LAUSR

BACKGROUND Computational tools may have an edge over conventional method for preliminary evaluation of food allergenicity. In this study, allergenic potential of Lentinula edodes was evaluated and validated via in silico tools. RESULTS Potential cross-reactivity of mushroom proteins with fungal allergens were determined using sequence alignment - FASTA and BLAST algorithm. Eight L. edodes proteins were cross-reactive with fungal allergens showing 52%-89% sequence identity (FASTA algorithm-based alignment) by consensus. BLAST data was corroborated by percent identity and query coverage. Physico-chemical property based allergenicity was deciphered by AlgPred, Allermatch and AllergenFP software which predicted 6 out of 8 proteins as allergens. Sequence alignment showed 66%-86% conservancy between mushroom protein and known fungal allergens. Secondary structure and amino acid composition supported structural affinity between query and fungal proteins. Three dimensional structures of 5 mushroom proteins were generated, quality assessed and superimposed with fungal allergens suggesting possible allergenicity of mushroom proteins. ELISA demonstrated IgE binding in 13 out of 21 food hypersensitive patients' sera. CONCLUSION In silico tools provide preliminary indication about potential allergenicity and cross-reactivity of mushroom proteins which can be established by in vitro and in vivo results. This approach may be used for prelusive allergenicity assessment of allergen source. This article is protected by copyright. All rights reserved.