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Computational analysis of missense mutations in squalene epoxidase associated with terbinafine resistance in clinically reported dermatophytes

Summary

Certain fungal skin infections are becoming resistant to terbinafine, a common antifungal medication, due to genetic mutations in an enzyme called squalene epoxidase. Using computer models and analysis tools, researchers identified which mutations most strongly reduce the drug’s effectiveness and where the protein changes occur. Four specific mutations were found to prevent terbinafine from binding to its target, offering insights that could help develop better antifungal treatments.

Background

Dermatophyte infections affect approximately 20-25% of the global population and are becoming increasingly difficult to manage due to rising antifungal resistance. Terbinafine resistance is frequently associated with missense mutations in the squalene epoxidase (SQLE) gene, which may reduce drug binding affinity and compromise antifungal efficacy.

Objective

This study applied comprehensive computational tools to assess the structural and functional impact of clinically reported SQLE missense mutations in terbinafine-resistant dermatophyte isolates. The goal was to understand molecular mechanisms underlying terbinafine resistance and identify key mutation-sensitive sites that may guide antifungal drug development.

Results

Twelve of fourteen mutations significantly reduced SQLE stability, with L393F, L393S, and F397L identified as most destabilizing. Four mutations (F397L, L437P, F415V, Y394N) showed altered terbinafine binding pockets, and STRING analysis revealed SQLE interactions with ten proteins in the ergosterol biosynthesis pathway.

Conclusion

SQLE mutations linked to terbinafine resistance destabilize protein structure, alter critical residues, and reduce terbinafine binding. Conserved regions unaffected by mutations may serve as alternative targets for future antifungal development, and these computational insights can guide experimental validation and therapeutic strategy design.
  • Published in:Scientific Reports,
  • Study Type:Computational Analysis Study,
  • Source: PMID: 40436978, DOI: 10.1038/s41598-025-03300-4
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