基于3D QSAR、分子对接和MMGBSA分析的新型嘧啶衍生物表皮生长因子受体抑制剂结构鉴定:抗癌药物设计的一种合理方法

Pradipta Jana, Shivangi Agarwal, Varsha Kashaw, R. Das, A. Dixit, S. Kashaw
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引用次数: 0

摘要

非小细胞肺癌(NSCLC)已经发展成为目前最致命的疾病。NSCLC的进展主要是由于酪氨酸激酶家族表皮生长因子受体(EGFR)的失调。因此,EGFR作为治疗NSCLC的主要靶点已被广泛研究,但缺乏选择性和耐药限制了现有治疗剂的使用。考虑到进一步开发EGFR抑制剂的迫切需要,我们对一系列嘧啶衍生物进行了三维构效关系(3D QSAR)、分子对接和MMGBSA研究。在三维QSAR中,获得比较分子场分析模型(CoMFA),相关系数(r2) = 0.698,交叉验证相关系数(q2) = 0.541,预测r2 (r2pred) = 0.509。比较分子相似指数分析(CoMSIA)模型也显示出相似的结果,r2 = 0.72, q2 = 0.586, r2pred= 0.495。统计参数满足模型的可接受性标准。对接研究揭示了嘧啶衍生物与双突变体EGFRL858R/T790M的结合相互作用。前两位入选化合物29和34的对接得分分别为92.99和92.13。通过对QSAR三维等高线图和对接结果的分析,回顾了EGFR L858R/T790M选择性抑制剂的一些重要结构属性,为新分子的设计提供了指导。设计的化合物具有良好的预测活性,并且与EGFRL858R/T790M的结合相互作用比参考配体吉非替尼更高。此外,为了评估对接中选择的顶部命中点与设计化合物的结合,进行了MMGBSA(分子力学-广义Born表面积)分析,结果表明,与其他化合物相比,设计的化合物(N7)与EGFRL858R/T790M具有良好的结合亲和力(dG = -68.59 kcal/mol)。此外,计算机ADME预测揭示了所设计化合物的药物相似性。因此,这项工作将指导研究人员在未来发展嘧啶衍生物作为EGFR抑制剂。
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Structural identification of novel pyrimidine derivatives as epidermal growth factor receptor inhibitors using 3D QSAR, molecular docking, and MMGBSA analysis: a rational approach in anticancer drug design
Non-small cell lung cancer (NSCLC) has evolved into the deadliest in the present scenario. The progression of NSCLC is mainly due to the dysregulation of the tyrosine kinase family's epidermal growth factor receptor (EGFR). Thus, EGFR has been widely studied as a major target in the treatment of NSCLC, but the lack of selectivity and drug resistance limit the use of existing therapeutic agents. Considering the urgent necessity for the advanced development of EGFR inhibitors, we have implemented a three-dimensional structure-activity relationship (3D QSAR), molecular docking, and MMGBSA studies on a series of pyrimidine derivatives. In the 3D QSAR, the comparative molecular field analysis model (CoMFA) was obtained with a correlation coefficient (r2) = 0.698, cross-validated correlation coefficient (q2) = 0.541, and predictive r2 (r2pred) = 0.509. The comparative molecular similarity indices analysis (CoMSIA) model also displayed similar results with r2 = 0.72, q2 = 0.586, and r2pred= 0.495. The statistical parameters fulfill the acceptability criteria of the models. Docking studies revealed the binding interactions of the pyrimidine derivatives with double mutant EGFRL858R/T790M. Docking scores of the top two selected compounds 29 and 34 were 92.99 and 92.13, respectively. Analyzing 3D QSAR contour plots and docking results reviewed some important structural attributes of EGFR L858R/T790M selective inhibitors, which directed the designing of some new molecules. The designed compounds showed good predictive activity and exhibited higher binding interactions with EGFRL858R/T790M than the reference ligand gefitinib. Moreover, to evaluate the binding of selected top hits from docking and designed compounds, MMGBSA (Molecular Mechanics-Generalized Born Surface Area) analysis was performed, which revealed that the designed compound (N7) showed a good binding affinity with EGFRL858R/T790M (dG = -68.59 kcal/mol) as compared to other compounds. Further, in silico ADME predictions revealed the drug-likeness of the designed compounds. Thus, this work will guide researchers in future developments of pyrimidine derivatives as EGFR inhibitors.
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