Shaikh Gulam Moin, Murahari Manikanta, Thakur Shikha, Kumar Maushmi S, Yc Mayur
Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM'S NMIMS, V.L. Mehta Road, Vile Parle West, Mumbai, 400056, India.
Department of Pharmaceutical Chemistry, Faculty of Pharmacy, M.S. Ramaiah University of Applied Sciences, Bangalore, 560054, India.
J Mol Graph Model. 2022 May;112:108114. doi: 10.1016/j.jmgm.2021.108114. Epub 2021 Dec 25.
Epidermal growth factor receptor (EGFR) is a validated drug target for cancer chemotherapy. Mutations in EGFR are directly linked with the development of drug resistance and this has led for the development of newer drugs in quest for more efficacious inhibitors. The current research is focused on identifying potential and safe molecules as EGFR inhibitors by using both structure and ligand based computational approaches. In quest for finding newer moieties, we have developed a pharmacophore model utilizing drugs like lazertinib, osimertinib, nazartinib, avitinib, afatininb, and talazoparib that are known to inhibit EGFR along with their downstream signaling. Ligand-based pharmacophore model have been developed to screen the ZINC database through ZINCPharmer webserver. The server has identified 9482 best possible ligands with high pharmacophoric similarity i.e., RMSD value less than 0.2 Å. The top 10 ligands with the criteria of dock score(s) and interactions were further subjected to in silico ADMET studies giving two plausible ligands that were further subjected to Molecular Dynamics and MM/PBSA free energy calculations to ensure stability to the target site. Results deduced by in silico work in the current study may be corroborated biologically in the future. The current work, therefore, provides ample opportunity for computational and medicinal chemists to work in allied areas to facilitate the design and development of novel and more efficacious EGFR inhibitors for future experimental studies.
表皮生长因子受体(EGFR)是癌症化疗中一个经过验证的药物靶点。EGFR突变与耐药性的产生直接相关,这促使人们开发更新的药物以寻找更有效的抑制剂。当前的研究重点是通过基于结构和配体的计算方法来识别潜在的安全分子作为EGFR抑制剂。为了寻找更新的部分,我们利用了拉泽替尼、奥希替尼、纳扎替尼、阿维替尼、阿法替尼和他拉唑帕尼等已知能抑制EGFR及其下游信号传导的药物开发了一个药效团模型。基于配体的药效团模型已被开发出来,通过ZINCPharmer网络服务器筛选ZINC数据库。该服务器已识别出9482种具有高药效团相似性(即RMSD值小于0.2 Å)的最佳可能配体。根据对接分数和相互作用标准,对前10种配体进一步进行了计算机辅助的ADMET研究,得到了两种合理的配体,进一步对其进行了分子动力学和MM/PBSA自由能计算,以确保对靶点部位的稳定性。当前研究中计算机模拟工作得出的结果未来可能会在生物学上得到证实。因此,当前的工作为计算化学家和药物化学家提供了充足的机会,在相关领域开展工作,以促进新型和更有效EGFR抑制剂的设计和开发,用于未来的实验研究。