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计算鉴定印度药用和芳香植物物种中针对 SARS-CoV-2 主要致病性决定因素的潜在抑制化合物。

Computational identification of potential inhibitory compounds in Indian medicinal and aromatic plant species against major pathogenicity determinants of SARS-CoV-2.

机构信息

Department of Biotechnology, School of Engineering & Applied Sciences, Bennett University, Uttar Pradesh, India.

出版信息

J Biomol Struct Dyn. 2022;40(24):14096-14114. doi: 10.1080/07391102.2021.2000500. Epub 2021 Nov 12.

Abstract

SARS-CoV-2 (COVID-19) viral pandemic has been reported across 223 countries and territories. Globalized vaccination programs alongside administration of repurposed drugs will assumingly confer a stronger and longer individual specific immune protection. However, considering possible recurrence of the disease via new variants, a conveniently deliverable phytopharmaceutical drug might be the best option for COVID-19 treatment. In the current study, the efforts have been made to identify potential leads for inhalation therapy as nasal swabs have been reported to transfer viral load prominently. In that direction, 2363 Essential oil (EOs) compounds from Indian medicinal and aromatic plants were screened through docking analysis and potential candidates were shortlisted that can interfere with viral pathogenicity. The main protease (M) of SARS-CoV-2 interacted closely with jatamansin (JM), 6,7-dehydroferruginol (FG) and beta-sitosterol (BS), while Papain-like Protease (PL) with friedelane-3-one (F3O) and lantadene D (LD) independently. Reduced Lantadene A (LAR) exhibited preferable interaction with RNA-dependent-RNA-polymerase (RdRp) whereas Lantadene A (LA) with RdRp and spike-glycoprotein (SG-pro) both target proteins. When compared against highest binding affinity conformations of well-known inhibitors of targets, these prioritized compounds conferred superior or comparable SARS-CoV-2 protein inhibition. Additionally, promising results were noted from pharmacokinetics prediction for all shortlisted compounds. Besides, molecular dynamics simulation for 100 ns in two replicates and binding free energy analysis revealed the stability of complexes with optimum compactness. To the best of our knowledge, the current investigation is a unique initial attempt whereby EO compounds have been computationally screened, irrespective of their known medicinal properties to fight COVID-19 infection.Communicated by Ramaswamy H. Sarma.

摘要

SARS-CoV-2(COVID-19)病毒大流行已在 223 个国家和地区报告。全球化的疫苗接种计划以及重新利用药物的管理,预计将提供更强、更持久的个体特异性免疫保护。然而,考虑到疾病可能通过新的变体再次发生,一种方便可交付的植物药物可能是 COVID-19 治疗的最佳选择。在当前的研究中,我们努力寻找用于吸入治疗的潜在先导化合物,因为鼻拭子已被报道可显著转移病毒载量。为此,通过对接分析筛选了来自印度药用和芳香植物的 2363 种精油(EO)化合物,并确定了可以干扰病毒致病性的潜在候选药物。SARS-CoV-2 的主要蛋白酶(M)与 jatamansin(JM)、6,7-脱氢铁杉醇(FG)和β-谷甾醇(BS)密切相互作用,而木瓜蛋白酶样蛋白酶(PL)与 friedelane-3-one(F3O)和lantadene D(LD)相互作用。还原 lantadene A(LAR)与 RNA 依赖性 RNA-聚合酶(RdRp)表现出更好的相互作用,而 lantadene A(LA)与 RdRp 和刺突糖蛋白(SG-pro)这两种靶蛋白均相互作用。与靶蛋白的已知抑制剂的最高结合亲和力构象相比,这些优先化合物赋予了 SARS-CoV-2 蛋白更好或相当的抑制作用。此外,所有筛选化合物的药代动力学预测均取得了有希望的结果。此外,在两个重复的 100ns 分子动力学模拟和结合自由能分析中,发现复合物具有最佳紧凑性的稳定性。据我们所知,这是一项独特的初步尝试,其中计算筛选了精油化合物,而不论其已知的药用特性如何,以对抗 COVID-19 感染。由 Ramaswamy H. Sarma 传达。

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