Department of Software Engineering, Faculty of Mathematics and Physics, Charles University, Czech Republic.
Department of Cell Biology, Faculty of Science, Charles University, Czech Republic.
Nucleic Acids Res. 2022 Jul 5;50(W1):W593-W597. doi: 10.1093/nar/gkac389.
Knowledge of protein-ligand binding sites (LBSs) enables research ranging from protein function annotation to structure-based drug design. To this end, we have previously developed a stand-alone tool, P2Rank, and the web server PrankWeb (https://prankweb.cz/) for fast and accurate LBS prediction. Here, we present significant enhancements to PrankWeb. First, a new, more accurate evolutionary conservation estimation pipeline based on the UniRef50 sequence database and the HMMER3 package is introduced. Second, PrankWeb now allows users to enter UniProt ID to carry out LBS predictions in situations where no experimental structure is available by utilizing the AlphaFold model database. Additionally, a range of minor improvements has been implemented. These include the ability to deploy PrankWeb and P2Rank as Docker containers, support for the mmCIF file format, improved public REST API access, or the ability to batch download the LBS predictions for the whole PDB archive and parts of the AlphaFold database.
蛋白质-配体结合位点(LBS)的知识使研究范围从蛋白质功能注释扩展到基于结构的药物设计。为此,我们之前开发了一个独立的工具 P2Rank 和网络服务器 PrankWeb(https://prankweb.cz/),用于快速准确地预测 LBS。在这里,我们对 PrankWeb 进行了重大改进。首先,引入了一个新的、更准确的基于 UniRef50 序列数据库和 HMMER3 包的进化保守性估计管道。其次,PrankWeb 现在允许用户输入 UniProt ID,利用 AlphaFold 模型数据库在没有实验结构的情况下进行 LBS 预测。此外,还实施了一系列较小的改进。其中包括能够将 PrankWeb 和 P2Rank 部署为 Docker 容器,支持 mmCIF 文件格式,改进公共 REST API 访问,或能够批量下载整个 PDB 档案和部分 AlphaFold 数据库的 LBS 预测。