Unveiling new therapeutic candidates for dystrophinopathies: computational insights into FBXO32 and CD4 modulation

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dc.contributor.author Trivedi, Pooja
dc.contributor.author Dixit, Nandan
dc.contributor.author Patel, Saumya
dc.contributor.author Gupta, Sharad
dc.contributor.author Sindhav, Gaurang
dc.coverage.spatial United Kingdom
dc.date.accessioned 2025-08-21T08:23:49Z
dc.date.available 2025-08-21T08:23:49Z
dc.date.issued 2025-12
dc.identifier.citation Trivedi, Pooja; Dixit, Nandan; Patel, Saumya; Gupta, Sharad and Sindhav, Gaurang, "Unveiling new therapeutic candidates for dystrophinopathies: computational insights into FBXO32 and CD4 modulation", Network Modeling Analysis in Health Informatics and Bioinformatics, DOI: 10.1007/s13721-025-00581-7, vol. 14, no. 01, Dec. 2025.
dc.identifier.issn 2192-6662
dc.identifier.issn 2192-6670
dc.identifier.uri https://doi.org/10.1007/s13721-025-00581-7
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/11778
dc.description.abstract Duchenne Muscular Dystrophy (DMD) and its allelic counterpart, Becker Muscular Dystrophy (BMD), are rare, severe, and prevalent neuromuscular conditions, collectively termed dystrophinopathies. They result from variants in the DMD gene, which encodes dystrophin, a 427 kDa protein essential for skeletal muscle fiber integrity. Clinically manifests as toe walking, waddling gait, Gowers’ sign, scoliosis, calf pseudohypertrophy, wheelchair dependence, and cardiorespiratory complications leading to reduced life expectancy. Amid the unmet need for a cure, this study aims to advance therapeutic discovery through complementary computational methods, ultimately contributing to the potential treatment of D/BMD. Gene expression profiles from GEO datasets (GSE6011, GSE1004, GSE38417, GSE3307, and GSE1007) were analyzed for Differentially Expressed Genes (DEGs). Protein-Protein Interactions (PPI) were mapped using Cytoscape, and hub genes were identified with CytoHubba. Gene Ontology and KEGG pathway analyses were performed via Enrichr. Essential proteins underwent molecular docking in Schrödinger Maestro, using Vamorolone (FDA-approved corticosteroid alternative) and NPASS-screened top 3 ligands. Docking results were evaluated with MM-GBSA (OPLS4), ADME profiling was conducted using QikProp, and Molecular Dynamics (MD) simulations in Desmond assessed protein-ligand stability and interactions. 1,159 DEGs, including 259 upregulated and 900 downregulated genes. Among these, FBXO32, a key regulator of muscle atrophy, and CD4, an immune marker, were selected as central hub genes, with significant enrichment in FOXO signaling and immune regulatory pathways. Molecular docking revealed that Princepin (-7.175 kcal/mol) strongly inhibits FBXO32, while Norkurarinol (-8.141 kcal/mol) enhances CD4 regulation. MM-GBSA analysis confirmed Princepin’s strongest binding energy (-60.34 kcal/mol) and Norkurarinol’s high affinity (-47.44 kcal/mol). The simulation revealed varying stability and hydrogen bond dynamics across protein-ligand complexes. The findings highlight the potential of FBXO32 and CD4 as complementary therapeutic targets addressing both muscle degeneration and immune dysregulation in DMD. Their dual targeting paves the way for novel drug development while necessitating both in vivo and in vitro validation.
dc.description.statementofresponsibility by Pooja Trivedi, Nandan Dixit, Saumya Patel, Sharad Gupta and Gaurang Sindhav
dc.format.extent vol. 14, no. 01
dc.language.iso en_US
dc.publisher Springer
dc.subject Duchenne muscular dystrophy (DMD)
dc.subject Differentially expressed genes (DEGs)
dc.subject Molecular docking
dc.subject Drug discovery
dc.title Unveiling new therapeutic candidates for dystrophinopathies: computational insights into FBXO32 and CD4 modulation
dc.type Article
dc.relation.journal Network Modeling Analysis in Health Informatics and Bioinformatics


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