Exploration of the Conformational Dynamics of Major Histocompatibility Complex Molecules

Crystal structures of MHC class I complexes reveal the elusive intermediate conformations explored during peptide editing

Studies have suggested that MHC class I (MHC I) molecules fluctuate rapidly between numerous conformational states and these motions support peptide sampling. To date, MHC I intermediates are largely uncharacterized experimentally and remain elusive. Here, we present x-ray crystal structures of HLA-B8 loaded with 20mer peptides that show pronounced distortions at the N-terminus of the groove. Long stretches of N-terminal amino acid residues are missing in the electron density maps creating an open-ended groove. Our structures also reveal highly unusual features in MHC I-peptide interaction at the N-terminus of the groove. Molecular dynamics simulations indicate that the complexes have varying degrees of conformational flexibility in a manner consistent with the structures. We suggest that our structures have captured the remarkable molecular dynamics of MHC I-peptide interaction. The visualization of peptide-dependent conformational motions in MHC I is a major step forward in our conceptual understanding of dynamics in high-affinity peptide selection.

Venus flytrap or pas de trois? The dynamics of MHC class I molecules

The peptide binding site of major histocompatibility complex (MHC) class I molecules is natively unfolded when devoid of peptides. Peptide binding stabilizes the structure and slows the dynamics, but peptide-specific and subtype-specific motions influence, and are influenced by, interaction with assembly chaperones, the T cell receptor, and other class I-binding proteins. The molecular mechanisms of cooperation between peptide, class I heavy chain, and beta-2 microglobulin are insufficiently known but are being elucidated by nuclear magnetic resonance and other modern methods. It appears that micropolymorphic clusters of charged amino acids, often hidden in the molecule interior, determine the dynamics and thus chaperone dependence, cellular fate, and disease association of class I.

Markov state modeling reveals alternative unbinding pathways for peptide-MHC complexes

Peptide binding to major histocompatibility complexes (MHCs) is a central component of the immune system, and understanding the mechanism behind stable peptide-MHC binding will aid the development of immunotherapies. While MHC binding is mostly influenced by the identity of the so-called anchor positions of the peptide, secondary interactions from nonanchor positions are known to play a role in complex stability. However, current MHC-binding prediction methods lack an analysis of the major conformational states and might underestimate the impact of secondary interactions. In this work, we present an atomically detailed analysis of peptide-MHC binding that can reveal the contributions of any interaction toward stability. We propose a simulation framework that uses both umbrella sampling and adaptive sampling to generate a Markov state model (MSM) for a coronavirus-derived peptide (QFKDNVILL), bound to one of the most prevalent MHC receptors in humans (HLA-A24:02). While our model reaffirms the importance of the anchor positions of the peptide in establishing stable interactions, our model also reveals the underestimated importance of position 4 (p4), a nonanchor position. We confirmed our results by simulating the impact of specific peptide mutations and validated these predictions through competitive binding assays. By comparing the MSM of the wild-type system with those of the D4A and D4P mutations, our modeling reveals stark differences in unbinding pathways. The analysis presented here can be applied to any peptide-MHC complex of interest with a structural model as input, representing an important step toward comprehensive modeling of the MHC class I pathway.

Computational investigation of peptide binding stabilities of HLA-B*27 and HLA-B*44 alleles

Major Histocompatibility Complex (MHC) is a cell surface glycoprotein that binds to foreign antigens and presents them to T lymphocyte cells on the surface of Antigen Presenting Cells (APCs) for appropriate immune recognition. Recently, studies focusing on peptide-based vaccine design have allowed a better understanding of peptide immunogenicity mechanisms, which is defined as the ability of a peptide to stimulate CTL-mediated immune response. Peptide immunogenicity is also known to be related to the stability of peptide-loaded MHC (pMHC) complex. In this study, ENCoM server was used for structure-based estimation of the impact of single point mutations on pMHC complex stabilities. For this purpose, two human MHC molecules from the HLA-B*27 group (HLA-B*27:05 and HLA-B*27:09) in complex with four different peptides (GRFAAAIAK, RRKWRRWHL, RRRWRRLTV and IRAAPPPLF) and three HLA-B*44 molecules (HLA-B*44:02, HLA-B*44:03 and HLA-B*44:05) in complex with two different peptides (EEYLQAFTY and EEYLKAWTF) were analyzed. We found that the stability of pMHC complexes is dependent on both peptide sequence and MHC allele. Furthermore, we demonstrate that allele-specific peptide-binding preferences can be accurately revealed using structure-based computational methods predicting the effect of mutations on protein stability.

Dynamically Driven Allostery in MHC Proteins: Peptide-Dependent Tuning of Class I MHC Global Flexibility

T cell receptor (TCR) recognition of antigenic peptides bound and presented by class I major histocompatibility complex (MHC) proteins underlies the cytotoxic immune response to diseased cells. Crystallographic structures of TCR-peptide/MHC complexes have demonstrated how TCRs simultaneously interact with both the peptide and the MHC protein. However, it is increasingly recognized that, beyond serving as a static platform for peptide presentation, the physical properties of class I MHC proteins are tuned by different peptides in ways that are not always structurally visible. These include MHC protein motions, or dynamics, which are believed to influence interactions with a variety of MHC-binding proteins, including not only TCRs, but other activating and inhibitory receptors as well as components of the peptide loading machinery. Here, we investigated the mechanisms by which peptides tune the dynamics of the common class I MHC protein HLA-A2. By examining more than 50 lengthy molecular dynamics simulations of HLA-A2 presenting different peptides, we identified regions susceptible to dynamic tuning, including regions in the peptide binding domain as well as the distal α3 domain. Further analyses of the simulations illuminated mechanisms by which the influences of different peptides are communicated throughout the protein, and involve regions of the peptide binding groove, the β₂-microglobulin subunit, and the α3 domain. Overall, our results demonstrate that the class I MHC protein is a highly tunable peptide sensor whose physical properties vary considerably with bound peptide. Our data provides insight into the underlying principles and suggest a role for dynamically driven allostery in the immunological function of MHC proteins.

Integrating Experiment and Theory to Understand TCR-pMHC Dynamics

The conformational dynamism of proteins is well established. Rather than having a single structure, proteins are more accurately described as a conformational ensemble that exists across a rugged energy landscape, where different conformational sub-states interconvert. The interaction between αβ T cell receptors (TCR) and cognate peptide-MHC (pMHC) is no exception, and is a dynamic process that involves substantial conformational change. This review focuses on technological advances that have begun to establish the role of conformational dynamics and dynamic allostery in TCR recognition of the pMHC and the early stages of signaling. We discuss how the marriage of molecular dynamics (MD) simulations with experimental techniques provides us with new ways to dissect and interpret the process of TCR ligation. Notably, application of simulation techniques lags behind other fields, but is predicted to make substantial contributions. Finally, we highlight integrated approaches that are being used to shed light on some of the key outstanding questions in the early events leading to TCR signaling.

Previously Hidden Dynamics at the TCR-Peptide-MHC Interface Revealed

A structural characterization of the interaction between αβ TCRs and cognate peptide-MHC (pMHC) is central to understanding adaptive T cell-mediated immunity. X-ray crystallography, although the source of much structural data, traditionally provides only a static snapshot of the protein. Given the emerging evidence for the important role of conformational dynamics in protein function, we interrogated 309 crystallographic structures of pMHC complexes using ensemble refinement, a technique that can extract dynamic information from the x-ray data. Focusing on a subset of human pMHC class I systems, we found that in many cases, ensemble methods were able to uncover previously hidden evidence of significant conformational plasticity, thereby revealing additional information that can build upon and significantly enhance functional interpretations that are based on a single static structure. Notable examples include the interpretation of differences in the disease association of HLA subtypes, the relationship between peptide prominence and TCR recognition, the role of conformational flexibility in vaccine design, and the discrimination between induced fit and conformational selection models of TCR binding. We show that the currently widespread practice of analyzing pMHC interactions via the study of a single crystallographic structure does not make use of pertinent and easily accessible information from x-ray data concerning alternative protein conformations. This new analysis therefore not only highlights the capacity for ensemble methods to significantly enrich the interpretation of decades of structural data but also provides previously missing information concerning the dynamics of existing characterized TCR-pMHC interactions.

General Prediction of Peptide-MHC Binding Modes Using Incremental Docking: A Proof of Concept

The class I major histocompatibility complex (MHC) is capable of binding peptides derived from intracellular proteins and displaying them at the cell surface. The recognition of these peptide-MHC (pMHC) complexes by T-cells is the cornerstone of cellular immunity, enabling the elimination of infected or tumoral cells. T-cell-based immunotherapies against cancer, which leverage this mechanism, can greatly benefit from structural analyses of pMHC complexes. Several attempts have been made to use molecular docking for such analyses, but pMHC structure remains too challenging for even state-of-the-art docking tools. To overcome these limitations, we describe the use of an incremental meta-docking approach for structural prediction of pMHC complexes. Previous methods applied in this context used specific constraints to reduce the complexity of this prediction problem, at the expense of generality. Our strategy makes no assumption and can potentially be used to predict binding modes for any pMHC complex. Our method has been tested in a re-docking experiment, reproducing the binding modes of 25 pMHC complexes whose crystal structures are available. This study is a proof of concept that incremental docking strategies can lead to general geometry prediction of pMHC complexes, with potential applications for immunotherapy against cancer or infectious diseases.