AUTHOR=Saeed Mohd , Haque Ashanul , Shoaib Ambreen , Danish Rizvi Syed Mohd 

TITLE=Exploring novel natural compound-based therapies for Duchenne muscular dystrophy management: insights from network pharmacology, QSAR modeling, molecular dynamics, and free energy calculations

JOURNAL=Frontiers in Pharmacology

VOLUME=Volume 15 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2024.1395014

DOI=10.3389/fphar.2024.1395014

ISSN=1663-9812

ABSTRACT=Muscular dystrophies encompass a heterogeneous group of rare neuromuscular ailments distinguished by progressive muscle degeneration and weakness. Among these, Duchenne muscular dystrophy stands out as one of the most severe forms. The present study employs an integrative approach combining network pharmacology, quantitative structure-activity relationship (QSAR) modeling, molecular dynamics (MD) simulations, and free energy calculations to identify potential therapeutic targets and natural compounds for Duchenne muscular dystrophy (DMD). Upon analyzing the GSE38417 dataset, it was found that individuals with Duchenne muscular dystrophy exhibited 290 up-regulated differentially expressed genes (DEGs) compared to healthy controls. By utilizing gene ontology (GO) and protein-protein interaction (PPI) network analysis, this study provides insights into the functional roles of the identified DEGs, identifying ten hub genes that play a critical role in the pathology of Duchenne muscular dystrophy. These key genes include DMD, TTN, PLEC, DTNA, PKP2, SLC24A, FBXO32, SNTA1, SMAD3, and NOS1. Furthermore, through the use of ligand-based pharmacophore modeling and virtual screening, three natural compounds were identified as potential candidates. Among these, compound 5281600 has demonstrated significant promise as an inhibitor of the SMAD3 protein, a crucial factor in the fibrotic and inflammatory mechanisms associated with Duchenne muscular dystrophy. The therapeutic potential of the compounds was further supported by molecular dynamics simulation and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) analysis. These findings suggest that the compounds are viable candidates for experimental validation against Duchenne muscular dystrophy.