4D-QSAR and MIA-QSAR Studies of Aminobenzimidazole Derivatives as Fourth-generation EGFR Inhibitors

数量结构-活动关系 偏最小二乘回归 T790米 化学 表皮生长因子受体抑制剂 表皮生长因子受体 计算生物学 立体化学 计算机科学 生物 机器学习 生物化学 受体 吉非替尼
作者
Xuegong Jia,Chaochun Wei,Nana Tian,Hong Yan,Hongjun Wang
出处
期刊:Medicinal Chemistry [Bentham Science Publishers]
卷期号:20 (2): 140-152 被引量:1
标识
DOI:10.2174/0115734064258994231106052633
摘要

Background:: The epidermal growth factor receptor (EGFR) protein has been intensively studied as a therapeutic target for non-small cell lung cancer (NSCLC). The aminobenzimidazole derivatives as the fourth-generation EGFR inhibitors have achieved promising results and overcame EGFR mutations at C797S, del19 and T790M in NSCLC. Objective:: In order to understand the quantitative structure-activity relationship (QSAR) of aminobenzimidazole derivatives as EGFRdel19 T790M C797S inhibitors, the four-dimensional QSAR (4D-QSAR) and multivariate image analysis (MIA-QSAR) have been performed on the data of 45 known aminobenzimidazole derivatives. Methods:: The 4D-QSAR descriptors were acquired by calculating the association energies between probes and aligned conformational ensemble profiles (CEP), and the regression models were established by partial least squares (PLS). In order to further understand and verify the 4D-QSAR model, MIA-QSAR was constructed by using chemical structure pictures to generate descriptors and PLS regression. Furthermore, the molecular docking and averaged noncovalent interactions (aNCI) analysis were also performed to further understand the interactions between ligands and the EGFR targets, which was in good agreement with the 4D-QSAR model. Results:: The established 4D-QSAR and MIA-QSAR models have strong stability and good external prediction ability. Conclusion:: These results will provide theoretical guidance for the research and development of aminobenzimidazole derivatives as new EGFRdel19 T790M C797S inhibitors.

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