Fang Ye
Biochemical Technologies, Science and Technology Division, Corning Incorporated Corning, NY, USA.
Front Pharmacol. 2014 Mar 27;5:52. doi: 10.3389/fphar.2014.00052. eCollection 2014.
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.
当前的药物发现主要由依赖标记的分子方法主导，这些方法在体外基于预定义的基于靶点的假设筛选药物。鉴于基于靶点的发现并未改变该行业，基于细胞、组织或动物的特定表型来识别药物的表型筛选重新引起了人们的兴趣。然而，由于药物-靶点相互作用的内在复杂性，所筛选的表型与所寻求的最终分子作用机制之间往往存在显著差距。本文提出了一种用于早期药物发现的无标记策略。该策略将无标记细胞表型分析与计算方法相结合，有望通过提供药物在疾病相关细胞中的功能后果的动力学和整体表征来弥合这一差距，这种表征便于进行机制反卷积。
