4.5 Article

Ligand Affinities within the Open-Boundary Molecular Mechanics/Coarse-Grained Framework (I): Alchemical Transformations within the Hamiltonian Adaptive Resolution Scheme

Journal

JOURNAL OF PHYSICAL CHEMISTRY B
Volume 125, Issue 3, Pages 789-797

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.jpcb.0c09805

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Funding

  1. RWTH Aachen University [rwth0571]

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The OB-MM/CG framework developed in this study allows for the prediction of ligand poses in important pharmaceutical targets using molecular mechanics and coarse grained methods, even in the absence of experimental structural information. By implementing H-AdResS in the GROMACS code, the estimation of ligand binding affinities within this framework is advanced. The accuracy of the predictions is confirmed through comparisons with experimental data, paving the way for studying large biological systems.
Our recently developed Open-Boundary Molecular Mechanics/Coarse Grained (OB-MM/CG) framework predicts ligand poses in important pharmaceutical targets, such as G-protein Coupled Receptors, even when experimental structural information is lacking. The approach, which is based on GROMOS and AMBER force fields, allows for grand-canonical simulations of protein-ligand complexes by using the Hamiltonian Adaptive Resolution Scheme (H-AdResS) for the solvent. Here, we present a key step toward the estimation of ligand binding affinities for their targets within this approach. This is the implementation of the H-AdResS in the GROMACS code. The accuracy of our implementation is established by calculating hydration free energies of several molecules in water by means of alchemical transformations. The deviations of the GROMOS- and AMBER-based H-AdResS results from the reference fully atomistic simulations are smaller than the accuracy of the force field and/or they are in the range of the published results. Importantly, our predictions are in good agreement with experimental data. The current implementation paves the way to the use of the OB-MM/CG framework for the study of large biological systems.

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