Adhikari Nilanjan, Banerjee Suvankar, Baidya Sandip Kumar, Ghosh Balaram, Jha Tarun
Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700032, India.
Epigenetic Research Laboratory, Birla Institute of Technology and Science-Pilani Hyderabad Campus, Shamirpet, Hyderabad, India, 500078.
J Mol Struct. 2022 Mar 5;1251:132041. doi: 10.1016/j.molstruc.2021.132041. Epub 2021 Nov 29.
Due to COVID-19, the whole world is undergoing a devastating situation, but treatment with no such drug candidates still has been established exclusively. In that context, 69 diverse chemicals with potential SARS-CoV-2 3CL inhibitory property were taken into consideration for building different internally and externally validated linear (SW-MLR and GA-MLR), non-linear (ANN and SVM) QSAR, and HQSAR models to identify important structural and physicochemical characters required for SARS-CoV-2 3CL inhibition. Importantly, 2-oxopyrrolidinyl methyl and benzylester functions, and methylene (hydroxy) sulphonic acid warhead group, were crucial for retaining higher SARS-CoV-2 3CL inhibition. These GA-MLR and HQSAR models were also applied to predict some already repurposed drugs. As per the GA-MLR model, curcumin, ribavirin, saquinavir, sepimostat, and remdesivir were found to be the potent ones, whereas according to the HQSAR model, lurasidone, saquinavir, lopinavir, elbasvir, and paritaprevir were the highly effective SARS-CoV-2 3CL inhibitors. The binding modes of those repurposed drugs were also justified by the molecular docking, molecular dynamics (MD) simulation, and binding energy calculations conducted by several groups of researchers. This current work, therefore, may be able to find out important structural parameters to accelerate the COVID-19 drug discovery processes in the future.
由于新冠疫情,全球正经历着一场毁灭性的局面,但针对该疾病仍未确定专门的治疗药物。在此背景下,研究人员考虑了69种具有潜在抗SARS-CoV-2 3CL活性的不同化学物质,构建了不同的内部和外部验证的线性(SW-MLR和GA-MLR)、非线性(ANN和SVM)定量构效关系(QSAR)以及全息定量构效关系(HQSAR)模型,以确定SARS-CoV-2 3CL抑制所需的重要结构和物理化学特征。重要的是,2-氧代吡咯烷基甲基和苄酯官能团以及亚甲基(羟基)磺酸弹头基团对于保持较高的SARS-CoV-2 3CL抑制活性至关重要。这些GA-MLR和HQSAR模型还被用于预测一些已被重新利用的药物。根据GA-MLR模型,姜黄素、利巴韦林、沙奎那韦匹莫司他和瑞德西韦被发现是有效的药物,而根据HQSAR模型,鲁拉西酮、沙奎那韦、洛匹那韦、埃尔巴韦和帕立普韦是高效的SARS-CoV-2 3CL抑制剂。几组研究人员通过分子对接、分子动力学(MD)模拟和结合能计算,也证明了这些重新利用药物的结合模式。因此,这项当前的工作或许能够找出重要的结构参数,以加速未来新冠药物的研发进程。