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首页> 外文期刊>Immunology: An Official Journal of the British Society for Immunology >Predicted MHC MHC peptide binding promiscuity explains MHC MHC class I ‘hotspots’ of antigen presentation defined by mass spectrometry eluted ligand data
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Predicted MHC MHC peptide binding promiscuity explains MHC MHC class I ‘hotspots’ of antigen presentation defined by mass spectrometry eluted ligand data

机译:预测的MHC MHC肽绑定滥用解释了由质谱层被洗脱的配体数据定义的抗原呈现的MHC MHC级I'热点'

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Summary Peptides that bind to and are presented by MHC class I and class II molecules collectively make up the immunopeptidome. In the context of vaccine development, an understanding of the immunopeptidome is essential, and much effort has been dedicated to its accurate and cost‐effective identification. Current state‐of‐the‐art methods mainly comprise in silico tools for predicting MHC binding, which is strongly correlated with peptide immunogenicity. However, only a small proportion of the peptides that bind to MHC molecules are, in fact, immunogenic, and substantial work has been dedicated to uncovering additional determinants of peptide immunogenicity. In this context, and in light of recent advancements in mass spectrometry ( MS ), the existence of immunological hotspots has been given new life, inciting the hypothesis that hotspots are associated with MHC class I peptide immunogenicity. We here introduce a precise terminology for defining these hotspots and carry out a systematic analysis of MS and in silico predicted hotspots. We find that hotspots defined from MS data are largely captured by peptide binding predictions, enabling their replication in silico . This leads us to conclude that hotspots, to a great degree, are simply a result of promiscuous HLA binding, which disproves the hypothesis that the identification of hotspots provides novel information in the context of immunogenic peptide prediction. Furthermore, our analyses demonstrate that the signal of ligand processing, although present in the MS data, has very low predictive power to discriminate between MS and in silico defined hotspots.
机译:总结肽与MHC I类和II类分子结合的肽共同构成免疫肽体。在疫苗发育的背景下,对免疫肽的理解是必不可少的,并且很多努力都致力于其准确和成本效益的鉴定。目前的最先进方法主要包括用于预测MHC结合的硅工具,其与肽免疫原性强烈地相关。然而,只有小比例的肽,其与MHC分子结合,实际上是免疫原性和实质性的作品一直专用于揭示肽免疫原性的额外决定因素。在这种情况下,鉴于质谱(MS)的最近进步,免疫热点的存在已经给出了新的寿命,煽动了热点与MHC I类肽免疫原性相关的假设。我们在这里介绍了一个精确的术语,用于定义这些热点,并对MS和Silico预测热点进行系统分析。我们发现,从MS数据定义的热点主要被肽绑定预测捕获,从而可以在硅中复制。这导致我们得出结论,热点到了很大程度,只是混杂的HLA结合的结果,这使得鉴定热点的假设提供了在免疫原肽预测的背景下提供了新颖的信息。此外,我们的分析表明配体处理的信号虽然存在于MS数据中,但在MS数据中具有非常低的预测力来区分MS和Silico定义的热点之间。

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