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Conformational B-Cell Epitope Prediction Method Based on Antigen Preprocessing and Mimotopes Analysis

机译:基于抗原预处理和拟态分析的构象B细胞表位预测方法

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Identification of epitopes which invokes strong humoral responses is an essential issue in the field of immunology. Various computational methods that have been developed based on the antigen structures and the mimotopes these years narrow the search for experimental validation. These methods can be divided into two categories: antigen structure-based methods and mimotope-based methods. Though new methods of the two kinds have been proposed in these years, they cannot maintain a high degree of satisfaction in various circumstances. In this paper, we proposed a new conformational B-cell epitope prediction method based on antigen preprocessing and mimotopes analysis. The method classifies the antigen surface residues into “epitopes” and “nonepitopes” by six epitope propensity scales, removing the “nonepitopes” and using the preprocessed antigen for epitope prediction based on mimotope sequences. The proposed method gives out the meanFscore of 0.42 on the testing dataset. When compared with other publicly available servers by using the testing dataset, the new method yields better performance. The results demonstrate the proposed method is competent for the conformational B-cell epitope prediction.
机译:鉴定引起强烈体液应答的表位是免疫学领域的重要问题。这些年来,基于抗原结构和模拟表位开发的各种计算方法使对实验验证的搜索范围缩小。这些方法可以分为两类:基于抗原结构的方法和基于模拟表位的方法。尽管近年来已经提出了两种新方法,但是它们不能在各种情况下保持高度的满意度。在本文中,我们提出了一种基于抗原预处理和模拟表位分析的新构象B细胞表位预测方法。该方法按六个表位倾向性等级将抗原表面残基分为“表位”和“非表位”,去除“非表位”,并使用预处理的抗原基于模拟表位序列进行表位预测。所提出的方法在测试数据集上给出了0.42的meanFscore。与使用测试数据集的其他公共服务器相比,新方法产生了更好的性能。结果表明,所提出的方法能够胜任构象B细胞表位的预测。

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