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Superior Performance of the SQM/COSMO Scoring Functions in Native Pose Recognition of Diverse Protein–Ligand Complexes in Cognate Docking
[Image: see text] General and reliable description of structures and energetics in protein–ligand (PL) binding using the docking/scoring methodology has until now been elusive. We address this urgent deficiency of scoring functions (SFs) by the systematic development of corrected semiempirical quant...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American
Chemical
Society
2017
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6044937/ https://www.ncbi.nlm.nih.gov/pubmed/30023710 http://dx.doi.org/10.1021/acsomega.7b00503 |
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author | Ajani, Haresh Pecina, Adam Eyrilmez, Saltuk M. Fanfrlík, Jindřich Haldar, Susanta Řezáč, Jan Hobza, Pavel Lepšík, Martin |
author_facet | Ajani, Haresh Pecina, Adam Eyrilmez, Saltuk M. Fanfrlík, Jindřich Haldar, Susanta Řezáč, Jan Hobza, Pavel Lepšík, Martin |
author_sort | Ajani, Haresh |
collection | PubMed |
description | [Image: see text] General and reliable description of structures and energetics in protein–ligand (PL) binding using the docking/scoring methodology has until now been elusive. We address this urgent deficiency of scoring functions (SFs) by the systematic development of corrected semiempirical quantum mechanical (SQM) methods, which correctly describe all types of noncovalent interactions and are fast enough to treat systems of thousands of atoms. Two most accurate SQM methods, PM6-D3H4X and SCC-DFTB3-D3H4X, are coupled with the conductor-like screening model (COSMO) implicit solvation model in so-called “SQM/COSMO” SFs and have shown unique recognition of native ligand poses in cognate docking in four challenging PL systems, including metalloprotein. Here, we apply the two SQM/COSMO SFs to 17 diverse PL complexes and compare their performance with four widely used classical SFs (Glide XP, AutoDock4, AutoDock Vina, and UCSF Dock). We observe superior performance of the SQM/COSMO SFs and identify challenging systems. This method, due to its generality, comparability across the chemical space, and lack of need for any system-specific parameters, gives promise of becoming, after comprehensive large-scale testing in the near future, a useful computational tool in structure-based drug design and serving as a reference method for the development of other SFs. |
format | Online Article Text |
id | pubmed-6044937 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | American
Chemical
Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-60449372018-07-16 Superior Performance of the SQM/COSMO Scoring Functions in Native Pose Recognition of Diverse Protein–Ligand Complexes in Cognate Docking Ajani, Haresh Pecina, Adam Eyrilmez, Saltuk M. Fanfrlík, Jindřich Haldar, Susanta Řezáč, Jan Hobza, Pavel Lepšík, Martin ACS Omega [Image: see text] General and reliable description of structures and energetics in protein–ligand (PL) binding using the docking/scoring methodology has until now been elusive. We address this urgent deficiency of scoring functions (SFs) by the systematic development of corrected semiempirical quantum mechanical (SQM) methods, which correctly describe all types of noncovalent interactions and are fast enough to treat systems of thousands of atoms. Two most accurate SQM methods, PM6-D3H4X and SCC-DFTB3-D3H4X, are coupled with the conductor-like screening model (COSMO) implicit solvation model in so-called “SQM/COSMO” SFs and have shown unique recognition of native ligand poses in cognate docking in four challenging PL systems, including metalloprotein. Here, we apply the two SQM/COSMO SFs to 17 diverse PL complexes and compare their performance with four widely used classical SFs (Glide XP, AutoDock4, AutoDock Vina, and UCSF Dock). We observe superior performance of the SQM/COSMO SFs and identify challenging systems. This method, due to its generality, comparability across the chemical space, and lack of need for any system-specific parameters, gives promise of becoming, after comprehensive large-scale testing in the near future, a useful computational tool in structure-based drug design and serving as a reference method for the development of other SFs. American Chemical Society 2017-07-27 /pmc/articles/PMC6044937/ /pubmed/30023710 http://dx.doi.org/10.1021/acsomega.7b00503 Text en Copyright © 2017 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes. |
spellingShingle | Ajani, Haresh Pecina, Adam Eyrilmez, Saltuk M. Fanfrlík, Jindřich Haldar, Susanta Řezáč, Jan Hobza, Pavel Lepšík, Martin Superior Performance of the SQM/COSMO Scoring Functions in Native Pose Recognition of Diverse Protein–Ligand Complexes in Cognate Docking |
title | Superior Performance
of the SQM/COSMO Scoring Functions
in Native Pose Recognition of Diverse Protein–Ligand Complexes
in Cognate Docking |
title_full | Superior Performance
of the SQM/COSMO Scoring Functions
in Native Pose Recognition of Diverse Protein–Ligand Complexes
in Cognate Docking |
title_fullStr | Superior Performance
of the SQM/COSMO Scoring Functions
in Native Pose Recognition of Diverse Protein–Ligand Complexes
in Cognate Docking |
title_full_unstemmed | Superior Performance
of the SQM/COSMO Scoring Functions
in Native Pose Recognition of Diverse Protein–Ligand Complexes
in Cognate Docking |
title_short | Superior Performance
of the SQM/COSMO Scoring Functions
in Native Pose Recognition of Diverse Protein–Ligand Complexes
in Cognate Docking |
title_sort | superior performance
of the sqm/cosmo scoring functions
in native pose recognition of diverse protein–ligand complexes
in cognate docking |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6044937/ https://www.ncbi.nlm.nih.gov/pubmed/30023710 http://dx.doi.org/10.1021/acsomega.7b00503 |
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