Byrne Ryan, Schneider Gisbert
Department of Chemistry and Applied Biosciences, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland.
Methods Mol Biol. 2019;1888:273-309. doi: 10.1007/978-1-4939-8891-4_16.
Drugs modulate disease states through their actions on targets in the body. Determining these targets aids the focused development of new treatments, and helps to better characterize those already employed. One means of accomplishing this is through the deployment of in silico methodologies, harnessing computational analytical and predictive power to produce educated hypotheses for experimental verification. Here, we provide an overview of the current state of the art, describe some of the well-established methods in detail, and reflect on how they, and emerging technologies promoting the incorporation of complex and heterogeneous data-sets, can be employed to improve our understanding of (poly)pharmacology.
药物通过作用于体内靶点来调节疾病状态。确定这些靶点有助于新疗法的针对性研发,并有助于更好地描述已使用疗法的特征。实现这一目标的一种方法是通过部署计算机模拟方法,利用计算分析和预测能力来生成有根据的假设以供实验验证。在此,我们概述了当前的技术水平,详细描述了一些成熟的方法,并思考如何利用这些方法以及促进纳入复杂和异构数据集的新兴技术来增进我们对(多)药理学的理解。