Improved Modeling of Cation-π and Anion-Ring Interactions Using the Drude Polarizable Empirical Force Field for Proteins.

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TitleImproved Modeling of Cation-π and Anion-Ring Interactions Using the Drude Polarizable Empirical Force Field for Proteins.
Publication TypeJournal Article
Year of Publication2019
AuthorsLin, F-Y, Mackerell, AD
JournalJ Comput Chem
Date Published2019 Sep 13

Cation-π interactions are noncovalent interactions between a π-electron system and a positively charged ion that are regarded as a strong noncovalent interaction and are ubiquitous in biological systems. Similarly, though less studied, anion-ring interactions are present in proteins along with in-plane interactions of anions with aromatic rings. As these interactions are between a polarizing ion and a polarizable π system, the accuracy of the treatment of these interactions in molecular dynamics (MD) simulations using additive force fields (FFs) may be limited. In the present work, to allow for a better description of ion-π interactions in proteins in the Drude-2013 protein polarizable FF, we systematically optimized the parameters for these interactions targeting model compound quantum mechanical (QM) interaction energies with atom pair-specific Lennard-Jones parameters along with virtual particles as selected ring centroids introduced to target the QM interaction energies and geometries. Subsequently, MD simulations were performed on a series of protein structures where ion-π pairs occur to evaluate the optimized parameters in the context of the Drude-2013 FF. The resulting FF leads to a significant improvement in reproducing the ion-π pair distances observed in experimental protein structures, as well as a smaller root-mean-square differences and fluctuations of the overall protein structures from experimental structures. Accordingly, the optimized Drude-2013 protein polarizable FF is suggested for use in MD simulations of proteins where cation-π and anion-ring interactions are critical. © 2019 Wiley Periodicals, Inc.

Alternate JournalJ Comput Chem
PubMed ID31518010
Grant List1053575 / / National Science Foundation /
GM131710 / / NIH Office of the Director /
/ / Samuel Waxman Cancer Foundation /
/ / University of Maryland Computer-Aided Drug Design Center /