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环己烷-1,3-二酮衍生物作为非小细胞肺癌的未来治疗药物:定量构效关系建模、计算机辅助药物代谢动力学-毒理学性质研究及基于结构的药物设计方法

Cyclohexane-1,3-dione Derivatives as Future Therapeutic Agents for NSCLC: QSAR Modeling, In Silico ADME-Tox Properties, and Structure-Based Drug Designing Approach.

作者信息

Daoui Ossama, Elkhattabi Souad, Bakhouch Mohamed, Belaidi Salah, Bhandare Richie R, Shaik Afzal B, Mali Suraj N, Chtita Samir

机构信息

Laboratory of Engineering, Systems and Applications, National School of Applied Sciences, Sidi Mohamed Ben Abdellah-Fez University, BP Box 72, Fez30000, Morocco.

Laboratory of Bioorganic Chemistry, Department of Chemistry, Faculty of Sciences, Chouaïb Doukkali University, P.O. Box 24, 24000El Jadida, Morocco.

出版信息

ACS Omega. 2023 Jan 19;8(4):4294-4319. doi: 10.1021/acsomega.2c07585. eCollection 2023 Jan 31.

Abstract

The abnormal expression of the c-Met tyrosine kinase has been linked to the proliferation of several human cancer cell lines, including non-small-cell lung cancer (NSCLC). In this context, the identification of new c-Met inhibitors based on heterocyclic small molecules could pave the way for the development of a new cancer therapeutic pathway. Using multiple linear regression (MLR)-quantitative structure-activity relationship (QSAR) and artificial neural network (ANN)-QSAR modeling techniques, we look at the quantitative relationship between the biological inhibitory activity of 40 small molecules derived from cyclohexane-1,3-dione and their topological, physicochemical, and electronic properties against NSCLC cells. In this regard, screening methods based on QSAR modeling with density-functional theory (DFT) computations, in silico pharmacokinetic/pharmacodynamic (ADME-Tox) modeling, and molecular docking with molecular electrostatic potential (MEP) and molecular mechanics-generalized Born surface area (MM-GBSA) computations were used. Using physicochemical (stretch-bend, hydrogen bond acceptor, Connolly molecular area, polar surface area, total connectivity) and electronic (total energy, highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy levels) molecular descriptors, compound is identified as the optimal scaffold for drug design based on in silico screening tests. The computer-aided modeling developed in this study allowed us to design, optimize, and screen a new class of 36 small molecules based on cyclohexane-1,3-dione as potential c-Met inhibitors against NSCLC cell growth. The in silico rational drug design approach used in this study led to the identification of nine lead compounds for NSCLC therapy via c-Met protein targeting. Finally, the findings are validated using a 100 ns series of molecular dynamics simulations in an aqueous environment on c-Met free and complexed with samples of the proposed lead compounds and Foretinib drug.

摘要

c-Met酪氨酸激酶的异常表达与包括非小细胞肺癌(NSCLC)在内的多种人类癌细胞系的增殖有关。在此背景下,基于杂环小分子鉴定新的c-Met抑制剂可为开发新的癌症治疗途径铺平道路。利用多元线性回归(MLR)-定量构效关系(QSAR)和人工神经网络(ANN)-QSAR建模技术,我们研究了40种源自环己烷-1,3-二酮的小分子对NSCLC细胞的生物抑制活性与其拓扑、物理化学和电子性质之间的定量关系。在这方面,使用了基于QSAR建模与密度泛函理论(DFT)计算、计算机模拟药代动力学/药效学(ADME-Tox)建模以及分子对接与分子静电势(MEP)和分子力学-广义玻恩表面积(MM-GBSA)计算的筛选方法。利用物理化学(伸缩弯曲、氢键受体、康诺利分子面积、极性表面积、总连接性)和电子(总能量、最高占据分子轨道(HOMO)和最低未占据分子轨道(LUMO)能级)分子描述符,基于计算机模拟筛选试验确定化合物为药物设计的最佳支架。本研究中开发的计算机辅助建模使我们能够设计、优化和筛选一类基于环己烷-1,3-二酮的新型36种小分子作为潜在的c-Met抑制剂,以抑制NSCLC细胞生长。本研究中使用的计算机模拟合理药物设计方法通过靶向c-Met蛋白鉴定出9种用于NSCLC治疗的先导化合物。最后,使用100纳秒的分子动力学模拟在水性环境中对游离的c-Met以及与所提出的先导化合物样品和Foretinib药物复合的c-Met进行验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28ae/9893467/270847ee00be/ao2c07585_0002.jpg

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