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A general and efficient approach for NMR studies of peptide dynamics in class I MHC peptide binding grooves.

ABSTRACT: T-Cell receptor recognition of peptides bound by major histocompatibility complex (MHC) proteins initiates a cellular immune response. Dynamics of peptides within MHC binding grooves can influence TCR recognition, yet NMR studies which could address this rigorously have been hindered by the expense of isotopically labeled peptides and the large size of peptide-MHC complexes. Here we describe a methodology for characterizing peptide dynamics within MHC binding grooves via NMR, using a biosynthetic approach for producing labeled peptide. With the Tax(11-19) peptide bound to the human class I MHC HLA-A*0201, we demonstrate that peptide generated in this manner can be well characterized in MHC binding grooves by NMR, providing opportunities to more precisely study the role of peptide dynamics in TCR recognition. Demonstrating the utility of such studies, the data with the Tax(11-19) peptide indicate the presence of slow conformational exchange in the peptide, supporting an "induced-fit" style TCR binding mechanism.

SUBMITTER: Insaidoo FK

PROVIDER: S-EPMC2762276 | biostudies-literature | 2009 Oct

REPOSITORIES: biostudies-literature

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A general and efficient approach for NMR studies of peptide dynamics in class I MHC peptide binding grooves.

Insaidoo Francis K FK Zajicek Jaroslav J Baker Brian M BM

Biochemistry 20091001 41

T-Cell receptor recognition of peptides bound by major histocompatibility complex (MHC) proteins initiates a cellular immune response. Dynamics of peptides within MHC binding grooves can influence TCR recognition, yet NMR studies which could address this rigorously have been hindered by the expense of isotopically labeled peptides and the large size of peptide-MHC complexes. Here we describe a methodology for characterizing peptide dynamics within MHC binding grooves via NMR, using a biosyntheti ...[more]

PMID: 19772349

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Project description:Major Histocompatibility Complex (MHC) class I molecules enable cytotoxic T lymphocytes to destroy virus-infected or cancerous cells, thereby preventing disease progression. MHC class I molecules provide a snapshot of the contents of a cell by binding to protein fragments arising from intracellular protein turnover and presenting these fragments at the cell surface. Competing fragments (peptides) are selected for cell-surface presentation on the basis of their ability to form a stable complex with MHC class I, by a process known as peptide optimization. A better understanding of the optimization process is important for our understanding of immunodominance, the predominance of some T lymphocyte specificities over others, which can determine the efficacy of an immune response, the danger of immune evasion, and the success of vaccination strategies. In this paper we present a dynamical systems model of peptide optimization by MHC class I. We incorporate the chaperone molecule tapasin, which has been shown to enhance peptide optimization to different extents for different MHC class I alleles. Using a combination of published and novel experimental data to parameterize the model, we arrive at a relation of peptide filtering, which quantifies peptide optimization as a function of peptide supply and peptide unbinding rates. From this relation, we find that tapasin enhances peptide unbinding to improve peptide optimization without significantly delaying the transit of MHC to the cell surface, and differences in peptide optimization across MHC class I alleles can be explained by allele-specific differences in peptide binding. Importantly, our filtering relation may be used to dynamically predict the cell surface abundance of any number of competing peptides by MHC class I alleles, providing a quantitative basis to investigate viral infection or disease at the cellular level. We exemplify this by simulating optimization of the distribution of peptides derived from Human Immunodeficiency Virus Gag-Pol polyprotein.

Project description:BACKGROUND:MHC class II proteins bind oligopeptide fragments derived from proteolysis of pathogen antigens, presenting them at the cell surface for recognition by CD4+ T cells. Human MHC class II alleles are grouped into three loci: HLA-DP, HLA-DQ and HLA-DR. In contrast to HLA-DR and HLA-DQ, HLA-DP proteins have not been studied extensively, as they have been viewed as less important in immune responses than DRs and DQs. However, it is now known that HLA-DP alleles are associated with many autoimmune diseases. Quite recently, the X-ray structure of the HLA-DP2 molecule (DPA*0103, DPB1*0201) in complex with a self-peptide derived from the HLA-DR ?-chain has been determined. In the present study, we applied a validated molecular docking protocol to a library of 247 modelled peptide-DP2 complexes, seeking to assess the contribution made by each of the 20 naturally occurred amino acids at each of the nine binding core peptide positions and the four flanking residues (two on both sides). RESULTS:The free binding energies (FBEs) derived from the docking experiments were normalized on a position-dependent (npp) and on an overall basis (nap), and two docking score-based quantitative matrices (DS-QMs) were derived: QMnpp and QMnap. They reveal the amino acid preferences at each of the 13 positions considered in the study. Apart from the leading role of anchor positions p1 and p6, the binding to HLA-DP2 depends on the preferences at p2. No effect of the flanking residues was found on the peptide binding predictions to DP2, although all four of them show strong preferences for particular amino acids. The predictive ability of the DS-QMs was tested using a set of 457 known binders to HLA-DP2, originating from 24 proteins. The sensitivities of the predictions at five different thresholds (5%, 10%, 15%, 20% and 25%) were calculated and compared to the predictions made by the NetMHCII and IEDB servers. Analysis of the DS-QMs indicated an improvement in performance. Additionally, DS-QMs identified the binding cores of several known DP2 binders. CONCLUSIONS:The molecular docking protocol, as applied to a combinatorial library of peptides, models the peptide-HLA-DP2 protein interaction effectively, generating reliable predictions in a quantitative assessment. The method is structure-based and does not require extensive experimental sequence-based data. Thus, it is universal and can be applied to model any peptide - protein interaction.

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A general and efficient approach for NMR studies of peptide dynamics in class I MHC peptide binding grooves.

Publications

A general and efficient approach for NMR studies of peptide dynamics in class I MHC peptide binding grooves.

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