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Updated: Feb 7, 2026

Quantifying the Antifungal Activity of Peptides Against Candida albicans
Published on: January 13, 2023
FungiGuard: identification of plant antifungal peptides with artificial intelligence
Xiang Li1, Yitian Fang2, You Wu3
1Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.
Abstract:
Antifungal peptides (AFPs) are crucial for plant defense against biotic stress. Yet, no artificial intelligence tool specifically classifies plant AFPs. To fill this gap, we develop FungiGuard, which integrates Random Forest, Long Short-Term Memory, and attention mechanisms to identify AFPs using functionally annotated plant small peptides. FungiGuard outperforms existing generalized AFP model in classifying plant AFPs, and detects candidate AFPs in Arabidopsis, wheat, rice, and maize. It also discovers novel AFPs through randomly generated sequences. Experimental validation confirms the antifungal activity of candidate AFP against Botrytis cinerea. This tool deepens plant AFP understanding and facilitates novel AFP discovery.
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