Network pharmacology speaking to ethnopharmacology: new data on an ancient remedy

Junying Liu
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引用次数: 0

Abstract

Network pharmacology as a “green approach”, predicting metabolite behaviours chemically and biologically and guid¬ing biological experimental design, is a new strategy aiming to uncover the mechanism of action of natural products as drug candidates. It provides a powerful way to identify novel mechanisms of natural products with potential thera¬peutic effects. This approach has emerged as a powerful tool to overcome the limitations of traditional methods, such as the ability to predict the adverse effects of a drug and the likelihood of failure during clinical trials, by applying systems biology principles to the field of pharmacology. This method combines the multi-omics dataset, computer modeling, and chemical biology so as to reveal pharmaceutical actions and guide drug discovery. Therefore, computer-aided drug design combined with network pharmacology can be viewed as a novel in silico screening ap¬proach to drug discovery, by utilising chemoinformatics, bioinformatics, structure biology, and chemical biology. This strategy includes target-based virtual screening - molecular docking, ligand similarity-based virtual screening, and inverse screening (Inver-dock), providing a powerful tool for target identification of drug candidates, multitarget dis¬covery, and natural bioactive product profiling. It can also be used for selectivity profiling of drugs, drug repositioning, safety profiling, and metabolism profiling prediction (ADMET).
网络药理学与民族药理学的对话:关于一种古老药方的新数据
网络药理学作为一种 "绿色方法",从化学和生物学角度预测代谢物的行为,并指导生物学实验设计,是一种旨在揭示天然产物作为候选药物的作用机制的新策略。它为确定天然产品的新机制提供了一种强有力的方法,使其具有潜在的治疗效果。这种方法将系统生物学原理应用于药理学领域,克服了传统方法的局限性,如无法预测药物的不良反应以及临床试验失败的可能性等。这种方法结合了多组学数据集、计算机建模和化学生物学,从而揭示药物作用并指导药物发现。因此,计算机辅助药物设计与网络药理学相结合,可以看作是利用化学信息学、生物信息学、结构生物学和化学生物学进行药物发现的一种新型硅筛选方法。这一策略包括基于靶点的虚拟筛选--分子对接、基于配体相似性的虚拟筛选和反向筛选(Inver-dock),为候选药物的靶点识别、多靶点发现和天然生物活性产物分析提供了强有力的工具。它还可用于药物选择性分析、药物重新定位、安全性分析和代谢分析预测(ADMET)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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