Department of Chemistry, Centre for Molecular Informatics, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, U.K.
Data Sciences & Quantitative Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB2 0AA, U.K.
ACS Chem Biol. 2022 Jul 15;17(7):1733-1744. doi: 10.1021/acschembio.2c00076. Epub 2022 Jul 6.
PROteolysis TArgeting Chimeras (PROTACs) use the ubiquitin-proteasome system to degrade a protein of interest for therapeutic benefit. Advances made in targeted protein degradation technology have been remarkable, with several molecules having moved into clinical studies. However, robust routes to assess and better understand the safety risks of PROTACs need to be identified, which is an essential step toward delivering efficacious and safe compounds to patients. In this work, we used Cell Painting, an unbiased high-content imaging method, to identify phenotypic signatures of PROTACs. Chemical clustering and model prediction allowed the identification of a mitotoxicity signature that could not be expected by screening the individual PROTAC components. The data highlighted the benefit of unbiased phenotypic methods for identifying toxic signatures and the potential to impact drug design.
蛋白水解靶向嵌合体(PROTACs)利用泛素-蛋白酶体系统降解靶蛋白以实现治疗效果。靶向蛋白降解技术的进步引人注目,已有几种分子进入临床研究。然而,需要确定评估和更好地了解 PROTAC 安全性风险的有效途径,这是向患者提供有效和安全化合物的重要步骤。在这项工作中,我们使用 Cell Painting(一种无偏的高通量成像方法)来鉴定 PROTAC 的表型特征。化学聚类和模型预测允许鉴定出一个不能通过筛选单个 PROTAC 成分预测到的有丝分裂毒性特征。该数据突出了无偏表型方法在鉴定毒性特征方面的优势,以及对药物设计产生影响的潜力。