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Khabre desk
Recent reporting, analysis and explainers from the Drug Discovery desk.
science
A bioRxiv preprint describes PRIORITI, a framework that combines language-model synthesis of human genetic evidence with supervised learning to forecast whether a proposed drug target–disease pairing will succeed. The authors report results on historical and post-cutoff benchmark sets.
science
A bioRxiv preprint describes REAL-SWIT, a generative system for exploring make-on-demand chemical space. In experiments on ROCK1, six of 23 synthesized compounds inhibited the target in biochemical tests.
science
A bioRxiv preprint presents a machine-learning structural atlas of kinase inhibitor binding sites, built from 11,945 inhibitor complexes. The analysis suggests that evolutionary relationships between kinases can help predict shared access to allosteric drug pockets.