Literature DB >> 34516130

Expanded Ensemble Methods Can be Used to Accurately Predict Protein-Ligand Relative Binding Free Energies.

Si Zhang1, David F Hahn2, Michael R Shirts3, Vincent A Voelz1.   

Abstract

Alchemical free energy methods have become indispensable in computational drug discovery for their ability to calculate highly accurate estimates of protein-ligand affinities. Expanded ensemble (EE) methods, which involve single simulations visiting all of the alchemical intermediates, have some key advantages for alchemical free energy calculation. However, there have been relatively few examples published in the literature of using expanded ensemble simulations for free energies of protein-ligand binding. In this paper, as a test of expanded ensemble methods, we compute relative binding free energies using the Open Force Field Initiative force field (codename "Parsley") for 24 pairs of Tyk2 inhibitors derived from a congeneric series of 16 compounds. The EE predictions agree well with the experimental values (root-mean-square error (RMSE) of 0.94 ± 0.13 kcal mol-1 and mean unsigned error (MUE) of 0.75 ± 0.12 kcal mol-1). We find that while increasing the number of alchemical intermediates can improve the phase space overlap, faster convergence can be obtained with fewer intermediates, as long as acceptance rates are sufficient. We also find that convergence can be improved using more aggressive updating of biases, and that estimates can be improved by performing multiple independent EE calculations. This work demonstrates that EE is a viable option for alchemical free energy calculation. We discuss the implications of these findings for rational drug design, as well as future directions for improvement.

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Year:  2021        PMID: 34516130      PMCID: PMC9333416          DOI: 10.1021/acs.jctc.1c00513

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.578


  44 in total

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Authors:  Zoe Cournia; Bryce K Allen; Thijs Beuming; David A Pearlman; Brian K Radak; Woody Sherman
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5.  Free Energy Perturbation Hamiltonian Replica-Exchange Molecular Dynamics (FEP/H-REMD) for Absolute Ligand Binding Free Energy Calculations.

Authors:  Wei Jiang; Benoît Roux
Journal:  J Chem Theory Comput       Date:  2010-07-01       Impact factor: 6.006

6.  Lead optimization of a 4-aminopyridine benzamide scaffold to identify potent, selective, and orally bioavailable TYK2 inhibitors.

Authors:  Jun Liang; Anne van Abbema; Mercedesz Balazs; Kathy Barrett; Leo Berezhkovsky; Wade Blair; Christine Chang; Donnie Delarosa; Jason DeVoss; Jim Driscoll; Charles Eigenbrot; Nico Ghilardi; Paul Gibbons; Jason Halladay; Adam Johnson; Pawan Bir Kohli; Yingjie Lai; Yanzhou Liu; Joseph Lyssikatos; Priscilla Mantik; Kapil Menghrajani; Jeremy Murray; Ivan Peng; Amy Sambrone; Steven Shia; Young Shin; Jan Smith; Sue Sohn; Vickie Tsui; Mark Ultsch; Lawren C Wu; Yisong Xiao; Wenqian Yang; Judy Young; Birong Zhang; Bing-yan Zhu; Steven Magnuson
Journal:  J Med Chem       Date:  2013-05-29       Impact factor: 7.446

7.  Variance minimization of free energy estimates from optimized expanded ensembles.

Authors:  Francisco J Martínez-Veracoechea; Fernando A Escobedo
Journal:  J Phys Chem B       Date:  2008-06-14       Impact factor: 2.991

8.  OpenMM 7: Rapid development of high performance algorithms for molecular dynamics.

Authors:  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
Journal:  PLoS Comput Biol       Date:  2017-07-26       Impact factor: 4.475

9.  Fast, Accurate, and Reliable Protocols for Routine Calculations of Protein-Ligand Binding Affinities in Drug Design Projects Using AMBER GPU-TI with ff14SB/GAFF.

Authors:  Xibing He; Shuhan Liu; Tai-Sung Lee; Beihong Ji; Viet H Man; Darrin M York; Junmei Wang
Journal:  ACS Omega       Date:  2020-02-25
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