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Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes Using Nonequilibrium Candidate Monte Carlo

, , , , , , , and . (2017)

Abstract

Accurately predicting protein-ligand binding is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid frag- ments. That is, we focus on computing the domi- nant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a recep- tor, and the populations of the multiple binding modes which may be relevant. This problem is im- portant in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increas- ingly used to predict binding free energies of lig- ands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, lig- and binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current tech- niques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we de- velop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes. In this technique the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation be- fore accepting or rejecting the rotation and relax- ation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics sim- ulation. This is a first step towards applying this methodology to pharmaceutically-relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.

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BibTeX key:
Gill2017BLUES
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