Network Pharmacology of Natural Polyphenols for Stroke: A Bioinformatic Approach to Drug Design

天然多酚在卒中治疗中的网络药理学研究:一种基于生物信息学的药物设计方法

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Abstract

BACKGROUND: Globally, stroke is a major contributor to disability and a leading cause of death. Stroke is more frequent in underdeveloped countries, where ischemic stroke is one of the most common kinds. Therefore, it is imperative to unravel the processes of ischemic stroke in more depth and develop novel therapeutics to combat the condition. Polyphenols provide a significant preventive role against multiple diseases, including cancer, cardiovascular disorders, atherosclerosis, brain dysfunction, and stroke. METHODS: In the current investigation, computational tools including Swiss Target prediction, DisGeNET, SwissADME, pkCSM, Cytoscape, InterActiVenn, STRING database, and DAVID database were utilized to identify the signaling pathways, putative targets, along with associated genes of the polyphenols for stroke prevention. RESULTS: This study revealed the possible interactions between the disease targets for Stroke and the selected plant-based polyphenols. Docking results also exhibited the strong to moderate affinity of the selected ligands (Apigenin, Ellagic acid, Ferulic acid, Kaempferol, Genistein, Luteolin, Naringenin, and Quercetin) towards the selected disease target. CONCLUSION: This study highlights the neuroprotective role of selected polyphenols through the PI3K/Akt pathway. Further studies are required to investigate additional molecular mechanisms between the polyphenols and their derivatives against pathological targets of Stroke.

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