Department of Biotechnology, School of Applied Science, REVA University, Bangalore, Karnataka, India.
Department of Biochemistry, School of Applied Science, REVA University, Bangalore, Karnataka, India.
J Mol Graph Model. 2021 Jan;102:107769. doi: 10.1016/j.jmgm.2020.107769. Epub 2020 Oct 13.
Coronavirus outbreak in December 2019 (COVID-19) is an emerging viral disease that poses major menace to Humans and it's a crucial need to find the possible treatment strategies. Spike protein (S2), a envelop glycoprotein aids viral entry into the host cells that corresponds to immunogenic ACE2 receptor binding and represents a potential antiviral drug target. Several drugs such as antimalarial, antibiotic, anti-inflammatory and HIV-protease inhibitors are currently undergoing treatment as clinical studies to test the efficacy and safety of COVID-19. Some promising results have been observed with the patients and also with high mortality rate. Hence, there is a need to screen the best CoV inhibitors using insilico analysis. The Molecular methodologies applied in the present study are, Molecular docking, virtual screening, drug-like and ADMET prediction helps to target CoV inhibitors. The results were screened based on docking score, H-bonds, and amino acid interactions. The results shows HIV-protease inhibitors such as cobicistat (-8.3kcal/mol), Darunavir (-7.4kcal/mol), Lopinavir (-9.1kcal/mol) and Ritonavir (-8.0 kcal/mol), anti-inflammatory drugs such as Baricitinib (-5.8kcal/mol), Ruxolitinib (-6.5kcal/mol), Thalidomide (-6.5kcal/mol), antibiotic drugs such as Erythromycin(-9.0kcal/mol) and Spiramycin (-8.5kcal/mol) molecules have good affinity towards spike protein compared to antimalarial drugs Chloroquine (-6.2kcal/mol), Hydroxychloroquine (-5.2kcal/mol) and Artemisinin (-6.8kcal/mol) have poor affinity to spike protein. The insilico pharmacological evaluation shows that these molecules exhibit good affinity of drug-like and ADMET properties. Hence, we propose that HIVprotease, anti-inflammatory and antibiotic inhibitors are the potential lead drug molecules for spike protein and preclinical studies needed to confirm the promising therapeutic ability against COVID-19.
2019 年 12 月爆发的冠状病毒(COVID-19)是一种新兴的病毒性疾病,对人类构成重大威胁,因此迫切需要寻找可能的治疗策略。刺突蛋白(S2)是一种包膜糖蛋白,有助于病毒进入宿主细胞,与免疫原性 ACE2 受体结合,并代表潜在的抗病毒药物靶点。目前正在进行几种药物的临床试验,如抗疟药、抗生素、抗炎药和 HIV 蛋白酶抑制剂,以测试其对 COVID-19 的疗效和安全性。一些有希望的结果已经在患者身上观察到,但死亡率仍然很高。因此,有必要使用计算机模拟分析筛选出最好的 CoV 抑制剂。本研究应用的分子方法包括分子对接、虚拟筛选、类药性和 ADMET 预测,有助于靶向 CoV 抑制剂。结果根据对接评分、氢键和氨基酸相互作用进行筛选。结果表明,HIV 蛋白酶抑制剂如考比司他(-8.3kcal/mol)、达芦那韦(-7.4kcal/mol)、洛匹那韦(-9.1kcal/mol)和利托那韦(-8.0 kcal/mol)、抗炎药如巴瑞替尼(-5.8kcal/mol)、鲁索利替尼(-6.5kcal/mol)、沙利度胺(-6.5kcal/mol)、抗生素如红霉素(-9.0kcal/mol)和螺旋霉素(-8.5kcal/mol)与刺突蛋白的亲和力优于抗疟药氯喹(-6.2kcal/mol)、羟氯喹(-5.2kcal/mol)和青蒿素(-6.8kcal/mol)。计算机药理学评价表明,这些分子具有良好的类药性和 ADMET 特性。因此,我们认为 HIV 蛋白酶、抗炎药和抗生素抑制剂是刺突蛋白的潜在先导药物分子,需要进行临床前研究来确认其对 COVID-19 的有前途的治疗能力。