虚拟筛选
药效团
药物发现
计算生物学
数量结构-活动关系
蛋白质酪氨酸磷酸酶
生物
化学
生物信息学
生物化学
酶
作者
Ying Ma,Yuanyuan Jin,Ye‐Liu Wang,Run‐Ling Wang,Xinhua Lu,Dexin Kong,Weiren Xu
摘要
Given the special role of insulin and leptin signaling in various biological responses, protein-tyrosine phosphatase-1B (PTP1B) was regarded as a novel therapeutic target for treating type 2 diabetes and obesity. However, owing to the highly conserved (sequence identity of about 74%) in active pocket, targeting PTP1B for drug discovery is a great challenge. In this study, we employed the software package Discovery Studio to develop 3D QSAR pharmacophore models for PTP1B and TCPTP inhibitors. It was further validated by three methods (cost analysis, test set prediction, and Fisher's test) to show that the models can be used to predict the biological activities of compounds without costly and time-consuming synthesis. The criteria for virtual screening were also validated by testing the selective PTP1B inhibitors. Virtual screening experiments and subsequent in vitro evaluation of promising hits revealed a novel and selective inhibitor of PTP1B over TCPTP. After that, a most likely binding mode was proposed. Thus, the findings reported here may provide a new strategy in discovering selective PTP1B inhibitors.
科研通智能强力驱动
Strongly Powered by AbleSci AI