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CB-Dock2: improved protein–ligand blind docking by integrating cavity detection, docking and homologous template fitting
Protein-ligand blind docking is a powerful method for exploring the binding sites of receptors and the corresponding binding poses of ligands. It has seen wide applications in pharmaceutical and biological researches. Previously, we proposed a blind docking server, CB-Dock, which has been under heav...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252749/ https://www.ncbi.nlm.nih.gov/pubmed/35609983 http://dx.doi.org/10.1093/nar/gkac394 |
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author | Liu, Yang Yang, Xiaocong Gan, Jianhong Chen, Shuang Xiao, Zhi-Xiong Cao, Yang |
author_facet | Liu, Yang Yang, Xiaocong Gan, Jianhong Chen, Shuang Xiao, Zhi-Xiong Cao, Yang |
author_sort | Liu, Yang |
collection | PubMed |
description | Protein-ligand blind docking is a powerful method for exploring the binding sites of receptors and the corresponding binding poses of ligands. It has seen wide applications in pharmaceutical and biological researches. Previously, we proposed a blind docking server, CB-Dock, which has been under heavy use (over 200 submissions per day) by researchers worldwide since 2019. Here, we substantially improved the docking method by combining CB-Dock with our template-based docking engine to enhance the accuracy in binding site identification and binding pose prediction. In the benchmark tests, it yielded the success rate of ∼85% for binding pose prediction (RMSD < 2.0 Å), which outperformed original CB-Dock and most popular blind docking tools. This updated docking server, named CB-Dock2, reconfigured the input and output web interfaces, together with a highly automatic docking pipeline, making it a particularly efficient and easy-to-use tool for the bioinformatics and cheminformatics communities. The web server is freely available at https://cadd.labshare.cn/cb-dock2/. |
format | Online Article Text |
id | pubmed-9252749 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-92527492022-07-05 CB-Dock2: improved protein–ligand blind docking by integrating cavity detection, docking and homologous template fitting Liu, Yang Yang, Xiaocong Gan, Jianhong Chen, Shuang Xiao, Zhi-Xiong Cao, Yang Nucleic Acids Res Web Server Issue Protein-ligand blind docking is a powerful method for exploring the binding sites of receptors and the corresponding binding poses of ligands. It has seen wide applications in pharmaceutical and biological researches. Previously, we proposed a blind docking server, CB-Dock, which has been under heavy use (over 200 submissions per day) by researchers worldwide since 2019. Here, we substantially improved the docking method by combining CB-Dock with our template-based docking engine to enhance the accuracy in binding site identification and binding pose prediction. In the benchmark tests, it yielded the success rate of ∼85% for binding pose prediction (RMSD < 2.0 Å), which outperformed original CB-Dock and most popular blind docking tools. This updated docking server, named CB-Dock2, reconfigured the input and output web interfaces, together with a highly automatic docking pipeline, making it a particularly efficient and easy-to-use tool for the bioinformatics and cheminformatics communities. The web server is freely available at https://cadd.labshare.cn/cb-dock2/. Oxford University Press 2022-05-24 /pmc/articles/PMC9252749/ /pubmed/35609983 http://dx.doi.org/10.1093/nar/gkac394 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Web Server Issue Liu, Yang Yang, Xiaocong Gan, Jianhong Chen, Shuang Xiao, Zhi-Xiong Cao, Yang CB-Dock2: improved protein–ligand blind docking by integrating cavity detection, docking and homologous template fitting |
title | CB-Dock2: improved protein–ligand blind docking by integrating cavity detection, docking and homologous template fitting |
title_full | CB-Dock2: improved protein–ligand blind docking by integrating cavity detection, docking and homologous template fitting |
title_fullStr | CB-Dock2: improved protein–ligand blind docking by integrating cavity detection, docking and homologous template fitting |
title_full_unstemmed | CB-Dock2: improved protein–ligand blind docking by integrating cavity detection, docking and homologous template fitting |
title_short | CB-Dock2: improved protein–ligand blind docking by integrating cavity detection, docking and homologous template fitting |
title_sort | cb-dock2: improved protein–ligand blind docking by integrating cavity detection, docking and homologous template fitting |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252749/ https://www.ncbi.nlm.nih.gov/pubmed/35609983 http://dx.doi.org/10.1093/nar/gkac394 |
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