Three-dimensional analysis of binding sites for predicting binding affinities in drug design

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dc.contributor.authorErdaş Çicek, Özlem
dc.contributor.authorAtaç, Ali Osman
dc.contributor.authorGürkan Alp, A. Selen
dc.contributor.authorBüyükbingol, Erdem
dc.contributor.authorAlpaslan, Ferda Nur
dc.date.accessioned2021-02-19T21:16:09Z
dc.date.available2021-02-19T21:16:09Z
dc.date.issued2019
dc.departmentALKÜ
dc.descriptionAlpaslan, Ferda Nur/0000-0002-9806-1543; Erdas Cicek, Ozlem/0000-0003-4019-7744
dc.description.abstractUnderstanding the interaction between drug molecules and proteins is one of the main challenges in drug design. Several tools have been developed recently to decrease the complexity of the process. Artificial intelligence and machine learning methods offer promising results in predicting the binding affinities. It becomes possible to do accurate predictions by using the known protein-ligand interactions. In this study, the electrostatic potential values extracted from 3-dimensional grid cubes of the drug-protein binding sites are used for predicting binding affinities of related complexes. A new algorithm with a dynamic feature selection method was implemented, which is derived from Compressed Images For Affinity Prediction (CIFAP) study, to predict binding affinities of Checkpoint Kinase 1 and Caspase 3 inhibitors.
dc.identifier.doi10.1021/acs.jcim.9b00206
dc.identifier.endpage4662en_US
dc.identifier.issn1549-9596
dc.identifier.issn1549-960X
dc.identifier.issue11en_US
dc.identifier.pmid31596082
dc.identifier.scopusqualityQ1
dc.identifier.startpage4654en_US
dc.identifier.urihttps://doi.org/10.1021/acs.jcim.9b00206
dc.identifier.urihttps://hdl.handle.net/20.500.12868/273
dc.identifier.volume59en_US
dc.identifier.wosWOS:000500038700016
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.institutionauthor0-belirlenecek
dc.language.isoen
dc.publisherAmer Chemical Soc
dc.relation.ispartofJournal of Chemical Information And Modeling
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.titleThree-dimensional analysis of binding sites for predicting binding affinities in drug design
dc.typeArticle

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