Automated generation and evaluation of specific MHC binding predictive tools:: ARB matrix applications
Automated generation and evaluation of specific MHC binding predictive tools:: ARB matrix applications
复制标题
DOI：
10.1007/s00251-005-0798-y
复制
发表时间：
2005-06-01
期刊：
影响因子：
3.2
通讯作者：
Sette, A
中科院分区：
文献类型：
--
作者：
Bui, HH;Sidney, J;Sette, A
预测哪些肽可以结合主要组织相容性复合体（MHC）分子通常用于辅助鉴定T细胞表位。然而，由于大量不同的感兴趣的MHC分子，每个分子与不同的预测工具相关，工具生成和评估可能是一项非常资源密集的任务。通常用于预测MHC结合亲和力的方法是矩阵或线性系数法。在本文中，我们描述了直接预测IC 50值的平均相对结合（ARB）矩阵方法，其允许将涉及不同肽大小和等位基因的搜索组合成单个全局预测。开发了一个计算机程序来自动生成和评估ARB预测工具。使用内部MHC结合数据库，我们分别生成了总共85个和13个MHC I类和II类矩阵。工具效率的自动化评价的结果。我们预计，这种自动化框架将普遍适用于大量的MHC预测方法和工具的生成和评估，并将有价值的集中和合理化的MHC预测的评估过程。基于ARB矩阵的MHC结合预测可在http://www.epitope.liai.org:8080/matrix网络服务器上获得。
Prediction of which peptides can bind major histocompatibility complex (MHC) molecules is commonly used to assist in the identification of T cell epitopes. However, because of the large numbers of different MHC molecules of interest, each associated with different predictive tools, tool generation and evaluation can be a very resource intensive task. A methodology commonly used to predict MHC binding affinity is the matrix or linear coefficients method. Herein, we described Average Relative Binding (ARB) matrix methods that directly predict IC50 values allowing combination of searches involving different peptide sizes and alleles into a single global prediction. A computer program was developed to automate the generation and evaluation of ARB predictive tools. Using an in-house MHC binding database, we generated a total of 85 and 13 MHC class I and class II matrices, respectively. Results from the automated evaluation of tool efficiency are presented. We anticipate that this automation framework will be generally applicable to the generation and evaluation of large numbers of MHC predictive methods and tools, and will be of value to centralize and rationalize the process of evaluation of MHC predictions. MHC binding predictions based on ARB matrices were made available at http://www.epitope.liai.org:8080/matrix web server.