4.7 Article

Improved Modeling of Halogenated Ligand-Protein Interactions Using the Drude Polarizable and CHARMM Additive Empirical Force Fields

Journal

JOURNAL OF CHEMICAL INFORMATION AND MODELING
Volume 59, Issue 1, Pages 215-228

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.jcim.8b00616

Keywords

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Funding

  1. National Institutes of Health [GM070855, GM072558]
  2. Samuel Waxman Cancer Foundation

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Halogenated ligands can participate in nonbonding interactions with proteins via halogen bond (XB) or halogen-hydrogen bond donor (X-HBD) interactions. In the context of molecular dynamics (MD) simulations, the accuracy of the simulations depends strongly on the force field (FF) used. To ensure good reproduction of XB and X-HBD interactions with proteins, we optimized the previously developed additive CHARMM36/CHARMM General force field (CGenFF) and Drude polarizable force field by including atom pair-specific Lennard-Jones parameters for aromatic halogen-protein interactions. The optimization targeted quantum mechanical interaction energy surfaces with the developed parameters then examined for their ability to reproduce experimental halogen-containing ligand-protein interactions in MD simulations. The calculated halogenated ligand interaction geometries were in good overall agreement with the experimental crystal data for both the polarizable and additive FFs, showing that these models can accurately treat both XB and X-HBD interactions. Analysis of the ligand-protein interactions shows significant contributions of polarizability to binding occurring in the Drude FF, with self-polarization energy making both favorable and unfavorable contributions to binding. Further analysis of the dipole moments from aqueous solution to protein indicates the polarizable FF accounts for subtle changes of the environment of the ligands that can impact binding. The present work demonstrates the utility of the updated additive CHARMM36/CGenFF and polarizable Drude FFs for the study of halogenated ligand-protein interactions in computer-aided drug design.

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