Crowdsourced mapping of unexplored target space of kinase inhibitors

Cichońska, Anna; Ravikumar, Balaguru; Allaway, Robert J.; Wan, Fangping; Park, Sungjoon; Isayev, Olexandr; Li, Shuya; Mason, Michael; Lamb, Andrew; Tanoli, Ziaurrehman; Jeon, Minji; Kim, Sunkyu; Popova, Mariya; Capuzzi, Stephen; Zeng, Jianyang; Dang, Kristen; Koytiger, Gregory; Kang, Jaewoo; Wells, Carrow I.; Willson, Timothy M.; Oršolić, Davor; Lučić, Bono; Stepanić, Višnja; Šmuc, Tomislav; Oprea, Tudor I.; Schlessinger, Avner; Drewry, David H.; Stolovitzky, Gustavo; Wennerberg, Krister; Guinney, Justin; Aittokallio, Tero (2021) Crowdsourced mapping of unexplored target space of kinase inhibitors. Nature communications, 12 . ISSN 2041-1723

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Official URL: https://www.nature.com/articles/s41467-021-23165-1

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benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data.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.

Item Type:

Article

Additional Information:

Davor Oršolić, Bono Lučić, Višnja Stepanić & Tomislav Šmuc participated in the IDG-DREAM Drug-Kinase Binding Prediction Challengeas the members of the team Prospectors Davor Oršolić, Bono Lučić, Višnja Stepanić & Tomislav Šmuc

Uncontrolled Keywords:

Cheminformatics ; Kinases ; Machine learning

Subjects:

NATURAL SCIENCES > Biology

Divisions:

Division of Electronics

Projects:

Project title	Project leader	Project code	Project type
Bioprospecting Jadranskog mora	Čož-Rakovac, Rozelinda; Dragović-Uzelac, Verica; Šantek, Božidar; Jokić, Stela; Jerković, Igor; Kraljević Pavelić, Sandra	KK.01.1.1.01.0002	EK

Depositing User:

Višnja StepaniÄ�

Date Deposited:

04 Aug 2021 07:49

URI:

http://fulir.irb.hr/id/eprint/6507

DOI:

10.1038/s41467-021-23165-1