Evidence map›Paper›PMID 41385176›Full record

ArticleActa neurologica Belgica2026

Network-based identification of regulatory hubs and therapeutic targets in multiple sclerosis: an integrated transcriptomic and molecular docking approach.

Pouria Abidi, Sepideh Ebrahimi, Saeedeh Sadat Mirtooni, Alireza Pasdar, Forouzan Amerizadeh

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Article in Acta neurologica Belgica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Pouria Abidi *Education Development Center, Student Committee of Medical Education Development, Mashhad University of Medical Sciences, Mashhad, Iran.
Sepideh Ebrahimi *Department of Clinical Biochemistry, Shiraz University of Medical Sciences, Shiraz, Iran.
Saeedeh Sadat MirtooniDepartment of Neurology, Mashhad University of Medical Sciences, Mashhad, Iran.
Alireza PasdarBioinformatics Research Centre, Mashhad University of Medical Sciences, Mashhad, Iran.
Forouzan AmerizadehDepartment of Neurology, Mashhad University of Medical Sciences, Mashhad, Iran. amerizadehf951@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMultiple sclerosis (MS) is a chronic neurodegenerative disease marked by inflammation, demyelination, and neuronal loss. Despite research, the mechanisms remain unclear, requiring further investigation into pathways and therapeutic targets.

methodsA bioinformatics-driven approach was employed to analyze gene expression data from the GEO database (GSE135511). Differentially expressed genes (DEGs) were identified and subjected to GO and KEGG enrichment analysis. A protein-protein interaction (PPI) network was constructed using STRING and Cytoscape with key hub genes detected via CytoHubba. Functional clustering was performed using ClusterONE and promoter motif analysis was conducted using MEME suite. Finally, DrugBank database was screened to identify potential drug-target interactions for hub proteins. Molecular docking was performed to evaluate binding affinities between identified drugs and target proteins.

resultsFunctional enrichment analysis revealed involvement of oxidative phosphorylation, immune regulation, and neurodegenerative pathways in MS. The PPI network analysis identified SLC32A1, PVALB, GAD1, GAD2, SNAP25, NRXN1, CDC42 and CD44 as key hub proteins. Functional clustering highlighted distinct biological modules related to mitochondrial metabolism, immunity, and cytoskeletal remodeling. Promoter motif analysis identified transcription factor binding sites regulating neuronal survival and apoptosis. Drug–target interaction analysis, followed by molecular docking using PyRx, demonstrated strong binding affinities between hub proteins and endogenous or approved compounds: NRXN1 with calcium citrate (–7.4 kcal/mol), GAD1 with pyridoxal phosphate (–6.7 kcal/mol), CD44 with hyaluronic acid (–6.8 kcal/mol). These findings provide new insights into pivotal molecular mechanisms and druggable targets within MS pathology.

conclusionThis study presents a molecular landscape of MS, integrating gene expression, pathway enrichment, regulatory analysis, and pharmacotherapy strategies. The findings reveal novel MS pathogenesis insights and identify promising therapeutic targets for clinical validation.

Indexed as

Molecular Docking SimulationMultiple SclerosisProtein Interaction MapsTranscriptomeComputational BiologyHumansDasatinibMultiple sclerosis (MS)Protein-protein interaction networkVenetoclax

Identifiers

PMID41385176

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.