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Bioinformatics Advance Access originally published online on April 28, 2008
Bioinformatics 2008 24(12):1459-1460; doi:10.1093/bioinformatics/btn199
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

PEPITO: improved discontinuous B-cell epitope prediction using multiple distance thresholds and half sphere exposure

Michael J. Sweredoski 1,2 and Pierre Baldi 1,2,*

1Department of Computer Science and 2Institute for Genomics and Bioinformatics, University of California, Irvine, 92697-3435, California, USA

*To whom correspondence should be addressed.


  Abstract

Motivation: Accurate prediction of B-cell epitopes is an important goal of computational immunology. Up to 90% of B-cell epitopes are discontinuous in nature, yet most predictors focus on linear epitopes. Even when the tertiary structure of the antigen is available, the accurate prediction of B-cell epitopes remains challenging.

Results: Our predictor, PEPITO, uses a combination of amino-acid propensity scores and half sphere exposure values at multiple distances to achieve state-of-the-art performance. PEPITO achieves an area under the curve (AUC) of 75.4 on the Discotope dataset. Additionally, we benchmark PEPITO as well as the Discotope predictor on the more recent Epitome dataset, achieving AUCs of 68.3 and 66.0, respectively.

Availability: PEPITO is available as part of the SCRATCH suite of protein structure predictors via www.igb.uci.edu.

Contact: pfbaldi{at}ics.uci.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Anna Tramontano

Received on March 3, 2008; revised on April 18, 2008; accepted on April 20, 2008

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