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g_mmpbsa—A GROMACS Tool for High-Throughput MM-PBSA Calculations

Kumari, Rashmi, Kumar, Rajendra, Open Source Drug Discovery Consortium, Lynn, Andrew·2014·Journal of Chemical Information and Modeling

DOI 10.1021/ci500020m

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Abstract

Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA), a method to estimate interaction free energies, has been increasingly used in the study of biomolecular interactions. Recently, this method has also been applied as a scoring function in computational drug design. Here a new tool g_mmpbsa, which implements the MM-PBSA approach using subroutines written in-house or sourced from the GROMACS and APBS packages is described. g_mmpbsa was developed as part of the Open Source Drug Discovery (OSDD) consortium. Its aim is to integrate high-throughput molecular dynamics (MD) simulations with binding energy calculations. The tool provides options to select alternative atomic radii and different nonpolar solvation models including models based on the solvent accessible surface area (SASA), solvent accessible volume (SAV), and a model which contains both repulsive (SASA-SAV) and attractive components (described using a Weeks-Chandler-Andersen like integral method). We showcase the effectiveness of the tool by comparing the calculated interaction energy of 37 structurally diverse HIV-1 protease inhibitor complexes with their experimental binding free energies. The effect of varying several combinations of input parameters such as atomic radii, dielectric constant, grid resolution, solute-solvent dielectric boundary definition, and nonpolar models was investigated. g_mmpbsa can also be used to estimate the energy contribution per residue to the binding energy. It has been used to identify those residues in HIV-1 protease that are most critical for binding a range of inhibitors.

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Authors: Kumari, R., Kumar, R., Open Source Drug Discovery Consortium, & Lynn, A.
Venue: Journal of Chemical Information and Modeling
Publisher: American Chemical Society (ACS)
Published: 2014-06-19
Volume: 54
Issue: 7
Pages: 1951-1962
ISSN: 1549-9596 (ISSN-L)
1549-960X
DOI: 10.1021/ci500020m
OpenAlex: W2044172327
Cited by: 4,882
References: 90
FWCI: 97.47
Type: journal article
Language: en
Open access: closed

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Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.

g_mmpbsa—A GROMACS Tool for High-Throughput MM-PBSA Calculations

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Self-check

Citations

Cites

Cited by

Metadata

Record

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Data sources