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MM/PB(GB)SA benchmarks on soluble proteins and membrane proteins
Predicting protein-ligand binding free energy rapidly and accurately remains a challenging question in modern drug discovery. Molecular mechanics/Poisson-Boltzmann (Generalized Born) surface area (MM/PB(GB)SA) has emerged as an essential tool for accelerating cost-efficient binding free energy calcu...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9751045/ https://www.ncbi.nlm.nih.gov/pubmed/36532746 http://dx.doi.org/10.3389/fphar.2022.1018351 |
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author | Wang, Shiyu Sun, Xiaolin Cui, Wenqiang Yuan, Shuguang |
author_facet | Wang, Shiyu Sun, Xiaolin Cui, Wenqiang Yuan, Shuguang |
author_sort | Wang, Shiyu |
collection | PubMed |
description | Predicting protein-ligand binding free energy rapidly and accurately remains a challenging question in modern drug discovery. Molecular mechanics/Poisson-Boltzmann (Generalized Born) surface area (MM/PB(GB)SA) has emerged as an essential tool for accelerating cost-efficient binding free energy calculation. This study presents benchmarks with three membrane-bound protein systems and six soluble protein systems. Different parameters were sampled for different benchmarks to explore the highest accuracy. These include ligand charges, protein force fields, extra points, GB models, nonpolar optimization methods, internal dielectric constants and membrane dielectric constants. Comparisons of accuracy were made between MM/PB(GB)SA, docking and free energy perturbation (FEP). The results reveal a competitive performance between MM/PB(GB)SA and FEP. In summary, MM/PB(GB)SA is a powerful approach to predict ligand binding free energy rapidly and accurately. Parameters of MM/PB(GB)SA calculations, such as the GB models and membrane dielectric constants, need to be optimized for different systems. This method can be served as a powerful tool for drug design. |
format | Online Article Text |
id | pubmed-9751045 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97510452022-12-16 MM/PB(GB)SA benchmarks on soluble proteins and membrane proteins Wang, Shiyu Sun, Xiaolin Cui, Wenqiang Yuan, Shuguang Front Pharmacol Pharmacology Predicting protein-ligand binding free energy rapidly and accurately remains a challenging question in modern drug discovery. Molecular mechanics/Poisson-Boltzmann (Generalized Born) surface area (MM/PB(GB)SA) has emerged as an essential tool for accelerating cost-efficient binding free energy calculation. This study presents benchmarks with three membrane-bound protein systems and six soluble protein systems. Different parameters were sampled for different benchmarks to explore the highest accuracy. These include ligand charges, protein force fields, extra points, GB models, nonpolar optimization methods, internal dielectric constants and membrane dielectric constants. Comparisons of accuracy were made between MM/PB(GB)SA, docking and free energy perturbation (FEP). The results reveal a competitive performance between MM/PB(GB)SA and FEP. In summary, MM/PB(GB)SA is a powerful approach to predict ligand binding free energy rapidly and accurately. Parameters of MM/PB(GB)SA calculations, such as the GB models and membrane dielectric constants, need to be optimized for different systems. This method can be served as a powerful tool for drug design. Frontiers Media S.A. 2022-12-01 /pmc/articles/PMC9751045/ /pubmed/36532746 http://dx.doi.org/10.3389/fphar.2022.1018351 Text en Copyright © 2022 Wang, Sun, Cui and Yuan. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pharmacology Wang, Shiyu Sun, Xiaolin Cui, Wenqiang Yuan, Shuguang MM/PB(GB)SA benchmarks on soluble proteins and membrane proteins |
title | MM/PB(GB)SA benchmarks on soluble proteins and membrane proteins |
title_full | MM/PB(GB)SA benchmarks on soluble proteins and membrane proteins |
title_fullStr | MM/PB(GB)SA benchmarks on soluble proteins and membrane proteins |
title_full_unstemmed | MM/PB(GB)SA benchmarks on soluble proteins and membrane proteins |
title_short | MM/PB(GB)SA benchmarks on soluble proteins and membrane proteins |
title_sort | mm/pb(gb)sa benchmarks on soluble proteins and membrane proteins |
topic | Pharmacology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9751045/ https://www.ncbi.nlm.nih.gov/pubmed/36532746 http://dx.doi.org/10.3389/fphar.2022.1018351 |
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