Journal of Chemical Information and Modeling· 2014Q1
<i>g_mmpbsa</i>—A GROMACS Tool for High-Throughput MM-PBSA Calculations
- 4,822citations
- Q1SCImago
- 2014year
Short summary
A new tool, g_mmpbsa, integrates high-throughput molecular dynamics simulations with MM-PBSA binding energy calculations, demonstrating effectiveness by correlating calculated energies of 37 HIV-1 protease inhibitor complexes with experimental binding free energies.
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Key points
- g_mmpbsa is a new tool for high-throughput MM-PBSA calculations, integrating molecular dynamics simulations with binding energy estimation.
- It offers flexibility in atomic radii, nonpolar solvation models (SASA, SAV, SASA-SAV), and parameter choices.
- The tool successfully correlated calculated interaction energies with experimental binding free energies for 37 HIV-1 protease inhibitor complexes.
- g_mmpbsa can also determine residue-specific contributions to binding energy, identifying critical residues for inhibitor binding in HIV-1 protease.
AI-generated from the title and abstract; the full text is not read.
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.
The authors' abstract, as published at the source. Journal of Chemical Information and Modeling, 2014 · DOI ↗
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Field: Infectious Diseases
Infectious DiseasesMedicine