Prediction of linear B-cell epitopes using amino acid pair antigenicity scale
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- 26 January 2007
- journal article
- research article
- Published by Springer Nature in Amino Acids
- Vol. 33 (3) , 423-428
- https://doi.org/10.1007/s00726-006-0485-9
Abstract
Identification of antigenic sites on proteins is of vital importance for developing synthetic peptide vaccines, immunodiagnostic tests and antibody production. Currently, most of the prediction algorithms rely on amino acid propensity scales using a sliding window approach. These methods are oversimplified and yield poor predicted results in practice. In this paper, a novel scale, called the amino acid pair (AAP) antigenicity scale, is proposed that is based on the finding that B-cell epitopes favor particular AAPs. It is demonstrated that, using SVM (support vector machine) classifier, the AAP antigenicity scale approach has much better performance than the existing scales based on the single amino acid propensity. The AAP antigenicity scale can reflect some special sequence-coupled feature in the B-cell epitopes, which is the essence why the new approach is superior to the existing ones. It is anticipated that with the continuous increase of the known epitope data, the power of the AAP antigenicity scale approach will be further enhanced.Keywords
This publication has 42 references indexed in Scilit:
- Predicting protein structural class with pseudo-amino acid composition and support vector machine fusion networkAnalytical Biochemistry, 2006
- Prediction of protein structural class with Rough SetsBMC Bioinformatics, 2006
- Benchmarking B cell epitope prediction: Underperformance of existing methodsProtein Science, 2005
- Prediction of Tight Turns and Their Types in ProteinsAnalytical Biochemistry, 2000
- Predictive estimation of protein linear epitopes by using the program PEOPLEVaccine, 1999
- Using Pair-Coupled Amino Acid Composition to Predict Protein Secondary Structure ContentProtein Journal, 1999
- Prediction and classification of α-turn typesBiopolymers, 1997
- Prediction of β‐turnsChemical Biology & Drug Design, 1997
- Prediction of Human Immunodeficiency Virus Protease Cleavage Sites in ProteinsAnalytical Biochemistry, 1996
- A sequence‐coupled vector‐projection model for predicting the specificity of GalNAc‐transferaseProtein Science, 1995