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An Efficient Computational Method for Calculating Ligand Binding Affinities

Virtual compound screening using molecular docking is widely used in the discovery of new lead compounds for drug design. However, the docking scores are not sufficiently precise to represent the protein-ligand binding affinity. Here, we developed an efficient computational method for calculating pr...

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Detalles Bibliográficos
Autores principales: Suenaga, Atsushi, Okimoto, Noriaki, Hirano, Yoshinori, Fukui, Kazuhiko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3423425/
https://www.ncbi.nlm.nih.gov/pubmed/22916168
http://dx.doi.org/10.1371/journal.pone.0042846
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author Suenaga, Atsushi
Okimoto, Noriaki
Hirano, Yoshinori
Fukui, Kazuhiko
author_facet Suenaga, Atsushi
Okimoto, Noriaki
Hirano, Yoshinori
Fukui, Kazuhiko
author_sort Suenaga, Atsushi
collection PubMed
description Virtual compound screening using molecular docking is widely used in the discovery of new lead compounds for drug design. However, the docking scores are not sufficiently precise to represent the protein-ligand binding affinity. Here, we developed an efficient computational method for calculating protein-ligand binding affinity, which is based on molecular mechanics generalized Born/surface area (MM-GBSA) calculations and Jarzynski identity. Jarzynski identity is an exact relation between free energy differences and the work done through non-equilibrium process, and MM-GBSA is a semimacroscopic approach to calculate the potential energy. To calculate the work distribution when a ligand is pulled out of its binding site, multiple protein-ligand conformations are randomly generated as an alternative to performing an explicit single-molecule pulling simulation. We assessed the new method, multiple random conformation/MM-GBSA (MRC-MMGBSA), by evaluating ligand-binding affinities (scores) for four target proteins, and comparing these scores with experimental data. The calculated scores were qualitatively in good agreement with the experimental binding affinities, and the optimal docking structure could be determined by ranking the scores of the multiple docking poses obtained by the molecular docking process. Furthermore, the scores showed a strong linear response to experimental binding free energies, so that the free energy difference of the ligand binding (ΔΔG) could be calculated by linear scaling of the scores. The error of calculated ΔΔG was within ≈±1.5 kcal•mol(−1) of the experimental values. Particularly, in the case of flexible target proteins, the MRC-MMGBSA scores were more effective in ranking ligands than those generated by the MM-GBSA method using a single protein-ligand conformation. The results suggest that, owing to its lower computational costs and greater accuracy, the MRC-MMGBSA offers efficient means to rank the ligands, in the post-docking process, according to their binding affinities, and to compare these directly with the experimental values.
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spelling pubmed-34234252012-08-22 An Efficient Computational Method for Calculating Ligand Binding Affinities Suenaga, Atsushi Okimoto, Noriaki Hirano, Yoshinori Fukui, Kazuhiko PLoS One Research Article Virtual compound screening using molecular docking is widely used in the discovery of new lead compounds for drug design. However, the docking scores are not sufficiently precise to represent the protein-ligand binding affinity. Here, we developed an efficient computational method for calculating protein-ligand binding affinity, which is based on molecular mechanics generalized Born/surface area (MM-GBSA) calculations and Jarzynski identity. Jarzynski identity is an exact relation between free energy differences and the work done through non-equilibrium process, and MM-GBSA is a semimacroscopic approach to calculate the potential energy. To calculate the work distribution when a ligand is pulled out of its binding site, multiple protein-ligand conformations are randomly generated as an alternative to performing an explicit single-molecule pulling simulation. We assessed the new method, multiple random conformation/MM-GBSA (MRC-MMGBSA), by evaluating ligand-binding affinities (scores) for four target proteins, and comparing these scores with experimental data. The calculated scores were qualitatively in good agreement with the experimental binding affinities, and the optimal docking structure could be determined by ranking the scores of the multiple docking poses obtained by the molecular docking process. Furthermore, the scores showed a strong linear response to experimental binding free energies, so that the free energy difference of the ligand binding (ΔΔG) could be calculated by linear scaling of the scores. The error of calculated ΔΔG was within ≈±1.5 kcal•mol(−1) of the experimental values. Particularly, in the case of flexible target proteins, the MRC-MMGBSA scores were more effective in ranking ligands than those generated by the MM-GBSA method using a single protein-ligand conformation. The results suggest that, owing to its lower computational costs and greater accuracy, the MRC-MMGBSA offers efficient means to rank the ligands, in the post-docking process, according to their binding affinities, and to compare these directly with the experimental values. Public Library of Science 2012-08-20 /pmc/articles/PMC3423425/ /pubmed/22916168 http://dx.doi.org/10.1371/journal.pone.0042846 Text en © 2012 Suenaga et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Suenaga, Atsushi
Okimoto, Noriaki
Hirano, Yoshinori
Fukui, Kazuhiko
An Efficient Computational Method for Calculating Ligand Binding Affinities
title An Efficient Computational Method for Calculating Ligand Binding Affinities
title_full An Efficient Computational Method for Calculating Ligand Binding Affinities
title_fullStr An Efficient Computational Method for Calculating Ligand Binding Affinities
title_full_unstemmed An Efficient Computational Method for Calculating Ligand Binding Affinities
title_short An Efficient Computational Method for Calculating Ligand Binding Affinities
title_sort efficient computational method for calculating ligand binding affinities
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3423425/
https://www.ncbi.nlm.nih.gov/pubmed/22916168
http://dx.doi.org/10.1371/journal.pone.0042846
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