Antifungal drug discovery

Transcriptomics Insights into Targeting CK2 Complex in Cryptococcus neoformans: Implications for Large-Scale Antifungal Virtual Screening

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Scientists studied how a fungus called Cryptococcus neoformans causes serious brain infections and found that disabling a specific protein complex (CK2) could be an effective treatment strategy. Using computer analysis of genetic data, they identified three existing drugs—amphotericin B, idarubicin, and candicidin—that could potentially target and kill this dangerous fungus. This research provides a foundation for developing better treatments for cryptococcal meningitis, a life-threatening infection that kills hundreds of thousands of people annually, especially those with weakened immune systems.

Discovery of novel targets for important human and plant fungal pathogens via an automated computational pipeline HitList

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Researchers created a computer program called HitList that searches fungal DNA to find new targets for antifungal medications. The program identified 16 promising protein targets that could be attacked by new antifungal drugs, including 8 completely new targets never before considered. This discovery could help develop new antifungal treatments to fight drug-resistant fungal infections in both humans and crops.

A novel pan-fungal screening platform for antifungal drug discovery: proof of principle study

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Researchers developed a faster, more efficient screening method to test potential antifungal drugs against multiple disease-causing fungi simultaneously. Using an improved growth medium and screening 500 chemical fragments, they identified compounds with antifungal activity and demonstrated the platform can reliably detect promising drug candidates. This approach could accelerate the discovery of new antifungal medications, which are urgently needed as fungi develop resistance to current treatments.

Discovery of novel targets for important human and plant fungal pathogens via an automated computational pipeline HitList

mycolabadmin

Scientists developed a computer program called HitList that searches through fungal genes to find new targets for antifungal medicines. The program identifies proteins that are unique to harmful fungi and missing from humans and plants, making them ideal drug targets. The study found several promising new protein targets that could lead to development of more effective antifungal drugs to treat both human fungal infections and crop diseases caused by fungi.

Research Topic: Antifungal drug discovery

Transcriptomics Insights into Targeting CK2 Complex in Cryptococcus neoformans: Implications for Large-Scale Antifungal Virtual Screening

Discovery of novel targets for important human and plant fungal pathogens via an automated computational pipeline HitList

A novel pan-fungal screening platform for antifungal drug discovery: proof of principle study

Discovery of novel targets for important human and plant fungal pathogens via an automated computational pipeline HitList