Dissecting RAF Inhibitor Resistance by Structure-based Modeling Reveals Ways to Overcome Oncogenic RAS Signaling

DC FieldValueLanguage
dc.contributor.authorRukhlenko, Oleksii S.-
dc.contributor.authorKhorsand, Fahimeh-
dc.contributor.authorKrstic, Aleksandar-
dc.contributor.authorRauch, Nora-
dc.contributor.authorFitzgibbon, Cheree-
dc.contributor.authorMatallanas, David-
dc.contributor.authorRauch, Jens-
dc.contributor.authorKolch, Walter-
dc.contributor.authorKholodenko, Boris N.-
dc.contributor.authoret al.-
dc.date.accessioned2019-07-08T08:47:13Z-
dc.date.available2019-07-08T08:47:13Z-
dc.date.copyright2018 Elsevieren_US
dc.date.issued2018-08-22-
dc.identifier.citationCell Systemsen_US
dc.identifier.issn2405-4712-
dc.identifier.urihttp://hdl.handle.net/10197/10852-
dc.description.abstractClinically used RAF inhibitors are ineffective in RAS-mutant tumors because they enhance homo- and heterodimerization of RAF kinases, leading to paradoxical activation of ERK signaling. Overcoming enhanced RAF dimerization and the resulting resistance is a challenge for drug design. Combining multiple inhibitors could be more effective, but it is unclear how the best combinations can be chosen. We built a next-generation mechanistic dynamic model to analyze combinations of structurally different RAF inhibitors, which can efficiently suppress MEK/ERK signaling. This rule-based model of the RAS/ERK pathway integrates thermodynamics and kinetics of drug-protein interactions, structural elements, post-translational modifications and cell mutational status as model rules to predict RAF inhibitor combinations for inhibiting ERK activity in oncogenic RAS and/or BRAFV600E backgrounds. Predicted synergistic inhibition of ERK signaling was corroborated by experiments in mutant NRAS, HRAS and BRAFV600E cells, and inhibition of oncogenic RAS signaling was associated with reduced cell proliferation and colony formation.en_US
dc.description.sponsorshipEuropean Commission Horizon 2020en_US
dc.description.sponsorshipScience Foundation Irelanden_US
dc.format.mediumPrint-Electronic-
dc.language.isoenen_US
dc.publisherElsevier BVen_US
dc.rightsThis is the author’s version of a work that was accepted for publication in Cell Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Cell Systems (7, 2 (2018)) https://doi.org/10.1016/j.cels.2018.06.002en_US
dc.subjectRAF inhibitorsen_US
dc.subjectDrug resistanceen_US
dc.subjectMathematical modelingen_US
dc.subjectMAPK pathwayen_US
dc.subjectOncogenic RASen_US
dc.subjectDrug synergyen_US
dc.subjectRAF dimerizationen_US
dc.subjectConformational transitions of the DFG motif and αC helixen_US
dc.titleDissecting RAF Inhibitor Resistance by Structure-based Modeling Reveals Ways to Overcome Oncogenic RAS Signalingen_US
dc.typeJournal Articleen_US
dc.internal.authorcontactotheroleksii.rukhlenko@ucd.ieen_US
dc.statusPeer revieweden_US
dc.identifier.volume7en_US
dc.identifier.issue2en_US
dc.identifier.startpage161en_US
dc.identifier.endpage179.e14en_US
dc.identifier.doi10.1016/j.cels.2018.06.002-
dc.neeo.contributorRukhlenko|OS|aut|-
dc.neeo.contributorKhorsand|F|aut|-
dc.neeo.contributorKrstic|A|aut|-
dc.neeo.contributorRozanc|J|aut|-
dc.neeo.contributorAlexopoulos|LG|aut|-
dc.neeo.contributorRauch|N|aut|-
dc.neeo.contributorErickson|KE|aut|-
dc.neeo.contributorHlavacek|WS|aut|-
dc.neeo.contributorPosner|RG|aut|-
dc.neeo.contributorGómez-Coca|S|aut|-
dc.neeo.contributorRosta|E|aut|-
dc.neeo.contributorFitzgibbon|C|aut|-
dc.neeo.contributorMatallanas|D|aut|-
dc.neeo.contributorRauch|J|aut|-
dc.neeo.contributorKolch|W|aut|-
dc.neeo.contributorKholodenko|BN|aut|-
dc.date.updated2019-07-03T13:55:50Z-
dc.identifier.grantid750688 — SAMNets-
dc.identifier.grantidSFI - 14/IA/2395-
dc.identifier.grantidMel-Plex - 642295-
dc.identifier.grantidSmartNanoTox - 686098-
dc.identifier.grantidNanoCommons - 731032-
dc.identifier.grantidNIH/NIGMS - R01GM111510-
item.fulltextWith Fulltext-
item.grantfulltextopen-
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