Identification of potential isoform-selective histone deacetylase inhibitors for cancer therapy: a combined approach of structure-based virtual screening ADMET prediction and molecular dynamics simulation assay

dc.contributor.authorYelekçi, Kemal
dc.contributor.authorYelekçi, Kemal
dc.date.accessioned2019-06-27T08:01:09Z
dc.date.available2019-06-27T08:01:09Z
dc.date.issued2018
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Biyoinformatik ve Genetik Bölümüen_US
dc.description.abstractHistone deacetylases (HDACs) have gained increased attention as targets for anticancer drug design and development. HDAC inhibitors have proven to be effective for reversing the malignant phenotype in HDAC-dependent cancer cases. However lack of selectivity of the many HDAC inhibitors in clinical use and trials contributes to toxicities to healthy cells. It is believed that the continued identification of isoform-selective inhibitors will eliminate these undesirable adverse effects - a task that remains a major challenge to HDAC inhibitor designs. Here in an attempt to identify isoform-selective inhibitors a large compound library containing 2703000 compounds retrieved from Otava database was screened against class I HDACs by exhaustive approach of structure-based virtual screening using rDOCK and Autodock Vina. A total of 41 compounds were found to show high-isoform selectivity and were further redocked into their respective targets using Autodock4. Thirty-six compounds showed remarkable isoform selectivity and passed drug-likeness and absorption distribution metabolism elimination and toxicity prediction tests using ADMET Predictor and admetSAR. Furthermore to study the stability of ligand binding modes 10ns-molecular dynamics (MD) simulations of the free HDAC isoforms and their complexes with respective best-ranked ligands were performed using nanoscale MD software. The inhibitors remained bound to their respective targets over time of the simulation and the overall potential energy root-mean-square deviation root-mean-square fluctuation profiles suggested that the detected compounds may be potential isoform-selective HDAC inhibitors or serve as promising scaffolds for further optimization towards the design of selective inhibitors for cancer therapy.en_US]
dc.identifier.citation36
dc.identifier.doi10.1080/07391102.2017.1384402en_US
dc.identifier.endpage3245
dc.identifier.issn0739-1102en_US
dc.identifier.issn1538-0254en_US
dc.identifier.issn0739-1102
dc.identifier.issn1538-0254
dc.identifier.issue12
dc.identifier.pmid28938863en_US
dc.identifier.scopus2-s2.0-85031902133en_US
dc.identifier.scopusqualityQ2
dc.identifier.startpage3231en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12469/278
dc.identifier.urihttps://doi.org/10.1080/07391102.2017.1384402
dc.identifier.volume36en_US
dc.identifier.wosWOS:000451749300018en_US
dc.identifier.wosqualityN/A
dc.institutionauthorYelekçi, Kemalen_US
dc.language.isoenen_US
dc.publisherTaylor & Francis Incen_US
dc.relation.journalJournal of Biomolecular Structure and Dynamicsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectstructure-based virtual screeningen_US
dc.subjectADMET analysisen_US
dc.subjectMD simulationen_US
dc.subjectIsoform-selective HDAC inhibitorsen_US
dc.subjectAnticancer agentsen_US
dc.titleIdentification of potential isoform-selective histone deacetylase inhibitors for cancer therapy: a combined approach of structure-based virtual screening ADMET prediction and molecular dynamics simulation assayen_US
dc.typeArticleen_US
dspace.entity.typePublication
relation.isAuthorOfPublication9407938e-3d31-453b-9199-aaa8280a66c5
relation.isAuthorOfPublication.latestForDiscovery9407938e-3d31-453b-9199-aaa8280a66c5

Files