A transcriptome based approach to predict candidate drug targets and drugs for Parkinson's disease using an in vitro 6-OHDA model

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dc.authorid0000-0001-9037-5217
dc.contributor.authorYiğit, Esra Nur
dc.contributor.authorSönmez, Ekin
dc.contributor.authorYüksel, İsa
dc.contributor.authorAksan Kurnaz, Işıl
dc.contributor.authorÇakır, Tunahan
dc.date.accessioned2023-09-13T12:26:37Z
dc.date.available2023-09-13T12:26:37Z
dc.date.issued2023
dc.departmentİstanbul Medipol Üniversitesi, Rektörlük, Sağlık Bilim ve Teknolojileri Araştırma Enstitüsü
dc.description.abstractThe most common treatment strategies for Parkinson's disease (PD) aim to slow down the neurodegeneration process or control the symptoms. In this study, using an in vitro PD model we carried out a transcriptome-based drug target prediction strategy. We identified novel drug target candidates by mapping genes upregulated in 6-OHDA-treated cells on a human protein-protein interaction network. Among the predicted targets, we show that AKR1C3 and CEBPB are promising in validating our bioinformatics approach since their known ligands, rutin and quercetin, respectively, act as neuroprotective drugs that effectively decrease cell death, and restore the expression profiles of key genes upregulated in 6-OHDA-treated cells. We also show that these two genes upregulated in our in vitro PD model are downregulated to basal levels upon drug administration. As a further validation of our methodology, we further confirm that the potential target genes identified with our bioinformatics approach are also upregulated in post-mortem transcriptome samples of PD patients from the literature. Therefore, we propose that this methodology predicts novel drug targets AKR1C3 and CEBPB, which are relevant to future clinical applications as potential drug repurposing targets for PD. Our systems-based computational approach to predict candidate drug targets can be employed in identifying novel drug targets in other diseases without a priori assumption.
dc.identifier.citationYiğit, E. N., Sönmez, E., Yüksel, İ., Aksan Kurnaz, I. ve Çakır, T. (2023). A transcriptome based approach to predict candidate drug targets and drugs for Parkinson's disease using an in vitro 6-OHDA model. Molecular Omics, 19(3), 218-228. https://dx.doi.org/10.1039/d2mo00267a
dc.identifier.doi10.1039/d2mo00267a
dc.identifier.endpage228
dc.identifier.issn2515-4184
dc.identifier.issue3
dc.identifier.pmid36723117
dc.identifier.scopus2-s2.0-85147436735
dc.identifier.scopusqualityQ2
dc.identifier.startpage218
dc.identifier.urihttps://dx.doi.org/10.1039/d2mo00267a
dc.identifier.urihttps://hdl.handle.net/20.500.12511/11424
dc.identifier.volume19
dc.identifier.wos000920909700001en_US
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.institutionauthorYiğit, Esra Nur
dc.language.isoen
dc.publisherRoyal Society of Chemistry
dc.relation.ispartofMolecular Omicsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.relation.tubitakinfo:eu-repo/grantAgreement/TUBITAK/SOBAG/315S302
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subject6-OHDA Model
dc.subjectParkinson's Disease
dc.subjectDrugs
dc.subjectPredict Candidate
dc.titleA transcriptome based approach to predict candidate drug targets and drugs for Parkinson's disease using an in vitro 6-OHDA model
dc.typeArticle

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