摘要
采用基于R基团搜索技术的Topomer Co MFA技术对一系列喹诺酮羧酸类衍生物进行三维定量构效(3D-QSAR)关系研究,所得模型结果的交叉验证相关系数(q2)为0.790,非交互验证系数(r2)为0.890,外部验证的复相关系数(r2pred)为0.878,研究结果表明该模型具有良好的稳定性和预测能力。采用Topomer search技术在ZINC数据库中进行虚拟筛选,筛选出6个Ra基团和3个Rb基团,进而设计出12个具有更高活性的新型喹诺酮羧酸类化合物。采用分子对接技术对药物与受体的作用机制进行了研究,结果显示,药物与蛋白酶的ASP 30、ASP 29和ASN 25位点作用明显,该QSAR的研究结果可为新药合成提供理论参考。
The 3 D-QSAR relationships of a series of quinolone carboxylic acid derivatives were studied by Topomer Co MFA technique based on R group search. The interaction validation coefficient(q2),the non-cross correlation coefficient(r~2) and the external validation coefficiont(r_(pred)~2) were0. 790,0. 890 and 0. 878,respectively. The results showed that the model had a good stability and a prediction ability. Topomer search was used to virtually screen lead-like compounds in the ZINC molecular database. As a result,6 Ra groups and 3 Rb groups with higher contribution values were selected. 12 new quinolone carboxylic acid compounds with higher predicted activity were designed.By using molecular docking,the action mechanism of drug and acceptor was studied,and the results showed that the drug functioned obviously with ASP 30,ASP 29 and ASN 25 sites of protease. The QSAR study could provide a theoretical reference for the synthesis of new drugs.
引文
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