Ayres Cory M, Riley Timothy P, Corcelli Steven A, Baker Brian M
Department of Chemistry and Biochemistry, University of Notre Dame , Notre Dame, Indiana 46556, United States.
J Chem Inf Model. 2017 Aug 28;57(8):1990-1998. doi: 10.1021/acs.jcim.7b00118. Epub 2017 Jul 25.
In cellular immunity, T cells recognize peptide antigens bound and presented by major histocompatibility complex (MHC) proteins. The motions of peptides bound to MHC proteins play a significant role in determining immunogenicity. However, existing approaches for investigating peptide/MHC motional dynamics are challenging or of low throughput, hindering the development of algorithms for predicting immunogenicity from large databases, such as those of tumor or genetically unstable viral genomes. We addressed this by performing extensive molecular dynamics simulations on a large structural database of peptides bound to the most commonly expressed human class-I MHC protein, HLA-A*0201. The simulations reproduced experimental indicators of motion and were used to generate simple models for predicting site-specific, rapid motions of bound peptides through differences in their sequence and chemical composition alone. The models can easily be applied on their own or incorporated into immunogenicity prediction algorithms. Beyond their predictive power, the models provide insight into how amino acid substitutions can influence peptide and protein motions and how dynamic information is communicated across peptides. They also indicate a link between peptide rigidity and hydrophobicity, two features known to be important in influencing cellular immune responses.
在细胞免疫中，T细胞识别由主要组织相容性复合体（MHC）蛋白结合并呈递的肽抗原。与MHC蛋白结合的肽的运动在决定免疫原性方面起着重要作用。然而，现有的研究肽/MHC运动动力学的方法具有挑战性或通量较低，这阻碍了从大型数据库（如肿瘤或基因不稳定病毒基因组数据库）预测免疫原性的算法的发展。我们通过对与最常见表达的人类I类MHC蛋白HLA-A*0201结合的肽的大型结构数据库进行广泛的分子动力学模拟来解决这个问题。这些模拟重现了运动的实验指标，并用于生成简单模型，仅通过结合肽的序列和化学组成差异来预测其位点特异性快速运动。这些模型可以很容易地单独应用，也可以纳入免疫原性预测算法中。除了具有预测能力外，这些模型还深入了解了氨基酸取代如何影响肽和蛋白质的运动，以及动态信息如何在肽之间传递。它们还表明了肽的刚性和疏水性之间的联系，这两个特征在影响细胞免疫反应中已知是重要的。
