A Photoaffinity‐Based Fragment‐Screening Platform for Efficient Identification of Protein Ligands. Issue 47 (7th September 2020)

• Record Type: Journal Article
• Authors: Grant, Emma K.; Fallon, David J.; Hann, Michael M.; Fantom, Ken G. M.; Quinn, Chad; Zappacosta, Francesca; Annan, Roland S.; Chung, Chun‐wa; Bamborough, Paul; Dixon, David P.; Stacey, Peter; House, David; Patel, Vipulkumar K.; Tomkinson, Nicholas C. O.; Bush, Jacob T.
• Is Part Of: Angewandte Chemie international edition. Volume 59:Issue 47(2020)
• Page Start: 21096
• Page End: 21105
• Publication Date: 2020-09-07
• Subjects: covalent -- drug discovery -- inhibitors -- photoaffinity -- proteins; Chemistry -- Periodicals; 540
• DOI: 10.1002/anie.202008361
• Languages: English
• ISSNs: 1433-7851

Abstract

Abstract: Advances in genomic analyses enable the identification of new proteins that are associated with disease. To validate these targets, tool molecules are required to demonstrate that a ligand can have a disease‐modifying effect. Currently, as tools are reported for only a fraction of the proteome, platforms for ligand discovery are essential to leverage insights from genomic analyses. Fragment screening offers an efficient approach to explore chemical space. Presented here is a fragment‐screening platform, termed PhABits (PhotoAffinity Bits), which utilizes a library of photoreactive fragments to covalently capture fragment–protein interactions. Hits can be profiled to determine potency and the site of crosslinking, and subsequently developed as reporters in a competitive displacement assay to identify novel hit matter. The PhABit platform is envisioned to be widely applicable to novel protein targets, identifying starting points in the development of therapeutics. Abstract : PhotoAffinity Bit (PhABit) is a photoreactive fragment‐screening platform to covalently capture fragment–protein interactions. Hits can be profiled and subsequently developed as reporters in a competitive displacement assay to identify novel hit matter. The PhABit platform is widely applicable to novel protein targets, identifying starting points in the development of therapeutics.