Network-based approach to identify molecular signatures and therapeutic agents in Alzheimer's disease

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dc.authoridArga, Kazim Yalcin/0000-0002-6036-1348
dc.authoridRahman, Md Rezanur/0000-0002-8739-8714
dc.authoridMoni, Mohammad Ali/0000-0003-0756-1006
dc.authoridFaruquee, Dr. Hossain Md/0000-0002-7596-8441
dc.authoridRahman, Md Mafizur/0000-0003-4066-1957
dc.authoridTURANLI, Beste/0000-0003-1330-9712
dc.authoridIslam, Tania/0000-0002-2254-7758
dc.contributor.authorRahman, Md. Rezanur
dc.contributor.authorIslam, Tania
dc.contributor.authorTuranli, Beste
dc.contributor.authorZaman, Toyfiquz
dc.contributor.authorFaruquee, Hossain Md.
dc.contributor.authorRahman, Md. Mafizur
dc.contributor.authorMollah, Md. Nurul Haque
dc.date.accessioned2025-01-06T17:36:20Z
dc.date.available2025-01-06T17:36:20Z
dc.date.issued2019
dc.description.abstractAlzheimer's disease (AD) is a dynamic degeneration of the brain with progressive dementia. Considering the uncertainties in its molecular mechanism, in the present study, we employed network-based integrative analyses, and aimed to explore the key molecules and their associations with small drugs to identify potential biomarkers and therapeutic agents for the AD. First of all, we studied a transcriptome dataset and identified 1521 differentially expressed genes (DEGs). Integration of transcriptome data with protein-protein and transcriptional regulatory interactions resulted with central (hub) proteins (UBA52, RAC1, CREBBP, AR, RPS11, SMAD3, RPS6, RPL12, RPL15, and UBC), regulatory transcription factors (FOXCl, GATA2, YY1, FOXL1, NFIC, E2F1, USF2, SRF, PPARG, and JUN) and microRNAs (mir-335-5p, mir-26b-5p, mir-93-5p, mir-124-3p, mir-17-5p, mir-16-5p, mir-20a-5p, mir-92a-3p, mir-106b-5p, and mir-192-5p) as key signaling and regulatory molecules associated with transcriptional changes for the AD. Considering these key molecules as potential therapeutic targets and Connectivity Map (CMap) architecture, candidate small molecular agents (such as STOCK1N-35696) were identified as novel potential therapeutics for the AD. This study presents molecular signatures at RNA and protein levels which might be useful in increasing discernment of the molecular mechanisms, and potential drug targets and therapeutics to design effective treatment strategies for the AD.
dc.identifier.doi10.1016/j.compbiolchem.2018.12.011
dc.identifier.endpage439
dc.identifier.issn1476-9271
dc.identifier.issn1476-928X
dc.identifier.pmid30606694
dc.identifier.scopus2-s2.0-85059230572
dc.identifier.scopusqualityQ1
dc.identifier.startpage431
dc.identifier.urihttps://doi.org/10.1016/j.compbiolchem.2018.12.011
dc.identifier.urihttps://hdl.handle.net/20.500.14669/1818
dc.identifier.volume78
dc.identifier.wosWOS:000459524900044
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherElsevier Sci Ltd
dc.relation.ispartofComputational Biology and Chemistry
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectAlzheimer's disease
dc.subjectNetwork biology
dc.subjectDifferentially expressed genes
dc.subjectTranscription factors
dc.subjectmicroRNAs
dc.subjectCandidate drugs
dc.titleNetwork-based approach to identify molecular signatures and therapeutic agents in Alzheimer's disease
dc.typeArticle

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