Computational Drug Discovery in Diaphragm Dysfunction via Text Mining and Biomedical Database.

The article focuses on identifying potential genes and drugs associated with diaphragmatic dysfunction (DD), a critical condition affecting the primary muscle responsible for inspiration, especially in patients with severe burns. Using bioinformatics and text-mining techniques, the study identified 96 genes common to DD and functional recovery, with 19 genes enriched in key biological pathways. Quantitative real-time PCR validation in a severe burn rat model confirmed increased expression of 13 hub genes, including CCL2, IL6, PTGS2, and TNF. Drug–gene interaction analysis revealed 56 drugs targeting five key genes, notably PTGS2, which is associated with numerous nonsteroidal anti-inflammatory drugs (NSAIDs) not previously used for DD treatment. These findings suggest new avenues for drug repurposing and therapeutic development for diaphragmatic dysfunction, though further experimental validation is necessary.