Suppr超能文献

通过能量分解分析预测抗原性B细胞和T细胞表位:基于网络的预测工具BEPPE的描述

Prediction of Antigenic B and T Cell Epitopes via Energy Decomposition Analysis: Description of the Web-Based Prediction Tool BEPPE.

作者信息

Peri Claudio, Solé Oscar C, Corrada Dario, Gori Alessandro, Daura Xavier, Colombo Giorgio

机构信息

Department of Computational Biology, Institute for Molecular Recognition Chemistry (ICRM), Italian National Research Council, Milan, Italy.

Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Barcelona, Spain.

出版信息

Methods Mol Biol. 2015;1348:13-22. doi: 10.1007/978-1-4939-2999-3_3.

Abstract

Unraveling the molecular basis of immune recognition still represents a challenging task for current biological sciences, both in terms of theoretical knowledge and practical implications. Here, we describe the physical-chemistry methods and computational protocols for the prediction of antibody-binding epitopes and MHC-II loaded epitopes, starting from the atomic coordinates of antigenic proteins (PDB file). These concepts are the base of the Web tool BEPPE (Binding Epitope Prediction from Protein Energetics), a free service that returns a list of putative epitope sequences and related blast searches against the Uniprot human complete proteome. BEPPE can be employed for the study of the biophysical processes at the basis of the immune recognition, as well as for immunological purposes such as the rational design of biomarkers and targets for diagnostics, therapeutics, and vaccine discovery.

摘要

无论是从理论知识还是实际应用的角度来看,揭示免疫识别的分子基础对于当前的生物科学而言仍然是一项具有挑战性的任务。在此,我们描述了从抗原蛋白的原子坐标(PDB文件)出发预测抗体结合表位和MHC-II负载表位的物理化学方法和计算协议。这些概念是网络工具BEPPE(基于蛋白质能量学的结合表位预测)的基础,这是一项免费服务,可返回推定表位序列列表以及针对Uniprot人类完整蛋白质组的相关blast搜索结果。BEPPE可用于研究免疫识别基础的生物物理过程,以及用于免疫目的,如合理设计生物标志物以及诊断、治疗和疫苗研发的靶点。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验