High-content phenotypic and pathway profiling to advance drug discovery in diseases of unmet need

被引:21
|
作者
Hughes, Rebecca E. [1 ]
Elliott, Richard J. R. [1 ]
Dawson, John C. [1 ]
Carragher, Neil O. [1 ]
机构
[1] Univ Edinburgh, Canc Res UK Edinburgh Ctr, MRC Inst Genet & Mol Med, Edinburgh EH4 2XR, Midlothian, Scotland
来源
CELL CHEMICAL BIOLOGY | 2021年 / 28卷 / 03期
基金
英国医学研究理事会;
关键词
TARGET PREDICTION; GENE-EXPRESSION; CONNECTIVITY MAP; SYSTEMS BIOLOGY; STEM-CELLS; WEB SERVER; IDENTIFICATION; MECHANISM; DATABASE; PLATFORM;
D O I
10.1016/j.chembiol.2021.02.015
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Conventional thinking in modern drug discovery postulates that the design of highly selective molecules which act on a single disease-associated target will yield safer and more effective drugs. However, high clinical attrition rates and the lack of progress in developing new effective treatments for many important diseases of unmet therapeutic need challenge this hypothesis. This assumption also impinges upon the efficiency of target agnostic phenotypic drug discovery strategies, where early target deconvolution is seen as a critical step to progress phenotypic hits. In this review we provide an overview of how emerging phenotypic and pathwayprofiling technologies integrate to deconvolute the mechanism-of-action of phenotypic hits. We propose that such in-depth mechanistic profiling may support more efficient phenotypic drug discovery strategies that are designed to more appropriately address complex heterogeneous diseases of unmet need.
引用
收藏
页码:338 / 355
页数:18
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