R基团搜索技术用于硼酸三肽蛋白酶体抑制剂的分子设计
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摘要
本文采用Topomer CoMFA对44个Tyropeptin硼酸三肽类蛋白酶体抑制剂进行三维定量构效关系(3D-QSAR)分析。所得最优模型的拟合、交互验证、及外部验证的复相关系数分别为0.983、0.651、0.963。采用Topomer search对ZINC数据库进行R基团的虚拟筛选,得到具有特定活性贡献的R基团,以活性最高的分子为模板过滤,得到7个R1和5个R2基团。并以此设计得到活性优于模板分子的20个新化合物。结果表明,所建立的Topomer CoMFA模型具有良好的稳定性和预测能力,基于R集团的Topomer search技术可以有效筛选,并为设计出新的蛋白酶体抑制剂提供理论依据。
Topomer CoMFA was adopted to study the three-dimensional quantitative structure-activity relationship(3D-QSAR)for 44 boric acid derivatives of tyropetin inhibitors.The correlation coefficient of cross-validation,non cross-validation and external validation were 0.612,0.985 and 0.963,respectively.Topomer search was used to search R-groups with special activity contribution from ZINC database.As a result,a series of R groups with relatively high activity contribution were obtained.By the highest active molecule filtering 7R_1 group and 5R_3 groups were selected.Finally,20 new compounds with higher activities than that of the template molecule were acquired.The result indicated that Topomer CoMFA model had both favorable estimation stability and good predictive capability.Topomer Search could be effectively used to screen with good predictive capability to guide the design of new anti-cancer drugs.
Topomer CoMFA was adopted to study the three-dimensional quantitative structure-activity relationship(3D-QSAR)for 44 boric acid derivatives of tyropetin inhibitors.The correlation coefficient of cross-validation,non cross-validation and external validation were 0.612,0.985 and 0.963,respectively.Topomer search was used to search R-groups with special activity contribution from ZINC database.As a result,a series of R groups with relatively high activity contribution were obtained.By the highest active molecule filtering 7R_1 group and 5R_3 groups were selected.Finally,20 new compounds with higher activities than that of the template molecule were acquired.The result indicated that Topomer CoMFA model had both favorable estimation stability and good predictive capability.Topomer Search could be effectively used to screen with good predictive capability to guide the design of new anti-cancer drugs.
引文
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