Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
Proc Natl Acad Sci U S A. 2011 Apr 26;108(17):6981-6. doi: 10.1073/pnas.1018165108. Epub 2011 Apr 8.
Class I major histocompatibility complex proteins play a critical role in the adaptive immune system by binding to peptides derived from cytosolic proteins and presenting them on the cell surface for surveillance by T cells. The varied peptide binding specificity of these highly polymorphic molecules has important consequences for vaccine design, transplantation, autoimmunity, and cancer development. Here, we describe a molecular modeling study of MHC-peptide interactions that integrates sampling techniques from protein-protein docking, loop modeling, de novo structure prediction, and protein design in order to construct atomically detailed peptide binding landscapes for a diverse set of MHC proteins. Specificity profiles derived from these landscapes recover key features of experimental binding profiles and can be used to predict peptide binding with reasonable accuracy. Family wide comparison of the predicted binding landscapes recapitulates previously reported patterns of specificity divergence and peptide-repertoire diversity while providing a structural basis for observed specificity patterns. The size and sequence diversity of these structure-based binding landscapes enable us to identify subtle patterns of covariation between peptide sequence positions; analysis of the associated structural models suggests physical interactions that may mediate these sequence correlations.
I 类主要组织相容性复合体蛋白通过与来自胞质蛋白的肽结合，并将其呈现在细胞表面以供 T 细胞监测，在适应性免疫系统中发挥着关键作用。这些高度多态性分子的多样化肽结合特异性对疫苗设计、移植、自身免疫和癌症发展具有重要意义。在这里，我们描述了一项 MHC-肽相互作用的分子建模研究，该研究整合了来自蛋白质-蛋白质对接、环建模、从头结构预测和蛋白质设计的采样技术，以便为多样化的 MHC 蛋白质构建原子细节的肽结合景观。从这些景观中得出的特异性谱可以恢复实验结合谱的关键特征，并可用于合理准确地预测肽结合。对预测的结合景观进行全家族比较，再现了先前报道的特异性分化和肽库多样性模式，同时为观察到的特异性模式提供了结构基础。这些基于结构的结合景观的大小和序列多样性使我们能够识别肽序列位置之间的细微共变模式;对相关结构模型的分析表明，可能介导这些序列相关性的物理相互作用。
