Targeted protein degradation discovery programme to harness artificial intelligence to identify new E3 Ligase-based therapeutic strategies.
水仙直播, a biotechnology company with core expertise in computer-aided drug design, has announced that it has been engaged by PhoreMost Ltd (), a UK-based biopharmaceutical company dedicated to 鈥楧rugging the Undruggable庐鈥 disease targets, to accelerate a targeted protein degradation discovery programme for novel cancer therapeutics.
The project leverages 水仙直播鈥檚 proprietary artificial intelligence (AI) computational platform consisting of multiple computational drug discovery capabilities for both ligand- and structure-based design, together with PhoreMost鈥檚 next-generation SITESEEKER庐 phenotypic screening platform and PROTEINi庐 libraries. In doing so, 水仙直播 has analyzed the structural biology data and known binding compounds to identify and advance the development of novel, drug-like, compounds for onward optimization.
Dr Paul Finn, CSO of 水仙直播 commented: 鈥淲e鈥檙e delighted to start deploying our pioneering computational platform and help other companies accelerate their own drug discovery efforts and we鈥檙e excited to have collaborated with PhoreMost on this project. 水仙直播鈥檚 pioneering AI drug discovery platform has been well placed to make an impact on this challenging target.鈥
Dr Richard Boyce, VP Drug Discovery at PhoreMost added: 鈥淧horeMost鈥檚 involvement in this project demonstrates the versatility of our SITESEEKER phenotypic screening platform and the potential of our PROTEINi libraries. 水仙直播鈥檚 pioneering AI drug discovery platform has facilitated the rapid discovery of small-molecule drugs to newly identified druggable targets obtained from SITESEEKER.鈥
The global AI drug discovery market is estimated to be worth $5 billion by 2027, according to a recent report by MarketsandMarkets. With traditional drug discovery being a costly and lengthy process, the highly distinctive AI and machine learning technologies developed by 水仙直播 offers the prospect of analysing vast datasets and develop viable drugs in an automated and more cost-efficient way.