Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11851/8214
Title: | Crowdsourced Mapping of Unexplored Target Space of Kinase Inhibitors | Authors: | Cichonska, Anna Ravikumar, Balaguru Allaway, Robert J. Wan, Fangping Park, Sungjoon Isayev, Olexandr Li, Shuya |
Keywords: | Drug Pharmacology Prediction Discovery Package |
Publisher: | Nature Portfolio | Abstract: | 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benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data.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. The IDG-DREAM Challenge carried out crowdsourced benchmarking of predictive algorithms for kinase inhibitor activities on unpublished data. This study provides a resource to compare emerging algorithms and prioritize new kinase activities to accelerate drug discovery and repurposing efforts. | URI: | https://doi.org/10.1038/s41467-021-23165-1 https://hdl.handle.net/20.500.11851/8214 |
ISSN: | 2041-1723 |
Appears in Collections: | Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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