PEASE: Predicting B-cell epitopes utilizing antibody sequence

Inbal Sela-Culang, Shaul Ashkenazi, Bjoern Peters, Yanay Ofran

Research output: Contribution to journalArticlepeer-review

39 Scopus citations

Abstract

Summary: 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.

Original languageEnglish
Pages (from-to)1313-1315
Number of pages3
JournalBioinformatics
Volume31
Issue number8
DOIs
StatePublished - 15 Apr 2015

Bibliographical note

Publisher Copyright:
© 2014 The Author.

Funding

This project has been funded in whole or in part with federal funds from the National Institutes of Allergy and Infectious Diseases [contract no: HHSN272200900048C].

FundersFunder number
National Institute of Allergy and Infectious DiseasesHHSN272200900048C

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