Balogun Toheeb A, Chukwudozie Onyeka S, Ogbodo Uchechukwu C, Junaid Idris O, Sunday Olugbodi A, Ige Oluwasegun M, Aborode Abdullahi T, Akintayo Abiola D, Oluwarotimi Emmanuel A, Oluwafemi Isaac O, Saibu Oluwatosin A, Chuckwuemaka Prosper, Omoboyowa Damilola A, Alausa Abdullahi O, Atasie Nkechi H, Ilesanmi Ayooluwa, Dairo Gbenga, Tiamiyu Zainab A, Batiha Gaber E, Alkhuriji Afrah Fahad, Al-Megrin Wafa Abdullah I, De Waard Michel, Sabatier Jean-Marc
Department of Biochemistry, Adekunle Ajasin University, Akungba-Akoko, Nigeria.
Department of Biological Sciences, University of California, San Diego, San Diego, CA, United States.
Front Chem. 2022 Oct 11;10:964446. doi: 10.3389/fchem.2022.964446. eCollection 2022.
SARS-CoV-2 triggered a worldwide medical crisis, affecting the world's social, emotional, physical, and economic equilibrium. However, treatment choices and targets for finding a solution to COVID-19's threat are becoming limited. A viable approach to combating the threat of COVID-19 is by unraveling newer pharmacological and therapeutic targets pertinent in the viral survival and adaptive mechanisms within the host biological milieu which in turn provides the opportunity to discover promising inhibitors against COVID-19. Therefore, using high-throughput virtual screening, manually curated compounds library from some medicinal plants were screened against four main drivers of SARS-CoV-2 (spike glycoprotein, PLpro, 3CLpro, and RdRp). In addition, molecular docking, Prime MM/GBSA (molecular mechanics/generalized Born surface area) analysis, molecular dynamics (MD) simulation, and drug-likeness screening were performed to identify potential phytodrugs candidates for COVID-19 treatment. In support of these approaches, we used a series of computational modeling approaches to develop therapeutic agents against COVID-19. Out of the screened compounds against the selected SARS-CoV-2 therapeutic targets, only compounds with no violations of Lipinski's rule of five and high binding affinity were considered as potential anti-COVID-19 drugs. However, lonchocarpol A, diplacol, and broussonol E (lead compounds) were recorded as the best compounds that satisfied this requirement, and they demonstrated their highest binding affinity against 3CLpro. Therefore, the 3CLpro target and the three lead compounds were selected for further analysis. Through protein-ligand mapping and interaction profiling, the three lead compounds formed essential interactions such as hydrogen bonds and hydrophobic interactions with amino acid residues at the binding pocket of 3CLpro. The key amino acid residues at the 3CLpro active site participating in the hydrophobic and polar inter/intra molecular interaction were TYR54, PRO52, CYS44, MET49, MET165, CYS145, HIS41, THR26, THR25, GLN189, and THR190. The compounds demonstrated stable protein-ligand complexes in the active site of the target (3CLpro) over a 100 ns simulation period with stable protein-ligand trajectories. Drug-likeness screening shows that the compounds are druggable molecules, and the toxicity descriptors established that the compounds demonstrated a good biosafety profile. Furthermore, the compounds were chemically reactive with promising molecular electron potential properties. Collectively, we propose that the discovered lead compounds may open the way for establishing phytodrugs to manage COVID-19 pandemics and new chemical libraries to prevent COVID-19 entry into the host based on the findings of this computational investigation.
严重急性呼吸综合征冠状病毒2引发了一场全球医疗危机,影响着世界的社会、情感、身体和经济平衡。然而,应对2019冠状病毒病威胁的治疗选择和靶点正变得有限。对抗2019冠状病毒病威胁的一种可行方法是揭示与病毒在宿主生物环境中的生存和适应机制相关的新的药理学和治疗靶点,这反过来又为发现有前景的抗2019冠状病毒病抑制剂提供了机会。因此,利用高通量虚拟筛选,针对严重急性呼吸综合征冠状病毒2的四个主要驱动因子(刺突糖蛋白、木瓜蛋白酶样蛋白酶、3C样蛋白酶和RNA依赖性RNA聚合酶),对一些药用植物的人工精选化合物库进行了筛选。此外,还进行了分子对接、Prime MM/GBSA(分子力学/广义玻恩表面积)分析、分子动力学模拟和类药性筛选,以确定用于治疗2019冠状病毒病的潜在植物药候选物。为支持这些方法,我们使用了一系列计算建模方法来开发抗2019冠状病毒病的治疗药物。在针对选定的严重急性呼吸综合征冠状病毒2治疗靶点筛选出的化合物中,只有不违反Lipinski五规则且具有高结合亲和力的化合物才被视为潜在的抗2019冠状病毒病药物。然而,鱼藤醇A、二氢愈创木醇和 Broussonol E(先导化合物)被记录为满足这一要求的最佳化合物,它们对3C样蛋白酶表现出最高的结合亲和力。因此,选择3C样蛋白酶靶点和这三种先导化合物进行进一步分析。通过蛋白质-配体图谱和相互作用分析,这三种先导化合物与3C样蛋白酶结合口袋处的氨基酸残基形成了诸如氢键和疏水相互作用等重要相互作用。参与疏水和极性分子间/分子内相互作用的3C样蛋白酶活性位点的关键氨基酸残基为TYR54、PRO52、CYS44、MET49、MET165、CYS145、HIS41、THR26、THR25、GLN189和THR190。在100纳秒的模拟期内,这些化合物在靶点(3C样蛋白酶)的活性位点表现出稳定的蛋白质-配体复合物,且蛋白质-配体轨迹稳定。类药性筛选表明这些化合物是可成药分子,毒性描述符表明这些化合物具有良好的生物安全性。此外,这些化合物具有化学反应性,具有良好的分子电子势性质。总体而言,基于这项计算研究的结果,我们提出所发现的先导化合物可能为建立用于管理2019冠状病毒病大流行的植物药以及用于防止2019冠状病毒病进入宿主的新化学文库开辟道路。