CHARMM-Compatible Molecular Mechanics Force Fields for Multiscale Modeling of HIV-1 Replication Inhibitors

Abstract Molecular dynamics simulations provide insight into inhibitor-protein interactions and support rational drug design; however, their accuracy depends on reliable molecular mechanics force field parameters and coarse-grained representations that retain relevant molecular features. Although force field parameter sets for biomacromolecules are well established, the chemical diversity of small-molecule inhibitors often requires the development of system-specific parameters. Here, we present a parametrization framework integrating quantum mechanical optimization, experimental benchmarking, and small-molecule coarse-graining, demonstrated using HIV-1 inhibitors targeting multiple stages of the viral replication cycle. We provide a curated data set of CHARMM-compatible force field parameters for 12 HIV-1 inhibitors and the HIV assembly cofactor inositol hexakisphosphate (IP6), together with geometry-optimized atomic structures and ligand restraint files. The resulting parameters are validated against experimental structural and thermodynamic benchmarks, including lenacapavir binding free energy estimates, through inhibitor-bound complex simulations. We demonstrate applications of the parameter data set by quantifying inhibitor-protein interactions, including the free-energy profile of an integrase strand transfer inhibitor interacting with the viral capsid lattice, and the binding energetics of an allosteric integrase inhibitor. Furthermore, we extend the all-atom inhibitor parameter data set through a novel coarse-graining strategy for small molecules that preserves key electrostatic features. The HIV-1 inhibitor force field parameter data set is a publicly available resource that establishes a unified framework for multiscale modeling of HIV-1 inhibitors and facilitates computational and structural biology studies of drug resistance and inhibitor design. More generally, the framework presented here is broadly applicable to small-molecule parametrization and multiscale simulations in other therapeutic and biomolecular contexts.

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Publication Details

Journal
Journal of the American Chemical Society
Published
2026-11-08
DOI
https://doi.org/10.1021/jacs.6c11578
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

CHARMM-Compatible Molecular Mechanics Force Fields for Multiscale Modeling of HIV-1 Replication Inhibitors

Amanda C. Macke, Craig A. Peeples, Juan S. Rey, Juan R. Perilla
Journal of the American Chemical Society
Computational Drug Discovery Methods
article

CHARMM-Compatible Molecular Mechanics Force Fields for Multiscale Modeling of HIV-1 Replication Inhibitors

Amanda C. Macke, Craig A. Peeples, Juan S. Rey, Juan R. Perilla
article en

Abstract

Abstract Molecular dynamics simulations provide insight into inhibitor-protein interactions and support rational drug design; however, their accuracy depends on reliable molecular mechanics force field parameters and coarse-grained representations that retain relevant molecular features. Although force field parameter sets for biomacromolecules are well established, the chemical diversity of small-molecule inhibitors often requires the development of system-specific parameters. Here, we present a parametrization framework integrating quantum mechanical optimization, experimental benchmarking, and small-molecule coarse-graining, demonstrated using HIV-1 inhibitors targeting multiple stages of the viral replication cycle. We provide a curated data set of CHARMM-compatible force field parameters for 12 HIV-1 inhibitors and the HIV assembly cofactor inositol hexakisphosphate (IP6), together with geometry-optimized atomic structures and ligand restraint files. The resulting parameters are validated against experimental structural and thermodynamic benchmarks, including lenacapavir binding free energy estimates, through inhibitor-bound complex simulations. We demonstrate applications of the parameter data set by quantifying inhibitor-protein interactions, including the free-energy profile of an integrase strand transfer inhibitor interacting with the viral capsid lattice, and the binding energetics of an allosteric integrase inhibitor. Furthermore, we extend the all-atom inhibitor parameter data set through a novel coarse-graining strategy for small molecules that preserves key electrostatic features. The HIV-1 inhibitor force field parameter data set is a publicly available resource that establishes a unified framework for multiscale modeling of HIV-1 inhibitors and facilitates computational and structural biology studies of drug resistance and inhibitor design. More generally, the framework presented here is broadly applicable to small-molecule parametrization and multiscale simulations in other therapeutic and biomolecular contexts.

Journal of the American Chemical Society
University of Delaware (US)
National Science Foundation, U.S. Department of Energy, National Institutes of Health, Office of Science, National Institute of Allergy and Infectious Diseases, Office of Advanced Cyberinfrastructure, Advanced Scientific Computing Research, Oak Ridge National Laboratory
Computational Drug Discovery Methods
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