Bioinformatics Centre, Indian Institute of Science, Bangalore, India.
BMC Bioinformatics. 2010 Jan 18;11 Suppl 1(Suppl 1):S55. doi: 10.1186/1471-2105-11-S1-S55.
MHC/HLA class II molecules are important components of the immune system and play a critical role in processes such as phagocytosis. Understanding peptide recognition properties of the hundreds of MHC class II alleles is essential to appreciate determinants of antigenicity and ultimately to predict epitopes. While there are several methods for epitope prediction, each differing in their success rates, there are no reports so far in the literature to systematically characterize the binding sites at the structural level and infer recognition profiles from them.
Here we report a new approach to compare the binding sites of MHC class II molecules using their three dimensional structures. We use a specifically tuned version of our recent algorithm, PocketMatch. We show that our methodology is useful for classification of MHC class II molecules based on similarities or differences among their binding sites. A new module has been used to define binding sites in MHC molecules. Comparison of binding sites of 103 MHC molecules, both at the whole groove and individual sub-pocket levels has been carried out, and their clustering patterns analyzed. While clusters largely agree with serotypic classification, deviations from it and several new insights are obtained from our study. We also present how differences in sub-pockets of molecules associated with a pair of autoimmune diseases, narcolepsy and rheumatoid arthritis, were captured by PocketMatch13.
The systematic framework for understanding structural variations in MHC class II molecules enables large scale comparison of binding grooves and sub-pockets, which is likely to have direct implications towards predicting epitopes and understanding peptide binding preferences.
MHC/HLA Ⅱ类分子是免疫系统的重要组成部分，在吞噬等过程中起着关键作用。了解数百种 MHC Ⅱ类等位基因的肽识别特性对于理解抗原性决定因素并最终预测表位至关重要。虽然有几种方法可用于预测表位，但每种方法的成功率都不同，目前文献中尚无系统地从结构水平上描述结合位点并从这些结合位点推断识别特征的报道。
本文报道了一种使用 MHC Ⅱ类分子三维结构比较其结合位点的新方法。我们使用了我们最近的算法 PocketMatch 的专门调整版本。结果表明，我们的方法可用于根据其结合位点的相似性或差异性对 MHC Ⅱ类分子进行分类。我们使用了一个新的模块来定义 MHC 分子中的结合位点。对 103 种 MHC 分子的整个凹槽和各个亚口袋水平的结合位点进行了比较，并对其聚类模式进行了分析。虽然聚类在很大程度上与血清型分类一致，但从我们的研究中还获得了一些偏离和一些新的见解。我们还介绍了 PocketMatch13 如何捕获与两种自身免疫性疾病——嗜睡症和类风湿性关节炎相关的分子亚口袋差异。
理解 MHC Ⅱ类分子结构变化的系统框架使我们能够大规模比较结合凹槽和亚口袋，这可能对预测表位和理解肽结合偏好具有直接意义。
