ABSTRACT Oral squamous cell carcinoma (OSCC) presents significant clinical challenges due to high recurrence and limited treatment options. This study utilized a multi‐omics computational strategy comprising transcriptome profiling, network analysis, and structure‐based virtual screening—to identify repurposed medications for preventing OSCC recurrence. Analysis of the GSE217142 dataset identified 267 differentially expressed genes (DEGs), with SPRR1B, TGM1, S100A7, CDSN, and IVL identified as key hub genes. S100A7 was selected for virtual screening due to its critical role in tumor progression. Structural analysis of S100A7 revealed a high‐affinity binding cavity (Pocket 1) characterized by polar and aromatic residues. Using the DrugRep platform to test over 2000 FDA‐approved drugs, meclofenamic acid was identified as the top candidate with a binding affinity of −6.1 kcal/mol and favorable ADMET properties. Docking confirmed substantial interactions with residues ASP80 and TYR53, supporting its potential to inhibit S100A7‐mediated pathways. These findings demonstrate the efficacy of computational drug repurposing and provide a foundation for further in vitro and in vivo validation in recurrent oral cancer.
Sahoo et al. (Sat,) studied this question.