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bioRxiv · 10.64898/2025.12.29.696830

AntiFP2: Genome and Metagenome-Wide Prediction of Antifungal Proteins

Shinde, P. B.·Choudhury, S.·Tomer, R.·Raghava, G. P. S.
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Abstract

The identification of antifungal proteins (AFPs) is crucial for understanding microbial interactions and facilitating the discovery of antifungals on a large scale from genomic and metagenomic data. Most existing computational tools are developed for predicting antifungal peptides rather than proteins. To address this limitation, we developed AntiFP2. A manually curated dataset of experimentally validated AFPs was used to train and develop prediction models using cross-validation techniques. The ensemble strategy, which combined ESM2, BLAST, and MERCI, achieved the best results across independent validation. Beyond prediction, we implemented a complete pipeline for genome- and metagenome-wide AFP screening. AntiFP2 is freely available as a web server, standalone package, and Docker container, enabling scalable and reproducible antifungal protein discovery.

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Shinde, P. B., Choudhury, S., Tomer, R., Raghava, G. P. S.. 2025-12-29. AntiFP2: Genome and Metagenome-Wide Prediction of Antifungal Proteins. https://doi.org/10.64898/2025.12.29.696830

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