Cross-React: A new structural bioinformatics method for predicting allergen cross-reactivity

Surendra S. Negi, Werner Braun

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

The phenomenon of cross-reactivity between allergenic proteins plays an important role to understand how the immune system recognizes different antigen proteins. Allergen proteins are known to cross-react if their sequence comparison shows a high sequence identity which also implies that the proteins have a similar 3D fold. In such cases, linear sequence alignment methods are frequently used to predict cross-reactivity between allergenic proteins. However, the prediction of cross-reactivity between distantly related allergens continues to be a challenging task. To overcome this problem, we developed a new structure-based computational method, Cross-React, to predict cross-reactivity between allergenic proteins available in the Structural Database of Allergens (SDAP). Our method is based on the hypothesis that we can find surface patches on 3D structures of potential allergens with amino acid compositions similar to an epitope in a known allergen. We applied the Cross-React method to a diverse set of seven allergens, and successfully identified several cross-reactive allergens with high to moderate sequence identity which have also been experimentally shown to cross-react. Based on these findings, we suggest that Cross- React can be used as a predictive tool to assess protein allergenicity and cross-reactivity. Availability and Implementation: Cross-React is available at: http://curie.utmb.edu/Cross-React. html.

Original languageEnglish (US)
Pages (from-to)1014-1020
Number of pages7
JournalBioinformatics
Volume33
Issue number7
DOIs
StatePublished - Apr 1 2017

Fingerprint

Allergens
Reactivity
Bioinformatics
Computational Biology
Proteins
Protein
Epitopes
Predict
Sequence Comparison
Sequence Alignment
Immune system
Immune System
Antigens
Computational methods
Computational Methods
Patch
Amino Acids
Amino acids
Fold
Continue

ASJC Scopus subject areas

  • Statistics and Probability
  • Medicine(all)
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

Cite this

Cross-React : A new structural bioinformatics method for predicting allergen cross-reactivity. / Negi, Surendra S.; Braun, Werner.

In: Bioinformatics, Vol. 33, No. 7, 01.04.2017, p. 1014-1020.

Research output: Contribution to journalArticle

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