烟台大学学报（自然科学与工程版）2025，Vol.38Issue(1)：92-100,9.DOI:10.13951/j.cnki.37-1213/n.240112
基于人工智能的PLK1 PBD新型抑制剂的筛选
Screening of Novel Inhibitors of PLK1 PBD Based on Artificial Intelligence
摘要
Abstract
The COVIDVS model,based on compound property prediction,and the RTMScore model,based on pro-tein-compound interaction prediction,were used for virtual screening of more than 1.4 million compounds.New small molecule inhibitors targeting PLK1 PBD were selected according to their binding patterns in binding pockets(tyrosine binding pockets and phosphopeptide-binding pockets containing H538 and K540).The inhibitory activity on HCT116 tumor cells was determined by MTT assay,and the anti-proliferation and migration ability of HCT116 tumor cells were assessed by cell cloning and cell scratch experiments.Finally,the targeting properties of the com-pounds were verified by molecular dynamics simulation and cell heat transfer analysis experiments.The results showed that 5 compounds were selected from the 2291 compounds with a COVIDVS predicted score of 1 and RTM-Score ≥80,among which compound 1 had an inhibition rate of more than 60％on HCT116 tumor cells at 10 μmol·L-1,with an IC50 of 7.24 μmol·L-1.Compound 1 inhibited the formation of HCT116 cell clones and the migration of HCT116 tumor cells.Molecular simulations showed that compound 1 could bind to the PLK1 PBD domain,which was confirmed by the cell heat transfer experiments.关键词
PLK1/PBD结构域/小分子抑制剂/活性测试Key words
PLK1/Polo-box domain/small-molecule inhibitor/activity assay分类
医药卫生引用本文复制引用
朱艳娟,刘小倩,冯大为,王璐琪,刘钰杭,曹琳慧,芦静..基于人工智能的PLK1 PBD新型抑制剂的筛选[J].烟台大学学报（自然科学与工程版）,2025,38(1):92-100,9.基金项目
泰山学者项目(主持人:赵克浩). （主持人:赵克浩）
