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
Issue Date: 2021
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benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data.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IDG-DREAM Challenge carried out crowdsourced benchmarking of predictive algorithms for kinase inhibitor activities on unpublished data.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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