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Identification of Flavonoids as Putative ROS-1 Kinase Inhibitors Using Pharmacophore Modeling for NSCLC Therapeutics

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dc.contributor.authorParate, Shraddha-
dc.contributor.authorKumar, Vikas-
dc.contributor.authorHong, Jong Chan-
dc.contributor.authorLee, Keun Woo-
dc.date.accessioned2022-12-26T10:31:03Z-
dc.date.available2022-12-26T10:31:03Z-
dc.date.issued2021-04-
dc.identifier.issn1420-3049-
dc.identifier.issn1420-3049-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/3909-
dc.description.abstractNon-small cell lung cancer (NSCLC) is a lethal non-immunogenic malignancy and proto-oncogene ROS-1 tyrosine kinase is one of its clinically relevant oncogenic markers. The ROS-1 inhibitor, crizotinib, demonstrated resistance due to the Gly2032Arg mutation. To curtail this resistance, researchers developed lorlatinib against the mutated kinase. In the present study, a receptor-ligand pharmacophore model exploiting the key features of lorlatinib binding with ROS-1 was exploited to identify inhibitors against the wild-type (WT) and the mutant (MT) kinase domain. The developed model was utilized to virtually screen the TimTec flavonoids database and the retrieved drug-like hits were subjected for docking with the WT and MT ROS-1 kinase. A total of 10 flavonoids displayed higher docking scores than lorlatinib. Subsequent molecular dynamics simulations of the acquired flavonoids with WT and MT ROS-1 revealed no steric clashes with the Arg2032 (MT ROS-1). The binding free energy calculations computed via molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) demonstrated one flavonoid (Hit) with better energy than lorlatinib in binding with WT and MT ROS-1. The Hit compound was observed to bind in the ROS-1 selectivity pocket comprised of residues from the beta-3 sheet and DFG-motif. The identified Hit from this investigation could act as a potent WT and MT ROS-1 inhibitor.-
dc.language영어-
dc.language.isoENG-
dc.publisherMDPI-
dc.titleIdentification of Flavonoids as Putative ROS-1 Kinase Inhibitors Using Pharmacophore Modeling for NSCLC Therapeutics-
dc.typeArticle-
dc.publisher.location스위스-
dc.identifier.doi10.3390/molecules26082114-
dc.identifier.scopusid2-s2.0-85105142196-
dc.identifier.wosid000644619100001-
dc.identifier.bibliographicCitationMOLECULES, v.26, no.8-
dc.citation.titleMOLECULES-
dc.citation.volume26-
dc.citation.number8-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaBiochemistry & Molecular Biology-
dc.relation.journalResearchAreaChemistry-
dc.relation.journalWebOfScienceCategoryBiochemistry & Molecular Biology-
dc.relation.journalWebOfScienceCategoryChemistry, Multidisciplinary-
dc.subject.keywordPlusCELL LUNG-CANCER-
dc.subject.keywordPlusTARGETED THERAPIES-
dc.subject.keywordPlusCRIZOTINIB-
dc.subject.keywordPlusALK-
dc.subject.keywordPlusGENERATION-
dc.subject.keywordPlusRESISTANCE-
dc.subject.keywordPlusPROTEIN-
dc.subject.keywordPlusGROWTH-
dc.subject.keywordPlusPOTENT-
dc.subject.keywordPlusSELECTIVITY-
dc.subject.keywordAuthorROS-1 kinase-
dc.subject.keywordAuthordrug resistance-
dc.subject.keywordAuthorNSCLC-
dc.subject.keywordAuthorflavonoids-
dc.subject.keywordAuthorstructure-based pharmacophore-
dc.subject.keywordAuthorvirtual screening-
dc.subject.keywordAuthormolecular docking-
dc.subject.keywordAuthormolecular dynamics simulations-
dc.subject.keywordAuthorMM-
dc.subject.keywordAuthorPBSA-
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