Centre for Environmental Assessment and Climate Change, G.B. Pant National Institute of Himalayan Environment (GBP-NIHE), Kosi-Katarmal, Almora 263643, Uttarakhand, India.
Department of Botany, DSB Campus, Kumaun University, Nainital 263002, Uttarakhand, India.
Molecules. 2022 Mar 2;27(5):1639. doi: 10.3390/molecules27051639.
Among the various types of cancer, lung cancer is the second most-diagnosed cancer worldwide. The kinesin spindle protein, Eg5, is a vital protein behind bipolar mitotic spindle establishment and maintenance during mitosis. Eg5 has been reported to contribute to cancer cell migration and angiogenesis impairment and has no role in resting, non-dividing cells. Thus, it could be considered as a vital target against several cancers, such as renal cancer, lung cancer, urothelial carcinoma, prostate cancer, squamous cell carcinoma, etc. In recent years, fungal secondary metabolites from the Indian Himalayan Region (IHR) have been identified as an important lead source in the drug development pipeline. Therefore, the present study aims to identify potential mycotic secondary metabolites against the Eg5 protein by applying integrated machine learning, chemoinformatics based in silico-screening methods and molecular dynamic simulation targeting lung cancer. Initially, a library of 1830 mycotic secondary metabolites was screened by a predictive machine-learning model developed based on the random forest algorithm with high sensitivity (1) and an ROC area of 0.99. Further, 319 out of 1830 compounds screened with active potential by the model were evaluated for their drug-likeness properties by applying four filters simultaneously, viz., Lipinski's rule, CMC-50 like rule, Veber rule, and Ghose filter. A total of 13 compounds passed from all the above filters were considered for molecular docking, functional group analysis, and cell line cytotoxicity prediction. Finally, four hit mycotic secondary metabolites found in fungi from the IHR were screened viz., (-)-Cochlactone-A, Phelligridin C, Sterenin E, and Cyathusal A. All compounds have efficient binding potential with Eg5, containing functional groups like aromatic rings, rings, carboxylic acid esters, and carbonyl and with cell line cytotoxicity against lung cancer cell lines, namely, MCF-7, NCI-H226, NCI-H522, A549, and NCI H187. Further, the molecular dynamics simulation study confirms the docked complex rigidity and stability by exploring root mean square deviations, root mean square fluctuations, and radius of gyration analysis from 100 ns simulation trajectories. The screened compounds could be used further to develop effective drugs against lung and other types of cancer.
在各种癌症中，肺癌是全球第二大常见癌症。驱动蛋白纺锤体蛋白 Eg5 是有丝分裂纺锤体建立和维持过程中双极纺锤体所必需的蛋白质。据报道，Eg5 有助于癌细胞迁移和血管生成损伤，在静止、非分裂细胞中没有作用。因此，它可以被认为是对抗多种癌症的重要靶点，如肾癌、肺癌、尿路上皮癌、前列腺癌、鳞状细胞癌等。近年来，印度喜马拉雅地区（IHR）的真菌次生代谢产物已被确定为药物开发管道中的重要先导来源。因此，本研究旨在通过应用集成机器学习、基于化学生信学的虚拟筛选方法和针对肺癌的分子动力学模拟，鉴定针对 Eg5 蛋白的潜在真菌次生代谢产物。最初，通过基于随机森林算法的预测性机器学习模型筛选了 1830 种真菌次生代谢产物库，该模型具有高灵敏度（1）和 ROC 面积为 0.99。进一步，通过模型筛选出具有潜在活性的 1830 种化合物中，有 319 种化合物同时应用四个过滤器评估其药物相似性特性，即 Lipinski 规则、CMC-50 相似规则、Veber 规则和 Ghose 过滤器。所有上述过滤器都通过的总共 13 种化合物被认为可用于分子对接、功能基团分析和细胞系细胞毒性预测。最后，从 IHR 真菌中筛选出四种命中的真菌次生代谢产物，即（-）-Cochlactone-A、Phelligridin C、Sterenin E 和 Cyathusal A。所有化合物与 Eg5 具有有效的结合潜力，含有芳香环、环、羧酸酯和羰基等功能基团，对肺癌细胞系 MCF-7、NCI-H226、NCI-H522、A549 和 NCI H187 具有细胞系细胞毒性。此外，分子动力学模拟研究通过探索 100ns 模拟轨迹的均方根偏差、均方根波动和回转半径分析，证实了对接复合物的刚性和稳定性。筛选出的化合物可进一步用于开发针对肺癌和其他类型癌症的有效药物。
