Repository logo
  • English
  • العربية
  • বাংলা
  • Català
  • Čeština
  • Deutsch
  • Ελληνικά
  • Español
  • Suomi
  • Français
  • Gàidhlig
  • हिंदी
  • Magyar
  • Italiano
  • Қазақ
  • Latviešu
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Srpski (lat)
  • Српски
  • Svenska
  • Türkçe
  • Yкраї́нська
  • Tiếng Việt
Log In
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Scholalry Output
  3. Publications
  4. Unveiling new therapeutic candidates for dystrophinopathies: computational insights into FBXO32 and CD4 modulation
 
  • Details

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

Source
Network Modeling Analysis in Health Informatics and Bioinformatics
ISSN
21926662
Date Issued
2025-12-01
Author(s)
Trivedi, Pooja
Dixit, Nandan
Patel, Saumya
Gupta, Sharad  
Sindhav, Gaurang
DOI
10.1007/s13721-025-00581-7
Volume
14
Issue
1
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.
Unpaywall
URI
http://repository.iitgn.ac.in/handle/IITG2025/27985
IITGN Knowledge Repository Developed and Managed by Library

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Privacy policy
  • End User Agreement
  • Send Feedback
Repository logo COAR Notify