Pure Health Laboratory, Mafraq Hospital, Abu Dhabi, United Arab Emirates.
Department of Biomedical Engineering, Faculty of Engineering, Science, Technology and Management, Ziauddin University, Karachi, Pakistan.
J Infect Dev Ctries. 2024 Apr 30;18(4):520-531. doi: 10.3855/jidc.18189.
The coronavirus disease 2019 (COVID-19) pandemic caused global health, economic, and population loss. Variants of the coronavirus contributed to the severity of the disease and persistent rise in infections. This study aimed to identify potential drug candidates from fifteen approved antiviral drugs against SARS-CoV-2 (6LU7), SARS-CoV (5B6O), and SARS-CoV-2 spike protein (6M0J) using virtual screening and pharmacokinetics to gain insights into COVID-19 therapeutics.
We employed drug repurposing approach to analyze binding performance of fifteen clinically approved antiviral drugs against the main protease of SARS-CoV-2 (6LU7), SARS-CoV (5B6O), and SARS-CoV-2 spike proteins bound to ACE-2 receptor (6M0J), to provide an insight into the therapeutics of COVID-19. AutoDock Vina was used for docking studies. The binding affinities were calculated, and 2-3D structures of protein-ligand interactions were drawn.
Rutin, hesperidin, and nelfinavir are clinically approved antiviral drugs with high binding affinity to proteins 6LU7, 5B6O, and 6M0J. These ligands have excellent pharmacokinetics, ensuring efficient absorption, metabolism, excretion, and digestibility. Hesperidin showed the most potent interaction with spike protein 6M0J, forming four H-bonds. Nelfinavir had a high human intestinal absorption (HIA) score of 0.93, indicating maximum absorption in the body and promising interactions with 6LU7.
Our results indicated that rutin, hesperidin, and nelfinavir had the highest binding results against the proposed drug targets. The computational approach effectively identified SARS-CoV-2 inhibitors. COVID-19 is still a recurrent threat globally and predictive analysis using natural compounds might serve as a starting point for new drug development against SARS-CoV-2 and related viruses.
2019 年冠状病毒病(COVID-19)大流行造成了全球健康、经济和人口损失。冠状病毒变体导致了疾病的严重程度和感染的持续上升。本研究旨在通过虚拟筛选和药代动力学,从 15 种针对 SARS-CoV-2(6LU7)、SARS-CoV(5B6O)和 SARS-CoV-2 刺突蛋白(6M0J)的已批准抗病毒药物中确定潜在的药物候选物,以深入了解 COVID-19 的治疗方法。
我们采用药物再利用方法分析了 15 种临床批准的抗病毒药物对 SARS-CoV-2 主要蛋白酶(6LU7)、SARS-CoV(5B6O)和与 ACE-2 受体结合的 SARS-CoV-2 刺突蛋白(6M0J)的结合性能,以深入了解 COVID-19 的治疗方法。使用 AutoDock Vina 进行对接研究。计算了结合亲和力,并绘制了蛋白质-配体相互作用的 2-3D 结构。
芦丁、橙皮苷和奈非那韦是具有高结合亲和力的临床批准抗病毒药物,与蛋白 6LU7、5B6O 和 6M0J 结合。这些配体具有良好的药代动力学特性,可确保有效吸收、代谢、排泄和消化。橙皮苷与刺突蛋白 6M0J 表现出最强的相互作用,形成四个氢键。奈非那韦的人体肠道吸收率(HIA)评分为 0.93,表明在体内最大吸收,与 6LU7 有很好的相互作用。
我们的结果表明,芦丁、橙皮苷和奈非那韦对提出的药物靶标具有最高的结合效果。计算方法有效地鉴定了 SARS-CoV-2 抑制剂。COVID-19 仍然是全球持续存在的威胁,使用天然化合物进行预测分析可能成为开发针对 SARS-CoV-2 和相关病毒的新药的起点。