摘要：  随着经济社会的发展，人们的生活水平也提高了，可与此同时人类也面临着更多的问题，尤其是身体健康方面。目前为止最严重的问题基本上都是高频率出现的癌症。因此，新型PI3K抑制剂和抗癌剂的发现吸引了许多对抗癌药物研究领域的兴趣，并夺得了人们大量的关注与期待。在本课题中，对三维定量结构-活动关系（3D-QSAR）和分子对接进行了综合性研究，探讨了34个氨基吡啶类PI3K抑制剂的结构与活性的影响，建立了配体合成比较分子场分析（COMFA）和分子相似性指数分析（COMSIA）模型，其显示出了良好的可预测性（COMFA：q2为0.514，R2为0.970，F为124.189;  COMSIA：q2为0.579，R2为0.993，F为435.286）。三维轮廓图和对接结果提示着不同化合物核心部分的群体可以增强生物活性。69700

毕业论文关键词:  癌症; 3D-QSAR; PI3K抑制剂; 计算机辅助药物设计; 分子对接

3D-QSAR model study of Aminopyridine PI3K inhibitors

Abstract:  With the economic and social development, people's living standards have increased, but at the same time humans are also facing more problems, especially in terms of health. So far the most serious problems are basically high frequency of cancer. Therefore, the discovery of new PI3K inhibitors and anticancer agents has attracted many interest in the field of anticancer drug research and has received a lot of attention and expectation. In this study, 3D-QSAR and molecular docking were studied comprehensively. The effects of 34 aminopyridine PI3K inhibitors on the structure and activity were discussed, and the results based on ligand . The COMFA and COMIA models showed good predictability (COMFA: q2 is 0.514, R2 is 0.970, F is 124.189; COMSIA: q2 is 0.579, R2 is 0.993, F is 435.286). The three-dimensional profile and docking results suggest that the population of the core of the different compounds can enhance biological activity.

Keywords:  cancer; 3D-QSAR; PI3K inhibitor; CADD; molecular docking 

目  录

第1章 前言.... 1

1.1 癌症 1

1.2 PI3K类抗癌药的研究 1

    1.3计算机辅助药物设计 3

       1.3.1 计算机辅助药物设计的定义 3

       1.3.2 计算机辅助药物设计的原理 4

    1.4 3D-QSAR的简介 4

    1.5分子的对接 4

第2章 数据的来源、方法与结果分析 5

2.1 数据的来源 5

   2.1.1 化合物的选取 5

   2.1.2 氨基吡啶类衍生物的结构与IC50值 5

2.2 化合物的基本骨架和叠合 10

 2.2.1 骨架的选取 10

 2.2.2 最佳训练集的选取 12

    2.3 3D-QSAR模型 12

2.4 3D-QSAR等高线图 14

 2.4.1 CoMFA模型的等高线图 17

 2.4.2 CoMSIA模型的等高线图 19

2.5 分子对接 22

 2.5.1 分子对接的研究与结果 22

 2.5.2 对接分析