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用于研究真菌代谢产物对SARS-CoV-2 RdRp蛋白抑制作用的分子建模和模拟技术。

Molecular modelling and simulation techniques to investigate the effects of fungal metabolites on the SARS-CoV-2 RdRp protein inhibition.

作者信息

Muddapur Uday M, Badiger Shrikanth, Shaikh Ibrahim Ahmed, Ghoneim Mohammed M, Alshamrani Saleh A, Mahnashi Mater H, Alsaikhan Fahad, El-Sherbiny Mohamed, Al-Serwi Rasha Hamed, Khan Aejaz Abdul Latif, Mannasaheb Basheerahmed Abdulaziz, Bahafi Amal, Iqubal S M Shakeel, Begum Touseef, Gouse Helen Suban Mohammed, Mohammed Tasneem, Hombalimath Veeranna S

机构信息

Department of Biotechnology, KLE Technological University, BVB Campus, Hubballi 580031, Karnataka, India.

Department of Pharmacology, College of Pharmacy, Najran University, Najran, Saudi Arabia.

出版信息

J King Saud Univ Sci. 2022 Aug;34(6):102147. doi: 10.1016/j.jksus.2022.102147. Epub 2022 Jun 3.

Abstract

Various protein/receptor targets have been discovered through research. They are expanding rapidly due to their extensive advantage of delivering new drug candidates more quickly, efficiently, and at a lower cost. The automation of organic synthesis and biochemical screening will lead to a revolution in the entire research arena in drug discovery. In this research article, a few fungal metabolites were examined through an approach which involves major steps such as (a) Molecular Docking Analysis, (b) Drug likeness and ADMET studies, and (c) Molecular Dynamics Simulation. Fungal metabolites were taken from Antibiotic Database which showed antiviral effects on severe viral diseases such as HIV. Docking, Lipinski's, and ADMET analyses investigated the binding affinity and toxicity of five metabolites: Chromophilone I, iso; F13459; Stachyflin, acetyl; A-108836; Integracide A (A-108835). Chromophilone I, iso was subjected to additional analysis, including a 50 ns MD simulation of the protein to assess the occurring alterations. This molecule's docking data shows that it had the highest binding affinity. ADMET research revealed that the ligand might be employed as an oral medication. MD simulation revealed that the ligand-protein interaction was stable. Finally, this ligand can be exploited to develop SARS-CoV-2 therapeutic options. Fungal metabolites that have been studied could be a potential source for future lead candidates. Further study of these molecules may result in creating an antiviral drug to battle the SARS-CoV-2 virus.

摘要

通过研究已经发现了各种蛋白质/受体靶点。由于它们在更快、更高效且成本更低地提供新候选药物方面具有广泛优势,其数量正在迅速增加。有机合成和生化筛选的自动化将引发药物发现整个研究领域的一场革命。在这篇研究文章中,通过一种涉及以下主要步骤的方法对一些真菌代谢产物进行了研究:(a) 分子对接分析,(b) 类药性质和ADMET研究,以及 (c) 分子动力学模拟。真菌代谢产物取自抗生素数据库,该数据库显示对诸如HIV等严重病毒性疾病具有抗病毒作用。对接、Lipinski法则和ADMET分析研究了五种代谢产物的结合亲和力和毒性:异嗜铬菌素I;F13459;水苏菌素,乙酰化物;A - 108836;整合菌素A(A - 108835)。对异嗜铬菌素I进行了额外分析,包括对该蛋白质进行50纳秒的分子动力学模拟以评估发生的变化。该分子的对接数据表明它具有最高的结合亲和力。ADMET研究表明该配体可用作口服药物。分子动力学模拟表明配体 - 蛋白质相互作用是稳定的。最后,这种配体可用于开发针对严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的治疗选择。已研究的真菌代谢产物可能是未来潜在候选先导物的一个来源。对这些分子的进一步研究可能会产生一种对抗SARS-CoV-2病毒的抗病毒药物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d329/9186507/a93db0727497/ga1_lrg.jpg

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