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Breaking down biofilms across critical priority fungal pathogens: proteomics and computational innovation for mechanistic insights and new target discovery

Summary

This comprehensive review examines how scientists are fighting dangerous fungal infections that form protective biofilms resistant to current antifungal drugs. Researchers are using advanced protein analysis techniques (proteomics) and artificial intelligence-based computational tools to identify new targets for drug development against four critical fungal pathogens that cause life-threatening infections like meningitis and lung infections. By combining these technologies, scientists can better understand how these fungal biofilms form and develop more effective treatments.

Background

Fungal biofilms are complex microbial structures associated with persistent and progressive infections such as cryptococcal meningitis, invasive aspergillosis, and invasive candidiasis, leading to thousands of deaths annually. The prevalence of fungal biofilm formation during infections with heightened resistance to antifungal drugs highlights the urgent need for discovery and development of new antifungals with antibiofilm activity.

Objective

This review highlights fungal biofilms of four critical priority fungal pathogens designated by the World Health Organization (Cryptococcus neoformans, Aspergillus fumigatus, Candida albicans, and Candida auris) and defines important technological considerations for proteomics and computational methodologies. The review explores recent proteomics and computational applications within fungal biofilms for identifying biological mechanisms and discovering novel putative antibiofilm targets.

Results

Studies using mass spectrometry-based proteomics identified key proteins associated with biofilm formation including heat shock proteins, metabolic enzymes, oxidative stress response proteins, and adhesion factors across all four priority pathogens. Computational approaches including AlphaFold structure prediction combined with virtual high-throughput screening identified promising ligand candidates targeting biofilm-associated proteins in C. albicans stress response proteins.

Conclusion

Mass spectrometry-based proteomics has successfully identified essential processes and proteins activated during biofilm formation as potential therapeutic targets. Integration of computational tools such as AlphaFold with proteomics data represents a promising future direction for accelerating drug discovery against fungal biofilms through de novo drug design and virtual screening approaches.
  • Published in:mBio,
  • Study Type:Review,
  • Source: 40693795
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