Identifying Linear B-cell Epitopes Based on Incorporated Sequence Information

Author(s): Yixia Shi*.

Journal Name: Current Proteomics

Volume 15 , Issue 3 , 2018

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Graphical Abstract:


Background: An epitope is a specific portion of a macromolecular antigen that can determine antigen specificity, and has great significance in studying adaptive immune responses. It can be a linear fragment in the antigen structure (also called a linear B-cell epitope) or an area of conformational structure in space (also known as a conformational B-cell epitope). However, the methods of empirical testing used to identify epitopes are costly and time consuming.

Objective: The objective of this study is to provide an efficient predictor for distinguishing linear B-cell epitopes.

Method: In this study, we present a predictor model based on the incorporation of information on the position- specific amino acid propensity, composition of amino acids, composition of pairs of amino acids and position-specific pair of amino acids propensity. And F-Score was used to select valid features.

Results: In jackknife cross-validation, our model achieved an overall sensitivity of 92.59%, specificity of 95.47%, accuracy of 94.36% and Matthews correlation coefficient of 0.8729 on a non-redundant dataset.

Conclusion: The results confirm the constructed model is superior to other existing methods.

Keywords: B-cell, PSAAP, AAC, prediction, SVM, feature extraction.

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Article Details

Year: 2018
Page: [190 - 195]
Pages: 6
DOI: 10.2174/1570164615666180328145806
Price: $58

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