Discovery of High Affinity Ligands for Beta(2)-Adrenergic Receptor Through Pharmacophore-Based High-Throughput Virtual Screening and Docking

dc.contributor.authorYakar, Rüya
dc.contributor.authorAkten, Ebru Demet
dc.date.accessioned2019-06-27T08:02:49Z
dc.date.available2019-06-27T08:02:49Z
dc.date.issued2014
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Biyoinformatik ve Genetik Bölümüen_US
dc.description.abstractNovel high affinity compounds for human beta(2)-adrenergic receptor (beta(2)-AR) were searched among the clean drug-like subset of ZINC database consisting of 9928465 molecules that satisfy the Lipinski's rule of five. The screening protocol consisted of a high-throughput pharmacophore screening followed by an extensive amount of docking and rescoring. The pharmacophore model was composed of key features shared by all five inactive states of beta(2)-AR in complex with inverse agonists and antagonists. To test the discriminatory power of the pharmacophore model a small-scale screening was initially performed on a database consisting of 117 compounds of which 53 antagonists were taken as active inhibitors and 64 agonists as inactive inhibitors. Accordingly 7.3% of the ZINC database subset (729413 compounds) satisfied the pharmacophore requirements along with 44 antagonists and 17 agonists. Afterwards all these hit compounds were docked to the inactive apo form of the receptor using various docking and scoring protocols. Following each docking experiment the best pose was further evaluated based on the existence of key residues for antagonist binding in its vicinity. After final evaluations based on the human intestinal absorption (HIA) and the blood brain barrier (BBB) penetration properties 62 hit compounds have been clustered based on their structural similarity and as a result four scaffolds were revealed. Two of these scaffolds were also observed in three high affinity compounds with experimentally known K-i values. Moreover novel chemical compounds with distinct structures have been determined as potential beta(2)-AR drug candidates. (C) 2014 Elsevier Inc. All rights reserved.en_US]
dc.identifier.citation5
dc.identifier.doi10.1016/j.jmgm.2014.07.007en_US
dc.identifier.endpage160
dc.identifier.issn1093-3263en_US
dc.identifier.issn1873-4243en_US
dc.identifier.issn1093-3263
dc.identifier.issn1873-4243
dc.identifier.pmid25137647en_US
dc.identifier.scopus2-s2.0-84906234617en_US
dc.identifier.scopusqualityQ2
dc.identifier.startpage148en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12469/690
dc.identifier.urihttps://doi.org/10.1016/j.jmgm.2014.07.007
dc.identifier.volume53en_US
dc.identifier.wosWOS:000343631800016en_US
dc.institutionauthorAkten, Ebru Demeten_US
dc.institutionauthorAkdoğan, Ebru Demet
dc.language.isoenen_US
dc.publisherElsevier Science Incen_US
dc.relation.journalJournal of Molecular Graphics and Modellingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectVirtual screeningen_US
dc.subjectPharmacophore modelingen_US
dc.subjectBeta(2)-Adrenergic receptoren_US
dc.subjectDockingen_US
dc.subjectScoringen_US
dc.titleDiscovery of High Affinity Ligands for Beta(2)-Adrenergic Receptor Through Pharmacophore-Based High-Throughput Virtual Screening and Dockingen_US
dc.typeArticleen_US
dspace.entity.typePublication
relation.isAuthorOfPublication558d2b8e-c713-49e0-9350-d354abb5cd69
relation.isAuthorOfPublication.latestForDiscovery558d2b8e-c713-49e0-9350-d354abb5cd69

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