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利用蛋白质三维结构预测不连续B细胞表位中的残基

Prediction of residues in discontinuous B-cell epitopes using protein 3D structures.

作者信息

Haste Andersen Pernille, Nielsen Morten, Lund Ole

机构信息

Center for Biological Sequence Analysis, BioCentrum, Technical University of Denmark, DK-2800 Lyngby, Denmark.

出版信息

Protein Sci. 2006 Nov;15(11):2558-67. doi: 10.1110/ps.062405906. Epub 2006 Sep 25.

Abstract

Discovery of discontinuous B-cell epitopes is a major challenge in vaccine design. Previous epitope prediction methods have mostly been based on protein sequences and are not very effective. Here, we present DiscoTope, a novel method for discontinuous epitope prediction that uses protein three-dimensional structural data. The method is based on amino acid statistics, spatial information, and surface accessibility in a compiled data set of discontinuous epitopes determined by X-ray crystallography of antibody/antigen protein complexes. DiscoTope is the first method to focus explicitly on discontinuous epitopes. We show that the new structure-based method has a better performance for predicting residues of discontinuous epitopes than methods based solely on sequence information, and that it can successfully predict epitope residues that have been identified by different techniques. DiscoTope detects 15.5% of residues located in discontinuous epitopes with a specificity of 95%. At this level of specificity, the conventional Parker hydrophilicity scale for predicting linear B-cell epitopes identifies only 11.0% of residues located in discontinuous epitopes. Predictions by the DiscoTope method can guide experimental epitope mapping in both rational vaccine design and development of diagnostic tools, and may lead to more efficient epitope identification.

摘要

发现不连续的B细胞表位是疫苗设计中的一项重大挑战。以往的表位预测方法大多基于蛋白质序列,效果不太理想。在此,我们提出了DiscoTope,一种利用蛋白质三维结构数据进行不连续表位预测的新方法。该方法基于由抗体/抗原蛋白复合物的X射线晶体学确定的不连续表位汇编数据集中的氨基酸统计、空间信息和表面可及性。DiscoTope是首个明确聚焦于不连续表位的方法。我们表明,这种基于结构的新方法在预测不连续表位的残基方面比仅基于序列信息的方法表现更好,并且能够成功预测已通过不同技术鉴定的表位残基。DiscoTope能检测出位于不连续表位中的15.5%的残基,特异性为95%。在这个特异性水平上,用于预测线性B细胞表位的传统帕克亲水性量表只能识别出位于不连续表位中的11.0%的残基。DiscoTope方法的预测可指导合理疫苗设计和诊断工具开发中的实验性表位定位,并可能带来更高效的表位识别。

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