化学
降级(电信)
计算生物学
表型筛选
表型
生物化学
计算机科学
生物
电信
基因
作者
Baoli Ding,Jiawen Hu,Binyan Shou,Jiang Li,Bo Yang,Ji Cao,Cheng‐Liang Zhu
标识
DOI:10.1021/acs.jmedchem.5c00949
摘要
Phenotypic screening is undergoing a resurgence in the field of targeted protein degradation as a powerful complement to target-based approaches, which are often constrained by requirements for detailed structural and ligand-binding information. Phenotypic protein degrader discovery (PPDD) instead follows a "biology-first" philosophy, identifying active degraders based on cellular responses. In this Perspective, we critically examine the core components of PPDD workflows, including assay selection, library construction, and target/E3 ligase deconvolution, highlighting how this approach accesses novel degradation and biological insights. We also analyze key challenges, such as discerning degradation-driven phenotypes and elucidating mechanisms, and emphasize how emerging technologies like CRISPR screens, multiomics, automation, and machine learning-based analysis are reshaping the PPDD landscape. This Perspective underscores the unique potential of phenotypic screening to expand the degradable proteome by offering novel chemical and biological starting points for tackling traditionally intractable proteins.
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