Crowdsourced mapping of unexplored target space of kinase inhibitorsстатья из журнала
Аннотация: 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benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data.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.
Год издания: 2021
Авторы: Anna Cichońska, Balaguru Ravikumar, Robert J. Allaway, Fangping Wan, Sung‐Joon Park, Olexandr Isayev, Shuya Li, Mike J. Mason, Andrew Lamb, Ziaurrehman Tanoli, Minji Jeon, Sunkyu Kim, Mariya Popova, Stephen J. Capuzzi, Jianyang Zeng, Kristen K. Dang, Gregory Koytiger, Jaewoo Kang, Carrow I. Wells, Timothy M. Willson, Mehmet Tan, Chih-Han Huang, Edward S.C. Shih, Tsai‐Min Chen, Chih‐Hsun Wu, Wei-Quan Fang, Jhih-Yu Chen, Ming‐Jing Hwang, Xiaokang Wang, Marouen Ben Guebila, Behrouz Shamsaei, Sourav Singh, Thin Nguyen, Mostafa Karimi, Di Wu, Zhangyang Wang, Yang Shen, Hakime Öztürk, Elif Özkırımlı, Arzucan Özgür, Hansaim Lim, Lei Xie, Georgi K. Kanev, Albert J. Kooistra, Bart A. Westerman, P.J. Terzopoulos, Konstantinos Ntagiantas, Christos Fotis, Leonidas G. Alexopoulos, Dimitri Boeckaerts, Michiel Stock, Bernard De Baets, Yves Briers, Yunan Luo, Hailin Hu, Jian Peng, Tunca Doğan, Ahmet Süreyya Rifaioğlu, Heval Ataş, Rengül Çetin-Atalay, Volkan Atalay, María Martin, Minji Jeon, Junhyun Lee, Seongjun Yun, Bumsoo Kim, Buru Chang, Gábor Turu, Ádám Misák, Bence Szalai, László Hunyady, Matthias Lienhard, Paul Prasse, Ivo Bachmann, Julia Ganzlin, Gal Barel, Ralf Herwig, Davor Oršolić, Bono Lučić, Višnja Stepanić, Tomislav Šmuc, Tudor I. Oprea, Avner Schlessinger, David H. Drewry, Gustavo Stolovitzky, Krister Wennerberg, Justin Guinney, Tero Aittokallio
Издательство: Nature Portfolio
Источник: Nature Communications
Ключевые слова: Computational Drug Discovery Methods, Cell Image Analysis Techniques, Advanced Biosensing Techniques and Applications
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DOAJ (DOAJ: Directory of Open Access Journals) (HTML)
Ghent University Academic Bibliography (Ghent University) (PDF)
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Ghent University Academic Bibliography (Ghent University) (HTML)
OPAL (Open@LaTrobe) (La Trobe University) (PDF)
OPAL (Open@LaTrobe) (La Trobe University) (HTML)
Duo Research Archive (University of Oslo) (PDF)
Duo Research Archive (University of Oslo) (HTML)
OpenMETU (Middle East Technical University) (PDF)
OpenMETU (Middle East Technical University) (HTML)
Own your potential (DEAKIN) (PDF)
Own your potential (DEAKIN) (HTML)
Institutional Repository of the Ruđer Bošković Institute (Ruđer Bošković Institute) (HTML)
UTUPub (University of Turku) (PDF)
UTUPub (University of Turku) (HTML)
Aaltodoc (Aalto University) (PDF)
Aaltodoc (Aalto University) (HTML)
PubMed Central (HTML)
www.biorxiv.org (PDF)
doi.org (HTML)
PubMed (HTML)
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