AlgPred: prediction of allergenic proteins and mapping of IgE epitopes

TLDR

The study aims to integrate multiple computational approaches to predict allergenic proteins with high accuracy. The authors developed and evaluated support vector machine, motif‑based, epitope‑search, BLAST, and hybrid classifiers on a curated dataset of 578 allergens and 700 non‑allergens, tested them on an independent set of 323 allergens and 101,725 non‑allergens, and deployed the best models in the AlgPred web server. AlgPred achieved up to 93.94% sensitivity with the motif‑based method, 85.02% accuracy with the SVM approach, and is available online at www.imtech.res.in/raghava/algpred/.

Abstract

In this study a systematic attempt has been made to integrate various approaches in order to predict allergenic proteins with high accuracy. The dataset used for testing and training consists of 578 allergens and 700 non-allergens obtained from A. K. Bjorklund, D. Soeria-Atmadja, A. Zorzet, U. Hammerling and M. G. Gustafsson (2005) Bioinformatics , 21 , 39–50. First, we developed methods based on support vector machine using amino acid and dipeptide composition and achieved an accuracy of 85.02 and 84.00%, respectively. Second, a motif-based method has been developed using MEME/MAST software that achieved sensitivity of 93.94 with 33.34% specificity. Third, a database of known IgE epitopes was searched and this predicted allergenic proteins with 17.47% sensitivity at specificity of 98.14%. Fourth, we predicted allergenic proteins by performing BLAST search against allergen representative peptides. Finally hybrid approaches have been developed, which combine two or more than two approaches. The performance of all these algorithms has been evaluated on an independent dataset of 323 allergens and on 101 725 non-allergens obtained from Swiss-Prot. A web server AlgPred has been developed for the predicting allergenic proteins and for mapping IgE epitopes on allergenic proteins ( http://www.imtech.res.in/raghava/algpred/ ). AlgPred is available at www.imtech.res.in/raghava/algpred/ .