Department of Pharmaceutics, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Udupi 576104, India.
Manipal Centre for Infectious Diseases, Prasanna School of Public Health, Manipal Academy of Higher Education, Udupi 576104, India.
Viruses. 2023 Jan 12;15(1):213. doi: 10.3390/v15010213.
The coronavirus disease (COVID-19) is a pandemic that started in the City of Wuhan, Hubei Province, China, caused by the spread of coronavirus (SARS-CoV-2). Drug discovery teams around the globe are in a race to develop a medicine for its management. It takes time for a novel molecule to enter the market, and the ideal way is to exploit the already approved drugs and repurpose them therapeutically. We have attempted to screen selected molecules with an affinity towards multiple protein targets in COVID-19 using the Schrödinger suit for in silico predictions. The proteins selected were angiotensin-converting enzyme-2 (ACE2), main protease (MPro), and spike protein. The molecular docking, prime MM-GBSA, induced-fit docking (IFD), and molecular dynamics (MD) simulations were used to identify the most suitable molecule that forms a stable interaction with the selected viral proteins. The ligand-binding stability for the proteins PDB-IDs 1ZV8 (spike protein), 5R82 (Mpro), and 6M1D (ACE2), was in the order of nintedanib > quercetin, nintedanib > darunavir, nintedanib > baricitinib, respectively. The MM-GBSA, IFD, and MD simulation studies imply that the drug nintedanib has the highest binding stability among the shortlisted. Nintedanib, primarily used for idiopathic pulmonary fibrosis, can be considered for repurposing for us against COVID-19.
新型冠状病毒病(COVID-19)是一种始于中国湖北省武汉市的大流行疾病,由冠状病毒(SARS-CoV-2)传播引起。全球的药物发现团队正在竞相开发一种治疗该病的药物。新型分子进入市场需要时间,理想的方法是利用已批准的药物并将其重新用于治疗。我们试图使用 Schrödinger 套件对 COVID-19 中具有多种蛋白质靶标亲和力的选定分子进行计算机预测筛选。选择的蛋白质是血管紧张素转化酶-2(ACE2)、主要蛋白酶(MPro)和刺突蛋白。使用分子对接、Prime MM-GBSA、诱导契合对接(IFD)和分子动力学(MD)模拟来识别与所选病毒蛋白形成稳定相互作用的最合适分子。蛋白质 PDB-ID 1ZV8(刺突蛋白)、5R82(Mpro)和 6M1D(ACE2)的配体结合稳定性顺序为:尼达尼布>槲皮素、尼达尼布>达芦那韦、尼达尼布>巴瑞替尼。MM-GBSA、IFD 和 MD 模拟研究表明,在筛选出的药物中,尼达尼布具有最高的结合稳定性。尼达尼布主要用于特发性肺纤维化,可考虑将其重新用于治疗 COVID-19。