John D. Chodera

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 31

Top Topics

Protein Protein

Machine Learning

Molecular Dynamics

Top Venues

J. Comput. Aided Mol. Des.

J. Chem. Inf. Model.

PLoS Comput. Biol.

Publications

Francesc Sabanés Zariquiey, Raimondas Galvelis, Emilio Gallicchio, John D. Chodera, Thomas E. Markland, Gianni De Fabritiis
Enhancing Protein-Ligand Binding Affinity Predictions Using Neural Network Potentials. J. Chem. Inf. Model. 64 (5) (2024)
Peter K. Eastman, Benjamin P. Pritchard, John D. Chodera, Thomas E. Markland
Nutmeg and SPICE: Models and Data for Biomolecular Machine Learning. CoRR (2024)
Peter K. Eastman, Raimondas Galvelis, Raúl P. Peláez, Charlles R. A. 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 P. G. L. M. Rodrigues, Jaime Rodríguez-Guerra, Andrew C. Simmonett, Jason M. Swails, Ivy Zhang, John D. Chodera, Gianni De Fabritiis, Thomas E. Markland
OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials. CoRR (2023)
Kenichiro Takaba, Iván Pulido, Mike Henry, Hugo MacDermott-Opeskin, John D. Chodera, Yuanqing Wang
Espaloma-0.3.0: Machine-learned molecular mechanics force field for the simulation of protein-ligand systems and beyond. CoRR (2023)
Yuanqing Wang, John D. Chodera
Spatial Attention Kinetic Networks with E(n)-Equivariance. CoRR (2023)
Yuanqing Wang, Iván Pulido, Kenichiro Takaba, Benjamin Kaminow, Jenke Scheen, Lily Wang, John D. Chodera
EspalomaCharge: Machine learning-enabled ultra-fast partial charge assignment. CoRR (2023)
Yuanqing Wang, John D. Chodera
Spatial Attention Kinetic Networks with E(n)-Equivariance. ICLR (2023)
Raimondas Galvelis, Alejandro Varela-Rial, Stefan Doerr, Roberto Fino, Peter K. Eastman, Thomas E. Markland, John D. Chodera, Gianni De Fabritiis
NNP/MM: Accelerating Molecular Dynamics Simulations with Machine Learning Potentials and Molecular Mechanics. J. Chem. Inf. Model. 63 (18) (2023)
Raimondas Galvelis, Alejandro Varela-Rial, Stefan Doerr, Roberto Fino, Peter K. Eastman, Thomas E. Markland, John D. Chodera, Gianni De Fabritiis
NNP/MM: Fast molecular dynamics simulations with machine learning potentials and molecular mechanics. CoRR (2022)
Peter K. 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
SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials. CoRR (2022)
Harold Grosjean, Mehtap Isik, Anthony Aimon, David L. Mobley, John D. Chodera, Frank von Delft, Philip C. Biggin
SAMPL7 protein-ligand challenge: A community-wide evaluation of computational methods against fragment screening and pose-prediction. J. Comput. Aided Mol. Des. 36 (4) (2022)
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
Open Force Field BespokeFit: Automating Bespoke Torsion Parametrization at Scale. J. Chem. Inf. Model. 62 (22) (2022)
Owen Madin, Simon Boothroyd, Richard A. Messerly, Josh Fass, John D. Chodera, Michael R. Shirts
Bayesian-Inference-Driven Model Parametrization and Model Selection for 2CLJQ Fluid Models. J. Chem. Inf. Model. 62 (4) (2022)
Mehtap Isik, Ariën S. Rustenburg, Andrea Rizzi, Marilyn R. Gunner, David L. Mobley, John D. Chodera
predictions. J. Comput. Aided Mol. Des. 35 (2) (2021)
Matthew N. Bahr, Aakankschit Nandkeolyar, John K. Kenna, Neysa Nevins, Luigi Da Vià, Mehtap Isik, John D. Chodera, David L. Mobley
and distribution coefficient measurements of pharmaceutical compounds for the SAMPL8 blind prediction challenge. J. Comput. Aided Mol. Des. 35 (11) (2021)
Steven K. Albanese, John D. Chodera, Andrea Volkamer, Simon Keng, Robert Abel, Lingle Wang
Is Structure-Based Drug Design Ready for Selectivity Optimization? J. Chem. Inf. Model. 60 (12) (2020)
Marilyn R. Gunner, Taichi Murakami, Ariën S. Rustenburg, Mehtap Isik, John D. Chodera
s, are ideal for describing small molecule protonation and tautomeric states. J. Comput. Aided Mol. Des. 34 (5) (2020)
Andrea Rizzi, Travis Jensen, David R. Slochower, Matteo Aldeghi, Vytautas Gapsys, Dimitris Ntekoumes, Stefano Bosisio, Michail Papadourakis, Niel M. Henriksen, Bert L. de Groot, Zoe Cournia, Alex Dickson, Julien Michel, Michael K. Gilson, Michael R. Shirts, David L. Mobley, John D. Chodera
The SAMPL6 SAMPLing challenge: assessing the reliability and efficiency of binding free energy calculations. J. Comput. Aided Mol. Des. 34 (5) (2020)
Yuanqing Wang, Josh Fass, John D. Chodera
End-to-End Differentiable Molecular Mechanics Force Field Construction. CoRR (2020)
Mehtap Isik, Dorothy Levorse, David L. Mobley, Timothy Rhodes, John D. Chodera
Octanol-water partition coefficient measurements for the SAMPL6 blind prediction challenge. J. Comput. Aided Mol. Des. 34 (4) (2020)
Mehtap Isik, Teresa Danielle Bergazin, Thomas Fox, Andrea Rizzi, John D. Chodera, David L. Mobley
Assessing the accuracy of octanol-water partition coefficient predictions in the SAMPL6 Part II log P Challenge. J. Comput. Aided Mol. Des. 34 (4) (2020)
Yuanqing Wang, Josh Fass, Chaya D. Stern, Kun Luo, John D. Chodera
Graph Nets for Partial Charge Prediction. CoRR (2019)
Mark James Abraham, Rossen Apostolov, Jonathan Barnoud, Paul Bauer, Christian Blau, Alexandre M. J. J. Bonvin, Matthieu Chavent, John D. Chodera, Karmen Condic-Jurkic, Lucie Delemotte, Helmut Grubmüller, Rebecca J. Howard, E. Joseph Jordan, Erik Lindahl, Samuli Ollila, Jana Selent, Daniel G. A. Smith, Phillip J. Stansfeld, Johanna K. S. Tiemann, Mikael Trellet, Christopher J. Woods, Artem A. Zhmurov
Sharing Data from Molecular Simulations. J. Chem. Inf. Model. 59 (10) (2019)
Andrea Rizzi, Steven Murkli, John N. McNeill, Wei Yao, Matthew R. Sullivan, Michael K. Gilson, Michael Chiu, Lyle Isaacs, Bruce C. Gibb, David L. Mobley, John D. Chodera
Overview of the SAMPL6 host-guest binding affinity prediction challenge. J. Comput. Aided Mol. Des. 32 (10) (2018)
Josh Fass, David A. Sivak, Gavin E. Crooks, Kyle Beauchamp, Benedict J. Leimkuhler, John D. Chodera
Quantifying Configuration-Sampling Error in Langevin Simulations of Complex Molecular Systems. Entropy 20 (5) (2018)
Mehtap Isik, Dorothy Levorse, Ariën S. Rustenburg, Ikenna E. Ndukwe, Heather Wang, Xiao Wang, Mikhail Y. Reibarkh, Gary E. Martin, Alexey A. Makarov, David L. Mobley, Timothy Rhodes, John D. Chodera
pK a measurements for the SAMPL6 prediction challenge for a set of kinase inhibitor-like fragments. J. Comput. Aided Mol. Des. 32 (10) (2018)
Peter K. Eastman, Jason M. Swails, John D. Chodera, Robert McGibbon, Yutong Zhao, Kyle Beauchamp, Lee-Ping Wang, Andrew C. Simmonett, Matthew P. Harrigan, Chaya D. Stern, Rafal P. Wiewiora, Bernard R. Brooks, Vijay S. Pande
OpenMM 7: Rapid development of high performance algorithms for molecular dynamics. PLoS Comput. Biol. 13 (7) (2017)
Daniel L. Parton, Patrick B. Grinaway, Sonya M. Hanson, Kyle Beauchamp, John D. Chodera
Ensembler: Enabling High-Throughput Molecular Simulations at the Superfamily Scale. PLoS Comput. Biol. 12 (6) (2016)
Ariën S. Rustenburg, Justin Dancer, Baiwei Lin, Jianwen A. Feng, Daniel F. Ortwine, David L. Mobley, John D. Chodera
Measuring experimental cyclohexane-water distribution coefficients for the SAMPL5 challenge. J. Comput. Aided Mol. Des. 30 (11) (2016)
Christian Kramer, John D. Chodera, Terry R. Stouch
Introduction to the special issue: Data Part 2: Experimental Data. J. Comput. Aided Mol. Des. 29 (9) (2015)
Sonya M. Hanson, Sean Ekins, John D. Chodera
Modeling error in experimental assays using the bootstrap principle: understanding discrepancies between assays using different dispensing technologies. J. Comput. Aided Mol. Des. 29 (12) (2015)
Kai Wang, John D. Chodera, Yanzhi Yang, Michael R. Shirts
Identifying ligand binding sites and poses using GPU-accelerated Hamiltonian replica exchange molecular dynamics. J. Comput. Aided Mol. Des. 27 (12) (2013)
John D. Chodera, William C. Swope, Jed W. Pitera, Ken A. Dill
Long-Time Protein Folding Dynamics from Short-Time Molecular Dynamics Simulations. Multiscale Model. Simul. 5 (4) (2006)
Chaok Seok, J. Ben Rosen, John D. Chodera, Ken A. Dill
MOPED: Method for optimizing physical energy parameters using decoys. J. Comput. Chem. 24 (1) (2003)