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Enhancing water sampling of buried binding sites using nonequilibrium candidate Monte Carlo

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Abstract

Water molecules can be found interacting with the surface and within cavities in proteins. However, water exchange between bulk and buried hydration sites can be slow compared to simulation timescales, thus leading to the inefficient sampling of the locations of water. This can pose problems for free energy calculations for computer-aided drug design. Here, we apply a hybrid method that combines nonequilibrium candidate Monte Carlo (NCMC) simulations and molecular dynamics (MD) to enhance sampling of water in specific areas of a system, such as the binding site of a protein. Our approach uses NCMC to gradually remove interactions between a selected water molecule and its environment, then translates the water to a new region, before turning the interactions back on. This approach of gradual removal of interactions, followed by a move and then reintroduction of interactions, allows the environment to relax in response to the proposed water translation, improving acceptance of moves and thereby accelerating water exchange and sampling. We validate this approach on several test systems including the ligand-bound MUP-1 and HSP90 proteins with buried crystallographic waters removed. We show that our BLUES (NCMC/MD) method enhances water sampling relative to normal MD when applied to these systems. Thus, this approach provides a strategy to improve water sampling in molecular simulations which may be useful in practical applications in drug discovery and biomolecular design.

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Data availability

The Supporting Information is available free of charge on https://github.com/MobleyLab/blues-water-hopping-paper and includes the code, scripts and input files used in this work.

Abbreviations

BLUES:

Binding modes of Ligands Using Enhanced Sampling

MD:

Molecular Dynamics

NCMC:

Nonequilibrium Candidate Monte Carlo

MUP-1:

Major Urinary Protein

HSP90:

Heat Shock Protein 90

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Acknowledgements

TDB acknowledges support from the ACM SIGHPC/Intel Fellowship. DLM appreciates financial support from the National Institutes of Health (1R01GM108889-01) and the National Science Foundation (CHE 1352608). MKG acknowledges funding from the National Institute of General Medical Sciences (GM61300). The contents of this paper are solely the responsibility of the authors and do not necessarily represent the official views of the NIH.

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Authors and Affiliations

  1. Department of Pharmaceutical Sciences, University of California, Irvine, CA, 92697, USA

    Teresa Danielle Bergazin, Nathan M. Lim & David L. Mobley

  2. Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, 92093, USA

    Ido Y. Ben-Shalom & Michael K. Gilson

  3. Department of Chemistry, University of California, Irvine, Irvine, CA, 92697, USA

    Sam C. Gill & David L. Mobley

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  1. Teresa Danielle Bergazin
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Correspondence to David L. Mobley.

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DLM is a Member of the Scientific Advisory Board of OpenEye Scientific Software and an Open Science Fellow with Silicon Therapeutics. MKG has an equity interest in and is a Cofounder and Scientific Advisor of VeraChem LLC.

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Bergazin, T.D., Ben-Shalom, I.Y., Lim, N.M. et al. Enhancing water sampling of buried binding sites using nonequilibrium candidate Monte Carlo. J Comput Aided Mol Des 35, 167–177 (2021). https://doi.org/10.1007/s10822-020-00344-8

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