Frontiers in Drug Discovery · Published 2026-07-07 · DOI 10.3389/fddsv.2026.1834905
Aylin del Moral-Morales, Jean Arguello‐Camarillo, Jesús Yael Castañón Bello, Angélica Chavez-Romero, José L. Medina-Franco, Hugo Nájera, Gerardo Pérez-Hernández
Several widely used drugs have been associated with inner ear damage, including aminoglycosides prescribed for bacterial infections and cisplatin, a principal component of several chemotherapeutic regimens. Drug-induced ototoxicity remains a significant clinical challenge, often exacerbated by the lack of a systematic framework to map the growing body of scientific literature. To fill this gap, we developed a high-throughput computational pipeline to characterize the chemical and biological landscape of otoactive small-molecules. To do so, an automated Python-based workflow was developed to retrieve and process 7,801 PubMed abstracts. GPT-4 was employed as a text extraction tool, identifying compound names and their explicitly reported roles directly from the provided abstracts. Extracted compounds were enriched with structural data from PubChem and cross-referenced with experimental drug–protein interactions from BindingDB to construct a comprehensive drug-target network. Our LLM-driven approach identified 1,758 otoactive compounds, of which 619 are otoprotective and 1,092 ototoxic. Network analysis revealed the transporters ABCC3, ABCC4, and albumin as central hubs of drug interaction for the ototoxic compounds. All results are organized and publicly accessible through a dedicated web application at https://ototoxdb.streamlit.app. This comprehensive registry serves as a primary entry point for researchers screening otoactive molecules and provides a systematic framework for the automated surveillance of ototoxic drugs, supporting the future development of otoprotective strategies.
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Moral-Morales, A., Arguello‐Camarillo, J., Bello, J., et al. (2026). Mapping the otoactive landscape: an LLM-aided extraction of compounds and their targets. Frontiers in Drug Discovery. https://doi.org/10.3389/fddsv.2026.1834905