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Allergenicity prediction by protein sequence
Author(s) -
Stadler Michael B.,
Stadler Beda M.
Publication year - 2003
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fj.02-1052fje
Subject(s) - sequence (biology) , computational biology , food allergens , computer science , protein sequencing , sequence motif , microbiology and biotechnology , allergen , machine learning , biology , peptide sequence , genetics , gene , immunology , allergy
Potential allergenicity of transgenic proteins for consumption must be investigated before their introduction into the food chain. A prerequisite is sequence analysis. We have critically reviewed the performance of the current guidelines proposed by the Food and Agriculture Organization (FAO) and the World Health Organization (WHO) for allergenicity prediction based on protein sequence and show that its precision is very low. To improve prediction, we propose a new strategy based on sequence motifs identified from a new allergen database. If tested on random test sequences and known allergens, both methods are apparently very sensitive. However, the precision of our motif‐based prediction (95.5%) is superior to the current method (36.6%). We conclude that the proposed motif‐based prediction is a superior alternative to the current method for use in the decision‐tree approach for allergenicity assessment.