Ikeda Kazuyoshi, Maezawa Yuta, Yonezawa Tomoki, Shimizu Yugo, Tashiro Toshiyuki, Kanai Satoru, Sugaya Nobuyoshi, Masuda Yoshiaki, Inoue Naoko, Niimi Tatsuya, Masuya Keiichi, Mizuguchi Kenji, Furuya Toshio, Osawa Masanori
HPC-and AI-driven Drug Development Platform Division, Center for Computational Science, Yokohama, Kanagawa, Japan.
Division of Physics for Life Functions, Keio University Faculty of Pharmacy, Tokyo, Japan.
Front Chem. 2023 Jan 9;10:1090643. doi: 10.3389/fchem.2022.1090643. eCollection 2022.
Protein-protein interactions (PPIs) are recognized as important targets in drug discovery. The characteristics of molecules that inhibit PPIs differ from those of small-molecule compounds. We developed a novel chemical library database system (DLiP) to design PPI inhibitors. A total of 32,647 PPI-related compounds are registered in the DLiP. It contains 15,214 newly synthesized compounds, with molecular weight ranging from 450 to 650, and 17,433 active and inactive compounds registered by extracting and integrating known compound data related to 105 PPI targets from public databases and published literature. Our analysis revealed that the compounds in this database contain unique chemical structures and have physicochemical properties suitable for binding to the protein-protein interface. In addition, advanced functions have been integrated with the web interface, which allows users to search for potential PPI inhibitor compounds based on types of protein-protein interfaces, filter results by drug-likeness indicators important for PPI targeting such as rule-of-4, and display known active and inactive compounds for each PPI target. The DLiP aids the search for new candidate molecules for PPI drug discovery and is available online (https://skb-insilico.com/dlip).
蛋白质-蛋白质相互作用(PPIs)被认为是药物研发中的重要靶点。抑制PPIs的分子特性与小分子化合物不同。我们开发了一种新型化学文库数据库系统(DLiP)来设计PPI抑制剂。DLiP中总共注册了32647种与PPI相关的化合物。它包含15214种新合成的化合物,分子量在450到650之间,以及通过从公共数据库和已发表文献中提取并整合与105个PPI靶点相关的已知化合物数据而注册的17433种活性和非活性化合物。我们的分析表明,该数据库中的化合物具有独特的化学结构,并且具有适合与蛋白质-蛋白质界面结合的物理化学性质。此外,网络界面集成了先进功能,允许用户根据蛋白质-蛋白质界面的类型搜索潜在的PPI抑制剂化合物,通过对PPI靶向重要的类药指标(如4规则)过滤结果,并显示每个PPI靶点的已知活性和非活性化合物。DLiP有助于寻找用于PPI药物研发的新候选分子,可在线获取(https://skb-insilico.com/dlip)。