In Silico Prediction of Linear B-Cell Epitopes on Proteins
In Silico Prediction of Linear B-Cell Epitopes on Proteins
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DOI：
10.1007/978-1-4939-6406-2_17
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发表时间：
2017-01-01
期刊：
影响因子：
--
通讯作者：
Honavar, Vasant G.
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文献类型：
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作者：
EL-Manzalawy, Yasser;Dobbs, Drena;Honavar, Vasant G.
抗体-蛋白质相互作用在体液免疫应答中起关键作用。B细胞分泌结合抗原的抗体（例如，病原体的细胞表面蛋白）。被抗体识别的抗原的特定部分被称为B细胞表位。这些表位可以是线性的，对应于抗原的连续氨基酸序列片段，或者是构象的，其中对于识别至关重要的残基在一级序列中可能不是连续的，但是在折叠的蛋白质3D结构中非常接近。计算机生物信息学技术提供了一种有前途的和具有成本效益的方法，用于确定潜在的B细胞表位的目标疫苗候选人。在本章中，我们将展示如何利用在线B细胞表位预测工具来从蛋白质的一级氨基酸序列中识别线性B细胞表位。
Antibody-protein interactions play a critical role in the humoral immune response. B-cells secrete antibodies, which bind antigens (e.g., cell surface proteins of pathogens). The specific parts of antigens that are recognized by antibodies are called B-cell epitopes. These epitopes can be linear, corresponding to a contiguous amino acid sequence fragment of an antigen, or conformational, in which residues critical for recognition may not be contiguous in the primary sequence, but are in close proximity within the folded protein 3D structure.Identification of B-cell epitopes in target antigens is one of the key steps in epitope-driven subunit vaccine design, immunodiagnostic tests, and antibody production. In silico bioinformatics techniques offer a promising and cost-effective approach for identifying potential B-cell epitopes in a target vaccine candidate. In this chapter, we show how to utilize online B-cell epitope prediction tools to identify linear B-cell epitopes from the primary amino acid sequence of proteins.