Fu Songsen, Chen Zhen, Luo Zhiming, Nie Meiyun, Fu Tingting, Zhou Ying, Yang Qingxia, Zhu Feng, Ni Feng
Institute of Drug Discovery Technology, Ningbo University, Ningbo 315211, China.
LeadArt Biotechnologies Ltd., Ningbo 315201, China.
Nucleic Acids Res. 2025 Jan 6;53(D1):D1651-D1662. doi: 10.1093/nar/gkae943.
Chemoproteomic probes (CPPs) have been widely considered as powerful molecular biological tools that enable the highly efficient discovery of both binding proteins and modes of action for the studied compounds. They have been successfully used to validate targets and identify binders. The design of CPP has been considered extremely challenging, which asks for the generalization using a large number of probe data. However, none of the existing databases gives such valuable data of CPPs. Herein, a database entitled 'Chem(Pro)2' was therefore developed to systematically describe the atlas of diverse types of CPPs labelling human protein in living cell/lysate. With the booming application of chemoproteomic technique and artificial intelligence in current chemical biology study, Chem(Pro)2 was expected to facilitate the AI-based learning of interacting pattern among molecules for discovering innovative targets and new drugs. Till now, Chem(Pro)2 has been open to all users without any login requirement at: https://idrblab.org/chemprosquare/.
化学蛋白质组学探针(CPPs)已被广泛认为是强大的分子生物学工具,能够高效发现所研究化合物的结合蛋白和作用模式。它们已成功用于验证靶点和识别结合物。CPP的设计被认为极具挑战性,这需要使用大量探针数据进行归纳。然而,现有的数据库都没有提供如此有价值的CPP数据。因此,本文开发了一个名为“Chem(Pro)2”的数据库,用于系统描述在活细胞/裂解物中标记人类蛋白质的各种类型CPP的图谱。随着化学蛋白质组学技术和人工智能在当前化学生物学研究中的蓬勃应用,预计Chem(Pro)2将促进基于人工智能的分子间相互作用模式学习,以发现创新靶点和新药。到目前为止,Chem(Pro)2已向所有用户开放,无需任何登录,网址为:https://idrblab.org/chemprosquare/ 。