Design of a Dual Screening Tool for the Detection of Fungi and Mycotoxins in Stored Cocoa

This data is centered on the development of a cell-free screening method to identify mycotoxins and fungi in stored cocoa beans, addressing a critical gap in local knowledge about fungal contamination. Utilizing computational tools like Benchling for cassette design and AlphaFold for protein modeling, we identified cross-activity with Aflatoxin, specifically Gliotoxin and ABA. The constructed cassettes, featuring chimeric proteins Bichota and X19X, were validated through AlphaFold modeling, and their interactions with target molecules and natural components in healthy cacao were explored via Docking and Virtual Screening using SwissDock. The data suggests that our screening method has the potential to empower cocoa producers by providing real-time information to prevent economic losses due to fungal contamination and mycotoxin production. Furthermore, the application of this technology aligns with international market standards, ensuring compliance with maximum permissible limits of mycotoxins for cocoa exports according to European Union legislation. The success of this project could significantly contribute to strengthening the cocoa value chain, improving product quality, and expanding opportunities in global markets.