Folding@home is a critical piece of infrastructure for our mapping of an atlas of kinase conformations
        and associated energetics. Here, we report infrastructure developments that enabled this resource to become
        the first exaFLOP/s distributed computing platform in the world, more powerful than the top ten supercomputers
        combined.
    description: >
      To accelerate a multitude of drug development activities to combat the global threat posed by COVID-19,
      over a million citizen scientists have banded together through the Folding@home distributed computing
      project to create the world’s first Exascale computer and simulate protein dynamics. An unprecedented
      0.1 seconds of simulation of the viral proteome reveal how the spike complex uses conformational masking
      to evade an immune response, conformational changes implicated in the function of other viral proteins,
      and cryptic pockets that are absent in experimental structures. These structures and mechanistic insights
      present new targets for the design of therapeutics.


  # Title should have only initial letter capitalized
  - title: "Crowdsourcing drug discovery for pandemics"
    authors: # Use same name in publication
    - John D. Chodera
    - Alpha A. Lee
    - Nir London
    - Frank von Delft
    corresponding-authors:
    - John D. Chodera
    - Alpha A. Lee
    - Nir London
    - Frank von Delft
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: https://doi.org/10.1038/s41557-020-0496-2
      journal: Nature Chemistry
      volume: 12
      page: 581 # just first page
      year: 2020
      dates:
        published: 2020-06-18
    # Thumbnail
    thumbnail: covid-moonshot
    pdf: https://choderalab.squarespace.com/s/crowdsourcing-drug-discovery.pdf
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Visit the COVID Moonshot
        short: COVID Moonshot
        description: Biochemical inhibition data for the SARS-CoV-2 main viral protease (Mpro) for all compounds synthesized by the COVID Moonshot
        url: http://postera.ai/covid
    # Two newlines are needed after the description
    funding: null
    description: >
      The COVID-19 pandemic has left the world scrambling to find effective therapies
      to stem the tidal wave of death and put an end to the worldwide disruption
      caused by SARS-CoV-2. In this Correspondence, we argue for the need for a new open,
      collaborative drug discovery model (exemplified by our COVID Moonshot collaboration)
      that breaks free of the limitations of industry-led competitive drug discovery efforts
      that necessarily restrict information flow and hinder rapid progress by prioritizing
      profits and patent protection over human lives.


  # Title should have only initial letter capitalized
  - title: "Machine learning force fields and coarse-grained variables in molecular dynamics: application to materials and biological systems"
    authors: # Use same name in publication
    - Paraskevi Gkeka
    - Gabriel Stoltz
    - Amir Barati Farimani
    - Zineb Belkacemi
    - Michele Ceriotti
    - John Chodera
    - Aaron R. Dinner
    - Andrew Ferguson
    - Jean-Bernard Maillet
    - Hervé Minoux
    - Christine Peter
    - Fabio Pietrucci
    - Ana Silveira
    - Alexandre Tkatchenko
    - Zofia Trstanova
    - Rafal Wiewiora
    - Tony Lelièvre
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Paraskevi Gkeka
    - Gabriel Stoltz
    - Tony Lelièvre
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://arxiv.org/abs/2004.06950
      date: 2020-08-15
    # Thumbnail image URL
    thumbnail: coarse-graining
    funding:
    - id: NIH P30 CA008748
    description: >
      We review the state of the art in applying machine learning to coarse grain force fields in space and time to study mutliscale dynamics.


  # Title should have only initial letter capitalized
  - title: "Assessing the accuracy of octanol-water partition coefficient predictions in the SAMPL6 Part II log P Challenge"
    authors: # Use same name in publication
    - Mehtap Işık # note the characters are not Isik
    - Teresa Danielle Bergazin
    - Thomas Fox
    - Andrea Rizzi
    - John D. Chodera
    - David L. Mobley
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Mehtap Işık
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: http://dx.doi.org/10.1007/s10822-020-00295-0
      journal: Journal of Computer Aided Molecular Design
      volume: 34
      page: 335 # just first page
      year: 2020
      dates:
        published: 2020-02-27
        received: 2019-11-07
        accepted: 2020-01-24
    preprint:
      url: https://www.biorxiv.org/content/10.1101/2020.01.20.913178v1
      date: 2020-01-21
    # Thumbnail
    thumbnail: sampl6-logP-assessment
    pdf: http://www.choderalab.org/s/SAMPL6-pKa.pdf
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download SAMPL6 challenge data from GitHub
        short: GitHub
        description: The SAMPL6 Challenge blind predictive challenge instructions and datasets
        url: https://github.com/samplchallenges/SAMPL6
    # Two newlines are needed after the description
    funding:
    - id: NIH P30 CA008748
    - id: NIH R01 GM124270
      rationale: >
        This blind challenge focuses the community on assessing the accuracy of predicting
        free energy differences between aqueous and apolar environments in the absence of
        pKa and conformational sampling challenges, enabling a critical benchmark of the
        accuracy of physical models.
    description: >
      We report the performance assessment of the 91 methods that were submitted
      to the SAMPL6 blind challenge for predicting octanol-water partition coefficient
      (logP) measurements. The average RMSE of the most accurate five MM-based, QM-based,
      empirical, and mixed approach methods based on RMSE were 0.92±0.13, 0.48±0.06, 0.47±0.05,
      and 0.50±0.06, respectively.


  - title: "Standard state free energies, not pKas, are ideal for describing small molecule protonation and tautomeric states"
    authors: # Use same name in publication
    - MR Gunner
    - Taichi Murakami
    - Ariën S Rustenburg
    - Mehtap Işık
    - John Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - MR Gunner
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: https://doi.org/10.1007/s10822-020-00280-7
      journal: Journal of Computer-Aided Molecular Design
      volume: 34
      page:  561 # just first page
      year: 2020
      dates:
        published: 2020-02-12 # use ISO 8601 date format YYYY-MM-DD
    links:
      - action: Download code and plots from GitHub
        short: GitHub
        description: Utilities for calculating pH titration curves for small molecules
        url: https://github.com/choderalab/titrato
    # Thumbnail
    thumbnail: pka-free-energies
    pdf: https://link.springer.com/content/pdf/10.1007/s10822-020-00280-7.pdf
    # Funding
    funding:
    - id: NIH P30 CA008748
    - id: NIH R01 GM124270
      rationale: >
        As part of the first SAMPL6 pKa blind challenge, we realized that there was a much more
        straightforward approach to capturing all of the essential information about aqueous pKa
        values for small druglike molecules. This work summarizes our findings, and demonstrates
        how free energy plots are extremely useful in identifying modeling errors in predicting
        small molecule aqueous pKas.
    description: >
     Here, we demonstrate how the physical nature of protonation and tautomeric state effects
     means that the standard state free energies of each microscopic protonation/tautomeric
     state at a single pH is sufficient to describe the complete pH-dependent microscopic
     and macroscopic populations. We introduce a new kind of diagram that uses this concept
     to illustrate a variety of pH-dependent phenomena, and show how it can be used to identify
     common issues with protonation state prediction algorithms. As a result, we recommend
     future blind prediction challenges utilize microstate free energies at a single reference
     pH as the minimal sufficient information for assessing prediction accuracy and utility.


  - title: "The SAMPL6 SAMPLing challenge: Assessing the reliability and efficiency of binding free energy calculations"
    authors:
    - Andrea Rizzi
    - Travis Jensen
    - David R. Slochower
    - Matteo Aldeghi
    - Vytautas Gapsys
    - Dimitris Ntekoumes
    - Stefano Bosisio
    - Michail Papadourakis
    - Niel M. Hendriksen
    - Bert L. de Groot
    - Zoe Cournia
    - Alex Dickson
    - Julien Michel
    - Michael K. Gilson
    - Michael R. Shirts
    - David L. Mobley
    - John D. Chodera
    corresponding-authors:
    - Andrea Rizzi
    - David L. Mobley
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/content/10.1101/795005v2
      date: 2020-01-03
    published:
      doi: https://doi.org/10.1007/s10822-020-00290-5
      journal: Journal of Computer Aided Molecular Design
      volume: 34
      page: 601 # just first page
      year: 2020
      dates:
        published: 2020-01-27
    links:
      - action: Download code and data
        short: GitHub
        description: Input files for the SAMPL6 SAMPLing Challenge
        url: https://github.com/samplchallenges/SAMPL6/tree/master/host_guest/SAMPLing
    # Thumbnail
    thumbnail: sampl6-sampling
    pdf: https://choderalab.squarespace.com/s/SAMPL6-SAMPLing.pdf
    # These links may be listed in the choderalab.org/publications/ page
    funding:
    - NIH P30 CA008748
    - NIH R01 GM124270
    description: >
      To assess the relative efficiencies of alchemical binding free energy calculations,
      the SAMPL6 SAMPLing challenge asked participants to submit predictions as a function of
      computer effort for the same force field and charge model. Surprisingly, we found that
      most molecular simulation codes cannot agree on the binding free energy was, even for
      the same force field.


  - title: "Octanol-water partition coefficient measurements for the SAMPL6 blind prediction challenge"
    authors: # Use same name in publication
    - Mehtap Işık
    - Dorothy Levorse
    - David L. Mobley
    - Timothy Rhodes
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Timothy Rhodes
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: https://doi.org/10.1007/s10822-019-00271-3
      journal: Journal of Computer Aided Molecular Design
      volume: 34
      page: 405 # just first page
      year: 2019
      dates:
        published: 2019-12-19 # use ISO 8601 date format YYYY-MM-DD
    preprint:
      url: https://www.biorxiv.org/content/10.1101/757393v3
      date: 2019-12-02
    links:
      - action: Download code and data from GitHub
        short: GitHub
        github: https://github.com/samplchallenges/SAMPL6/tree/master/physical_properties/logP
    # Thumbnail
    thumbnail: sampl6-part2-logP
    pdf: https://choderalab.squarespace.com/s/SAMPL6-pKa.pdf
    # These links may be listed in the choderalab.org/publications/ page
    # Two newlines are needed after the description
    funding:
      - NIH P30 CA008748
      - NIH R01 GM124270
    description: >
      We describe the design and data collection (and associated challenges) for the SAMPL6
      part II logP octanol-water blind prediction challenge, where the goal was to benchmark the
      accuracy of force fields for druglike molecules (here, molecules
      resembling kinase inhibitors).


  - title: "A small-molecule pan-Id antagonist inhibits pathologic ocular neovascularization"
    authors: # Use same name in publication
    - Paulina M. Wojnarowicz
    - Raquel Lima e Silva
    - Masayuki Ohanka
    - Sang Bae Lee
    - Yvette Chin
    - Anita Kulukian
    - Sung-Hee Chang
    - Bina Desai
    - Marta Garcia Escolano
    - Riddhi Shah
    - Marta Garcia-Cao
    - Sijia Xu
    - Rashmi Thakar
    - Yehuda Goldgur
    - Meredith A. Miller
    - Ouathek Ouerfelli
    - Guangli Yang
    - Tsutomu Arakawa
    - Steven K. Albanese
    - William A. Garland
    - Glenn Stoller
    - Jaideep Chaudhary
    - Rajesh Soni
    - John Philip
    - Ronald C. Hendrickson
    - Antonio Iavarone
    - Andrew J. Dannenberg
    - John D. Chodera
    - Nikola Pavletich
    - Anna Lasorella
    - Peter A. Campochiaro
    - Robert Benezra
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Robert Benezra
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: https://doi.org/10.1016/j.celrep.2019.08.073
      journal: Cell Reports
      volume: 29
      page: 62 # just first page
      year: 2019
      dates:
        published: 2019-10-01 # use ISO 8601 date format YYYY-MM-DD
    # These links may be listed in the choderalab.org/publications/ page
    thumbnail: id1
    pdf: http://www.choderalab.org/s/benezra-cell-reports.pdf
    # Two newlines are needed after the description
    funding:
      - NIH P30 CA008748
    description: >
     We report the discovery and characterization of a small molecule, AGX51, with the
     surprising ability to inhibit the interaction of Id1 with E47, which leads to ubiquitin-mediated
     degradation of Ids.


  - title: "Graph nets for partial charge prediction"
    authors: # Use same name in publication
    - Yuanqing Wang
    - Josh Fass
    - Chaya D. Stern
    - Kun Luo
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Yuanqing Wang
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://arxiv.org/abs/1909.07903
      date: 2019-09-17
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download the code from GitHub
        short: GitHub
        url: https://github.com/choderalab/gimlet
    # Two newlines are needed after the description
    funding:
      - NIH P30 CA008748
      - NIH R01 GM121505
      - NSF CHE 1738979
      - MolSSI Fellowship to Chaya Stern
    description: >
       Graph convolutional and message-passing networks can be a powerful tool for predicting physical properties of
       small molecules when coupled to a simple physical model that encodes the relevant invariances. Here, we show
       the ability of graph nets to rapidly predict high-quality partial atomic charges of small drug-like molecules
       for use in molecular dynamics simulations, physical docking calculations, and alchemical free energy calculations
       for computing affinity and selectivity to various target proteins.


  - title: "Sharing data from molecular simulations"
    authors: # Use same name in publication
    - Abraham MJ
    - Apostolov R
    - Barnoud J
    - Bauer P
    - Blau C
    - Bonvin AMJJ
    - Chavent M
    - Chodera JD
    - Condic-Jurkic K
    - Delemotte L
    - Grubmüller H
    - Howard RJ
    - Lindahl E
    - Ollila S
    - Salent J
    - Smith D
    - Stansfeld PJ
    - Tiemann J
    - Trellet M
    - Woods C
    - Zhmurov A
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    -  Chavent M
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://chemrxiv.org/articles/Sharing_Data_from_Molecular_Simulations/9775493
      date: 2019-09-09
    published:
      doi: https://doi.org/10.1021/acs.jcim.9b00665
      journal: Journal of Chemical Information and Modeling ASAP
      volume: 59
      page: 10 # just first page
      year: 2019
      dates:
        published: 2019-09-17
    # These links may be listed in the choderalab.org/publications/ page
    thumbnail: sharing-data
    pdf: http://www.choderalab.org/s/sharing-data.pdf
    # Two newlines are needed after the description
    funding: [] # empty list
    description: >
     There is a dire need to establish standards for sharing data in the molecular sciences. Here, we
     review the findings of a workshop held in Stockholm in Nov 2018 to discuss this need.


  - title: "Ancestral reconstruction reveals mechanisms of ERK regulatory evolution"
    authors: # Use same name in publication
    - Dajun Sang
    - Sudarshan Pinglay
    - Rafal P Wiewiora
    - Myvizhi E Selvan
    - Hua Jane Lou
    - John D Chodera
    - Benjamin E Turk
    - Zeynep H Gümüş
    - Liam J Holt
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    -  Liam J Holt
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: https://doi.org/10.7554/eLife.38805.001
      journal: eLife
      volume: 8
      page: e38805
      year: 2019
      dates:
        published: 2019-08-13 # use ISO 8601 date format YYYY-MM-DD
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download trajectory data from
        short: GitHub
        url: https://github.com/choderalab/ERK-ancestral-materials
    # Thumbnail and PDF
    thumbnail: erk-reconstruction
    pdf: https://elifesciences.org/articles/38805#downloads
    # Two newlines are needed after the description
    funding:
    - NIH P30 CA008748
    - NIH R01 GM121505
    description: >
     To understand how kinase regulation by phosphorylation emerged, we reconstruct the common ancestor of CDKs and
     MAPKs, using biochemical experiments and massively parallel molecular simulations to study how a few mutations
     were sufficient to switch ERK-family kinases from high- to low-autophosphorylation.


  - title: "Binding thermodynamics of host-guest systems with SMIRNOFF99Frosst 1.0.5 from the Open Force Field Initiative"
    authors: # Use same name in publication
    - David R. Slochower
    - Neil M. Hendriksen
    - Lee-Ping Wang
    - John D. Chodera
    - David L. Mobley
    - Michael K. Gilson
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Michael K. Gilson
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://chemrxiv.org/articles/Binding_thermodynamics_of_host-guest_systems_with_SMIRNOFF99Frosst_1_0_5_from_the_Open_Force_Field_Initiative/9159872
      date: 2019-06-09
    published:
      doi: https://doi.org/10.1021/acs.jctc.9b00748
      journal: Journal of Chemical Theory and Computation
      volume: 15
      page: 6225  # just first page
      year: 2019
      dates:
        published: 2019-10-11 # use ISO 8601 date format YYYY-MM-DD
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download code and data from GitHub
        short: GitHub
        url: https://slochower.github.io/smirnoff-host-guest-manuscript/#code-and-data-availability
    # Two newlines are needed after the description
    funding:
    - Open Force Field Consortium
    - NIH P30 CA008748
    - NIH R01 GM121505
    - NIH R01 GM124270
    description: >
     We have recently developed the SMIRNOFF99Frosst 1.0.5 small molecule force field, a compact, minimalistic
     general small molecule force field intended for accurately modeling the interactions of small molecules with
     receptors. Here, we assess the ability of this force field to accurately reproduce the binding thermodynamics
     of host-guest systems featuring druglike small molecules, where high-quality calorimetric data is readily available.
     We show that SMIRNOFF99Frosst peforms well in comparison with the older GAFF force fields, despite having 20x
     fewer parameters.


  - title: "Small-molecule targeting of MUSASHI RNA-binding activity in acute myeloid leukemia"
    authors: # Use same name in publication
    - Gerard Minuesa
    - Steven K Albanese
    - Arthur Chow
    - Alexandra Schurer
    - Sun-Mi Park
    - Christina Z. Rotsides
    - James Taggart
    - Andrea Rizzi
    - Levi N. Naden
    - Timothy Chou
    - Saroj Gourkanti
    - Daniel Cappel-
    - Maria C Passarelli
    - Lauren Fairchild
    - Carolina Adura
    - Fraser J Glickman
    - Jessica Schulman
    - Christopher Famulare
    - Minal Patel
    - Gregory M Ross
    - Derek S Tan
    - Christina S Leslie
    - Thijs Beuming
    - Yehuda Goldgur
    - John D Chodera
    - Michael G Kharas
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Michael G Kharas
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://doi.org/10.1101/321174
      date: 2018-05-14
    published:
      doi: https://doi.org/10.1038/s41467-019-10523-3
      journal: Nature Communications
      volume: 10
      page: 2691
      year: 2019
      dates:
        submitted: 2018-11-19
        accepted: 2019-05-16
        published: 2019-06-19 # use ISO 8601 date format YYYY-MM-DD
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download models and data from GitHub
        short: GitHub
        url: https://github.com/choderalab/musashi
      - action: Read the MSKCC blog post
        short: MSKCC blog post
        url: https://www.mskcc.org/blog/ro-versus-musashi-how-one-molecule-can-turn-cancer-cells-back-normal
    # Two newlines are needed after the description
    funding:
    - NIH P30 CA008748
    - NIH R01 GM121505
    description: >
     We use absolute alchemical free energy calculations to identify the likely interaction site for a
     small hydrophobic ligand that shows activity against MUSASHI in AML.


  - title: "The dynamic conformational landscapes of the protein methyltransferase SETD8"
    authors: # Use same name in publication
    - Rafal P. Wiewiora
    - Shi Chen
    - Fanwang Meng
    - Nicolas Babault
    - Anqi Ma
    - Wenyu Yu
    - Kun Qian
    - Hao Hu,
    - Hua Zou
    - Junyi Wang
    - Shijie Fan
    - Gil Blum
    - Fabio Pittella-Silva
    - Kyle A. Beauchamp
    - Wolfram Tempel
    - Hualing Jiang
    - Kaixian Chen
    - Robert J. Skene
    - Y. George Zheng
    - Peter J. Brown
    - Jian Jin
    - Cheng Luo
    - John D. Chodera
    - Minkui Luo
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Cheng Luo
    - John D. Chodera
    - Minkui Luo
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: http://doi.org/10.7554/eLife.45403
      journal: eLife
      volume: 8
      page: e45403
      year: 2019
      dates:
        published: 2019-05-13 # use ISO 8601 date format YYYY-MM-DD
    preprint:
      url: https://www.biorxiv.org/content/10.1101/438994v1
      date: 2018-10-12
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download the code and data
        short: GitHub
        url: https://github.com/choderalab/SETD8-materials
      - action: Download the Folding@home datasets
        short: OSF
        url: https://osf.io/2h6p4/
      - action: Watch movies of SETD8 dynamics
        short: Movies
        url: https://www.youtube.com/watch?v=IDLEi-M8Aow
      - action: Read the MSKCC Blog post
        short: MSKCC Blog post
        url: https://www.mskcc.org/blog/computational-hive-mind-helps-scientists-solve-enzyme-s-cryptic-movements
      - action: Watch the string quartet composed around this work ("Metastable Impressions")
        short: String quartet (YouTube)
        url: https://www.youtube.com/watch?v=zmXO6AZMOYU

    # Two newlines are needed after the description
    funding:
    - Folding@Home
    - NIH R01 GM121505
    - NIH P30 CA008748
    description: >
      In this work, we show how targeted X-ray crystallography using covalent inhibitors and depletion of
      native ligands to reveal structures of low-population hidden conformations can be combined with
      massively distributed molecular simulation to resolve the functional dynamic landscape of the protein
      methyltransferase SETD8 in unprecedented atomistic detail. Using an aggregate of six milliseconds of
      fully atomistic simulation from Folding@home, we use a new approach to constructing Markov state models
      of conformational dynamics to to illuminate the conformations corresponding energetics for this important epigenetic protein.
      All Folding@home simulation trajectories for this paper are available on the Open Science Framework.
      The trajectories generated for this project were used as the source for a unique musical composition 'Metastable'
      by George Holloway, performed by the Ligeti String Quartet with visual accompaniment from Robert Arbon.


  - title: "What makes a kinase promiscuous for inhibitors?"
    authors: # Use same name in publication
    - Sonya M. Hanson
    - George Georghiou
    - Manish K. Thakur
    - W. Todd Miller
    - Joshua S. Rest
    - John D. Chodera
    - Markus A. Seeliger
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - John D. Chodera
     - Markus A. Seeliger
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: https://doi.org/10.1016/j.chembiol.2018.11.005
      journal: Cell Chemical Biology
      volume: 26
      page:  1 # just first page
      year: 2019
      dates:
        published: 2019-03-21 # use ISO 8601 date format YYYY-MM-DD
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download the code and data from GitHub
        short: GitHub
        url: https://github.com/choderalab/DDR1_and_kinase_promiscuity_materials
    thumbnail: ddr1-dfg-pmf
    pdf: http://www.choderalab.org/s/seeliger-ddr1-promiscuity.pdf
    # Two newlines are needed after the description
    funding:
    - NIH R01 GM121505
    - NIH P30 CA008748
    - Cycle For Survival
    description: >
      A class of kinases are particularly promiscuous binders of small molecule inhibitors. Using combined
      biomolecular simulations and biochemical studies, we show that the promiscuity of DDR1, one of the
      major members of this class, is likely due to an unusually stable DFG-out conformation.


  - title: "OpenPathSampling: A Python framework for path sampling simulations.
             II. Building and customizing path ensembles and sample schemes"
    authors: # Use same name in publication
    - David W.H. Swenson
    - Jan-Hendrik Prinz
    - Frank Noé
    - John D. Chodera
    - Peter G. Bolhuis
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    - Peter G. Bolhuis
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: https://doi.org/10.1021/acs.jctc.8b00627
      journal: Journal of Chemical Theory and Computation
      volume: 15
      page:  837 # just first page
      year: 2018
      dates:
        published: 2018-10-25 # use ISO 8601 date format YYYY-MM-DD
    preprint:
      url: https://www.biorxiv.org/content/10.1101/351510v1
      date: 2018-06-20
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download the code
        short: GitHub
        url: https://github.com/openpathsampling/openpathsampling
    thumbnail: ops
    pdf: http://www.choderalab.org/s/ops-2.pdf
    # Two newlines are needed after the description
    funding:
    - NIH P30 CA008748
    - NIH R01 GM121505
    description: >
      To make powerful path sampling techniques broadly accessible and efficient, we have produced
      a new Python framework for easily implementing path sampling strategies (such as transition
      path and interface sampling) in Python. This second publication describes advanced aspects
      of the theory and details of how to customize path ensembles.


  - title: "OpenPathSampling: A Python framework for path sampling simulations. I. Basics"
    authors: # Use same name in publication
    - David W.H. Swenson
    - Jan-Hendrik Prinz
    - Frank Noé
    - John D. Chodera
    - Peter G. Bolhuis
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    - Peter G. Bolhuis
    # Add these other fields are optional; fill in as much information as is available
    preprint:
      url: https://www.biorxiv.org/content/10.1101/351494v1
      date: 2018-06-20
    published:
      doi: https://doi.org/10.1021/acs.jctc.8b00626
      journal: Journal of Chemical Theory and Computation
      volume: 15
      page:  813 # just first page
      year: 2018
      dates:
        published: 2018-10-25 # use ISO 8601 date format YYYY-MM-DD
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download the code
        short: GitHub
        url: https://github.com/openpathsampling/openpathsampling
    pdf: http://www.choderalab.org/s/ops-1.pdf
    # Two newlines are needed after the description
    funding:
    - NIH P30 CA008748
    - NIH R01 GM121505
    description: >
      To make powerful path sampling techniques broadly accessible and efficient, we have produced
      a new Python framework for easily implementing path sampling strategies (such as transition
      path and interface sampling) in Python. This first publication describes some of the theory and
      capabilities behind the approach.


  - title: "Toward learned chemical perception of force field typing rules"
    authors: # Use same name in publication
    - Camila Zanette
    - Caitlin C. Bannan
    - Christopher I. Bayly
    - Josh Fass
    - Michael K. Gilson
    - Michael R. Shirts
    - John Chodera
    - David L. Mobley
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - David L. Mobley
    # Add these other fields are optional; fill in as much information as is available
    published:
      doi: http://doi.org/10.1021/acs.jctc.8b00821
      journal: Journal of Chemical Theory and Computation
      volume: 15
      page:  402 # just first page
      year: 2018
      dates:
        published: 2018-10-15 # use ISO 8601 date format YYYY-MM-DD
    preprint:
      url: https://chemrxiv.org/articles/Toward_Learned_Chemical_Perception_of_Force_Field_Typing_Rules/6230627
      date: 2018-10-15
    # These links may be listed in the choderalab.org/publications/ page
    links:
      - action: Download the code and data
        short: GitHub
        url: https://github.com/openforcefield/smarty
    # Two newlines are needed after the description
    funding:
    - NSF CHE 1738979
    description: >
      We show how machine learning can learn typing rules for molecular mechanics force fields
      within a Bayesian statistical framework.


  - title: "Overview of the SAMPL6 host-guest binding affinity prediction challenge"
    authors: # Use same name in publication
    - Andrea Rizzi
    - Steven Murkli
    - John N. McNeill
    - Wei Yao
    - Matthew Sullivan
    - Michael K. Gilson
    - Michael W. Chiu
    - David L. Mobley
    - Lyle Isaacs
    - Bruce C. Gibb
    - David L. Mobley
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - David L. Mobley
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Computer-Aided Molecular Design special issue on SAMPL6
    volume: 32
    page:  937 # just first page
    publication-date: 2018-11-10 # use ISO 8601 date format YYYY-MM-DD
    year: 2018
    # These links may be listed in the choderalab.org/publications/ page
    doi: https://doi.org/10.1007/s10822-018-0170-6
    bioRxiv: https://doi.org/10.1101/371724
    github: https://github.com/MobleyLab/SAMPL6/tree/master/host_guest
    # Two newlines are needed after the description
    funding: null
    description: >
      We present an overview of the host-guest systems and participant performance for the
      SAMPL6 host-guest blind affinity prediction challenges, assessing how well various
      physical modeling approaches were able to predict ligand binding affinities for simple
      ligand recognition problems where receptor sampling and protonation state effects are
      eliminated due to the simplicity of supramolecular hosts. We find that progress is
      now stagnated likely due to force field limitations.


  - title: "An open library of human kinase domain constructs for automated bacterial expression"
    authors: # Use same name in publication
    - Steven K. Albanese
    - Daniel L. Parton
    - Mehtap Isik
    - Lucelenie Rodríguez-Laureano
    - Sonya M. Hanson
    - Julie M. Behr
    - Scott Gradia
    - Chris Jeans
    - Nicholas M. Levinson
    - Markus A. Seeliger
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Biochemistry
    volume: 57
    page:  4675 # just first page
    publication-date: 2018-07-13 # use ISO 8601 date format YYYY-MM-DD
    year: 2018
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1021/acs.biochem.7b01081
    PDF: http://www.choderalab.org/s/kinase-expression-panel.pdf
    bioRxiv: http://dx.doi.org/10.1101/038711
    github: https://github.com/choderalab/kinase-ecoli-expression-panel
    github.io: http://choderalab.github.io/kinome-data/kinase_constructs-addgene_hip_sgc.html
    AddGene: https://www.addgene.org/kits/chodera-kinase-domains
    # Two newlines are needed after the description
    funding:
    - NIH P30 CA008748
    - NIH R01 GM121505
    description: >
      Human kinase catalytic domains---the therapeutic target of selective kinase inhibitors
      used in the treatment of cancer and other diseases---are notoriously difficult and expensive
      to express in insect or human cells. Here, we utilize the phosphatase co-expression technology
      developed by Markus Seeliger (now at Stony Brook) to develop a library of human kinase
      catalytic domains for facile and inexpensive expression in bacteria.


  - title: "pKa measurements for the SAMPL6 prediction challenge for a set of kinase inhibitor-like fragments"
    authors: # Use same name in publication
    - Mehtap Işık
    - Dorothy Levorse
    - Ariën S. Rustenburg
    - Ikenna E. Ndukwe
    - Heather Wang
    - Julie M. Behr
    - Mikhail Reibarkh
    - Gary E. Martin
    - Alexey A. Makarov
    - David L. Mobley
    - Timothy Rhodes
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Timothy Rhodes
     - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Computer-Aided Molecular Design special issue on SAMPL6
    volume: 32
    page:  1117 # just first page
    publication-date: 2018-11-07 # use ISO 8601 date format YYYY-MM-DD
    year: 2018
    # These links may be listed in the choderalab.org/publications/ page
    doi: https://doi.org/10.1007/s10822-018-0168-0
    PDF:  http://www.choderalab.org/s/sampl6-pka-measurements.pdf
    bioRxiv: http://biorxiv.org/cgi/content/short/368787v1
    Supplementary Tables and Figures:  http://www.choderalab.org/s/sampl6-pKa-measurements-SI-98l4.pdf
    github: https://github.com/choderalab/kinase-ecoli-expression-panel
    Supplementary Data (includes Sirius T3 reports on all measurements):   https://github.com/choderalab/sampl6-pKa-measurements-manuscript/tree/master/supplementary-info    # Two newlines are needed after the description
    funding:
    - NIH R01 GM124270
    - NIH P30 CA008748
    description: >
     The SAMPL5 blind challenge exercises identified neglect of protonation state effects as
     a major accuracy-limiting factor in physical modeling of biomolecular interactions. In
     this study, we report the experimental measurements behind a SAMPL6 blind challenges in
     which we assess the ability of community codes to predict small molecule pKas for small
     molecule resembling fragments of selective kinase inhibitors.


  - title: "Acquired resistance to IDH inhibition through trans or cis dimer-interface mutations"
    authors: # Use same name in publication
    - Andrew M. Intlekofer
    - Alan H. Shih
    - Bo Wang
    - Abbas Nazir
    - Ariën S. Rustenburg
    - Steven K. Albanese
    - Minal Patel
    - Christopher Famulare
    - Fabian M. Correa
    - Naofumi Takemoto
    - Vidushi Durani
    - Hui Liu
    - Justin Taylor
    - Noushin Farnoud
    - Elli Papaemmanuil
    - Justin R. Cross
    - Martin S. Tallman
    - Maria E. Arcila
    - Mikhail Roshal
    - Gregory A. Petsko
    - Bin Wu
    - Sung Choe
    - Zenon D. Konteatis
    - Scott A. Biller
    - John D. Chodera
    - Craig B. Thompson
    - Ross L. Levine
    - Eytan M. Stein
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Craig B. Thompson
     - Ross L. Levine
     - Eytan M. Stein
    # Add these other fields are optional; fill in as much information as is available
    journal: Nature
    volume: 559
    page:  125 # just first page
    publication-date: 2018-07-05 # use ISO 8601 date format YYYY-MM-DD
    year: 2018
    # These links may be listed in the choderalab.org/publications/ page
    doi: https://doi.org/10.1038/s41586-018-0251-7
    PDF: http://www.choderalab.org/s/idh1-tljz.pdf
    funding: null
    description: >
     We probe the biochemical and biophysical mechanisms underlying an unusual set of clinical
     resistance mutations that appeared in trans in the IDH2 dimer interface in cancer patients
     treated with IDH2 inhibitors.


  - title: "Predicting resistance of clinical Abl mutations to targeted kinase inhibitors using alchemical free-energy calculations"
    authors: # Use same name in publication
    - Kevin Hauser
    - Christopher Negron
    - Steven K. Albanese
    - Soumya Ray
    - Thomas Steinbrecher
    - Robert Abel
    - John D. Chodera
    - Lingle Wang
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Lingle Wang
    # Add these other fields are optional; fill in as much information as is available
    journal: Communications Biology
    volume: 1
    page:  70 # just first page
    publication-date: 2018-06-13 # use ISO 8601 date format YYYY-MM-DD
    year: 2018
    # These links may be listed in the choderalab.org/publications/ page
    doi: https://doi.org/10.1038/s42003-018-0075-x
    PDF: http://www.choderalab.org/s/abl-resistance-mutations.pdf
    input files and analysis scripts: https://github.com/kehauser/Predicting-resistance-of-clinical-Abl-mutations-to-targeted-kinase-inhibitors-using-FEP
    funding:
    - NIH P30 CA008748
    - NIH R01 GM121505
    - Cycle For Survival
    description: >
     In our first collaborative paper with Schrödinger, we present the first comprehensive benchmark
     assessing the ability for alchemical free energy calculations to predict clinical mutational
     resistance or susceptibility to targeted kinase inhibitors using the well-studied kinase Abl,
     the target of therapy for chronic myelogenous leukemia (CML).


  - title: "Bayesian analysis of isothermal titration calorimetry for binding thermodynamics"
    authors: # Use same name in publication
    - Trung Hai Nguyen
    - Arien S. Rustenburg
    - Stefan G. Krimmer
    - Hexi Zhang
    - John D. Clark
    - Paul A. Novick
    - Kim Branson
    - Vijay S. Pande
    - John D Chodera
    - David D. L. Minh
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - John D Chodera
     - David D. L. Minh
    # Add these other fields are optional; fill in as much information as is available
    journal: PLoS One
    volume: 13
    publication-date: 2018-09-13 # use ISO 8601 date format YYYY-MM-DD
    year: 2018
    # These links may be listed in the choderalab.org/publications/ page
    doi: https://doi.org/10.1371/journal.pone.0203224
    bioRxiv: https://doi.org/10.1101/327676
    GitHub: https://github.com/choderalab/bayesian-itc
    funding: null
    description: >
     We show how Bayesian inference can produce greatly improved estimates of statistical uncertainty from isothermal
     titration calorimetry (ITC) experiments, allowing the joint distribution of thermodynamic parameter uncertainties
     to be inferred.


  - title: "Quantifying configuration-sampling error in Langevin simulations of complex molecular systems"
    authors: # Use same name in publication
    - Josh Fass
    - David Sivak
    - Gavin E. Crooks
    - Kyle A. Beauchamp
    - Benedict Leimkuhler
    - John D Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: entropy
    volume: 20
    page:  318  # just first page
    publication-date: 2018-04-26 # use ISO 8601 date format YYYY-MM-DD
    year: 2018
    # These links may be listed in the choderalab.org/publications/ page
    doi: https://doi.org/10.3390/e20050318
    PDF: https://choderalab.squarespace.com/s/langevin-entropy-54gc.pdf
    GitHub: https://github.com/choderalab/integrator-benchmark
    bioRxiv: https://doi.org/10.1101/266619
    funding:
    - NIH P30 CA008748
    - NIH R01 GM121505
    - NSF CHE 1738979
    description: >
     Molecular dynamics simulations necessarily use a finite timestep, which introduces error
     or bias in the sampled configuration space density that grows rapidly with increasing timestep.
     For the first time, we show how to compute a natural measure of this error---the KL
     divergence---in both phase and configuration space for a widely used family of Langevin
     integrators, and show that VRORV is generally superior for simulation of molecular systems.


  - title: "Escaping atom types in force fields using direct chemical perception"
    authors: # Use same name in publication
    - David L. Mobley
    - Caitlin C. Bannan
    - Andrea Rizzi
    - Christopher I. Bayly
    - John D Chodera
    - Victoria T Lim
    - Nathan M. Lim
    - Kyle A. Beauchamp
    - Michael R. Shirts
    - Michael K. Gilson
    - Peter K. Eastman
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - David L. Mobley
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Chemical Theory and Computation
    volume: 14
    page:  6076  # just first page
    publication-date: 2018-10-18 # use ISO 8601 date format YYYY-MM-DD
    year: 2018
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://doi.org/10.1021/acs.jctc.8b00640
    bioRxiv: https://doi.org/10.1101/286542
    funding:
    - NSF CHE 1738979
    description: >
     We describe the philosophy behind a modern approach to molecular mechanics forcefield
     parameterization, and present initial results for the first SMIRNOFF-encoded
     forcefield: SMIRNOFF99Frosst.


  - title: "A dynamic mechanism for allosteric activation of Aurora kinase A by activation loop phosphorylation"
    authors: # Use same name in publication
    - Emily F. Ruff
    - Joseph M. Muretta
    - Andrew Thompson
    - Eric W. Lake
    - Soreen Cyphers
    - Steven K. Albanese
    - Sonya M. Hanson
    - Julie M. Behr
    - David D. Thomas
    - John D. Chodera
    - Nicholas M. Levinson
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Nicholas M. Levinson
    # Add these other fields are optional; fill in as much information as is available
    journal: eLife
    volume: 7
    publication-date: 2018-02-21 # use ISO 8601 date format YYYY-MM-DD
    year: 2018
    # These links may be listed in the choderalab.org/publications/ page
    doi: https://doi.org/10.7554/eLife.32766
    bioRxiv: https://doi.org/10.1101/205260
    funding:
    - NIH P30 CA008748
    - NIH R01 GM121505
    description: >
     We show that, contrary to the canonical belief that activation shifts DFG-out to DFG-in
     populations, phosphorylation of AurA does not shift DFG-in/out equilibrium but instead
     remodels the conformational distribution of the DFG-in state.


  - title: "Quantitative self-assembly prediction yields targeted nanomedicines"
    authors: # Use same name in publication
    - Yosi Shamay
    - Janki Shah
    - Mehtap Işık
    - Aviram Mizrachi
    - Josef Leibold
    - Darjus F. Tschaharganeh
    - Daniel Roxbury
    - Januka Budhathoki-Uprety
    - Karla Nawaly
    - James L. Sugarman
    - Emily Baut
    - Michelle R. Neiman
    - Megan Dacek
    - Kripa S. Ganesh
    - Darren C. Johnson
    - Ramya Sridharan
    - Karen L. Chu
    - Vinagolu K. Rajasekhar
    - Scott W. Lowe
    - John D. Chodera
    - Daniel A. Heller
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Daniel A. Heller
    # Add these other fields are optional; fill in as much information as is available
    journal: Nature Materials
    volume: 17
    page: 361   # just first page
    publication-date: 2018-02-05 # use ISO 8601 date format YYYY-MM-DD
    year: 2018
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://doi.org/10.1038/s41563-017-0007-z
    PDF: https://choderalab.squarespace.com/s/nanoparticles.pdf
    Supporting Info: https://choderalab.squarespace.com/s/nanoparticles-si-zd77.pdf
    nano-drugbank: https://github.com/choderalab/nano-drugbank
    funding:
    - NIH P30 CA008748
    - Cycle For Survival
    description: >
     In a collaboration with the Heller Lab at MSKCC, we show how indocyanine nanoparticles can
     package insoluble selective kinase inhibitors with high mass loadings and efficiently
     deliver them to tumors.


  - title: "Biomolecular simulations under realistic macroscopic salt conditions"
    authors: # Use same name in publication
    - Gregory A. Ross
    - Ariën S. Rustenburg
    - Patrick B. Grinaway
    - Josh Fass
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Physical Chemistry B
    volume: 122
    page: 5466   # just first page
    publication-date: 2018-04-13 # use ISO 8601 date format YYYY-MM-DD
    year: 2018
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://doi.org/10.1021/acs.jpcb.7b11734
    bioRxiv: https://doi.org/10.1101/226001
    simulation code: https://github.com/choderalab/saltswap
    resuts and analysis scripts: https://github.com/choderalab/saltswap-results
    funding:
    - NIH P30 CA008748
    - NSF CHE 1738979
    description: >
     We show how NCMC can be used to implement an efficient osmostat in molecular dynamics
     simulations to model realistic fluctuations in ion environments around biomolecules, and
     illustrate how the local salt environment around biological macromolecules can differ
     substantially from bulk.


  - title: "Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes Using Nonequilibrium Candidate Monte Carlo"
    authors: # Use same name in publication
    - Samuel Gill
    - Nathan M. Lim
    - Patrick B. Grinaway
    - Ariën S. Rustenburg
    - Josh Fass
    - Gregory Ross
    - John D. Chodera
    - David Mobley
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - David Mobley
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Physical Chemistry B
    volume: 122
    page: 5578   # just first page
    publication-date: 2018-02-27 # use ISO 8601 date format YYYY-MM-DD
    year: 2018
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://doi.org/10.1021/acs.jpcb.7b11820
    ChemRxiv: https://chemrxiv.org/articles/Binding_Modes_of_Ligands_Using_Enhanced_Sampling_BLUES_Rapid_Decorrelation_of_Ligand_Binding_Modes_Using_Nonequilibrium_Candidate_Monte_Carlo/5406907
    GitHub: https://github.com/mobleylab/blues
    funding:
    - NIH P30 CA008748
    description: >
     Nonequilibrium candidate Monte Carlo can be used to accelerate the sampling of ligand
     binding modes by orders of magnitude over instantaneous Monte Carlo.


  - title: "OpenMM 7: Rapid Development of High Performance Algorithms for Molecular Dynamics"
    authors: # Use same name in publication
    - Peter Eastman
    - Jason Swails
    - John D. Chodera
    - Robert T. McGibbon
    - Yutong Zhao
    - Kyle A. Beauchamp
    - Lee-Ping Wang
    - Andrew C. Simmonett
    - Matthew P. Harrigan
    - Chaya D. Stern
    - Rafal P. Wiewiora
    - Bernard R. Brooks
    - Vijay S. Pande
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Peter Eastman
    # Add these other fields are optional; fill in as much information as is available
    journal: PLoS Computational Biology
    volume: 13
    publication-date: 2017-07-26 # use ISO 8601 date format YYYY-MM-DD
    year: 2017
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1371/journal.pcbi.1005659
    bioRxiv: http://biorxiv.org/content/early/2016/12/06/091801
    website: http://openmm.org/
    GitHub: https://github.com/pandegroup/openmm
    funding:
    - NIH P30 CA008748
    - Starr Foundation I8-A8-058
    description: >
     We describe the latest version of OpenMM, a GPU-accelerated framework for high performance
     molecular simulation applications.


  - title: "Approaches for calculating solvation free energies and enthalpies demonstrated with an update of the FreeSolv database"
    authors: # Use same name in publication
    - Guilherme Duarte Ramos Matos
    - Daisy Y. Kyu
    - Hannes H. Loeffler
    - John D. Chodera
    - Michael R. Shirts
    - David Mobley
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - David Mobley
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Chemical Engineering Data
    volume: 62
    page: 1559   # just first page
    publication-date: 2017-04-27 # use ISO 8601 date format YYYY-MM-DD
    year: 2017
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1021/acs.jced.7b00104
    bioRxiv: https://doi.org/10.1101/104281
    GitHub: https://github.com/mobleylab/freesolv
    funding:
    - NIH P30 CA008748
    description: >
     We review alchemical methods for computing solvation free energies and present an update
     (version 0.5) to the FreeSolv database of experimental and calculated hydration free
     energies of neutral compounds.


  - title: "L-2-Hydroxyglutarate production arises from noncanonical enzyme function at acidic pH"
    authors: # Use same name in publication
    - Intlekofer A
    - Wang B
    - Liu H
    - Shah H
    - Carmona-Fontaine C
    - Rustenburg AS
    - Salah S
    - Gunner MR
    - Chodera JD
    - Cross JR
    - Thompson CB
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Thompson CB
    # Add these other fields are optional; fill in as much information as is available
    journal: Nature Chemical Biology
    volume: 13
    page: 494   # just first page
    publication-date: 2017-03-06 # use ISO 8601 date format YYYY-MM-DD
    year: 2017
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1038/nchembio.2307
    PDF: https://choderalab.squarespace.com/s/nchembio2307.pdf
    GitHub: https://github.com/choderalab/LDHA-MCCE
    funding:
    - NIH P30 CA008748
    description: >
     At low pH, metabolic enzymes lactate dehydrogenase and malate dehydrogenase undergo shifts
     in substrate utilization that have high relevance to cancer metabolism due to surprisingly
     simple protonation state effects.


  - title: "A water-mediated allosteric network governs activation of Aurora kinase A"
    authors: # Use same name in publication
    - Cyphers S
    - Ruff E
    - Behr JM
    - Chodera JD
    - Levinson NM
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Levinson NM
    # Add these other fields are optional; fill in as much information as is available
    journal: Nature Chemical Biology
    volume: 13
    page: 402   # just first page
    publication-date: 2017-02-06 # use ISO 8601 date format YYYY-MM-DD
    year: 2017
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1038/nchembio.2296
    PDF: https://choderalab.squarespace.com/s/nchembio2296.pdf
    GitHub: https://github.com/choderalab/AurA-materials
    funding:
    - NIH P30 CA008748
    description: >
     Over 50 microseconds of aggregate simulation data on Folding@home reveal a surprisingly
     stable hydrogen bond network underlies allosteric activation by Tpx2.


  - title: "Mechanistically distinct cancer-associated mTOR activation clusters predict sensitivity to rapamycin"
    authors: # Use same name in publication
    - Xu Jianing
    - Pham CG
    - Albanese SK
    - Dong Yiyu
    - Oyama T
    - Lee CH
    - Rodrik-Outmezguine V
    - Yao Z
    - Han S
    - Chen D
    - Parton DL
    - Chodera JD
    - Rosen N
    - Cheng EH
    - Hsieh J
   # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Hsieh J
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Clinical Investigation
    volume: 126
    page: 3526   # just first page
    publication-date: 2016-08-02 # use ISO 8601 date format YYYY-MM-DD
    year: 2016
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1172/JCI86120
    PDF: https://choderalab.squarespace.com/s/JCI86120.pdf
    funding:
    - NIH P30 CA008748
    - Folding@Home
    description: >
     In work with the James Hsieh lab at MSKCC, we examine the surprising origin of how
     different clinically-identified cancer-associated mutations in MTOR activate the
     kinase through distinct mechanisms.


  - title: "Measuring experimental cyclohexane-water distribution coefficients for the SAMPL5 challenge"
    authors: # Use same name in publication
    - Ariën S. Rustenburg
    - Justin Dancer
    - Baiwei Lin
    - Jianweng A. Feng
    - Daniel F. Ortwine
    - David L. Mobley
    - John D. Chodera
   # Corresponding authors have their email addresses listed
    corresponding-authors:
     - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Computer-Aided Molecular Design
    volume: 30
    page: 945   # just first page
    publication-date: 2016-10-07 # use ISO 8601 date format YYYY-MM-DD
    year: 2016
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1007/s10822-016-9971-7
    bioRxiv: http://dx.doi.org/10.1101/063081
    PDF: http://biorxiv.org/content/early/2016/07/10/063081.full.pdf
    GitHub: https://github.com/choderalab/sampl5-experimental-logd-data
    funding:
    - NIH P30 CA008748
    description: >
     Solicited manuscript for special issue of the Journal of Computer Aided Molecular Design on
     the SAMPL5 Challenge.
     The SAMPL Challenges have driven predictive physical modeling for ligand:protein binding
     forward by focusing the community on a series of blind challenges that evaluate performance
     on blind datasets, focus attention on current challenges for physical modeling techniques,
     and provide high-quality experimental datasets to the community after the challenge is over.
     For many years, challenges focused around hydration free energies have proven to be extremely
     useful, with theory now able to determine when experiment is wrong. To replace these challenges,
     since no more hydration free energy data is being measured, we proposed to use the partition or
     distribution coefficients of small druglike molecules between aqueous and apolar phases. We
     report the collection of cyclohexane-water partition data for a set of compounds used to
     drive the SAMPL5 distribution coefficient challenge, providing the experimental data,
     methodology, and insight for future iterations of this challenge.


  - title: "Ensembler: Enabling high-throughput molecular simulations at the superfamily scale"
    authors: # Use same name in publication
    - Daniel L. Parton
    - Patrick B. Grinaway
    - Sonya M. Hanson
    - Kyle A. Beauchamp
    - John D. Chodera
   # Corresponding authors have their email addresses listed
    corresponding-authors:
     - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: PLoS Computational Biology
    volume: 12
    page: 6  # just first page
    publication-date: 2016-06-23 # use ISO 8601 date format YYYY-MM-DD
    year: 2016
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1371/journal.pcbi.1004728
    PDF: https://choderalab.squarespace.com/s/Ensembler-enabling-high-throughput-molecular-simulations-at-the-superfamily-scale.pdf
    bioRxiv: http://dx.doi.org/10.1101/018036
    Dryad: http://dx.doi.org/10.5061/dryad.7fg32
    GitHub: https://github.com/choderalab/ensembler
    funding: null
    description: >
     We demonstrate a new tool that enables---for the first time---massively parallel molecular
     simulation studies of biomolecular dynamics at the superfamily scale, illustrating its
     application to protein tyrosine kinases, an important class of drug targets in cancer.


  - title: "A simple method for automated equilibration detection in molecular simulations"
    authors: # Use same name in publication
    - John D. Chodera
   # Corresponding authors have their email addresses listed
    corresponding-authors:
     - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Chemical Theory and Computation
    volume: 12
    page: 1799  # just first page
    publication-date: 2016-01-15 # use ISO 8601 date format YYYY-MM-DD
    year: 2016
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1021/acs.jctc.5b00784
    PDF: https://choderalab.squarespace.com/s/A-simple-method-for-automated-equilibration-detection-in-molecular-simulations.pdf
    bioRxiv: http://dx.doi.org/10.1101/021659
    pymbar.timeseries: http://pymbar.org/
    GitHub: https://github.com/choderalab/automatic-equilibration-detection
    funding: null
    description: >
     We present a simple scheme for automatically selecting how much initial simulation data to
     discard to equilibration or burn-in based on maximizing the number of statistically uncorrelated
     samples in the dataset.
     Keywords: molecular simulation; molecular dynamics; burn-in; equilibration; production; analysis


  - title: "Modeling error in experimental assays using the bootstrap principle: Understanding discrepancies between assays using different dispensing technologies"
    authors: # Use same name in publication
    - Sonya M. Hanson
    - Sean Ekins
    - John D. Chodera
   # Corresponding authors have their email addresses listed
    corresponding-authors:
     - John D. Chodera
     # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Computer Aided Molecular Design
    volume: 29
    page: 1073  # just first page
    publication-date: 2015-12-17 # use ISO 8601 date format YYYY-MM-DD
    year: 2015
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1007/s10822-015-9888-6
    PDF: https://choderalab.squarespace.com/s/Modeling-error-in-experimental-assays-using-the-bootstrap-principle-understanding-discrepancies-betw.pdf
    bioRxiv: http://dx.doi.org/10.1101/033985
    GitHub: https://github.com/choderalab/dispensing-errors-manuscript/blob/master/notebooks/echo-vs-tips.ipynb
    Pipeline Blog Post: http://blogs.sciencemag.org/pipeline/archives/2013/05/03/drug_assay_numbers_all_over_the_place
    funding: null
    description: >
     The drug development community faced a puzzling challenge when a disturbing paper published in PLoS
     One demonstrated results from the same assay performed with different dispensing technologies both
     varied wildly and significantly different in magnitude of reported potencies. Inspired by a talk
     given at the 2014 CADD GRC by Cosma Shalizi on bootstrapping to model error, we show how this
     simple idea can help explain a large amount of the discrepancy in this assay, and provide
     simple mathematical tools and an IPython notebook illustrating how easy it is to model the
     error and bias in experimental assays even when other information about assay reliability
     is unavailable.


  - title: "Avoiding accuracy-limiting pitfalls in the study of protein-ligand interactions with isothermal titration calorimetry"
    authors: # Use same name in publication
    - Sarah E. Boyce
    - Joel Tellinghuisen
    - John D. Chodera
   # Corresponding authors have their email addresses listed
    corresponding-authors:
     - John D. Chodera
     # Add these other fields are optional; fill in as much information as is available
    journal: Manuscript prior to submission
    publication-date: 2015-08-03 # use ISO 8601 date format YYYY-MM-DD
    year: 2015
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1101/023796
    PDF Worksheet: https://choderalab.squarespace.com/s/itc-worksheet.pdf
    PDF: https://choderalab.squarespace.com/s/ITC-Worksheet-for-bovine-CAII-CBS.pdf
    XLSX: https://choderalab.squarespace.com/s/ITC-Worksheet-for-bovine-CAII-CBS.xlsx
    ODS: https://choderalab.squarespace.com/s/ITC-Worksheet-for-bovine-CAII-CBS.ods
    bioRxiv: http://dx.doi.org/10.1101/023796
    GitHub: https://github.com/choderalab/dispensing-errors-manuscript/blob/master/notebooks/echo-vs-tips.ipynb
    Pipeline Blog Post: http://blogs.sciencemag.org/pipeline/archives/2013/05/03/drug_assay_numbers_all_over_the_place
    funding: null
    description: >
     We show how to avoid common accuracy-limiting mistakes in isothermal titration calorimetry, and
     provide a simple spreadsheet to aid in propagating the dominant source of uncertainty
     (titrant concentration errors) into the resulting thermodynamic parameters.
     Keywords: isothermal titration calorimetry; ITC; propagation of error; entropy-enthalpy compensation


  - title: "Hypoxia induces production of L-2-hydroxyglutarate"
    authors: # Use same name in publication
    - Andrew M. Intlekofer
    - Raymond G. Dematteo
    - Sriram Venneti
    - Lydia W.S. Finley
    - Chao Lu
    - Alexander R. Judkins
    - Ariën S. Rustenburg
    - Patrick B. Grinaway
    - John D. Chodera
    -  Justin R. Cross
    - Craig B. Thompson
    - John D. Chodera
   # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Craig B. Thompson
     # Add these other fields are optional; fill in as much information as is available
    journal: Cell Metabolism
    volume: 22
    page: 304  # just first page
    publication-date: 2015-08-04 # use ISO 8601 date format YYYY-MM-DD
    year: 2015
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1016/j.cmet.2015.06.023
    PDF: https://choderalab.squarespace.com/s/Hypoxia-induces-production-of-L-2-hyroxyglutarate.pdf
    funding: null
    description: >
     None


  - title: "Towards Automated Benchmarking of Atomistic Forcefields: Neat Liquid Densities and Static Dielectric Constants from the ThermoML Data Archive"
    authors: # Use same name in publication
    - Kyle A. Beauchamp
    - Julie M. Behr
    - Ariën S. Rustenburg
    - Christopher I. Bayly
    - Kenneth Kroenlein
    - John D. Chodera
   # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Kyle A. Beauchamp
     - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Physical Chemistry B
    volume: 119
    page: 12912  # just first page
    publication-date: 2015-09-04 # use ISO 8601 date format YYYY-MM-DD
    year: 2015
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1021/acs.jpcb.5b06703
    PDF: https://choderalab.squarespace.com/s/benchmark-27z0.pdf
    GitHub: https://github.com/choderalab/LiquidBenchmark
    arXiv: http://arxiv.org/abs/1506.00262
    funding: none
    description: >
     Progress in forcefield validation and parameterization has been hindered by the availability
     of high-quality machine-readable physical property data for small organic molecules. We show
     how the NIST ThermoML dataset provides a solution to this problem, and demonstrate its utility
     in benchmarking the GAFF/AM1-BCC small molecule forcefield on neat liquid densities and static
     dielectric constants to uncover problems in the representation of low-dielectric environments.


  - title: "Markov state models of biomolecular conformational dynamics"
    authors: # Use same name in publication
    - John D. Chodera
    - Frank Noé
   # Corresponding authors have their email addresses listed
    corresponding-authors:
     - John D. Chodera
     - Frank Noé
    # Add these other fields are optional; fill in as much information as is available
    journal: Current Opinion in Structural Biology
    volume: 25
    page: 135  # just first page
    publication-date: 2014-04-01 # use ISO 8601 date format YYYY-MM-DD
    year: 2014
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1016/j.sbi.2014.04.002
    PDF: https://choderalab.squarespace.com/s/14_CurrOpin_ChoderaNoe_MSMReview.pdf
    funding: none
    description: >
     A review of the exciting developments in the stochastic modeling of biomolecular dynamics
     over the last few years.


  - title: "Spectral rate theory for two-state kinetics"
    authors: # Use same name in publication
    - Jan-Hendrik Prinz
    - John D. Chodera
    - Frank Noé
   # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Frank Noé
    # Add these other fields are optional; fill in as much information as is available
    journal: Physical Review X
    volume: 4
    publication-date: 2014-02-21 # use ISO 8601 date format YYYY-MM-DD
    year: 2014
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1103/PhysRevX.4.011020
    PDF: https://choderalab.squarespace.com/s/Spectral-rate-theory-of-two-state-kinetics.pdf
    funding: none
    description: >
     We present a new mathematical framework for unifying various two-state rate theories presented in the
     physical chemistry literature over many decades, and provide a quantitative way to measure reaction
     coordinate quality.


  - title: "Time step rescaling recovers continuous-time dynamical properties for discrete-time Langevin integration of nonequilibrium systems"
    authors: # Use same name in publication
    - David A. Sivak
    - John D. Chodera
    - Gavin E. Crooks
   # Corresponding authors have their email addresses listed
    corresponding-authors:
     - David A. Sivak
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Physical Chemistry B
    volume: 118
    page: 6466  # just first page
    publication-date: 2014-02-20 # use ISO 8601 date format YYYY-MM-DD
    year: 2014
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1021/jp411770f
    PDF: https://choderalab.squarespace.com/s/Time-step-rescaling-recovers-continuous-time-dynamical-properties-for-discrete-time-Langevin-intergr.pdf
    funding: none
    description: >
     We derive a simple, easy to implement Langevin integrator that has universally useful properties in
     molecular simulations.


  - title: "Identifying ligand binding sites and poses using GPU-accelerated Hamiltonian replica exchange molecular dynamics"
    authors: # Use same name in publication
    - Kai Wang K
    - John D. Chodera
    - Yanzhi Yang
    - Michael R. Shirts
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Michael R. Shirts
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Computer-Aided Molecular Design
    volume: 27
    page: 989  # just first page
    publication-date: 2013-12-03 # use ISO 8601 date format YYYY-MM-DD
    year: 2013
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1007/s10822-013-9689-8
    PDF: https://choderalab.squarespace.com/s/J-Comput-Aided-Mol-Des-2013-Wang.pdf
    funding: none
    description: >
     We show how bound ligand poses can be identified even when the location of the binding sites
     are unknown using the machinery of alchemical modern free energy calculations on graphics
     processors.


  - title: "Systematic improvement of a classical molecular model of water"
    authors: # Use same name in publication
    - Lee-Ping Wang
    - Teresa L. Head-Gordon
    - Jay W. Ponder
    - Pengyu Ren
    - John D. Chodera
    - Peter K. Eastman
    - Todd J. Martinez
    - Vijay S. Pande
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Vijay S. Pande
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Physical Chemistry B
    volume: 117
    page: 9956  # just first page
    publication-date: 2013-06-11 # use ISO 8601 date format YYYY-MM-DD
    year: 2013
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1021/jp403802c
    PDF: https://choderalab.squarespace.com/s/Systematic-improvement-of-a-classical-molecular-model-of-water.pdf
    funding: none
    description: >
     A new inexpensive polarizable model of liquid water for next-generation forcefields is derived using an
     automated parameterization engine.


  - title: "Entropy-enthalpy compensation: Role and ramifications for rational ligand design"
    authors: # Use same name in publication
    - John D. Chodera
    - David L. Mobley
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - John D. Chodera
     - David L. Mobley
    # Add these other fields are optional; fill in as much information as is available
    journal: Annual Review of Biophysics
    volume: 42
    page: 121  # just first page
    publication-date: 2013-05-01 # use ISO 8601 date format YYYY-MM-DD
    year: 2013
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1146/annurev-biophys-083012-130318
    PDF: https://choderalab.squarespace.com/s/Annu-Rev-Biophys-2013-Chodera.pdf
    funding: none
    description: >
     Entropy-enthalpy compensation is likely a universal phenomena, but not as severe as widely thought, and
     likely not of enormous concern for drug discovery and ligand design.


  - title: "Using nonequilibrium fluctuation theorems to understand and correct errors in equilibrium and nonequilibrium discrete Langevin dynamics simulations"
    authors: # Use same name in publication
    - David A. Sivak
    - John D. Chodera
    - Gavin E. Crooks
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - David A. Sivak
    # Add these other fields are optional; fill in as much information as is available
    journal: Physical Review X
    volume: 3
    publication-date: 2013-01-29 # use ISO 8601 date format YYYY-MM-DD
    year: 2013
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1103/PhysRevX.3.011007
    PDF: https://choderalab.squarespace.com/s/using-nonequilibrium-flucuation-theorems-to-understand-and-correct-errors-in-equilibrium-and-nonequi.pdf
    funding:
    description: >
     The finite-timestep errors in molecular dynamics simulations can be interpreted as a form of
     nonequilibrium work.  We show how this leads to straightforward schemes for correcting for these errors
     or assessing their impact. Keywords: velocity verlet with Velocity randomization; VVVR; nonequilibrium
     free energy; integrator error; nonequilibrium integration


  - title: "OpenMM 4: A reusable, extensible, hardware independent library for high performance molecular simulation"
    authors: # Use same name in publication
    - Peter Eastman
    - Mark S. Friedrichs
    - John D. Chodera
    - Randy J. Radmer
    - Chris M. Bruns
    - Joy P. Ku
    - Kyle A. Beauchamp
    - T. J. Lane
    - Lee-Ping Wang
    - Diwakar Shukla
    - Tony Tye
    - Mike Houston
    - Timo Stich
    - Christoph Klein
    - Michael R. Shirts
    - Vijay S. Pande
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Peter Eastman
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Chemical Theory and Computation
    volume: 9
    page: 461  # just first page
    publication-date: 2012-10-18 # use ISO 8601 date format YYYY-MM-DD
    year: 2012
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1021/ct300857j
    PDF: https://choderalab.squarespace.com/s/openmm-4-a-reusableextensible-hardware-independent-library-for-high-performance-molecular-simulation.pdf
    funding: none
    description: >
     We describe the latest version of an open-source, GPU-accelerated library and toolkit for molecular simulation.


  - title: "The limitations of constant-force-feedback experiments"
    authors: # Use same name in publication
    - Phillip J. Elms
    - John D. Chodera
    - Carlos J. Bustamante
    - Susan Marqusee
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Susan Marqusee
    # Add these other fields are optional; fill in as much information as is available
    journal: National Academy of Sciences
    volume: 103
    page: 3796  # just first page
    publication-date: 2012-03-06 # use ISO 8601 date format YYYY-MM-DD
    year: 2012
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1073/pnas.1115519109
    PDF: https://choderalab.squarespace.com/s/PNAS-2012-Elms-3796-801.pdf
    funding: none
    description: >
     Popular constant-force-feedback single-molecule experiments can cause severe artifacts in
     single-molecule force spectroscopy data.  We demonstrate a simple alternative that eliminates
     these artifacts.


  - title: "On the use of experimental observations to bias simulated ensembles"
    authors: # Use same name in publication
    - Jed W. Pitera
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     -Jed W. Pitera
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Chemical Theory and Computation
    volume: 8
    page: 3445  # just first page
    publication-date: 2012-08-21 # use ISO 8601 date format YYYY-MM-DD
    year: 2012
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1021/ct300112v
    PDF: https://choderalab.squarespace.com/s/on-the-use-of-experimental-observations-to-bias-simulated-ensembles.pdf
    funding: none
    description: >
     We show how the concept of maximum entropy can be used to recover unbiased conformational distributions
     from experimental data, and how this concept relates to the popular `ensemble refinement' schemes for
     NMR data analysis.


  - title: "The molten globule state is unusually deformable under mechanical force"
    authors: # Use same name in publication
    - Philip J. Elms
    - John D. Chodera
    - Carlos Bustamante
    - Susan Marqusee
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Susan Marqusee
    # Add these other fields are optional; fill in as much information as is available
    journal: Proceedings of the National Academy of Sciences USA
    volume: 109
    page: 3796  # just first page
    publication-date: 2012-03-06 # use ISO 8601 date format YYYY-MM-DD
    year: 2012
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1073/pnas.1115519109
    PDF: https://choderalab.squarespace.com/s/the-molten-globule-state-is-unusually-deformable-under-mechanical-force.pdf
    funding: none
    description: >
     We measure the physical properties of the molten globule state of apo-myoglobin, and
     show that it is unusually deformable compared to typical protein native states.


  - title: "Replica exchange and expanded ensemble simulations as Gibbs sampling: Simple improvements for enhanced mixing"
    authors: # Use same name in publication
    - John D. Chodera
    - Michael R. Shirts
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     -  Michael R. Shirts
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Chemical Physics
    volume: 135
    page: 194110  # just first page
    publication-date: 2011-11-21 # use ISO 8601 date format YYYY-MM-DD
    year: 2011
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1063/1.3660669
    PDF: https://choderalab.squarespace.com/s/replica-exchange-and-expanded-ensemble-simulations-as-gibbs-sampling-simple-improvements-for-enhance.pdf
    funding: none
    description: >
     We show how a simple change to the way exchanges are handled in the popular replica-exchange
     simulation methodology can enormously increase efficiency at no increase in computational cost.


  - title: "The ribosome modulates nascent protein folding"
    authors: # Use same name in publication
    - Christian M. Kaiser
    - Daniel H. Goldman
    - John D. Chodera
    - Ignacio Tinoco Jr.
    - Carlos Bustamante
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Carlos Bustamante
    # Add these other fields are optional; fill in as much information as is available
    journal: Science
    volume: 334
    page: 1723 # just first page
    publication-date: 2011-12-23 # use ISO 8601 date format YYYY-MM-DD
    year: 2011
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1063/1.3660669
    PDF: https://choderalab.squarespace.com/s/replica-exchange-and-expanded-ensemble-simulations-as-gibbs-sampling-simple-improvements-for-enhance.pdf
    funding: none
    description: >
     Using single-molecule force spectroscopy, we show how the ribosome itself modulates the folding
     dynamics of nascent protein chains emerging from the exit tunnel.


  - title: "Nonequilibrium candidate Monte Carlo is an efficient tool for equilibrium simulation"
    authors: # Use same name in publication
    - Jerome P. Nilmeier
    - Gavin E. Crooks
    - David D. L. Minh
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Proceedings of the National Academy of Sciences USA
    volume: 108
    page: 1009 # just first page
    publication-date: 2011-11-08 # use ISO 8601 date format YYYY-MM-DD
    year: 2011
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1073/pnas.1106094108
    PDF: https://choderalab.squarespace.com/s/nonequilibrium-candidate-monte-carlo-is-an-effecient-tool-for-equilibrium-simulation.pdf
    funding: none
    description: >
     We present a significant generalization of Monte Carlo methods that provide an enormously useful
     tool for enhancing the efficiency of molecular simulations and enabling molecular design. Keywords: NCMC;
     Monte Carlo; Metropolis-Hastings; acceptance rates; molecular dynamics


  - title: "Splitting probabilities as a test of reaction coordinate choice in single-molecule experiments"
    authors: # Use same name in publication
    - John D. Chodera
    - Vijay S. Pande
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Vijay S. Pande
    # Add these other fields are optional; fill in as much information as is available
    journal: Physical Review Letters
    volume: 107
    page: 098102 # just first page
    publication-date: 2011-08-23 # use ISO 8601 date format YYYY-MM-DD
    year: 2011
    # These links may be listed in the choderalab.org/publications/ page
    doi: http://dx.doi.org/10.1103/PhysRevLett.107.098102
    PDF: https://choderalab.squarespace.com/s/spitting-probabilities-as-a-test-of-reaction-coordinate-choice-in-single-molecule-experiments.pdf
    funding: none
    description: >
     We demonstrate a simple test for identifying poor reaction coordinates in single-molecule experiments.


  - title: "A robust approach to estimating rates from time-correlation functions"
    authors: # Use same name in publication
    - John D. Chodera
    - Phillip J. Elms
    - William C. Swope
    - Jan-Hendrik Prinz
    - Susan Marqusee
    - Carlos Bustamante
    - Frank Noé
    - Vijay S. Pande
   # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Vijay S. Pande
    # Add these other fields are optional; fill in as much information as is available
    journal: Preprint ahead of submission
    publication-date: 2011-08-10 # use ISO 8601 date format YYYY-MM-DD
    year: 2011
    # These links may be listed in the choderalab.org/publications/ page
    arXiov: https://arxiv.org/abs/1108.2304
    PDF: https://arxiv.org/pdf/1108.2304.pdf
    SI: https://arxiv.org/src/1108.2304v1/anc/rate-theory-supplementary.pdf
    funding: none
    description: >
     The estimation of rates from experimental single-molecule data is fraught with peril. We
     describe some of the failures of existing methods and suggest a robust way to estimate
     rates from time-correlation functions.


  - title: "The Social Network (of protein conformations)"
    authors: # Use same name in publication
    - John D. Chodera
    - Vijay S. Pande
   # Corresponding authors have their email addresses listed
    corresponding-authors:
     - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Proceedings of the National Academy of Sciences USA
    volume: 108
    page: 12969 # just first page
    publication-date: 2011-07-29 # use ISO 8601 date format YYYY-MM-DD
    year: 2011
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1073/pnas.1109571108
    PDF: https://choderalab.squarespace.com/s/the-social-network-of-protein-conformations.pdf
    funding: none
    description: >
     Commentary: A new methodology for mapping protein conformational spaces is reminiscent of how we
     use two-dimensional maps to navigate a three-dimensional world.


  - title: "Bayesian hidden Markov model analysis of single-molecule force spectroscopy: Characterizing kinetics under measurement uncertainty"
    authors: # Use same name in publication
    - John D. Chodera
    - Phillip Elms
    - Frank Noé
    - Bettina Keller
    - Christian M. Kaiser
    - Aaron Ewall-Wice
    - Susan Marqusee
    - Carlos Bustamante
    - Nina Singhal Hinrichs
   # Corresponding authors have their email addresses listed
    corresponding-authors:
     - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: preprint
    publication-date: 2011-08-06 # use ISO 8601 date format YYYY-MM-DD
    year: 2011
    # These links may be listed in the choderalab.org/publications/ page
    arXiv: http://arxiv.org/abs/1108.1430
    funding: none
    description: >
     We describe the general theory and implementation for a Bayesian extension of hidden Markov models
     applicable to the characterization of how measurement uncertainty and finite statistics can impact
     the confidence in rate constants and conformational state properties.



  - title: "Systematic errors in isothermal titration calorimetry: Concentrations and baselines"
    authors: # Use same name in publication
    - Joel T. Tellinghuisen
    - John D. Chodera
   # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Joel T. Tellinghuisen
    # Add these other fields are optional; fill in as much information as is available
    journal: Analytical Biochemistry
    volume: 414
    page: 297 # just first page
    publication-date: 2011-07-15 # use ISO 8601 date format YYYY-MM-DD
    year: 2011
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1016/j.ab.2011.03.024
    PDF: https://choderalab.squarespace.com/s/systematic-errors-in-isothermal-titration-calorimetry-concentrations-and-baselines.pdf
    funding: none
    description: >
     A word of caution about large errors in isothermal titration calorimetry measurements arising from
     ligand concentration errors.


  - title: "Dynamical reweighting: Improved estimates for dynamical properties from simulations at multiple temperatures"
    authors: # Use same name in publication
    - John D. Chodera
    - William C. Swope
    - Frank Noé
    - Jan-Hendrik Prinz
    - Michael R. Shirts
    - Vijay S. Pande
   # Corresponding authors have their email addresses listed
    corresponding-authors:
     - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Chemical Physics
    volume: 134
    page:  244107 # just first page
    publication-date: 2011-06-24 # use ISO 8601 date format YYYY-MM-DD
    year: 2011
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1063/1.3592152
    PDF: https://choderalab.squarespace.com/s/Dynamical-reweighting-improved-estimates-of-dynamical-propeerties-from-simulations-at-multiple-tempe.pdfines.pdf
    funding: none
    description: >
     We describe how reweighing techniques can provide optimal estimates of temperature-dependent dynamical
     properties from simulations conducted at multiple temperatures.


  - title: "Optimal use of data in parallel tempering simulations for the construction of discrete-state Markov models of biomolecular dynamics"
    authors: # Use same name in publication
    - Jan-Hendrik Prinz
    - John D. Chodera
    - Vijay S. Pande
    - Jeremy C. Smith
    - Frank Noé
   # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Jan-Hendrik Prinz
     - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Chemical Physics
    volume: 134
    page:  244108 # just first page
    publication-date: 2011-06-24 # use ISO 8601 date format YYYY-MM-DD
    year: 2011
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1063/1.3592153
    PDF: https://choderalab.squarespace.com/s/optimal-use-of-data-in-parallel-tempering-simulations-for-the-construction-of-discrete-state-markov.pdf
    funding: none
    description: >
     None


  - title: "Markov models of molecular kinetics: Generation and validation"
    authors: # Use same name in publication
    - Jan-Hendrik Prinz
    - Hao Wu
    - Marco Sarich
    - Bettina Keller
    - Martin Fischbach
    - Martin Held
    - John D. Chodera
    - Christof Schüttle
    - Frank Noé
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Frank Noé
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Chemical Physics
    volume: 134
    page:  174105 # just first page
    publication-date: 2011-05-04 # use ISO 8601 date format YYYY-MM-DD
    year: 2011
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1063/1.3565032
    PDF: https://choderalab.squarespace.com/s/markov-models-of-molecular-kinetics-generation-and-validation.pdf
    funding: none
    description: >
     A review of current best practices for the generation and validation of Markov state models for
     describing the stochastic dynamics of biomolecular systems.


  - title: "Machine learning force fields and coarse-grained variables in molecular dynamics: application to materials and biological systems"
    authors: # Use same name in publication
    - Paraskevi Gkeka
    - Gabriel Stoltz
    - Amir Barati Farimani
    - Zineb Belkacemi
    - Michele Ceriotti
    - John Chodera
    - Aaron R Dinner
    - Andrew Ferguson
    - Jean-Bernard Maillet
    - Hervé Minoux
    - Christine Peter
    - Fabio Pietrucci
    - Ana Silveira
    - Alexandre Tkatchenko
    - Zofia Trstanova
    - Rafal Wiewiora
    - Tony Lelièvre
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Paraskevi Gkeka
     - Gabriel Stoltz
     - Tony Lelièvre
    # Add these other fields are optional; fill in as much information as is available
    journal: arXiv preprint
    volume: 2004
    publication-date: 2020-04-15 # use ISO 8601 date format YYYY-MM-DD
    year: 2020
    # These links may be listed in the choderalab.org/publications/ page
    PDF: https://arxiv.org/pdf/2004.06950
    funding: none
    description: >
     Machine learning encompasses a set of tools and algorithms which are now becoming popular in almost
     all scientific and technological fields. This is true for molecular dynamics as well, where machine
     learning offers promises of extracting valuable information from the enormous amounts of data
     generated by simulation of complex systems. We provide here a review of our current understanding
     of goals, benefits, and limitations of machine learning techniques for computational studies on
     atomistic systems, focusing on the construction of empirical force fields from ab-initio
     databases and the determination of reaction coordinates for free energy computation and enhanced
     sampling.


  - title: "Free energy methods in drug discovery and design: Progress and challenges"
    authors: # Use same name in publication
    - John D. Chodera
    - David L. Mobley
    - Michael R. Shirts
    - Richard W. Dixon
    - Kim M. Branson
    - Vijay S. Pande
    # Corresponding authors have their email addresses listed
    corresponding-authors:
     - Vijay S. Pande
    # Add these other fields are optional; fill in as much information as is available
    journal: Current Opinion in Structural Biology
    volume: 21
    page: 150  # just first page
    publication-date: 2011-04-01 # use ISO 8601 date format YYYY-MM-DD
    year: 2011
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1016/j.sbi.2011.01.011
    PDF: http://www.choderalab.org/s/free-energy-methods-in-drug-discovery-and-design-progress-and-challenges.pdf
    funding: none
    description: >
     A review of the opportunities and challenges for alchemical free energy calculations in drug discovery
     and design.


  - title: "Dynamical fingerprints: A theoretical framework for understanding biomolecular processes by combination of simulation and kinetic experiments"
    authors: # Use same name in publication
    - Frank Noé
    - Sören Doose
    - Isabella Daidone
    - Marc Löllmann
    - Markus Sauer
    - John D. Chodera
    - Jeremy C. Smith
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Frank Noé
    # Add these other fields are optional; fill in as much information as is available
    journal: Proceedings of the National Academy of Sciences USA
    volume: 108
    page: 4822  # just first page
    publication-date: 2011-03-22 # use ISO 8601 date format YYYY-MM-DD
    year: 2011
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1073/pnas.1004646108
    PDF: http://www.choderalab.org/s/dynamical-fingerprints-a-theoretical-framework-for-understanding-biomolecular-processes-by-combinati.pdf
    funding: none
    description: >
     We present a new framework for comparing essential features of the dynamics between experiment and
     simulation to identify the kinetics processes contributing to individual relaxation timescales in
     perturbation-response or correlation spectroscopy experiments.


  - title: "Estimating equilibrium ensemble averages using multiple time slices from driven nonequilibrium processes"
    authors: # Use same name in publication
    - David D. L. Minh
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Chemical Physics
    volume: 134
    publication-date: 2011-01-12 # use ISO 8601 date format YYYY-MM-DD
    year: 2011
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1063/1.3516517
    PDF: http://www.choderalab.org/s/Estimating-equilibrium-ensemble-averages-using-multiple-time-slices-from-driven-nonequilibrium-proce.pdf
    funding: none
    description: >
     We derive a new estimator for estimating equilibrium expectations from nonequilibrium experiments,
     and show how it can be used to estimate a variety of useful quantities in simulated single-molecule
     force spectroscopy experiments.


  - title: "Probability distributions of molecular observables computed from Markov models. II. Uncertainties in observables and their time-evolution"
    authors: # Use same name in publication
    - Frank Noé
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Frank Noé
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Chemical Physics
    volume: 133
    page:   # just first page
    publication-date: 2010-09-08 # use ISO 8601 date format YYYY-MM-DD
    year: 2010
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1063/1.3463406
    PDF: http://www.choderalab.org/s/probability-distributions-of-molecular-observables-computed-from-Markov-models.pdf
    funding: none
    description: >
     A simple Bayesian approach for the modeling of statistical uncertainties in kinetic and equilibrium
     quantities computed from Markov state models of biomolecular dynamics.


  - title: "The mechanical properties of PCNA: Implications for the loading and function of a DNA sliding clamp"
    authors: # Use same name in publication
    - Joshua L. Adelman
    - John D. Chodera
    - I. W. Kuo
    - Thomas F. Miller III
    - Daniel Barsky
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Daniel Barsky
    # Add these other fields are optional; fill in as much information as is available
    journal: Biophysical Journal
    volume: 98
    page: 3062  # just first page
    publication-date: 2010-06-16 # use ISO 8601 date format YYYY-MM-DD
    year: 2010
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1016/j.bpj.2010.03.056
    PDF: http://www.choderalab.org/s/the-mechanical-properties-of-PCNA-implications-for-the-loading-and-function-of-a-DNA-sliding-clamp.pdf
    funding: none
    description: >
     Molecular simulations of the PCNA clamp responsible for DNA polymerase processivity show a surprisingly
     small energetic penalty for the deformation required for clamp loading.


  - title: "Current status of the AMOEBA polarizable force field"
    authors: # Use same name in publication
    - Jay W. Ponder
    - Chuanjie Wu
    - Pengyu Ren
    - Vijay S. Pande
    - John D. Chodera
    - Joshua L. Adelman
    - John D. Chodera
    - David L. Mobley
    - Michael J. Schnieders
    - Imran Haque
    - David S. Lambrecht
    - Robert A. DiStasio Jr.
    - Martin Head-Gordon
    - Gary N. I. Clark
    - Margaret E. Johnson
    - Teresa Head-Gordon
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Teresa Head-Gordon
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Physical Chemistry B
    volume: 114
    page: 2549  # just first page
    publication-date: 2010-02-05 # use ISO 8601 date format YYYY-MM-DD
    year: 2010
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1021/jp910674d
    PDF: http://www.choderalab.org/s/current-status-of-the-AMOEBA-polarizable-force-field.pdf
    funding: none
    description: >
     A report on the status of the AMOEBA polarizable force field and its ability to reproduce a diverse
     set of physical chemical phenomenon to high accuracy.


  - title: "Optimal estimators and asymptotic variances for nonequilibrium path-ensemble averages"
    authors: # Use same name in publication
    - David D. D. L. Minh
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Chemical Physics
    volume: 131
    page: 134110  # just first page
    publication-date: 2009-10-06 # use ISO 8601 date format YYYY-MM-DD
    year: 2009
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1063/1.3242285
    PDF: http://www.choderalab.org/s/optimal-estimators-and-asymptotic-variances-for-nonequilibrium-path-ensemble-averages.pdf
    funding: none
    description: >
     We derive an optimal estimator and corresponding statistical uncertainties for inferring expectations
     of bidirectional nonequilibrium processes.  These estimators have widespread applicability in
     single-molecule biophysical force-spectroscopy experiments and nonequilibrium molecular simulations.



  - title: "Bayesian comparison of Markov models of molecular dynamics with detailed balance constraint"
    authors: # Use same name in publication
    - Sergio Bacallado
    - John D. Chodera
    - Vijay S. Pande
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Vijay S. Pande
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Chemical Physics
    volume: 131
    page: 045106  # just first page
    publication-date: 2009-07-30 # use ISO 8601 date format YYYY-MM-DD
    year: 2009
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1063/1.3192309
    PDF: http://www.choderalab.org/s/Bayesian-comparison-of-Markov-models-of-molecular-dynamics-with-detailed-balance-constraint.pdf
    funding: none
    description: >
     A Bayesian scheme for comparing state space decompositions for Markov state models of biomolecular
     dynamics that incorporates the fact that physical systems must obey detailed balance.  This paper
     utilizes recent results from Markov chain theory on edge-reinforced random walks.


  - title: "Statistically optimal analysis of samples from multiple equilibrium states"
    authors: # Use same name in publication
    - Michael R. Shirts
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Chemical Physics
    volume: 129
    page: 124105  # just first page
    publication-date: 2008-09-23 # use ISO 8601 date format YYYY-MM-DD
    year: 2008
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1063/1.2978177
    PDF: http://www.choderalab.org/s/MBAR-paper.pdf
    funding: none
    description: >
     We present a highly general, statistically optimal approach for producing estimates of free energies
     and equilibrium expectations from multiple simulations that provably extracts all useful information
     from the data. Keywords: Multistate Bennett acceptance ratio; MBAR; Bennett acceptance ratio;
     BAR; molecular dynamics; Monte Carlo; replica exchange


  - title: "Technical Report: Self-consistent definition and computation of the electrostatic field for the Amber and related forcefields with particle-mesh Ewald"
    authors: # Use same name in publication
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Technical Report
    publication-date: 2008-05-22 # use ISO 8601 date format YYYY-MM-DD
    year: 2008
    # These links may be listed in the choderalab.org/publications/ page
    PDF: http://www.choderalab.org/s/pme-field.pdf
    funding: none
    description: >
     This technical report provides information on the computation of the electric field and its gradient
     for the Amber forcefield in particle-mesh Ewald (PME) in AMBER 10.


  - title: "Predicting small-molecule solvation free energies: A blind challenge test for computational chemistry"
    authors: # Use same name in publication
    - Anthony Nicholls
    - David L. Mobley
    - J. Peter Guthrie
    - John D. Chodera
    - Vijay S. Pande
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Anthony Nicholls
    - David L. Mobley
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Medicinal Chemistry
    volume: 51
    page: 769  # just first page
    publication-date: 2008-01-24 # use ISO 8601 date format YYYY-MM-DD
    year: 2008
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1021/jm070549+
    PDF: http://www.choderalab.org/s/predicting-small-molecule-solvation-free-energies-a-blind-challenge-test-for-computational-chemistry.pdf
    funding: none
    description: >
     A blind evaluation of the accuracy of alchemical free energy methods for computing gas-to-water
     transfer free energies (solvation free energies) of small molecules demonstrates that modern
     forcefields are likely sufficiently accurate to be useful in drug design.


  - title: "Treating entropy and conformational changes in implicit solvent simulations of small molecules"
    authors: # Use same name in publication
    - David L. Mobley
    - John D. Chodera
    - Ken A. Dill
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - David L. Mobley
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Physical Chemistry B
    volume: 112
    page: 938  # just first page
    publication-date: 2008-01-03 # use ISO 8601 date format YYYY-MM-DD
    year: 2008
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1021/jp0764384
    PDF: http://www.choderalab.org/s/treating-entropy-and-conformational-changes-in-implicit-slovent-simulations-of-small-molecules.pdf
    funding: none
    description: >
     A quantitative examination of how much conformational entropy contributes to hydration free energies of
     small molecules, with implications for ligand binding.


  - title: "Accurate and efficient corrections for missing dispersion interactions in molecular simulations"
    authors: # Use same name in publication
    - Michael R. Shirts
    - David L. Mobley
    - John D. Chodera
    - Vijay S. Pande
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - David L. Mobley
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Physical Chemistry B
    volume: 111
    page: 13052  # just first page
    publication-date: 2007-10-19 # use ISO 8601 date format YYYY-MM-DD
    year: 2007
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1021/jp0735987
    PDF: http://www.choderalab.org/s/accurate-and-efficient-corrections-for-missing-dispersion-interactions-in-molecular-simulations.pdf
    funding: none
    description: >
     We identify a major source of systematic error in absolute alchemical free energy calculations of
     ligand binding and show how a simple procedure can inexpensively and accurately eliminate it.


  - title: "Alchemical free energy calculations: Ready for prime time?"
    authors: # Use same name in publication
    - Michael R. Shirts
    - David L. Mobley
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Michael R. Shirts
    - David L. Mobley
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Annual Reports in Computational Chemistry
    volume: 3
    page: 41  # just first page
    publication-date: 2007-12-01 # use ISO 8601 date format YYYY-MM-DD
    year: 2007
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1016/S1574-1400(07)03004-6
    PDF: http://www.choderalab.org/s/alchemical-free-energy-calculations-ready-for-prime-time.pdf
    funding: none
    description: >
     A review of current alchemical free energy methodologies assessing whether they are ready for
     practical use in drug discovery and ligand design.


  - title: "Predicting absolute ligand binding free energies to a simple model site"
    authors: # Use same name in publication
    - David L. Mobley
    - Alan P. Graves
    - John D. Chodera
    - Andrea C. McReynolds
    - Brian K. Shoichet
    - Ken A. Dill
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Brian K. Shoichet
    - Ken A. Dill
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Molecular Biology
    volume: 371
    page: 1118  # just first page
    publication-date: 2007-08-24 # use ISO 8601 date format YYYY-MM-DD
    year: 2007
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1016/j.jmb.2007.06.002
    PDF: http://www.choderalab.org/s/predicting-absolute-ligand-binding-free-energies-to-a-simple-model-site.pdf
    funding: none
    description: >
     We show how alchemical free energy calculations are capable of accurate blind prediction of
     small-molecule binding affinities to a simple model protein binding site.


  - title: "The protein folding problem: When will it be solved?"
    authors: # Use same name in publication
    - Ken A. Dill
    - S. Banu Ozkan
    - Thomas R. Weikl
    - John D. Chodera
    - Vincent A. Voelz
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Ken A. Dill
    # Add these other fields are optional; fill in as much information as is available
    journal: Current Opinion in Structural Biology
    volume: 17
    page: 342  # just first page
    publication-date: 2007-06-01 # use ISO 8601 date format YYYY-MM-DD
    year: 2007
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1016/j.sbi.2007.06.001
    PDF: http://www.choderalab.org/s/the-protein-folding-problem-when-will-it-be-solved.pdf
    funding: none
    description: >
     A review of the current state of the protein folding problem.


  - title: "Confine-and-release method: Obtaining correct binding free energies in the presence of protein conformational change"
    authors: # Use same name in publication
    - David L. Mobley
    - John D. Chodera
    - Ken A. Dill
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Ken A. Dill
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Chemical Theory and Computation
    volume: 3
    page: 1231  # just first page
    publication-date: 2007-05-23 # use ISO 8601 date format YYYY-MM-DD
    year: 2007
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1021/ct700032n
    PDF: http://www.choderalab.org/s/confine-and-release-method-obtaining-correct-binding-free-energies-in-the-prescence-of-protein-confo.pdf
    funding: none
    description: >
     We present a general scheme for obtaining correct ligand binding affinities when protein
     conformational change is implicated in ligand binding


  - title: "Protein Folding by Zipping and Assembly"
    authors: # Use same name in publication
    - S. Banu Ozkan
    - G. Albert Wu
    - John D. Chodera
    - Ken A. Dill
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Ken A. Dill
    # Add these other fields are optional; fill in as much information as is available
    journal: Proceedings of the National Academy of Sciences USA
    volume: 104
    page: 11987  # just first page
    publication-date: 2007-07-17
    # use ISO 8601 date format YYYY-MM-DD
    year: 2007
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1073/pnas.0703700104
    PDF: http://www.choderalab.org/s/protein-folding-by-zipping-and-assembly.pdf
    funding: none
    description: >
     A review of the utility of the proposed zipping and assembly mechanism for the concomitant formation
     of secondary and tertiary structure in protein folding for predicting folding pathways and native
     structures.


  - title: "Automatic discovery of metastable states for the construction of Markov models of macromolecular conformational dynamics"
    authors: # Use same name in publication
    - John D. Chodera
    - Nina Singhal
    - William C. Swope
    - Jed W. Pitera
    - Vijay S. Pande
    - Ken A. Dill
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - William C. Swope
    # Add these other fields are optional; fill in as much information as is available
    journal: Jouyrnal of Chemical Physics
    volume: 126
    page: 155191  # just first page
    publication-date: 2007-04-19
    # use ISO 8601 date format YYYY-MM-DD
    year: 2007
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1063/1.2714538
    PDF: http://www.choderalab.org/s/automatic-discovery-of-metastable-states-for-the-construction-of-markov-models-of-macromolecular-con.pdf
    funding: none
    description: >
     Proposing one of the first automated algorithms for discovering kinetically metastable states of
     biomolecules from molecular simulations, this paper shows how many biomolecules can possess
     numerous distinct long-lived conformational states even though the the equilibrium populations of
     these states may too small for standard structural biology techniques to detect.


  - title: "Comparison of charge models for fixed-charge force fields: Small-molecule hydration free energies in explicit solvent"
    authors: # Use same name in publication
    - David L. Mobley
    - Élise Dumont
    - John D. Chodera
    - Christopher I. Bayly
    - Matthew D. Cooper
    - Ken A. Dill
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - David L. Mobley
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Physical Chemistry B
    volume: 111
    page: 2242  # just first page
    publication-date: 2007-02-10
    # use ISO 8601 date format YYYY-MM-DD
    year: 2007
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1021/jp0667442
    PDF: http://www.choderalab.org/s/comparison-of-charge-models-for-fixed-charge-force-fields-small-molecule-free-energies-in-explicit-s.pdf
    funding: none
    description: >
     We compare a number of popular methods for deriving charge models for small molecules, deriving lessons
     about best practices for accurate simulations.


  - title: "Long-time protein folding dynamics from short-time molecular dynamics simulations"
    authors: # Use same name in publication
    - John D. Chodera
    - William C. Swope
    - Jed W. Pitera
    - Ken A. Dill
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Multiscale Modeling & Simulation
    volume: 5
    page: 1214  # just first page
    publication-date: 2006-12-28  # use ISO 8601 date format YYYY-MM-DD
    year: 2006
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1137/06065146X
    PDF: http://www.choderalab.org/s/long-time-protein-folding-dynamics-from-short-time-molecular-dynamic-simulations.pdf
    funding:
    description: >
     We show how the long-time dynamics of biomolecular systems can be recapitulated from statistics
     collected from short molecular simulations sampling transitions between kinetically
     metastable states.


  - title: "Use of the weighted histogram analysis method for the analysis of simulated and parallel tempering simulations"
    authors: # Use same name in publication
    - John D. Chodera
    - William C. Swope
    - Jed W. Pitera
    - Chaok Seok
    - Ken A. Dill
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Chemical Theory and Computation
    volume: 3
    page: 26  # just first page
    publication-date: 2006-11-09  # use ISO 8601 date format YYYY-MM-DD
    year: 2007
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1021/ct0502864
    PDF: http://www.choderalab.org/s/Use-of-the-Weighted-Histogram-Analysis-Method-for-the-Analysis-of-Simulated-and-Parallel-Tempering-S.pdf
    funding:
    description: >
     The weighted histogram analysis method (WHAM), a mainstay of molecular dynamics simulation analysis,
     is thoroughly explained and modernized for the analysis of simulated and parallel tempering simulation
     data.


  - title: "On the use of orientational restraints and symmetry corrections in alchemical free energy calculations"
    authors: # Use same name in publication
    - David L. Mobley
    - John D. Chodera
    - Ken A. Dill
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - David L. Mobley
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Chemical Physics
    volume: 125
    page: 084902  # just first page
    publication-date: 2006-08-22  # use ISO 8601 date format YYYY-MM-DD
    year: 2006
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1063/1.2221683
    PDF: http://www.choderalab.org/s/on-the-use-of-orientational-restraints-and-symmetry-corrections-in-alchemical-free-energy-calculatio.pdf
    funding:
    description: >
     We illustrate how orientational restraints can be used to greatly reduce the computational effort in alchemical
     calculations of ligand binding free energies, and clarify how symmetry corrections are necessary when
     molecules contain symmetric or pseudosymmetric substituents.


  - title: "MOPED: Method for optimizing physical energy parameters using decoys"
    authors: # Use same name in publication
    - Chaok Seok
    - J. B. Rosen
    - John D. Chodera
    - Ken A. Dill
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Ken A. Dill
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of Computational Chemistry
    volume: 24
    page: 89  # just first page
    publication-date: 2002-12-06  # use ISO 8601 date format YYYY-MM-DD
    year: 2002
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1002/jcc.10124
    PDF: http://www.choderalab.org/s/Moped-method-for-optimizing-physical-energy-parameters-using-decoys.pdf
    funding: none
    description: >
     We show how the long-time dynamics of biomolecular systems can be recapitulated from statistics collected
     from short molecular simulations sampling transitions between kinetically metastable states.


  - title: "An alternative explanation for the catalytic proficiency of orotidine 5'-phosphate decarboxylase"
    authors: # Use same name in publication
    - Tai-Sung Lee
    - Lillian T. Chong
    - John D. Chodera
    - Peter A. Kollman
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Tai-Sung Lee
    # Add these other fields are optional; fill in as much information as is available
    journal: Journal of the American Chemical Society
    volume: 123
    page: 12837  # just first page
    publication-date: 2001-12-19  # use ISO 8601 date format YYYY-MM-DD
    year: 2001
    # These links may be listed in the choderalab.org/publications/ page
    DOI: http://dx.doi.org/10.1021/ja011096f
    PDF: http://www.choderalab.org/s/an-alternative-explanation-for-the-catalytic-proficiency-of-orotidine-5-phosphate-decarboxylase.pdf
    funding: none
    description: >
     A combined QM and MD analysis of potential plausible mechanisms to explain the enormous catalytic acceleration
     of one of the most proficient enzymes known.


  - title: "Ensemble docking in drug discovery"
    authors: # Use same name in publication
    - Rommie E Amaro
    - Jerome Baudry
    - John D. Chodera
    - Özlem Demir
    - J Andrew McCammon
    - Yinglong Miao
    - Jeremy C Smith
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Jeremy C Smith
    # Add these other fields are optional; fill in as much information as is available
    journal: Biophysical Journal
    volume: 114
    page: 2271  # just first page
    publication-date: 2018-05-22  # use ISO 8601 date format YYYY-MM-DD
    year: 2018
    # These links may be listed in the choderalab.org/publications/ page
    DOI: https://doi.org/10.1016/j.bpj.2018.02.038
    PDF: https://reader.elsevier.com/reader/sd/pii/S0006349518303242?token=85F48C4D928468CDA07A873E3B211CF5A89996E0FC86867073834AB1CE01EF2781E6706EE1C7BD7EE56FBD9F04B9FACB
    funding: none
    description: >
     Ensemble docking corresponds to the generation of an “ensemble” of drug target conformations
     in computational structure-based drug discovery, often obtained by using molecular dynamics
     simulation, that is used in docking candidate ligands. This approach is now well established
     in the field of early-stage drug discovery. This review gives a historical account of the
     development of ensemble docking and discusses some pertinent methodological advances in
     conformational sampling.


  - title: "Results of the 2017 Roadmap survey of the Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) challenge community"
    authors: # Use same name in publication
    - David L Mobley
    - John D. Chodera
    - Michael K Gilson
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: UC Irvine escholarship.org
    publication-date: 2017-06-21  # use ISO 8601 date format YYYY-MM-DD
    year: 2017
    # These links may be listed in the choderalab.org/publications/ page
    PDF: https://escholarship.org/content/qt2jq8s2zr/qt2jq8s2zr.pdf
    funding: none
    description: >
     The Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) series of blind prediction
     challenges provide unbiased, prospective tests of computational methods, serving as a crowdsourcing
     mechanism to drive innovation. These challenges solicit submissions from the computational community to
     predict properties of interest, such as solvation, partition, or binding of drug-like molecules.
     These challenges provided substantial benefit to the community, and have led to roughly 100 publications,
     many of which are broadly cited (see attached bibliography). We are currently seeking funding from the
     NIH and surveyed the community concerning experiences with SAMPL and how our future plans for SAMPL
     can best align with the community’s interests and needs. This document summarizes the results of
     this survey and describes our findings. On the whole, the community enthusiastically supports our
     plans for the future of SAMPL, and provided modest suggestions to further strengthen our plans.
     For up-to-date info please see the SAMPL website.


  - title: "Uncertainty Estimation"
    authors: # Use same name in publication
    - Frank Noé
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    book: An Introduction to Markov State Models and Their Application to Long Timescale Molecular Simulation
    page: 61  # just first page
    publication-date: 2014-01-01  # use ISO 8601 date format YYYY-MM-DD
    year: 2014
    # These links may be listed in the choderalab.org/publications/ page
    PDF: https://scholar.google.com/citations?hl=en&user=nnEg7_8AAAAJ&view_op=list_works&authuser=2&sortby=pubdate#d=gs_md_cita-d&u=%2Fcitations%3Fview_op%3Dview_citation%26hl%3Den%26user%3DnnEg7_8AAAAJ%26cstart%3D20%26pagesize%3D80%26sortby%3Dpubdate%26authuser%3D2%26citation_for_view%3DnnEg7_8AAAAJ%3AStPPYsf1FV0C%26tzom%3D240
    funding: none
    description: >
     Markov models provide a useful simplified representation for characterizing the long-time statistical
     evolution of biomolecules in a manner that allows direct comparison with experiments as well as the
     elucidation of mechanistic pathways for an inherently stochastic process. A vital part of meaningful
     comparison with experiment is the characterization of the statistical uncertainty in the predicted
     experimental measurement, which may take the form of an equilibrium measurement of some spectroscopic
     signal, the time-evolution of this signal following a perturbation, or the observation of some statistic
     such as the correlation function of the equilibrium dynamics of a single molecule. Without meaningful
     error bars which arise from both approximation and statistical error, there is no way to determine
     whether the deviations between model and experiment are statistically meaningful. In this chapter,
     we describe …


  - title: "Estimation and validation of Markov models"
    authors: # Use same name in publication
    - Jan-Hendrik Prinz
    - Frank Noé
    - John D. Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D. Chodera
    # Add these other fields are optional; fill in as much information as is available
    book: An Introduction to Markov State Models and Their Application to Long Timescale Molecular Simulation
    page: 45 # just first page
    publication-date: 2014-01-01  # use ISO 8601 date format YYYY-MM-DD
    year: 2014
    # These links may be listed in the choderalab.org/publications/ page
    PDF: https://scholar.google.com/citations?hl=en&user=nnEg7_8AAAAJ&view_op=list_works&authuser=2&sortby=pubdate#d=gs_md_cita-d&u=%2Fcitations%3Fview_op%3Dview_citation%26hl%3Den%26user%3DnnEg7_8AAAAJ%26cstart%3D20%26pagesize%3D80%26sortby%3Dpubdate%26authuser%3D2%26citation_for_view%3DnnEg7_8AAAAJ%3A6jAoOr-ogVAC%26tzom%3D240
    funding: none
    description: >
     This chapter describes approaches to estimate a Markov model transition matrices from simulation data
     that has been mapped to a discrete state space, and approaches to validate whether this estimate
     is consistent with the simulation data at hand.


  - title: "Driven Langevin dynamics: heat, work and pseudo-work"
    authors: # Use same name in publication
    - David A Sivak
    - John D. Chodera
    - Gavin E Crooks
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - David A Sivak
    # Add these other fields are optional; fill in as much information as is available
    journal: arXiv preprint arXiv
    volume: 1107
    page: 2967 # just first page
    publication-date: 2011-07-18  # use ISO 8601 date format YYYY-MM-DD
    year: 2011
    # These links may be listed in the choderalab.org/publications/ page
    arXiv: https://d1wqtxts1xzle7.cloudfront.net/47085375/Using_Nonequilibrium_Fluctuation_Theorem20160707-8500-1ivdnu3.pdf?1467914204=&response-content-disposition=inline%3B+filename%3DUsing_Nonequilibrium_Fluctuation_Theorem.pdf&Expires=1591814597&Signature=OHFCTqttb1-yRpXKR62K2QqxwgJ1G8vPXmVIACyYsIyKUZ9BVKaFI14gGeAkQm2KQW0x2ggYSpgbzeac1zbllH9bCiYIw-zu-LQ1dE97cLleLucVHZJvGy6YSQves8r4mRvo0FE0WL9746HBONs7T4vgOBIPCcBi8b04XOcVA4oZyEes1~LgXJWVysWAj8Vm~Z2r3AavRoRHXsz4hsU~~s7enBbyAetUp5r9S1IvMCHyMNrLVBbX7f8LxaSDcMems6m0CpMFSj-f5RFMf-BURe0ZBdfJI5q95bSh2FHpT~ao1ZmyBSqvAWIjoe-tBpf3C4ZF2scRcz5WX6TLMDsrzQ__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA
    PDF: http://www.academia.edu/download/47085375/Using_Nonequilibrium_Fluctuation_Theorem20160707-8500-1ivdnu3.pdf
    funding: none
    description: >
     In order to simulate Langevin dynamics on a digital computer it is necessary to adopt some approximate
     algorithm that divides time into discrete steps. 2 However, such schemes have an inherent problem: even
     with a time-independent Hamiltonian, they do not preserve the canonical equilibrium distribution, nor
     are they microscopically reversible (since trajectories and their timereversal do not have the same
     probability), but instead simulate a driven nonequilibrium dynamics. Happily, the complications
     generated by this unwanted but inevitable breaking of time-reversal symmetry can be remedied3–6 with
     insights from nonequilibrium statistical thermodynamics, and by adopting an integration scheme in which
     the breaking of time-reversal symmetry can be isolated and measured.


  - title: "Alchemical free energy methods for drug discovery: progress and challenges"
    authors: # Use same name in publication
    - John D Chodera
    - David L Mobley
    - Michael R Shirts
    - Richard W Dixon
    - Kim Branson
    - Vijay S Pande
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - Vijay S Pande
    # Add these other fields are optional; fill in as much information as is available
    journal: Current Opinion in Structural Biology
    volume: 21
    page: 150 # just first page
    publication-date: 2011-02-11  # use ISO 8601 date format YYYY-MM-DD
    year: 2011
    # These links may be listed in the choderalab.org/publications/ page
    DOI: https://dx.doi.org/10.1016%2Fj.sbi.2011.01.011
    PDF: https://reader.elsevier.com/reader/sd/pii/S0959440X11000261?token=AE5F80C35C9319EA26078098A610CA146621256FDA8F0CC6E5CB6353F9DD645042FC2EB325CB6BEEE23AC6D3B52982F2
    funding: none
    description: >
     Improved rational drug design methods are needed to lower the cost and increase the success rate of drug
     discovery and development. Alchemical binding free energy calculations, one potential tool for rational
     design, have progressed rapidly over the past decade, but still fall short of providing robust tools for
     pharmaceutical engineering. Recent studies, especially on model receptor systems, have clarified many of
     the challenges that must be overcome for robust predictions of binding affinity to be useful in rational
     design. In this review, inspired by a recent joint academic/industry meeting organized by the authors,
     we discuss these challenges and suggest a number of promising approaches for overcoming them.


  - title: "Master equation models of macromolecular dynamics from atomistic simulation"
    authors: # Use same name in publication
    - John D Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: UCSF Dissertation
    year: 2006
    # These links may be listed in the choderalab.org/publications/ page
    Google Scholar Link: https://scholar.google.com/citations?hl=en&user=nnEg7_8AAAAJ&view_op=list_works&authuser=2&sortby=pubdate#d=gs_md_cita-d&u=%2Fcitations%3Fview_op%3Dview_citation%26hl%3Den%26user%3DnnEg7_8AAAAJ%26cstart%3D20%26pagesize%3D80%26sortby%3Dpubdate%26authuser%3D2%26citation_for_view%3DnnEg7_8AAAAJ%3ACd1N8iHLSCsC%26tzom%3D240
    funding: none
    description: >
     This dissertation is concerned with the construction, validation, and use of master equation models
     for the study of macromolecular conformational dynamics. The master equation formalism is a powerful
     tool for describing the dynamics of a system that can be characterized by a discrete-state,
     continuous-time Markov process. Once constructed from a large quantities of short trajectories,
     the evolution of experimentally measurable dynamical observables can be computed and compared
     with experiment. Additionally, information not yet directly accessible to experiment but which
     may be useful in aiding understanding or the generation of novel hypotheses, such as folding
     pathways, transiently populated conformations, and mean first passage times, can also be easily
     obtained. We demonstrate that a master equation model constructed from short trajectories can
     describe slow conformational dynamics for a solvated alanine peptide over long times,
     propose a number of tests to tell whether a model constructed from short trajectories will
     adequately describe dynamics over long times, and describe an algorithm for the automatic construction
     of these models from simulation data. While the focus here is on protein folding and dynamics,
     these techniques are very general, and can be broadly applied to problems in biomolecular dynamics.


  - title: "Technical report: An integrated system for executing and analyzing large-scale molecular dynamics simulations"
    authors: # Use same name in publication
    - John D Chodera
    - David E Eramian
    - Larry Schweitzer
    - Ken A Dill
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: UCSF
    publication-date: 2004-09-03  # use ISO 8601 date format YYYY-MM-DD
    year: 2004
    # These links may be listed in the choderalab.org/publications/ page
    PDF: https://www.researchgate.net/profile/John_Chodera/publication/266455666_Technical_report_An_integrated_system_for_executing_and_analyzing_large-scale_molecular_dynamics_simulations/links/570bc1e708aee06603519f8e/Technical-report-An-integrated-system-for-executing-and-analyzing-large-scale-molecular-dynamics-simulations.pdf
    funding: none
    description: >
     This technical report outlines the requirements of a system for the execution and analysis of parallel
     molecular dynamics simulations that allows the easy implementation of efficient modern simulation
     algorithms for computing thermodynamic and kinetic quantities with classical molecular dynamics.
     Some notes on a possible design for such a system are also included as a first step toward the
     construction a generally useful system for the biomolecular simulation community.


  - title: "Constructing master equation models of protein folding and dynamics from atomistic simulation"
    authors: # Use same name in publication
    - JD Chodera
    - KA Dill
    - WC Swope
    - JW Pitera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D Chodera
    # Add these other fields are optional; fill in as much information as is available
    journal: Protein Science
    volume: 13
    page: 101 # just first page
    publication-date: 2004-08-01  # use ISO 8601 date format YYYY-MM-DD
    year: 2004
    # These links may be listed in the choderalab.org/publications/ page
    Google Scholar Link: https://scholar.google.com/citations?hl=en&user=nnEg7_8AAAAJ&view_op=list_works&authuser=2&sortby=pubdate#d=gs_md_cita-d&u=%2Fcitations%3Fview_op%3Dview_citation%26hl%3Den%26user%3DnnEg7_8AAAAJ%26cstart%3D20%26pagesize%3D80%26sortby%3Dpubdate%26authuser%3D2%26citation_for_view%3DnnEg7_8AAAAJ%3AA1VvXmYcXXgC%26tzom%3D240
    funding: none
    description: >
     None


  - title: "Constructing master equation models of peptide dynamics from molecular dynamics simulations. I. Simple solvated systems"
    authors: # Use same name in publication
    - JD Chodera
    - KA Dill
    - WC Swope
    - JW Pitera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D Chodera
    # Add these other fields are optional; fill in as much information as is available
    publication-date: 2004-03-24  # use ISO 8601 date format YYYY-MM-DD
    year: 2004
    # These links may be listed in the choderalab.org/publications/ page
    Google Scholar Link: https://scholar.google.com/citations?hl=en&user=nnEg7_8AAAAJ&view_op=list_works&authuser=2&sortby=pubdate#d=gs_md_cita-d&u=%2Fcitations%3Fview_op%3Dview_citation%26hl%3Den%26user%3DnnEg7_8AAAAJ%26cstart%3D100%26pagesize%3D100%26sortby%3Dpubdate%26authuser%3D2%26citation_for_view%3DnnEg7_8AAAAJ%3AI__7AI8a974C%26tzom%3D240
    funding: none
    description: >
     We demonstrate the long-time dynamics of a simple solvated peptide (terminally-blocked alanine) can
     described by a discrete-state, continuous-time master equation model constructed from molecular
     dynamics simulation data. Manual division of phase space into six states yields Markovian dynamics
     in this reduced state space.


  - title: "Technical Report: Deriving the discrete-state, continuous master equation from classical statistical mechanics: The Mori-Zwanzig projection operator method"
    authors: # Use same name in publication
    - JD Chodera
    # Corresponding authors have their email addresses listed
    corresponding-authors:
    - John D Chodera
    # These links may be listed in the choderalab.org/publications/ page
    Google Scholar Link: https://scholar.google.com/citations?hl=en&user=nnEg7_8AAAAJ&view_op=list_works&authuser=2&sortby=pubdate#d=gs_md_cita-d&u=%2Fcitations%3Fview_op%3Dview_citation%26hl%3Den%26user%3DnnEg7_8AAAAJ%26cstart%3D100%26pagesize%3D100%26sortby%3Dpubdate%26authuser%3D2%26citation_for_view%3DnnEg7_8AAAAJ%3ABQCiT8P4igIC%26tzom%3D240
    funding: none
    description: >
     Here, we show how the discrete-state, continuous-time memoryless (Markovian) master equation can
     be obtained from classical statistical mechanics. Our purpose is to (1) justify that the master
     equation can provide a good description of long-time dynamics provided certain conditions are met,
     (2) determine the necessary set of conditions that must be met and the minimum coarse-grained time
     over which the dynamics is accurate,(3) gain insight as to how to construct efficient algorithms for
     state decomposition to minimize the time for emergence of Markovian behavior, and (4) expose
     alternative expressions for the inter-state transition rates that may provide more efficient routes
     to their estimation by computer simulation.