基于虚拟筛选的3DQSAR药效团设计CDC25B抑制剂

3D QSAR pharmacophore based on virtual screening for design of CDC25B inhibitors

目的:用计算机辅助药物设计的方法发现潜在的CDC25B抑制剂。方法:用Hypogen方法研究CDC25B抑制剂。cost分析、测试集预测和Fisher检验用来验证该模型的可靠性。随后,运用hypo-1-CDC25B对ZINC数据库进行筛选,得到符合成药五规则的26个化合物,26个化合物进行分子对接得到6个对接得分高的化合物。结果:通过分子对接研究,发现6个化合物有较好的亲和力。结论:发现6个潜在的CDC25B抑制剂,这有助于发现治疗癌症的强有力的先导化合物。

Objective:To explore potential the cell division cycle25B(CDC25B)inhibitors by the method of computer-aided drug design.Methods:In this study,3D QSAR pharmacophore models for CDC25B inhibitors were developed by the module of Hypogen.Three methods(cost analysis,test set prediction,and Fisher’s test)were applied to validate whether the models could be used to predict the biological activities of compounds.Subsequently,26compounds meeting Lipinski’s rules of five were obtained by the virtual screening of the Hypo-1-CDC25B against ZINC databases.Results:It was discovered that six identified molecules had satisfying binding affinity.Conclusion:Thus,this study would be helpful to discover potent lead compounds for the treatment for cancers.