Nucleic Acids Research· 2022Q1
CB-Dock2: improved protein–ligand blind docking by integrating cavity detection, docking and homologous template fitting
- 1,855citations
- Q1SCImago
- 2022year
Short summary
CB-Dock2, a new blind docking server, integrates cavity detection, docking, and homologous template fitting to achieve ~85% success rate in binding pose prediction (RMSD < 2.0 Å), outperforming its predecessor and other popular tools.
AI-generated from the title and abstract; the full text is not read.
Key points
- CB-Dock2 integrates cavity detection, docking, and homologous template fitting for improved blind docking.
- Achieved a ~85% success rate in binding pose prediction (RMSD < 2.0 Å) on benchmark tests.
- Outperforms the original CB-Dock and most popular blind docking tools in accuracy.
- Features a highly automatic pipeline with reconfigured web interfaces for ease of use.
AI-generated from the title and abstract; the full text is not read.
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/.
The authors' abstract, as published at the source. Nucleic Acids Research, 2022 · DOI ↗
Continue with a free account
Ask the paper: 3 free questions a day about this paper; save it, get its citation, new summaries every day for your field. Takeaways are Premium.
Continue free on the webSign in with Google or Apple; no card needed. You come back to this paper.
On your phone:
Field: Computational Theory and Mathematics
Computational Theory and MathematicsComputer Science