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摘要:近年来肿瘤的病发率持续上升，已然成为了严重危害人们身体健康的一大疾病，并成为当今社会主要的致死原因之一，因此研究新型抗肿瘤药成为了我们现在的首要任务。Combretastatin A-4 是由南非的一类灌木（Combretum Caffrum）的树皮经过提炼而获得的拥有有效抗肿瘤活性的组分。本论文通过使用SYBYL-X 2.0，计算机辅助药物设计软件，根据所收集到的48个Combretastatin A-4类似物分子以及它们对于HELA细胞的IC50值，建立有效的3D-QSAR模型。在建模过程中，通过三维定量构效关系法首先建立预测模型，并由交叉验证留一法验证其预测性，其中CoMFA模型的交叉验证系数q2=0.787，最佳主成分数为9，相关系数R2=0.988，标准偏差为0.166，F值为284.546；CoMSIA模型的交叉验证系数q2 =0.779，最佳主成分数为9，相关系数R2=0.982，标准偏差为0.199，F值为196.993，随后进一步通过测试集对其进行验证，最终的结果显示出这一模型对生物活性拥有较好的预测性。然后通过对CoMFA以及CoMSIA模型的色块图进行分析，在所收集的48个Combretastatin A-4类似物中活性最好的分子的基础上设计出新分子，并用所建立的3D-QSAR模型对其活性进行预测，最后按照与蛋白对接的成果，即与蛋白结合的打分值从而筛选出有效抑制子宫颈癌HELA细胞毒性的新型抗肿瘤CombretastatinA-4类似物。最后用Discovery Studio（DS）2.5（Accelrys，San Diego，CA，USA）软件中的ADMET descriptors模块对所设计的新化合物进行药物动力学的预测。70080
毕业论文关键词: CombretastatinA-4；HELA；SYBYL-X 2.0；3D-QSAR；分子对接
Molecular Design of the new antitumor CombretastatinA - 4 Analogues
Abstract: In recent years, cancer incidence rates continue to rise, it has become a serious illness a major threat to people's health, and to become one of the major causes of death in today's society, so the research of new anticancer drugs now become our top priority.Combretastatin A-4 is a component that has an effective antitumor activity obtained by refining the bark of a class of shrubs (Combretum Caffrum) in South Africa.Based on SYBYL-X 2.0, computer-aided drug design software, an effective 3D-QSAR model was established based on the 48 Combretastatin A-4 analogues collected and their IC50 values for HELA cells. In the modeling process, the predictive model is established by the three-dimensional quantitative structure-activity relationship method, and the predictive model is verified by the cross-verification method. The CoMFA model has the cross validation coefficient q2 = 0.787, the best principal component is 9, The coefficient is R2 = 0.988, the standard deviation is 0.166, the F value is 284.546; the CoMSIA model has the cross validation coefficient q2 = 0.779, the best principal component number is 9, the correlation coefficient is R2 = 0.982, the standard deviation is 0.199, the F value is 196.993, Which was further verified by the test set. The final result showed that the model had better predictability for bioactivity.Then, by analyzing the color blocks of CoMFA and CoMSIA models, new molecules were designed on the basis of the best active molecules in the 48 Combretastatin A-4 analogs collected and analyzed with the established 3D-QSAR model. The results were compared with those of the protein, which was the result of the fusion with the protein, that is, the fraction of the protein binding to screen out the new anti-tumor CombretastatinA-4 analogues that effectively inhibited the cytotoxicity of HELA cells in cervical cancer.Finally, the proposed new compounds were predicted by pharmacokinetics using the ADMET descriptors module in Discovery Studio (DS) 2.5 (Accelrys, San Diego, CA, USA) software.
Keywords: CombretastatinA-4；HELA；SYBYL-X 2.0；3D-QSAR；Molecular docking
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