Dataset Information

Modeling Sequence-Dependent Peptide Fluctuations in Immunologic Recognition.

ABSTRACT: 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.

SUBMITTER: Ayres CM

PROVIDER: S-EPMC5573614 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Publications

Modeling Sequence-Dependent Peptide Fluctuations in Immunologic Recognition.

Ayres Cory M CM Riley Timothy P TP Corcelli Steven A SA Baker Brian M BM

Journal of chemical information and modeling 20170725 8

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. W ...[more]

PMID: 28696685

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Project description:UnlabelledKiller cell immunoglobulin-like receptors (KIRs) play an important role in the activation of natural killer (NK) cells, which in turn contribute to the effective immune control of many viral infections. In the context of HIV infection, the closely related KIR3DL1 and KIR3DS1 molecules, in particular, have been associated with disease outcome. Inhibitory signals via KIR3DL1 are disrupted by downregulation of HLA class I ligands on the infected cell surface and can also be impacted by changes in the presented peptide repertoire. In contrast, the activatory ligands for KIR3DS1 remain obscure. We used a structure-driven approach to define the characteristics of HLA class I-restricted peptides that interact with KIR3DL1 and KIR3DS1. In the case of HLA-B*57:01, we used this knowledge to identify bona fide HIV-derived peptide epitopes with similar properties. Two such peptides facilitated productive interactions between HLA-B*57:01 and KIR3DS1. These data reveal the presence of KIR3DS1 ligands within the HIV-specific peptide repertoire presented by a protective HLA class I allotype, thereby enhancing our mechanistic understanding of the processes that enable NK cells to impact disease outcome.ImportanceNatural killer (NK) cells are implicated as determinants of immune control in many viral infections, but the precise molecular mechanisms that initiate and control these responses are unclear. The activating receptor KIR3DS1 in combination with HLA-Bw4 has been associated with better outcomes in HIV infection. However, evidence of a direct interaction between these molecules is lacking. In this study, we demonstrate that KIR3DS1 recognition of HLA-Bw4 is peptide dependent. We also identify HIV-derived peptide epitopes presented by the protective HLA-B*57:01 allotype that facilitate productive interactions with KIR3DS1. Collectively, these findings suggest a mechanism whereby changes in the peptide repertoire associated with viral infection provide a trigger for KIR3DS1 engagement and NK cell activation.

Dataset Information

Modeling Sequence-Dependent Peptide Fluctuations in Immunologic Recognition.

Publications

Modeling Sequence-Dependent Peptide Fluctuations in Immunologic Recognition.

Similar Datasets

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