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MimoPro: a more efficient Web-based tool for epitope prediction using phage display libraries

Wen Han Chen1, Ping Ping Sun12, Yang Lu1, William W Guo3, Yan Xin Huang4* and Zhi Qiang Ma1*

Author Affiliations

1 School of Computer Science and Information Technology, Northeast Normal University, Changchun 130024, P.R. China

2 Faculty of Chemistry, Northeast Normal University, Changchun 130024, P.R. China

3 School of Information and Communication Technology, Central Queensland University, North Rockhampton QLD 4702, Australia

4 National Engineering Laboratory for Druggable Gene and Protein Screening, Northeast Normal University, Changchun 130024, P.R. China

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BMC Bioinformatics 2011, 12:199  doi:10.1186/1471-2105-12-199

Published: 25 May 2011



A B-cell epitope is a group of residues on the surface of an antigen which stimulates humoral responses. Locating these epitopes on antigens is important for the purpose of effective vaccine design. In recent years, mapping affinity-selected peptides screened from a random phage display library to the native epitope has become popular in epitope prediction. These peptides, also known as mimotopes, share the similar structure and function with the corresponding native epitopes. Great effort has been made in using this similarity between such mimotopes and native epitopes in prediction, which has resulted in better outcomes than statistics-based methods can. However, it cannot maintain a high degree of satisfaction in various circumstances.


In this study, we propose a new method that maps a group of mimotopes back to a source antigen so as to locate the interacting epitope on the antigen. The core of this method is a searching algorithm that is incorporated with both dynamic programming (DP) and branch and bound (BB) optimization and operated on a series of overlapping patches on the surface of a protein. These patches are then transformed to a number of graphs using an adaptable distance threshold (ADT) regulated by an appropriate compactness factor (CF), a novel parameter proposed in this study. Compared with both Pep-3D-Search and PepSurf, two leading graph-based search tools, on average from the results of 18 test cases, MimoPro, the Web-based implementation of our proposed method, performed better in sensitivity, precision, and Matthews correlation coefficient (MCC) than both did in epitope prediction. In addition, MimoPro is significantly faster than both Pep-3D-Search and PepSurf in processing.


Our search algorithm designed for processing well constructed graphs using an ADT regulated by CF is more sensitive and significantly faster than other graph-based approaches in epitope prediction. MimoPro is a viable alternative to both PepSurf and Pep-3D-Search for epitope prediction in the same kind, and freely accessible through the MimoPro server located at webcite.