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Large Scale Relative Protein Ligand Binding Affinities Using Non-Equilibrium Alchemy

Abstract

Ligand binding affinity calculations based on molecular dynamics (MD) simulations and non-physical (alchemical) thermodynamic cycles have shown great promise for structure-based drug design. However, their broad uptake and impact is held back by the notoriously complex setup of the calculations. Only a few tools other than the free energy perturbation approach by Schrödinger Inc. (referred to as FEP+) currently enable end-to-end application. Here, we present for the first time an approach based on the open-source software pmx that allows to easily setup and run alchemical calculations for diverse sets of small molecules using the GROMACS MD engine. The method relies on theoretically rigorous non-equilibrium thermodynamic integration (TI) founda-tions, and its flexibility allows calculations with multiple force fields. In this study, results from the Amber and Charmm force fields were combined to yield a consensus outcome per-forming on par with the commercial FEP+ approach. A large dataset of 482 perturbations from 13 different protein-ligand datasets led to an average unsigned error (AUE) of 3.64 ± 0.14 kJ/mol, equivalent to Schrödinger’s FEP+ AUE of 3.66 ± 0.14 kJ/mol. For the first time, a setup is presented for an overall high precision and high accuracy relative protein-ligand alchemical free energy calculations based on open source software.

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Publication details

The article was received on 25 Jul 2019, accepted on 01 Dec 2019 and first published on 02 Dec 2019


Article type: Edge Article
DOI: 10.1039/C9SC03754C
Chem. Sci., 2020, Accepted Manuscript
  • Open access: Creative Commons BY-NC license
    All publication charges for this article have been paid for by the Royal Society of Chemistry

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    Large Scale Relative Protein Ligand Binding Affinities Using Non-Equilibrium Alchemy

    V. Gapsys, L. Pérez-Benito, M. Aldeghi, D. Seeliger, H. Van Vlijmen, G. Tresdern and B. de Groot, Chem. Sci., 2020, Accepted Manuscript , DOI: 10.1039/C9SC03754C

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