Molecular Docking and Dynamics Simulation of Natural Phenolic Compounds with GSK-3β: A Putative Target to Combat Mortality in Patients with COVID-19.

Z. Khamverdi, Z. Mohamadi, Amir Taherkhani
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引用次数: 2

Abstract

OBJECTIVE In this study, molecular docking analysis was performed to evaluate the binding affinity of 52 plant-based phenolics with the GSK-3β active sites. Moreover, Molecular Dynamics (MD) simulation was conducted to investigate the stability of interactions between the topranked phenolics and residues within the GSK-3β active sites. METHODS Molecular docking and MD simulations were performed using AutoDock and Discovery Studio Client software, respectively. Thereafter, pharmacokinetic and toxicological properties of top inhibitors were predicted using bioinformatics web tools. This study aimed to identify the most effective amino acids involved in the inhibition of GSK-3β based on the most stabilizing interactions between the residues and compounds, and also by considering the degree centrality in the ligand- amino acid interaction network for GSK-3β. RESULTS It was observed that procyanidin and amentoflavone could bind to the GSK-3β active sites at the picomolar (pM) scale as well as the binding affinity of ΔG binding < -13 kcal/mol, while the inhibition constant for theaflavin 3'-gallate, procyanidin B4, and rutin was calculated at the nanomolar (nM) scale, suggesting that these phenolic compounds can be considered as potential effective GSK-3β inhibitors. Furthermore, Val70, Ala83, Val135, and Tyr134 were found to be the most important amino acids involved in the inhibition of GSK-3β. CONCLUSION The results of the current study may be useful in the prevention of several human disorders, including COVID-19, cancers, Alzheimer's disease, diabetes mellitus, and cardiovascular diseases. However, wet-lab experiments need to be performed in the future.
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天然酚类化合物与GSK-3β的分子对接和动力学模拟:抗COVID-19患者死亡率的推定靶点
目的通过分子对接分析,评价52种植物酚类物质与GSK-3β活性位点的结合亲和力。此外,通过分子动力学(MD)模拟研究了GSK-3β活性位点上排名靠前的酚类物质与残基之间相互作用的稳定性。方法分别使用AutoDock和Discovery Studio Client软件进行分子对接和MD模拟。然后,利用生物信息学网络工具预测顶级抑制剂的药代动力学和毒理学特性。本研究旨在通过残基与化合物之间最稳定的相互作用,并考虑GSK-3β在配体-氨基酸相互作用网络中的中心性,确定对GSK-3β抑制最有效的氨基酸。结果原花青素和丙烯黄酮与GSK-3β活性位点的结合在皮摩尔(pM)尺度上,结合亲和力为ΔG < -13 kcal/mol,而对茶黄素3′-没食子酸酯、原花青素B4和芦丁的抑制常数在纳摩尔(nM)尺度上计算,表明这些酚类化合物可能是GSK-3β潜在的有效抑制剂。此外,Val70、Ala83、Val135和Tyr134是参与GSK-3β抑制的最重要氨基酸。结论本研究结果可能有助于预防多种人类疾病,包括COVID-19、癌症、阿尔茨海默病、糖尿病和心血管疾病。然而,未来还需要进行湿室实验。
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CiteScore
4.30
自引率
0.00%
发文量
33
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