Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, China.
Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China.
Nucleic Acids Res. 2022 Jul 5;50(W1):W159-W164. doi: 10.1093/nar/gkac394.
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/.
蛋白配体盲态对接是一种探索受体结合位点和配体相应结合构象的强大方法。它在药物和生物研究中得到了广泛的应用。此前，我们提出了一个盲态对接服务器 CB-Dock，自 2019 年以来，它一直被全球研究人员大量使用（每天超过 200 次提交）。在这里，我们通过将 CB-Dock 与基于模板的对接引擎相结合，极大地改进了对接方法，从而提高了识别结合位点和预测结合构象的准确性。在基准测试中，它的结合构象预测成功率约为 85%（RMSD<2.0 Å），优于原始的 CB-Dock 和大多数流行的盲态对接工具。这个更新的对接服务器被命名为 CB-Dock2，它重新配置了输入和输出的网页界面，以及一个高度自动化的对接流程，使其成为生物信息学和化学信息学社区的一个特别高效和易于使用的工具。该网页服务器可在 https://cadd.labshare.cn/cb-dock2/ 免费获取。
