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dc.creatorNikolić, Katarina
dc.creatorMavridis, Lazaros
dc.creatorBautista-Aguilera, Oscar M.
dc.creatorMarco-Contelles, Jose
dc.creatorStark, Holger
dc.creatorCarreiras, Maria do Carmo
dc.creatorRossi, Ilaria
dc.creatorMassarelli, Paola
dc.creatorAgbaba, Danica
dc.creatorRamsay, Rona R.
dc.creatorMitchell, John B. O.
dc.date.accessioned2019-09-02T11:46:51Z
dc.date.available2019-09-02T11:46:51Z
dc.date.issued2015
dc.identifier.issn0920-654X
dc.identifier.urihttp://farfar.pharmacy.bg.ac.rs/handle/123456789/2395
dc.description.abstractRecently developed multi-targeted ligands are novel drug candidates able to interact with monoamine oxidase A and B; acetylcholinesterase and butyrylcholinesterase; or with histamine N-methyltransferase and histamine H-3-receptor (H3R). These proteins are drug targets in the treatment of depression, Alzheimer's disease, obsessive disorders, and Parkinson's disease. A probabilistic method, the Parzen-Rosenblatt window approach, was used to build a "predictor" model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. Molecular structures were represented based on the circular fingerprint methodology. The same approach was used to build a "predictor" model from the DrugBank dataset to determine the main pharmacological groups of the compound. The study of off-target interactions is now recognised as crucial to the understanding of both drug action and toxicology. Primary pharmaceutical targets and off-targets for the novel multi-target ligands were examined by use of the developed cheminformatic method. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. The cheminformatic targets identifications were in agreement with four 3D-QSAR (H3R/D1R/D2R/5-HT2aR) models and by in vitro assays for serotonin 5-HT1a and 5-HT2a receptor binding of the most promising ligand (71/MBA-VEG8).en
dc.publisherSpringer, Dordrecht
dc.relationEU COST Action STSM 10295
dc.relationScottish Universities Life Sciences Alliance (SULSA)
dc.relationElse Kroner-Fresenius-Stiftung
dc.relationTranslational Research Innovation-Pharma (TRIP)
dc.relationFraunhofer-Projektgruppe fur Translationale Medizin und Pharmakologie (TMP)
dc.rightsrestrictedAccess
dc.sourceJournal of Computer-Aided Molecular Design
dc.subjectMulti-targeted ligandsen
dc.subjectCircular fingerprintsen
dc.subjectOff-target studyen
dc.subjectChEen
dc.subjectMAOen
dc.subjectHistamine H3 receptoren
dc.subjectHMTen
dc.titlePredicting targets of compounds against neurological diseases using cheminformatic methodologyen
dc.typearticle
dc.rights.licenseARR
dcterms.abstractНиколић, Катарина; Марцо-Цонтеллес, Јосе; Митцхелл, Јохн Б. О.; Царреирас, Мариа до Цармо; Рамсаy, Рона Р.; Баутиста-Aгуилера, Осцар М.; Старк, Холгер; Мавридис, Лазарос; Aгбаба, Даница; Росси, Илариа; Массарелли, Паола;
dc.citation.volume29
dc.citation.issue2
dc.citation.spage183
dc.citation.epage198
dc.citation.other29(2): 183-198
dc.citation.rankM21
dc.identifier.wos000348190700007
dc.identifier.doi10.1007/s10822-014-9816-1
dc.identifier.pmid25425329
dc.identifier.scopus2-s2.0-84922105008
dc.identifier.rcubconv_3250
dc.type.versionpublishedVersion


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