Development and benchmarking of Open Force Field 2.0.0---the Sage small molecule force field

Boothroyd S, Behara PK, Madin OC, Hahn DF, Jang H, Gapsys V, Wagner JR, Horton JT, Dotson DL, Thompson MW, Maat J, Gokey T, Wang L-P, Cole DJ, Gilson MK, Chodera JD, Bayly CI, Shirts MR, Mobley DL
Journal of Chemical Theory and Computation 19:3251, 2023 [DOI] [chemRxiv] [GitHub] [examples]

We present a new generation of small molecule force field for molecular design from the Open Force Field Initiative fit to both quantum chemical and experimental liquid mixture data

Improving force field accuracy by training against condensed-phase mixture properties

Boothroyd S, Madin OC, Mobley DL, Wang L-P, Chodera JD, and Shirts MR
Journal of Chemical Theory and Computation 18:3577, 2022 [DOI] [GitHub]

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.

The Open Force Field Evaluator: An automated, efficient, and scalable framework for the estimation of physical properties from molecular simulation

Simon Boothroyd, Lee-Ping Wang, David L. Mobley, John D. Chodera, and Michael R. Shirts

Preprint ahead of submission: [ChemRxiv]

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.

Bayesian inference-driven model parameterization and model selection for 2CLJQ fluid models

Owen C Madin, Simon Boothroyd, Richard A Messerly, John D Chodera, Josh Fass, and Michael R Shirts
Preprint ahead of publication: [arXiv]

Here, we show how Bayesian inference can be used to automatically perform model selection and fit parameters for a molecular mechanics force field.

Development and benchmarking of Open Force Field v1.0.0, the Parsley small molecule force field

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
Preprint ahead of publication: [chemRxiv] [force fields] [Open Force Field Initiative]

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.

The SAMPL6 SAMPLing challenge: Assessing the reliability and efficiency of binding free energy calculations

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, and John D. Chodera
Journal of Computer Aided Molecular Design 34:601, 2020. [DOI] [PDF] [bioRxiv] [GitHub]

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.

Toward learned chemical perception of force field typing rules

Camila Zanette, Caitlin C. Bannan, Christopher I. Bayly, Josh Fass, Michael K. Gilson, Michael R. Shirts, John Chodera, and David L. Mobley
Journal of Chemical Theory and Computation, 15:402, 2019. [DOI] [ChemRxiv] [GitHub]

We show how machine learning can learn typing rules for molecular mechanics force fields within a Bayesian statistical framework.

Approaches for calculating solvation free energies and enthalpies demonstrated with an update of the FreeSolv database

Guilherme Duarte Ramos Matos, Daisy Y. Kyu, Hannes H. Loeffler, John D. Chodera, Michael R. Shirts, David Mobley
Journal of Chemical Engineering Data 62:1559, 2017. [DOI] [bioRxiv] [GitHub]

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.