Despite decades of intensive search for compounds that modulate the activity of particular protein targets, a large proportion of the human kinome remains as yet undrugged. Effective approaches are therefore required to map the massive space of unexplored compound–kinase interactions for novel and potent activities. Here, we carry out a crowdsourced benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data. We find the top-performing predictions are based on various models, including kernel learning, gradient boosting and deep learning, and their ensemble leads to a predictive accuracy exceeding that of single-dose kinase activity assays. We design experiments based on the model predictions and identify unexpected activities even for under-studied kinases, thereby accelerating experimental mapping efforts. The open-source prediction algorithms together with the bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking prediction algorithms and for extending the druggable kinome.

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Atrial Fibrillation (AF) is the most common cardiac arrhythmia, involving pathological triggers and substrate in the atria. In the clinical catheter laboratory, contact electrograms are an essential tool to characterise AF. Omnipolar electrograms (OE), derived from three or more neighbouring electrodes, are thought to be superior compared to traditional unipolar and bipolar electrograms by eliminating far-field effects and correcting for wavefront incidence angle. We sought to understand the changes in OE morphology under different electrode configurations using 2D simulations of healthy tissue and scarred tissue. Virtual unipolar electrograms (UE) were generated from single electrodes which were used to predict the local electric field and subsequently calculate OEs in cliques of 3, 4, and 6 electrodes at different inter-electrode spacings. Five features were identified on each OE to measure changes in OE morphology under different clique configurations. Additionally, the morphology of the OE signals in the presence of fibrosis was examined. OE signals obtained from scarred tissue are more fractionated compared to healthy tissue. The most appropriate inter-electrode distance for interpreting the OE signals was found to be 2-3mm, using either three or four electrodes.