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流感核酸内切酶抑制剂的3D-QSAR及分子对接研究

时间:2021-08-16 20:38来源:毕业论文
收集大量的苯甲酸及其衍生物,建立预测能力良好,具有显著统计学意义的三维定量构效关系(3D-QSAR)模型。其中所建CoMFA模型:q2值0.764,R2 值0.994,F值为688.780;CoMSIA模型的q2值0.792

摘要:流行性感冒,简称流感,是由流感病毒引起的急性呼吸道传染病,是一种严重威胁人类健康,具有极大危害性的疾病。RNA核酸内切酶是最新发现的抗流感药物作用的靶标。实验表明苯甲酸及其衍生物是RNA核酸内切酶的有效抑制剂。本文首先收集大量的苯甲酸及其衍生物,建立预测能力良好,具有显著统计学意义的三维定量构效关系(3D-QSAR)模型。其中所建CoMFA模型:q2值0.764,R2 值0.994,F值为688.780;CoMSIA模型的q2值0.792,R2值0.981, F值为327.939。根据所建模型产生的等势图,设计出高抑制活性的新化合物。通过分子对接技术研究其与受体蛋白的结合情况。新设计化合物的药代动力学性质,如吸收、分布、代谢、排泄和毒性(ADMET)等性质用ADMET描述符进行了预测,其预测参数为新型抗流感药物的设计与合成提供了有价值的信息。70963

毕业论文关键词: 3D-QSAR;分子对接;药代动力学;RNA

3D - QSAR and molecular docking studies of influenza endonuclease inhibitors

Abstract:Influenza virus referred to as influenza virus, is caused by human influenza, avian flu and other human and animal disease causes. Pandemic influenza outbreaks pose a significant threat to public health. RNA endonuclease is the newest and desired target for developing agents against influenza viruses.it was reported that benzoic acid and its derivatives are effective inhibitors of RNA endonuclease. In this paper, a large number of benzoic acid and its derivatives were collected. The 3D-QSAR models were built with significant statistical quality and excellent predictive ability. The square correlation coefficient (r2) and cross-validated squared correlation coefficient (q2) of CoMFA are 0.994 and 0.764; the r2 and q2 of CoMSIA are 0.981 and 0.792, respectively. Based on the built models, some new inhibitors were designed and predicted. Molecular docking elucidates the binding mode at the active site of RNA endonuclease. Absorption, distribution, metabolism, elimination, and toxicity (ADMET) properties were predicted using ADMET descriptors. Finally, several newly discovered inhibitors were found to pass the entire ADMET test.

Keywords:3D-QSAR; molecular docking;Pharmacokinetics; RNA

目录

第一章 7

1.1研究背景与目的 7

1.2研究现状与进展 7

1.2.1核酸内切酶抑制剂 9

1.3研究的基本内容 12

第二章理论原理及计算方法 13

2.1  SYBYL软件 13

2.2  三维定量构效关系 13

2.3 研究方法概述 14

2.3.1 分子力场选择……………………………………………………………14

2.3.2 分子叠合…………………………………………………………………14

2.3.3 CoMFA、CoMSIA和偏最小二乘法的简介……………………………14

2.4 研究方案 15

2.4.1 数据集的选择和结构的优化…………………………………………...15

2.4.2 共同骨架选取和分子叠合……………………………………………...15 流感核酸内切酶抑制剂的3D-QSAR及分子对接研究:http://www.youerw.com/huaxue/lunwen_80466.html

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