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The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

CB-Dock2: improved protein–ligand blind docking by integrating cavity detection, docking and homologous template fitting

Open access
Liu, Yang, Yang, Xiaocong, Gan, Jianhong, Chen, Shuang, Xiao, Zhi-Xiong, Cao, Yang·2022·Nucleic Acids Research

Abstract

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/.

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Metadata

Authors
Liu, Y., Yang, X., Gan, J., Chen, S., Xiao, Z.-X., & Cao, Y.
Venue
Nucleic Acids Research
Published
2022-05-24
Volume
50
Issue
W1
Pages
W159-W164
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
OpenAlex
W4282913408
Cited by
2,062
References
5
FWCI
160.52
Type
journal article
Language
en
Open access
gold

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