PEASE: Predicting B-cell epitopes utilizing antibody sequence

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

doi:10.1093/bioinformatics/btu790

PEASE: Predicting B-cell epitopes utilizing antibody sequence

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

The Mina and Everard Goodman Faculty of Life Sciences - at Bar-Ilan University

Bar-Ilan University
La Jolla Institute for Allergy and Immunology

Research output: Contribution to journal › Article › peer-review

58 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 language	English
Pages (from-to)	1313-1315
Number of pages	3
Journal	Bioinformatics
Volume	31
Issue number	8
DOIs	https://doi.org/10.1093/bioinformatics/btu790
State	Published - 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].

Funders	Funder number
National Institute of Allergy and Infectious Diseases	HHSN272200900048C

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Access to Document

10.1093/bioinformatics/btu790

Cite this

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PEASE: Predicting B-cell epitopes utilizing antibody sequence

Abstract

Bibliographical note

Funding

UN SDGs

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