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作 者:张继川 何严萍[2] 王月平[1] ZHANG Ji-chuan;HE Yan-ping;WANG Yue-ping(Department of Applied Chemistry,Faculty of Science,Kunming University of Science and Technology,Kunming 650500,Yunnan,China;Key Laboratory of Medicinal Chemistry for Natural Resource,Ministry of Education,Yunnan Research&Development Center for Natural Products,School of Chemical Science and Technology,Yunnan University,Kunming 650091,Yunnan,China)
机构地区:[1]昆明理工大学理学院应用化学系,云南昆明650500 [2]云南大学教育部自然资源药物化学重点实验室,化学科学与工程学院,云南昆明650091
出 处:《云南大学学报(自然科学版)》2022年第4期831-839,共9页Journal of Yunnan University(Natural Sciences Edition)
基 金:国家自然科学基金(21362017,21967020)。
摘 要:3CL蛋白酶在冠状病毒复制过程中起着极为关键的作用,是重要的药物靶标.采用分子对接的方法产生了38个三芳基吡啶酮类化合物的活性构象.并以此为基础,应用比较分子力场分析(CoMFA)方法对其三维定量构效关系进行了研究:以30个化合物构成的训练集所建立的CoMFA模型,其交叉验证系数q^(2)为0.810,非交叉验证相关系数r^(2)为0.981,标准偏差SEE为0.099.对由8个化合物构成的测试集进行了预测,其预测相关系数r^(2)_(pred)为0.855,表明所建模型具有良好的拟合能力及预测能力.基于CoMFA等势面图,探讨了此类化合物立体场与静电场的有利结构特征,并以此为理论指导设计了一组具有良好预测活性的三芳基吡啶酮类3CL蛋白酶抑制剂,为此类化合物的进一步优化提供了理论指导.3CL proteinase plays a critical role in the replication process of coronavirus and is an important drug target.The interaction of 38 triarylpyridinones with 3CL hydrolase was studied by molecular docking method.On this basis,comparative molecular force analysis(CoMFA)was applied to study the three-dimensional quantitative structure-activity relationships of these compounds.In the CoMFA model based on the training set of 30 compounds,the cross-validation coefficient q^(2) was 0.810,the non-cross-validation correlation coefficient r^(2) was 0.981,and the standard deviation SEE was 0.099.The prediction coefficient r^(2) _(pred) of the test set composed of 8 compounds was 0.855,which indicated that the model had good fitting ability and prediction ability.Based on the CoMFA contour maps,the favorable structural characteristics of these compounds in steric field and electrostatic field were discussed.On this basis,a group of triarylpyridinone 3CL proteinase inhibitors with good predictive activity were designed,which provides theoretical guidance for further structural optimization of these compounds.
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