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利用分子对接、分子动力学模拟和 MM-PBSA 方法鉴定针对 SARS-CoV-2 主要靶点的天然抑制剂。

Identification of natural inhibitors against prime targets of SARS-CoV-2 using molecular docking, molecular dynamics simulation and MM-PBSA approaches.

机构信息

B. V. Patel Pharmaceutical Education and Research Development (PERD) Centre, Ahmedabad, Gujarat, India.

Registered Ph.D. student of Department of Life science, Gujarat University, Ahmedabad, Gujarat, India.

出版信息

J Biomol Struct Dyn. 2022 Apr;40(7):3296-3311. doi: 10.1080/07391102.2020.1846624. Epub 2020 Nov 13.

DOI:10.1080/07391102.2020.1846624
PMID:33183178
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7678369/
Abstract

The recently emerged COVID-19 has been declared a pandemic by the World Health Organization as to date; no therapeutic drug/vaccine is available for the treatment. Due to the lack of time and the urgency to contain the pandemic, computational screening appears to be the best tool to find a therapeutic solution. Accumulated evidence suggests that many phyto-compounds possess anti-viral activity. Therefore, we identified possible phyto-compounds that could be developed and used for COVID-19 treatment. In particular, molecular docking was used to prioritize the possible active phyto-compounds against two key targets namely RNA dependent RNA polymerase (RdRp) and main protease (M) of SARS-CoV-2. In this study, an antiviral drug- Remdesivir (RdRp inhibitor) and Darunavir (M inhibitor) are used as reference drugs. This study revealed that phyto-molecules- Mulberroside-A/C/E/F, Emblicanin A, Nimbolide, and Punigluconin showed high binding affinity against RdRp while Andrographolides, Mulberrosides, Anolignans, Chebulic acid, Mimusopic acid, and Punigluconin showed better binding affinity against M as compared with the reference drug. Furthermore, ADME profiles validated the drug-likeness properties of prioritized phyto-compounds. Besides, to assess the stability, MD simulations studies were performed along with reference inhibitors for M (Darunavir) and RdRp (Remdesivir). Binding free energy calculations (MM-PBSA) revealed the estimated value (ΔG) of M_Darunavir; M_Mulberroside E; RdRp_Remdesivir and RdRp_Emblicanin A were -111.62 ± 6.788, -141.443 ± 9.313, 30.782 ± 5.85 and -89.424 ± 3.130 kJmol, respectively. Taken together, the study revealed the potential of these phyto-compounds as inhibitors of RdRp and M inhibitor that could be further validated against SARS-CoV-2 for clinical benefits.Communicated by Ramaswamy H. Sarma.

摘要

最近出现的 COVID-19 已被世界卫生组织宣布为大流行,目前尚无治疗该疾病的特效药物/疫苗。由于时间紧迫,需要遏制大流行,计算筛选似乎是寻找治疗方法的最佳工具。有大量证据表明,许多植物化合物具有抗病毒活性。因此,我们确定了可能开发并用于 COVID-19 治疗的植物化合物。特别是,分子对接用于针对两个关键靶标,即 SARS-CoV-2 的 RNA 依赖性 RNA 聚合酶(RdRp)和主要蛋白酶(M),对可能的活性植物化合物进行优先级排序。在这项研究中,抗病毒药物瑞德西韦(RdRp 抑制剂)和达芦那韦(M 抑制剂)被用作参考药物。这项研究表明,植物分子——Mulberroside-A/C/E/F、Emblicanin A、Nimbolide 和 Punigluconin 对 RdRp 具有高结合亲和力,而 Andrographolides、Mulberrosides、Anolignans、Chebulic acid、Mimusopic acid 和 Punigluconin 对 M 的结合亲和力优于参考药物。此外,ADME 概况验证了优先植物化合物的类药性。此外,为了评估稳定性,对 M(达芦那韦)和 RdRp(瑞德西韦)的参考抑制剂进行了 MD 模拟研究。结合自由能计算(MM-PBSA)揭示了 M_Darunavir、M_Mulberroside E、RdRp_Remdesivir 和 RdRp_Emblicanin A 的估计值(ΔG)分别为-111.62 ± 6.788、-141.443 ± 9.313、30.782 ± 5.85 和-89.424 ± 3.130 kJmol。总的来说,这项研究揭示了这些植物化合物作为 RdRp 和 M 抑制剂的潜力,它们可以进一步针对 SARS-CoV-2 进行验证,以获得临床益处。由 Ramaswamy H. Sarma 传达。

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