PEASE：利用抗体序列预测 B 细胞表位。

PEASE: predicting B-cell epitopes utilizing antibody sequence.

机构信息

The Goodman Faculty of Life Sciences, Nanotechnology Building, Bar-Ilan University, Ramat-Gan 52900, Israel and Division of Vaccine Discovery, La Jolla Institute for Allergy and Immunology, La Jolla, CA 92037, USA.

出版信息

Bioinformatics. 2015 Apr 15;31(8):1313-5. doi: 10.1093/bioinformatics/btu790. Epub 2014 Nov 27.

DOI:10.1093/bioinformatics/btu790

PMID:25432167

Abstract

UNLABELLED

Antibody epitope mapping is a key step in understanding antibody-antigen recognition and is of particular interest for drug development, diagnostics and vaccine design. Most computational methods for epitope prediction are based on properties of the antigen sequence and/or structure, not taking into account the antibody for which the epitope is predicted. Here, we introduce PEASE, a web server predicting antibody-specific epitopes, utilizing the sequence of the antibody. The predictions are provided both at the residue level and as patches on the antigen structure. The tradeoff between recall and precision can be tuned by the user, by changing the default parameters. The results are provided as text and HTML files as well as a graph, and can be viewed on the antigen 3D structure.

AVAILABILITY AND IMPLEMENTATION

PEASE is freely available on the web at www.ofranlab.org/PEASE.

CONTACT

yanay@ofranlab.org.

摘要

未标记

抗体表位作图是理解抗体-抗原识别的关键步骤，对于药物开发、诊断和疫苗设计特别感兴趣。大多数用于表位预测的计算方法都是基于抗原序列和/或结构的特性，而没有考虑到预测表位的抗体。在这里，我们引入了 PEASE，这是一个利用抗体序列预测抗体特异性表位的网络服务器。预测结果既可以在残基水平上提供，也可以作为抗原结构上的斑块提供。用户可以通过更改默认参数来调整召回率和精度之间的权衡。结果以文本和 HTML 文件以及图表的形式提供，并可以在抗原 3D 结构上查看。