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Nucleic Acids Research Advance Access originally published online on December 6, 2006
Nucleic Acids Research 2007 35(1):69-78; doi:10.1093/nar/gkl975
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Nucleic Acids Research, 2007, Vol. 35, No. 1 69-78
© 2006 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Computational Biology

Epitope mapping using combinatorial phage-display libraries: a graph-based algorithm

Itay Mayrose, Tomer Shlomi1, Nimrod D. Rubinstein, Jonathan M. Gershoni, Eytan Ruppin1, Roded Sharan1 and Tal Pupko*

Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences Tel-Aviv 69978, Israel 1 School of Computer Science, Tel-Aviv University Tel-Aviv 69978, Israel

*To whom correspondence should be addressed. Tel: +972 3 640 7693; Fax: +972 3 642 2046; Email: talp{at}post.tau.ac.il

Received July 26, 2006. Revised September 22, 2006. Accepted October 26, 2006.

A phage-display library of random peptides is a combinatorial experimental technique that can be harnessed for studying antibody–antigen interactions. In this technique, a phage peptide library is scanned against an antibody molecule to obtain a set of peptides that are bound by the antibody with high affinity. This set of peptides is regarded as mimicking the genuine epitope of the antibody's interacting antigen and can be used to define it. Here we present PepSurf, an algorithm for mapping a set of affinity-selected peptides onto the solved structure of the antigen. The problem of epitope mapping is converted into the task of aligning a set of query peptides to a graph representing the surface of the antigen. The best match of each peptide is found by aligning it against virtually all possible paths in the graph. Following a clustering step, which combines the most significant matches, a predicted epitope is inferred. We show that PepSurf accurately predicts the epitope in four cases for which the epitope is known from a solved antibody–antigen co-crystal complex. We further examine the capabilities of PepSurf for predicting other types of protein–protein interfaces. The performance of PepSurf is compared to other available epitope mapping programs.


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I. Mayrose, O. Penn, E. Erez, N. D. Rubinstein, T. Shlomi, N. T. Freund, E. M. Bublil, E. Ruppin, R. Sharan, J. M. Gershoni, et al.
Pepitope: epitope mapping from affinity-selected peptides
Bioinformatics, December 1, 2007; 23(23): 3244 - 3246.
[Abstract] [Full Text] [PDF]


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