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HawkDock: a web server to predict and analyze the protein–protein complex based on computational docking and MM/GBSA
Protein–protein interactions (PPIs) play an important role in the different functions of cells, but accurate prediction of the three-dimensional structures for PPIs is still a notoriously difficult task. In this study, HawkDock, a free and open accessed web server, was developed to predict and analy...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602443/ https://www.ncbi.nlm.nih.gov/pubmed/31106357 http://dx.doi.org/10.1093/nar/gkz397 |
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author | Weng, Gaoqi Wang, Ercheng Wang, Zhe Liu, Hui Zhu, Feng Li, Dan Hou, Tingjun |
author_facet | Weng, Gaoqi Wang, Ercheng Wang, Zhe Liu, Hui Zhu, Feng Li, Dan Hou, Tingjun |
author_sort | Weng, Gaoqi |
collection | PubMed |
description | Protein–protein interactions (PPIs) play an important role in the different functions of cells, but accurate prediction of the three-dimensional structures for PPIs is still a notoriously difficult task. In this study, HawkDock, a free and open accessed web server, was developed to predict and analyze the structures of PPIs. In the HawkDock server, the ATTRACT docking algorithm, the HawkRank scoring function developed in our group and the MM/GBSA free energy decomposition analysis were seamlessly integrated into a multi-functional platform. The structures of PPIs were predicted by combining the ATTRACT docking and the HawkRank re-scoring, and the key residues for PPIs were highlighted by the MM/GBSA free energy decomposition. The molecular visualization was supported by 3Dmol.js. For the structural modeling of PPIs, HawkDock could achieve a better performance than ZDOCK 3.0.2 in the benchmark testing. For the prediction of key residues, the important residues that play an essential role in PPIs could be identified in the top 10 residues for ∼81.4% predicted models and ∼95.4% crystal structures in the benchmark dataset. To sum up, the HawkDock server is a powerful tool to predict the binding structures and identify the key residues of PPIs. The HawkDock server is accessible free of charge at http://cadd.zju.edu.cn/hawkdock/. |
format | Online Article Text |
id | pubmed-6602443 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-66024432019-07-05 HawkDock: a web server to predict and analyze the protein–protein complex based on computational docking and MM/GBSA Weng, Gaoqi Wang, Ercheng Wang, Zhe Liu, Hui Zhu, Feng Li, Dan Hou, Tingjun Nucleic Acids Res Web Server Issue Protein–protein interactions (PPIs) play an important role in the different functions of cells, but accurate prediction of the three-dimensional structures for PPIs is still a notoriously difficult task. In this study, HawkDock, a free and open accessed web server, was developed to predict and analyze the structures of PPIs. In the HawkDock server, the ATTRACT docking algorithm, the HawkRank scoring function developed in our group and the MM/GBSA free energy decomposition analysis were seamlessly integrated into a multi-functional platform. The structures of PPIs were predicted by combining the ATTRACT docking and the HawkRank re-scoring, and the key residues for PPIs were highlighted by the MM/GBSA free energy decomposition. The molecular visualization was supported by 3Dmol.js. For the structural modeling of PPIs, HawkDock could achieve a better performance than ZDOCK 3.0.2 in the benchmark testing. For the prediction of key residues, the important residues that play an essential role in PPIs could be identified in the top 10 residues for ∼81.4% predicted models and ∼95.4% crystal structures in the benchmark dataset. To sum up, the HawkDock server is a powerful tool to predict the binding structures and identify the key residues of PPIs. The HawkDock server is accessible free of charge at http://cadd.zju.edu.cn/hawkdock/. Oxford University Press 2019-07-02 2019-05-20 /pmc/articles/PMC6602443/ /pubmed/31106357 http://dx.doi.org/10.1093/nar/gkz397 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://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 Weng, Gaoqi Wang, Ercheng Wang, Zhe Liu, Hui Zhu, Feng Li, Dan Hou, Tingjun HawkDock: a web server to predict and analyze the protein–protein complex based on computational docking and MM/GBSA |
title | HawkDock: a web server to predict and analyze the protein–protein complex based on computational docking and MM/GBSA |
title_full | HawkDock: a web server to predict and analyze the protein–protein complex based on computational docking and MM/GBSA |
title_fullStr | HawkDock: a web server to predict and analyze the protein–protein complex based on computational docking and MM/GBSA |
title_full_unstemmed | HawkDock: a web server to predict and analyze the protein–protein complex based on computational docking and MM/GBSA |
title_short | HawkDock: a web server to predict and analyze the protein–protein complex based on computational docking and MM/GBSA |
title_sort | hawkdock: a web server to predict and analyze the protein–protein complex based on computational docking and mm/gbsa |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602443/ https://www.ncbi.nlm.nih.gov/pubmed/31106357 http://dx.doi.org/10.1093/nar/gkz397 |
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