Improved methods for predicting peptide binding affinity to MHC class II molecules
Improved methods for predicting peptide binding affinity to MHC class II molecules
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DOI：
10.1111/imm.12889
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发表时间：
2018-07-01
期刊：
影响因子：
6.4
通讯作者：
Nielsen, Morten
中科院分区：
文献类型：
--
作者：
Jensen, Kamilla Kjaergaard;Andreatta, Massimo;Nielsen, Morten
主要组织相容性复合体 II 类 (MHC-II) 分子在专业抗原呈递细胞的表面表达，在其中向 T 辅助细胞展示肽，从而协调许多宿主免疫反应的发生和结果。因此，了解 MHC-II 分子将呈递哪些肽对于了解 T 辅助细胞的激活非常重要，并且可用于识别 T 细胞表位。我们在此介绍两种 MHC-II 肽结合亲和力预测方法 NetMHCII 和 NetMHCIIpan 的更新版本。这些是使用从免疫表位数据库获得的定量 MHC 肽结合亲和力数据的扩展数据集构建的，涵盖 HLA-DR、HLA-DQ、HLA-DP 和 H-2 小鼠分子。我们表明，使用此扩展数据集进行训练提高了两种方法的肽结合预测的性能。这两种方法均可在 和 上公开获取。
Major histocompatibility complex class II (MHC-II) molecules are expressed on the surface of professional antigen-presenting cells where they display peptides to T helper cells, which orchestrate the onset and outcome of many host immune responses. Understanding which peptides will be presented by the MHC-II molecule is therefore important for understanding the activation of T helper cells and can be used to identify T-cell epitopes. We here present updated versions of two MHC-II-peptide binding affinity prediction methods, NetMHCII and NetMHCIIpan. These were constructed using an extended data set of quantitative MHC-peptide binding affinity data obtained from the Immune Epitope Database covering HLA-DR, HLA-DQ, HLA-DP and H-2 mouse molecules. We show that training with this extended data set improved the performance for peptide binding predictions for both methods. Both methods are publicly available at and .