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Page 421                                      Aydin et al. J Transl Genet Genom. 2025;9:406-26  https://dx.doi.org/10.20517/jtgg.2025.108

               muscle. This targeted emphasis may overlook compounds with activation potential capable of restoring
               pathways related to muscle regeneration, mitochondrial bioenergetics, or metabolic homeostasis. The
               restricted scope of screening may therefore underrepresent the therapeutic potential of drugs that act
               through upregulatory mechanisms. The molecular docking simulations provide structural insight into
               potential ligand-protein interactions; however, docking remains an approximation that does not account for
               conformational flexibility, dynamic cellular environments, pharmacokinetic constraints, or drug
               metabolism. Protein dynamics, post-translational modifications, and tissue-specific isoforms may influence
               binding in vivo in ways that cannot be fully represented through static docking models.

               Despite these limitations, the study establishes a coherent computational framework capable of uncovering
               biologically meaningful targets and generating testable hypotheses for therapeutic development. The
               integration of network biomarkers, transcriptomic perturbation signatures, and ligand-target affinity
               modeling provides a foundation for future investigations that combine in silico predictions with cellular and
               animal validation studies. A key direction for subsequent work involves confirming whether the in silico
               predictions translate into measurable phenotypic improvements in experimental DMD models and
               exploring whether activation-based therapeutics could complement the inhibitory mechanisms identified
               here.


               CONCLUSION
               DMD is a rare and challenging disease, as there is no complete cure. In this study, omics-oriented network
               constructions were performed to integrate transcriptome-level data and multi-omic crosstalk in the
               pathogenesis of DMD. The identified biomarkers were used as targets to reverse the gene expression
               signatures of DMD via drug repositioning. Two repositioned drug candidates, emetine dihydrochloride
               hydrate and celastrol, were reported as potential therapeutic agents for the management of DMD. Emetine
               dihydrochloride hydrate, a potent plant-derived alkaloid, and celastrol, a bioactive compound derived from
               plants, exhibited promising pharmacological properties according to docking results. These findings
               demonstrate the significant therapeutic potential of these phytochemical-derived compounds and reinforce
               the importance of phytochemicals as a foundation for novel drug development in modern medicine.


               DECLARATIONS
               Authors’ contributions
               Made substantial contributions to drafting the work, methodology, and visualization: Parmak HB, İyisoy
               ME, Unal Z, Eskicubuk H
               Made substantial contributions to methodology, software development, data curation, and visualization:
               Okutan K
               Made substantial contributions to conceptualization, methodology, validation, software development, data
               curation, visualization, supervision, and writing - review & editing: Aydin B.
               All authors contributed to the original draft and approved the final version of the manuscript.


               Financial support and sponsorship
               Not applicable.

               Availability of data and materials
               The datasets used in this study are publicly available in the Gene Expression Omnibus (GEO) database at
               the  following  links:  GSE38417-  https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE38417,
               GSE109178- https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE109178, GSE70955- https://www.
               ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE70955. Additional data related to this study are available from
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