{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T00:25:01Z","timestamp":1780446301147,"version":"3.54.1"},"reference-count":96,"publisher":"Public Library of Science (PLoS)","issue":"7","license":[{"start":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T00:00:00Z","timestamp":1721779200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U01CA271318"],"award-info":[{"award-number":["U01CA271318"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U01CA271318"],"award-info":[{"award-number":["U01CA271318"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Protein kinase function and interactions with drugs are controlled in part by the movement of the DFG and \u0251C-Helix motifs that are related to the catalytic activity of the kinase. Small molecule ligands elicit therapeutic effects with distinct selectivity profiles and residence times that often depend on the active or inactive kinase conformation(s) they bind. Modern AI-based structural modeling methods have the potential to expand upon the limited availability of experimentally determined kinase structures in inactive states. Here, we first explored the conformational space of kinases in the PDB and models generated by AlphaFold2 (AF2) and ESMFold, two prominent AI-based protein structure prediction methods. Our investigation of AF2\u2019s ability to explore the conformational diversity of the kinome at various multiple sequence alignment (MSA) depths showed a bias within the predicted structures of kinases in DFG-in conformations, particularly those controlled by the DFG motif, based on their overabundance in the PDB. We demonstrate that predicting kinase structures using AF2 at lower MSA depths explored these alternative conformations more extensively, including identifying previously unobserved conformations for 398 kinases. Ligand enrichment analyses for 23 kinases showed that, on average, docked models distinguished between active molecules and decoys better than random (average AUC (avgAUC) of 64.58), but select models perform well (e.g., avgAUCs for PTK2 and JAK2 were 79.28 and 80.16, respectively). Further analysis explained the ligand enrichment discrepancy between low- and high-performing kinase models as binding site occlusions that would preclude docking. The overall results of our analyses suggested that, although AF2 explored previously uncharted regions of the kinase conformational space and select models exhibited enrichment scores suitable for rational drug discovery, rigorous refinement of AF2 models is likely still necessary for drug discovery campaigns.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1012302","type":"journal-article","created":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T17:39:38Z","timestamp":1721842778000},"page":"e1012302","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":15,"title":["A comprehensive exploration of the druggable conformational space of protein kinases using AI-predicted structures"],"prefix":"10.1371","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9467-238X","authenticated-orcid":true,"given":"Noah B.","family":"Herrington","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan Chak","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Stein","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1939-679X","authenticated-orcid":true,"given":"Gaurav","family":"Pandey","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4007-7814","authenticated-orcid":true,"given":"Avner","family":"Schlessinger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2024,7,24]]},"reference":[{"issue":"1","key":"pcbi.1012302.ref001","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1186\/s12943-018-0804-2","article-title":"Kinase-targeted cancer therapies: progress, challenges and future directions","volume":"17","author":"KS Bhullar","year":"2018","journal-title":"Mol Cancer"},{"issue":"3","key":"pcbi.1012302.ref002","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1016\/j.molcel.2020.07.001","article-title":"Kinase Interaction Network Expands Functional and Disease Roles of Human Kinases","volume":"79","author":"M Buljan","year":"2020","journal-title":"Mol Cell"},{"issue":"1","key":"pcbi.1012302.ref003","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/cei.12248","article-title":"Protein kinase inhibitors in the treatment of inflammatory and autoimmune diseases","volume":"176","author":"H Patterson","year":"2014","journal-title":"Clin Exp Immunol"},{"key":"pcbi.1012302.ref004","article-title":"Low-frequency ERK and Akt activity dynamics are predictive of stochastic cell division events","author":"JJR Bennett","year":"2024","journal-title":"bioRxiv"},{"issue":"1","key":"pcbi.1012302.ref005","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1038\/nrg2707","article-title":"Kinase mutations in human disease: interpreting genotype-phenotype relationships","volume":"11","author":"P Lahiry","year":"2010","journal-title":"Nat Rev Genet"},{"key":"pcbi.1012302.ref006","doi-asserted-by":"crossref","first-page":"106552","DOI":"10.1016\/j.phrs.2022.106552","article-title":"Properties of FDA-approved small molecule protein kinase inhibitors: A 2023 update","volume":"187","author":"R Roskoski","year":"2023","journal-title":"Pharmacol Res"},{"issue":"3","key":"pcbi.1012302.ref007","first-page":"81","article-title":"Protein kinases, their function and implication in cancer and other diseases","volume":"52","author":"I Shchemelinin","year":"2006","journal-title":"Folia Biol (Praha)"},{"key":"pcbi.1012302.ref008","doi-asserted-by":"crossref","first-page":"107059","DOI":"10.1016\/j.phrs.2024.107059","article-title":"Properties of FDA-approved small molecule protein kinase inhibitors: A 2024 update","volume":"200","author":"R Roskoski","year":"2024","journal-title":"Pharmacol Res"},{"issue":"7","key":"pcbi.1012302.ref009","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1038\/s41573-021-00195-4","article-title":"Kinase drug discovery 20 years after imatinib: progress and future directions","volume":"20","author":"P Cohen","year":"2021","journal-title":"Nat Rev Drug Discov"},{"issue":"7","key":"pcbi.1012302.ref010","doi-asserted-by":"crossref","first-page":"936","DOI":"10.1038\/s41416-018-0045-6","article-title":"New opportunities for kinase drug repurposing and target discovery","volume":"118","author":"S. 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