New Publication: Computational Approaches for Tailoring TLRs and AMPs Against Candida

We are pleased to announce a new publication in the Celal Bayar University Journal of Science.

Recent Advancements in Computational Approaches for Tailoring Toll-like Receptors and Antimicrobial Peptides Against Candida Infections

This review article summarizes recent advancements in computational approaches for designing and optimizing Toll-like receptors (TLRs) and antimicrobial peptides (AMPs) against Candida infections. The study highlights how computational methods can accelerate the development of novel therapeutic strategies against fungal pathogens.

The work discusses various in silico techniques including molecular modeling, docking simulations, and machine learning approaches that enable researchers to rationally design more effective antimicrobial agents targeting Candida species.