Data-driven discovery of novel antifungal small molecules from fungal genomes

Overview

Novogaia has developed an innovative platform that combines machine learning with metabologenomics to discover novel antifungal small molecules from fungal genomes. By leveraging the natural defense mechanisms of fungi, this approach identifies secondary metabolites with potential antifungal properties. The platform enables a data-driven search for novel compounds that can be used as natural food preservation ingredients, offering a sustainable and efficient solution to combat fungal spoilage.

Technical specifications

Key features:

• Utilizes machine learning to mine fungal genomes for biosynthetic gene clusters.
• Identifies resistance genes to predict the bioactivity of secondary metabolites.
• Focus on Generally Recognized As Safe (GRAS) fungal strains to accelerate discovery.
• Offers targeted mining approach to streamline the identification of effective antifungal compounds.

Technology readiness level

Currently at TRL 2, this technology has undergone initial validation and modeling. Future development plans involve partnering with organizations to test proposed molecules and conduct antifungal analyses, which will further refine and enhance the predictive capabilities of the platform.