Binding modes of ligands using enhanced sampling (BLUES): Rapid decorrelation of ligand binding modes via nonequilibrium candidate Monte Carlo Journal Article


Authors: Gill, S. C.; Lim, N. M.; Grinaway, P. B.; Rustenburg, A. S.; Fass, J.; Ross, G. A.; Chodera, J. D.; Mobley, D. L.
Article Title: Binding modes of ligands using enhanced sampling (BLUES): Rapid decorrelation of ligand binding modes via nonequilibrium candidate Monte Carlo
Abstract: Accurately predicting protein-ligand binding affinities and binding modes 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 fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation time scales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop 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 before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over 2 orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step toward 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. © 2018 American Chemical Society.
Keywords: proteins; molecular dynamics; forecasting; ligands; binding energy; computational chemistry; monte carlo methods; free energy; free-energy calculations; orders of magnitude; molecular dynamics simulations; binding free energy; ligand binding mode; prediction problem; protein-ligand binding affinities; sampling efficiency
Journal Title: Journal of Physical Chemistry B
Volume: 122
Issue: 21
ISSN: 1520-6106
Publisher: American Chemical Society  
Date Published: 2018-05-31
Start Page: 5579
End Page: 5598
Language: English
DOI: 10.1021/acs.jpcb.7b11820
PROVIDER: scopus
PMCID: PMC5980761
PUBMED: 29486559
DOI/URL:
Notes: Article -- Export Date: 2 July 2018 -- Source: Scopus
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MSK Authors
  1. John Damon Chodera
    72 Chodera
  2. Joshua Hanna Fass
    7 Fass
  3. Gregory Antonio Ross
    5 Ross