PEASE: predicting B-cell epitopes utilizing antibody sequence

Bioinformatics. 2015 Apr 15;31(8):1313-5. doi: 10.1093/bioinformatics/btu790. Epub 2014 Nov 27.

Abstract

Antibody epitope mapping is a key step in understanding antibody-antigen recognition and is of particular interest for drug development, diagnostics and vaccine design. Most computational methods for epitope prediction are based on properties of the antigen sequence and/or structure, not taking into account the antibody for which the epitope is predicted. Here, we introduce PEASE, a web server predicting antibody-specific epitopes, utilizing the sequence of the antibody. The predictions are provided both at the residue level and as patches on the antigen structure. The tradeoff between recall and precision can be tuned by the user, by changing the default parameters. The results are provided as text and HTML files as well as a graph, and can be viewed on the antigen 3D structure.

Availability and implementation: PEASE is freely available on the web at www.ofranlab.org/PEASE.

Contact: [email protected].

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Antibodies / chemistry*
  • Antibodies / metabolism
  • Antigens / chemistry*
  • Artificial Intelligence
  • Complementarity Determining Regions / genetics
  • Epitope Mapping / methods*
  • Epitopes, B-Lymphocyte / chemistry*
  • Epitopes, B-Lymphocyte / metabolism
  • Humans
  • Internet*
  • Protein Conformation

Substances

  • Antibodies
  • Antigens
  • Complementarity Determining Regions
  • Epitopes, B-Lymphocyte