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Predicting CD4 T-cell epitopes based on antigen cleavage MHCII presentation and TCR recognition

机译:基于抗原裂解MHCII呈递和TCR识别预测CD4 T细胞表位

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摘要

Accurate predictions of T-cell epitopes would be useful for designing vaccines, immunotherapies for cancer and autoimmune diseases, and improved protein therapies. The humoral immune response involves uptake of antigens by antigen presenting cells (APCs), APC processing and presentation of peptides on MHC class II (pMHCII), and T-cell receptor (TCR) recognition of pMHCII complexes. Most in silico methods predict only peptide-MHCII binding, resulting in significant over-prediction of CD4 T-cell epitopes. We present a method, ITCell, for prediction of T-cell epitopes within an input protein antigen sequence for given MHCII and TCR sequences. The method integrates information about three stages of the immune response pathway: antigen cleavage, MHCII presentation, and TCR recognition. First, antigen cleavage sites are predicted based on the cleavage profiles of cathepsins S, B, and H. Second, for each 12-mer peptide in the antigen sequence we predict whether it will bind to a given MHCII, based on the scores of modeled peptide-MHCII complexes. Third, we predict whether or not any of the top scoring peptide-MHCII complexes can bind to a given TCR, based on the scores of modeled ternary peptide-MHCII-TCR complexes and the distribution of predicted cleavage sites. Our benchmarks consist of epitope predictions generated by this algorithm, checked against 20 peptide-MHCII-TCR crystal structures, as well as epitope predictions for four peptide-MHCII-TCR complexes with known epitopes and TCR sequences but without crystal structures. ITCell successfully identified the correct epitopes as one of the 20 top scoring peptides for 22 of 24 benchmark cases. To validate the method using a clinically relevant application, we utilized five factor VIII-specific TCR sequences from hemophilia A subjects who developed an immune response to factor VIII replacement therapy. The known HLA-DR1-restricted factor VIII epitope was among the six top-scoring factor VIII peptides predicted by ITCall to bind HLA-DR1 and all five TCRs. Our integrative approach is more accurate than current single-stage epitope prediction algorithms applied to the same benchmarks. It is freely available as a web server ().
机译:T细胞表位的准确预测将对设计疫苗,癌症和自身免疫性疾病的免疫疗法以及改良的蛋白质疗法有用。体液免疫应答涉及抗原呈递细胞(APC)吸收抗原,APC处理并呈递II类MHC上的肽(pMHCII)以及对pMHCII复合物的T细胞受体(TCR)识别。大多数计算机方法只能预测肽与MHCII的结合,从而导致CD4 T细胞表位的明显过高预测。我们提出了一种方法ITCell,用于预测给定MHCII和TCR序列的输入蛋白抗原序列内的T细胞表位。该方法整合了有关免疫反应途径三个阶段的信息:抗原切割,MHCII呈递和TCR识别。首先,根据组织蛋白酶S,B和H的裂解图谱预测抗原的裂解位点。其次,根据建模得分,对于抗原序列中的每个12-mer肽,我们预测其是否将结合给定的MHCII肽-MHCII复合物。第三,基于建模的三元肽-MHCII-TCR复合物的分数和预测的切割位点的分布,我们预测得分最高的肽-MHCII复合物是否可以与给定的TCR结合。我们的基准测试包括由该算法生成的表位预测,针对20个肽-MHCII-TCR晶体结构进行的检查,以及四种具有已知表位和TCR序列但无晶体结构的肽-MHCII-TCR复合物的表位预测。 ITCell成功地将正确的表位确定为24个基准病例中22个的20个得分最高的肽之一。为了使用临床相关应用验证该方法,我们利用了来自对A型血友病患者产生的对A型凝血因子VIII替代疗法产生免疫应答的五种特定于A型凝血因子的TCR序列。 ITCall预测结合HLA-DR1和所有五个TCR的六个得分最高的VIII因子肽是已知的HLA-DR1限制性VIII因子表位。我们的集成方法比应用于相同基准的当前单阶段表位预测算法更准确。它可以作为Web服务器免费使用()。

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