基于药效团模型的PPAR激动剂的筛选及活性研究

Screening and activity of PPARδagonists based on pharmacophore model

目的筛选具有PPARδ激动活性的化合物。方法通过构建PPARδ药效团模型对Top Science数据库中的780万个小分子进行筛选,并采用对接分析通过化合物与受体之间的结合作用模式及其靶点选择性进行筛选;通过分子动力学模拟的方法,确定苗头化合物,进而通过体外活性实验获得PPARδ激动剂。结果通过计算机虚拟筛选获得了24个潜在PPARδ激动剂,分子对接结果表明,化合物3、5、9为潜在的PPARδ选择性激动剂。体外激动活性实验表明化合物3、5、9具有一定的PPARδ激动活性。结论与化合物3、5相比,化合物9拥有更强的体外激动活性(EC_(50)=17.66μmol·L^(-1)),后续可进行结构迭代优化,为进一步开发PPARδ激动剂奠定了基础。

Objective To screen the compounds with PPARδagonizing activity.Methods PPARδpharmacophore model was established to screen 7.8 million small molecules in the Top Science database.Docking analysis was used to screen the binding mode and target selectivity between compounds and receptors.PPARδagonists were obtained by in vitro activity experiment after identifying the hits with molecular dynamics simulation.Results Totally 24 potential PPARδagonists were obtained by computer virtual screening.Molecular docking indicated that compounds 3,5,and 9 were potential PPARδselective agonists and showed certain PPARδactivity in the in vitro activity tests.Conclusion Compound 9 can be used as a hit for structural iterative optimization,which lays a foundation for further development of PPARδagonists with stronger in vitro activity(EC_(50)=17.66μmol·L^(-1)).