- Article -

Volume 7

Full article

Improved prediction of allergenicity by combination of multiple sequence motifs

Waiming Kong*, Tsu Soo Tan, Lawrence Tham and Keng Wah Choo

Bioinformatics Group, Nanyang Polytechnic, 180 Ang Mo Kio Ave 8, Singapore (589 830)



* Corresponding author    Email: KONG_Wai_Ming@nyp.gov.sg


Edited by H. Michael; received June 27, 2006; revised December 06, 2006; accepted December 07, 2006; published January 05, 2007

Abstract

The identification and validation of protein allergens have become more important nowadays as more and more transgenic proteins are introduced into our food chains. Current allergen prediction algorithms focus on the identification of single motif or single allergen peptide for allergen detection. However, an analysis of the 575 allergen dataset shows that most allergens contain multiple motifs. Here, we present a novel algorithm that detects allergen by making use of combinations of motifs. Sensitivity of 0.772 and specificity of 0.904 were achieved by the proposed algorithm to predict allergen. The specificity of the proposed approach is found to be significantly higher than traditional single motif approaches. The high specificity of the proposed algorithm is useful in filtering out false positives, especially when laboratory resources are limited.

Keywords: allergen, allergen prediction, combination of motifs