Technical University of Denmark-DTU, Center for Biological Sequence Analysis, Department of Systems Biology, Kemitorvet 208, DK 2800, Kgs. Lyngby, Denmark.
Expert Rev Vaccines. 2012 Jan;11(1):43-54. doi: 10.1586/erv.11.160.
Prediction methods as well as experimental methods for T-cell epitope discovery have developed significantly in recent years. High-throughput experimental methods have made it possible to perform full-length protein scans for epitopes restricted to a limited number of MHC alleles. The high costs and limitations regarding the number of proteins and MHC alleles that are feasibly handled by such experimental methods have made in silico prediction models of high interest. MHC binding prediction methods are today of a very high quality and can predict MHC binding peptides with high accuracy. This is possible for a large range of MHC alleles and relevant length of binding peptides. The predictions can easily be performed for complete proteomes of any size. Prediction methods are still, however, dependent on good experimental methods for validation, and should merely be used as a guide for rational epitope discovery. We expect prediction methods as well as experimental validation methods to continue to develop and that we will soon see clinical trials of products whose development has been guided by prediction methods.
近年来，T 细胞表位发现的预测方法以及实验方法都有了显著的发展。高通量实验方法使得对受限于有限数量 MHC 等位基因的表位进行全长蛋白质扫描成为可能。这种实验方法在处理蛋白质和 MHC 等位基因的数量方面成本高且受到限制，这使得基于计算机的预测模型受到高度关注。MHC 结合预测方法如今具有非常高的质量，可以非常准确地预测 MHC 结合肽。这对于大量 MHC 等位基因和相关长度的结合肽都是可行的。对于任何大小的完整蛋白质组，都可以轻松地进行预测。然而，预测方法仍然依赖于良好的实验方法进行验证，并且仅应作为合理表位发现的指南。我们预计预测方法以及实验验证方法将继续发展，我们将很快看到其开发受到预测方法指导的产品的临床试验。
