药物发现
计算生物学
药品
背景(考古学)
表型
药物作用
表型筛选
机制(生物学)
仿形(计算机编程)
生物信息学
生物
计算机科学
神经科学
药理学
遗传学
基因
古生物学
操作系统
哲学
认识论
标识
DOI:10.3389/fphar.2014.00052
摘要
Current drug discovery is dominated by label-dependent molecular approaches, which screen drugs in the context of a predefined and target-based hypothesis in vitro. Given that target-based discovery has not transformed the industry, phenotypic screen that identifies drugs based on a specific phenotype of cells, tissues, or animals has gained renewed interest. However, owing to the intrinsic complexity in drug-target interactions, there is often a significant gap between the phenotype screened and the ultimate molecular mechanism of action sought. This paper presents a label-free strategy for early drug discovery. This strategy combines label-free cell phenotypic profiling with computational approaches, and holds promise to bridge the gap by offering a kinetic and holistic representation of the functional consequences of drugs in disease relevant cells that is amenable to mechanistic deconvolution.
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