Biotech Research & Innovation Centre and Bioinformatics Centre, University of Copenhagen, DK-2200 Copenhagen N, Denmark.
Bioinformatics. 2011 Jul 15;27(14):2013-4. doi: 10.1093/bioinformatics/btr335. Epub 2011 Jun 17.
The recognition of antigenic peptides is a major event of an immune response. In current mesoscopic-scale simulators of the immune system, this crucial step has been modeled in a very approximated way.
We have equipped an agent-based model of the immune system with immuno-informatics methods to allow the simulation of the cardinal events of the antigenic recognition, going from single peptides to whole proteomes. The recognition process accounts for B cell-epitopes prediction through Parker-scale affinity estimation, class I and II HLA peptide prediction and binding through position-specific scoring matrices based on information from known HLA epitopes prediction tools, and TCR binding to HLA-peptide complex calculated as the averaged sum of a residue-residue contact potential. These steps are executed for all lymphocytes agents encountering the antigen in a wide-reaching Monte Carlo simulation.
抗原肽的识别是免疫反应的一个主要事件。在当前的免疫 系统介观尺度模拟器中，这个关键步骤是以非常近似的方式建模的。
我们为基于代理的免疫系统模型配备了免疫信息学方法，以允许模拟抗原识别的主要事件，从单个肽到整个蛋白质组。识别过程通过帕克规模亲和力估计、I 类和 II 类 HLA 肽预测以及基于已知 HLA 表位预测工具信息的基于位置的评分矩阵来预测 B 细胞表位，并通过将残基-残基接触势能的平均值相加来计算 TCR 与 HLA-肽复合物的结合。这些步骤是在广泛的蒙特卡罗模拟中针对遇到抗原的所有淋巴细胞代理执行的。
