Structure-Based Virtual Screening for Novel Potential Selective Inhibitors of Class Iia Histone Deacetylases for Cancer Treatment

dc.contributor.author Elmezayen, Ammar D.
dc.contributor.author Yelekçi, Kemal
dc.contributor.author Kemal, Yelekçi
dc.contributor.other Molecular Biology and Genetics
dc.date.accessioned 2021-05-28T16:34:41Z
dc.date.available 2021-05-28T16:34:41Z
dc.date.issued 2021
dc.description.abstract The fundamental cause of human cancer is strongly influenced by down- or up-regulations of epigenetic factors. Upregulated histone deacetylases (HDAC) have been shown to be effectively neutralized by the action of HDACs inhibitors (HDACi). However, cytotoxicity has been reported in normal cells because of non-specificity of several available HDACis that are in clinical use or at different phases of clinical trials. Because of the high amino acid sequence and structural similarity among HDAC enzymes, it is believed to be a challenging task to obtain isoform-selectivity. The essential aim of the present research work was to identify isoform-selective inhibitors against class IIa HDACs via structure-based drug design. Based on the highest binding affinity and isoform-selectivity, the top-ranked inhibitors were in silico tested for their absorption, distribution, metabolism, elimination, and toxicity (ADMET) properties, which were classified as drug-like compounds. Later, molecular dynamics simulation (MD) was carried out for all compound-protein complexes to evaluate the structural stability and the biding mode of the inhibitors, which showed high stability throughout the 100 ns simulation. Free binding energy predictions by MM-PBSA method showed the high binding affinity of the identified compounds toward their respective targets. Hence, these inhibitors could be used as drug candidates or as lead compounds for more in silico or in vitro optimization to design safe isoform-selective HDACs inhibitors. en_US
dc.identifier.citationcount 8
dc.identifier.doi 10.1016/j.compbiolchem.2021.107491 en_US
dc.identifier.issn 1476-9271 en_US
dc.identifier.issn 1476-9271
dc.identifier.pmid 33930743 en_US
dc.identifier.scopus 2-s2.0-85105694556 en_US
dc.identifier.scopusquality Q2
dc.identifier.uri https://hdl.handle.net/20.500.12469/4032
dc.identifier.volume 92 en_US
dc.identifier.wos WOS:000656579000001 en_US
dc.institutionauthor Elmezayen, Ammar D. en_US
dc.institutionauthor Kemal, Yelekçi en_US
dc.language.iso en en_US
dc.publisher Elsevier Ltd en_US
dc.relation.journal Computational Biology and Chemistry en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 9
dc.subject ADMET en_US
dc.subject MD simulation en_US
dc.subject MM-PBSA en_US
dc.subject Selective HDAC inhibitors en_US
dc.subject Structure-based virtual screening en_US
dc.title Structure-Based Virtual Screening for Novel Potential Selective Inhibitors of Class Iia Histone Deacetylases for Cancer Treatment en_US
dc.type Article en_US
dc.wos.citedbyCount 10
dspace.entity.type Publication
relation.isAuthorOfPublication 9407938e-3d31-453b-9199-aaa8280a66c5
relation.isAuthorOfPublication.latestForDiscovery 9407938e-3d31-453b-9199-aaa8280a66c5
relation.isOrgUnitOfPublication 71ce8622-7449-4a6a-8fad-44d881416546
relation.isOrgUnitOfPublication.latestForDiscovery 71ce8622-7449-4a6a-8fad-44d881416546

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