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Relative Binding Free Energy Calculations with Transformato: A Molecular Dynamics Engine-independent Tool

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Specialty Biology
Date 2022 Sep 23
PMID 36148009
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Abstract

We present the software package transformato for the setup of large-scale relative binding free energy calculations. Transformato is written in Python as an open source project (https://github.com/wiederm/transformato); in contrast to comparable tools, it is not closely tied to a particular molecular dynamics engine to carry out the underlying simulations. Instead of alchemically transforming a ligand directly into another , the two ligands are mutated to a common core. Thus, while dummy atoms are required at intermediate states, in particular at the common core state, none are present at the physical endstates. To validate the method, we calculated 76 relative binding free energy differences for five protein-ligand systems. The overall root mean squared error to experimental binding free energies is 1.17 kcal/mol with a Pearson correlation coefficient of 0.73. For selected cases, we checked that the relative binding free energy differences between pairs of ligands do not depend on the choice of the intermediate common core structure. Additionally, we report results with and without hydrogen mass reweighting. The code currently supports OpenMM, CHARMM, and CHARMM/OpenMM directly. Since the program logic to choose and construct alchemical transformation paths is separated from the generation of input and topology/parameter files, extending transformato to support additional molecular dynamics engines is straightforward.

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References
1.
Zhang H, Kim S, Giese T, Lee T, Lee J, York D . CHARMM-GUI Free Energy Calculator for Practical Ligand Binding Free Energy Simulations with AMBER. J Chem Inf Model. 2021; 61(9):4145-4151. PMC: 8491128. DOI: 10.1021/acs.jcim.1c00747. View

2.
Soteras Gutierrez I, Lin F, Vanommeslaeghe K, Lemkul J, Armacost K, Brooks 3rd C . Parametrization of halogen bonds in the CHARMM general force field: Improved treatment of ligand-protein interactions. Bioorg Med Chem. 2016; 24(20):4812-4825. PMC: 5053860. DOI: 10.1016/j.bmc.2016.06.034. View

3.
Deflorian F, Perez-Benito L, Lenselink E, Congreve M, van Vlijmen H, Mason J . Accurate Prediction of GPCR Ligand Binding Affinity with Free Energy Perturbation. J Chem Inf Model. 2020; 60(11):5563-5579. DOI: 10.1021/acs.jcim.0c00449. View

4.
Shirts M, Klein C, Swails J, Yin J, Gilson M, Mobley D . Lessons learned from comparing molecular dynamics engines on the SAMPL5 dataset. J Comput Aided Mol Des. 2016; 31(1):147-161. PMC: 5581938. DOI: 10.1007/s10822-016-9977-1. View

5.
Lee J, Cheng X, Swails J, Yeom M, Eastman P, Lemkul J . CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field. J Chem Theory Comput. 2015; 12(1):405-13. PMC: 4712441. DOI: 10.1021/acs.jctc.5b00935. View