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Abstract：
Cancer is a serious threat to human life and social development and the use of scientific methods for cancer prevention and control is necessary. In this study, HQSAR, CoMFA, CoMSIA and TopomerCoMFA methods are used to establish models of 65 imidazo[4,5-b]pyridine derivatives to explore the quantitative structure-activity relationship between their anticancer activities and molecular conformations. The results show that the cross-validation coefficients q2 of HQSAR, CoMFA, CoMSIA and TopomerCoMFA are 0.892, 0.866, 0.877 and 0.905, respectively. The non-cross-validation coefficients r2 are 0.948, 0.983, 0.995 and 0.971, respectively. The externally validated complex correlation coefficients r2pred of external validation are 0.814, 0.829, 0.758 and 0.855, respectively. The PLS analysis verifies that the QSAR models have the highest prediction ability and stability. Based on these statistics, virtual screening based on R group is performed using the ZINC database by the Topomer search technology. Finally, 10 new compounds with higher activity are designed with the screened new fragments. In order to explore the binding modes and targets between ligands and protein receptors, these newly designed compounds are conjugated with macromolecular protein (PDB ID: 1MQ4) by molecular docking technology. Furthermore, to study the nature of the newly designed compound in dynamic states and the stability of the protein-ligand complex, molecular dynamics simulation is carried out for N3, N4, N5 and N7 docked with 1MQ4 protease structure for 50 ns. A free energy landscape is computed to search for the most stable conformation. These results prove the efficient and stability of the newly designed compounds. Finally, ADMET is used to predict the pharmacology and toxicity of the 10 designed drug molecules.
摘要：
癌症严重威胁着人类的生命和社会发展，运用科学的方法进行癌症的预防和控制是十分必要的。在这项研究中,HQSAR,CoMFA,CoMSIA和TopomerCoMFA方法用于建立65种咪唑并[4,5-b]吡啶衍生物的模型，以探索其抗癌活性与分子构象之间的定量构效关系。结果表明,HQSAR的交叉验证系数q2,CoMFA,CoMSIA和TopomerCoMFA分别为0.892、0.866、0.877和0.905。非交叉验证系数r2分别为0.948、0.983、0.995和0.971。外部验证的复相关系数r2pred分别为0.814、0.829、0.758和0.855。PLS分析验证了QSAR模型具有最高的预测能力和稳定性。根据这些统计数据,通过Topomer搜索技术使用ZINC数据库进行基于R组的虚拟筛查。最后,用筛选的新片段设计了10个具有较高活性的新化合物。为了探索配体与蛋白质受体之间的结合模式和作用靶点,这些新设计的化合物通过分子对接技术与大分子蛋白（PDBID：1MQ4）缀合。此外，为了研究新设计的化合物在动态状态下的性质和蛋白质-配体复合物的稳定性，对与1MQ4蛋白酶结构对接的N3，N4，N5和N7进行了50ns的分子动力学模拟。计算自由能景观以搜索最稳定的构象。这些结果证明了新设计的化合物的有效性和稳定性。最后,ADMET用于预测所设计的10种药物分子的药理学和毒性。
