Integrating Experiment and Theory to Understand TCR-pMHC Dynamics

In silico design of high-affinity antigenic peptides for HLA-B44

Cancer cell-killing by CD8+ T cells demands effective tumor antigen presentation by human leukocyte antigen class I (HLA-I) molecules. Screening and designing highly immunogenic neoantigens require quantitative computations to reliably predict HLA-peptide binding affinities. Here, with all-atom molecular dynamics (MD) simulations and free energy perturbation (FEP) methods, we design a collection of antigenic peptide candidates through in silico mutagenesis studies on immunogenic neoantigens, yielding enhanced binding affinities to HLA-B*44:02. In-depth structural dissection shows that introducing positively charged residues such as arginine to position 6 or lysine to position 7 of the candidates triggers conformational shifts in both peptides and the antigen-binding groove of the HLA, following the "induced-fit" mechanism. Enhancement in binding affinities compared to the wild-type was found in three out of five mutated candidates. The HLA pocket, capable of accommodating positively charged residues in positions from 5 to 7, is designated as the "dynamic pocket". Taken together, we showcase an effective structure-based binding affinity optimization framework for antigenic peptides of HLA-B*44:02 and underscore the importance of dynamic nature of the antigen-binding groove in concert with the anchoring motifs. This work provides structural insights for rational design of favorable HLA-peptide bindings and future developments in neoantigen-based therapeutics.

Peptide-dependent tuning of major histocompatibility complex motional properties and the consequences for cellular immunity

T cell receptors (TCRs) and other receptors of the immune system recognize peptides presented by class I or class II major histocompatibility complex (MHC) proteins. Although we generally distinguish between the MHC protein and its peptide, at an atomic level the two form a structural composite, which allows peptides to influence MHC properties and vice versa. One consequence is the peptide-dependent tuning of MHC structural dynamics, which contributes to protein structural adaptability and influences how receptors identify and bind targets. Peptide-dependent tuning of MHC protein dynamics can impact processes such as antigenicity, TCR cross-reactivity, and T cell repertoire selection. Motional tuning extends beyond the binding groove, influencing peptide selection and exchange, as well as interactions with other immune receptors. Here, we review recent findings showing how peptides can affect the dynamic and adaptable nature of MHC proteins. We highlight consequences for immunity and demonstrate how MHC proteins have evolved to be highly sensitive dynamic reporters, with broad immunological consequences.

A Subject-Tailored Variability-Based Platform for Overcoming the Plateau Effect in Sports Training: A Narrative Review

The plateau effect in training is a significant obstacle for professional athletes and average subjects. It evolves from both the muscle-nerve-axis-associated performance and various cardiorespiratory parameters. Compensatory adaptation mechanisms contribute to a lack of continuous improvement with most exercise regimens. Attempts to overcome this plateau in exercise have been only partially successful, and it remains a significant unmet need in both healthy subjects and those suffering from chronic neuromuscular, cardiopulmonary, and metabolic diseases. Variability patterns characterize many biological processes, from cellular to organ levels. The present review discusses the significant obstacles in overcoming the plateau in training and establishes a platform to implement subject-tailored variability patterns to prevent and overcome this plateau in muscle and cardiorespiratory performance.

Structural Prediction of Peptide-MHC Binding Modes

The immune system is constantly protecting its host from the invasion of pathogens and the development of cancer cells. The specific CD8⁺ T-cell immune response against virus-infected cells and tumor cells is based on the T-cell receptor recognition of antigenic peptides bound to class I major histocompatibility complexes (MHC) at the surface of antigen presenting cells. Consequently, the peptide binding specificities of the highly polymorphic MHC have important implications for the design of vaccines, for the treatment of autoimmune diseases, and for personalized cancer immunotherapy. Evidence-based machine-learning approaches have been successfully used for the prediction of peptide binders and are currently being developed for the prediction of peptide immunogenicity. However, understanding and modeling the structural details of peptide/MHC binding is crucial for a better understanding of the molecular mechanisms triggering the immunological processes, estimating peptide/MHC affinity using universal physics-based approaches, and driving the design of novel peptide ligands. Unfortunately, due to the large diversity of MHC allotypes and possible peptides, the growing number of 3D structures of peptide/MHC (pMHC) complexes in the Protein Data Bank only covers a small fraction of the possibilities. Consequently, there is a growing need for rapid and efficient approaches to predict 3D structures of pMHC complexes. Here, we review the key characteristics of the 3D structure of pMHC complexes before listing databases and other sources of information on pMHC structures and MHC specificities. Finally, we discuss some of the most prominent pMHC docking software.

Improving sampling of crystallographic disorder in ensemble refinement

Ensemble refinement, the application of molecular dynamics to crystallographic refinement, explicitly models the disorder inherent in macromolecular structures. These ensemble models have been shown to produce more accurate structures than traditional single-model structures. However, suboptimal sampling of the molecular-dynamics simulation and modelling of crystallographic disorder has limited the utility of the method, and can lead to unphysical and strained models. Here, two improvements to the ensemble refinement method implemented within Phenix are presented: DEN restraints, which guide the local sampling of conformations and allow a more robust exploration of local conformational landscapes, and ECHT disorder models, which allow the selection of more physically meaningful and effective disorder models for parameterizing the continuous disorder components within a crystal. These improvements lead to more consistent and physically interpretable simulations of macromolecules in crystals, and allow structural heterogeneity and disorder to be systematically explored on different scales. The new approach is demonstrated on several case studies and the SARS-CoV-2 main protease, and demonstrates how the choice of disorder model affects the type of disorder that is sampled by the restrained molecular-dynamics simulation.

A T-Cell Epitope-Based Multi-Epitope Vaccine Designed Using Human HLA Specific T Cell Epitopes Induces a Near-Sterile Immunity against Experimental Visceral Leishmaniasis in Hamsters

Visceral leishmaniasis is a neglected tropical disease affecting 12 million people annually. Even in the second decade of the 21st century, it has remained without an effective vaccine for human use. In the current study, we designed three multiepitope vaccine candidates by the selection of multiple IFN-γ inducing MHC-I and MHC-II binder T-cell specific epitopes from three previously identified antigen genes of Leishmania donovani from our lab by an immuno-informatic approach using IFNepitope, the Immune Epitope Database (IEDB) T cell epitope identification tools, NET-MHC-1, and NET MHC-2 webservers. We tested the protective potential of these three multiepitope proteins as a vaccine in a hamster model of visceral leishmaniasis. The immunization data revealed that the vaccine candidates induced a very high level of Th1 biased protective immune response in-vivo in a hamster model of experimental visceral leishmaniasis, with one of the candidates inducing a near-sterile immunity. The vaccinated animals displayed highly activated monocyte macrophages with the capability of clearing intracellular parasites due to increased respiratory burst. Additionally, these proteins induced activation of polyfunctional T cells secreting INF-γ, TNF-α, and IL-2 in an ex-vivo stimulation of human peripheral blood mononuclear cells, further supporting the protective nature of the designed candidates.

Platform introducing individually tailored variability in nerve stimulations and dietary regimen to prevent weight regain following weight loss in patients with obesity

Prevention of weight regain following successful weight loss is a major challenge in the treatment of obesity, irrespective of the weight reduction method used. The majority of individuals regain the lost weight over time; thus, achieving long-term sustainability in weight loss remains an unresolved issue. A compensatory adaptation to the weight loss methods occurs in several body organs and partly explains the lack of sustainable effect. Variability is inherent in many biological systems, and patterns of variability constitute a body mechanism that is active at several levels, starting from the genes and cellular pathways through to the whole-organ level. This study aimed to describe a platform that introduces individually tailored variability in vagal nerve stimulation and dietary regimen to ensure prolonged and sustainable weight loss and prevent weight regain. The platform is intended to provide a method that can overcome the body's compensatory adaptation mechanisms while ensuring a prolonged beneficial effect.

Second-Generation Digital Health Platforms: Placing the Patient at the Center and Focusing on Clinical Outcomes

Artificial intelligence (AI) digital health systems have drawn much attention over the last decade. However, their implementation into medical practice occurs at a much slower pace than expected. This paper reviews some of the achievements of first-generation AI systems, and the barriers facing their implementation into medical practice. The development of second-generation AI systems is discussed with a focus on overcoming some of these obstacles. Second-generation systems are aimed at focusing on a single subject and on improving patients' clinical outcomes. A personalized closed-loop system designed to improve end-organ function and the patient's response to chronic therapies is presented. The system introduces a platform which implements a personalized therapeutic regimen and introduces quantifiable individualized-variability patterns into its algorithm. The platform is designed to achieve a clinically meaningful endpoint by ensuring that chronic therapies will have sustainable effect while overcoming compensatory mechanisms associated with disease progression and drug resistance. Second-generation systems are expected to assist patients and providers in adopting and implementing of these systems into everyday care.

Establishing patient-tailored variability-based paradigms for anti-cancer therapy: Using the inherent trajectories which underlie cancer for overcoming drug resistance

Drug resistance is a major obstacle for successful therapy of many malignancies and is affecting the loss of response to chemotherapy and immunotherapy. Tumor-related compensatory adaptation mechanisms contribute to the development of drug resistance. Variability is inherent to biological systems and altered patterns of variability are associated with disease conditions. The marked intra and inter patient tumor heterogeneity, and the diverse mechanism contributing to drug resistance in different subjects, which may change over time even in the same patient, necessitate the development of personalized dynamic approaches for overcoming drug resistance. Altered dosing regimens, the potential role of chronotherapy, and drug holidays are effective in cancer therapy and immunotherapy. In the present review we describe the difficulty of overcoming drug resistance in a dynamic system and present the use of the inherent trajectories which underlie cancer development for building therapeutic regimens which can overcome resistance. The establishment of a platform wherein patient-tailored variability signatures are used for overcoming resistance for ensuing long term sustainable improved responses is presented.

Peptide-MHC Binding Reveals Conserved Allosteric Sites in MHC Class I- and Class II-Restricted T Cell Receptors (TCRs)

T cells are vital for adaptive immune responses that protect against pathogens and cancers. The T cell receptor (TCR)-CD3 complex comprises a diverse αβ TCR heterodimer in noncovalent association with three invariant CD3 dimers. The TCR is responsible for recognizing antigenic peptides bound to MHC molecules (pMHC), while the CD3 dimers relay activation signals to the T cell. However, the mechanisms by which TCR engagement by pMHC is transmitted to CD3 remain mysterious, although there is growing evidence that mechanosensing and allostery both play a role. Here, we carried out NMR analysis of a human autoimmune TCR (MS2-3C8) that recognizes a self-peptide from myelin basic protein presented by the MHC class II molecule HLA-DR4. We observed pMHC-induced NMR signal perturbations in MS2-3C8 that indicate long-range effects on TCR β chain conformation and dynamics. Our results demonstrate that, in addition to expected changes in the NMR resonances of pMHC-contacting residues, perturbations extend to the Vβ/Vα, Vβ/Cβ, and Cβ/Cα interfacial regions. Moreover, the pattern of long-range perturbations is similar to that detected previously in the β chains of two MHC class I-restricted TCRs, thereby revealing a common allosteric pathway among three unrelated TCRs. Molecular dynamics (MD) simulations predict similar pMHC-induced effects. Taken together, our results demonstrate that pMHC binding induces long-range allosteric changes in the TCR β chain at conserved sites in both representative MHC class I- and class II-restricted TCRs, and that these sites may play a role in the transmission of signaling information.

Impact of HLA-DR Antigen Binding Cleft Rigidity on T Cell Recognition

The interaction between T cell receptor (TCR) and peptide (p)-Human Leukocyte Antigen (HLA) complexes is the critical first step in determining T cell responses. X-ray crystallographic studies of pHLA in TCR-bound and free states provide a structural perspective that can help understand T cell activation. These structures represent a static “snapshot”, yet the nature of pHLAs and their interactions with TCRs are highly dynamic. This has been demonstrated for HLA class I molecules with in silico techniques showing that some interactions, thought to stabilise pHLA-I, are only transient and prone to high flexibility. Here, we investigated the dynamics of HLA class II molecules by focusing on three allomorphs (HLA-DR1, -DR11 and -DR15) that are able to present the same epitope and activate CD4+ T cells. A single TCR (F24) has been shown to recognise all three HLA-DR molecules, albeit with different affinities. Using molecular dynamics and crystallographic ensemble refinement, we investigate the molecular basis of these different affinities and uncover hidden roles for HLA polymorphic residues. These polymorphisms were responsible for the widening of the antigen binding cleft and disruption of pHLA-TCR interactions, underpinning the hierarchy of F24 TCR binding affinity, and ultimately T cell activation. We expanded this approach to all available pHLA-DR structures and discovered that all HLA-DR molecules were inherently rigid. Together with in vitro protein stability and peptide affinity measurements, our results suggest that HLA-DR1 possesses inherently high protein stability, and low HLA-DM susceptibility.

Order Through Disorder: The Characteristic Variability of Systems

Randomness characterizes many processes in nature, and therefore its importance cannot be overstated. In the present study, we investigate examples of randomness found in various fields, to underlie its fundamental processes. The fields we address include physics, chemistry, biology (biological systems from genes to whole organs), medicine, and environmental science. Through the chosen examples, we explore the seemingly paradoxical nature of life and demonstrate that randomness is preferred under specific conditions. Furthermore, under certain conditions, promoting or making use of variability-associated parameters may be necessary for improving the function of processes and systems.

Conformational Plasticity of HLA-B27 Molecules Correlates Inversely With Efficiency of Negative T Cell Selection

The development of autoimmune disorders is incompletely understood. Inefficient thymic T cell selection against self-peptides presented by major histocompatibility antigens (HLA in humans) may contribute to the emergence of auto-reactive effector cells, and molecular mimicry between foreign and self-peptides could promote T cell cross-reactivity. A pair of class I subtypes, HLA-B2705 and HLA-B2709, have previously been intensely studied, because they are distinguished from each other only by a single amino acid exchange at the floor of the peptide-binding groove, yet are differentially associated with the autoinflammatory disorder ankylosing spondylitis. Using X-ray crystallography in combination with ensemble refinement, we find that the non-disease-associated subtype HLA-B2709, when presenting the self-peptide pGR (RRRWHRWRL), exhibits elevated conformational dynamics, and the complex can also be recognized by T cells. Both features are not observed in case of the sequence-related self-peptide pVIPR (RRKWRRWHL) in complex with this subtype, and T cell cross-reactivity between pGR, pVIPR, and the viral peptide pLMP2 (RRRWRRLTV) is only rarely observed. The disease-associated subtype HLA-B2705, however, exhibits extensive conformational flexibility in case of the three complexes, all of which are also recognized by frequently occurring cross-reactive T cells. A comparison of the structural and dynamic properties of the six HLA-B27 complexes, together with their individual ability to interact with T cells, permits us to correlate the flexibility of HLA-B27 complexes with effector cell reactivity. The results suggest the existence of an inverse relationship between conformational plasticity of peptide-HLA-B27 complexes and the efficiency of negative selection of self-reactive cells within the thymus.

The structural basis of T-cell receptor (TCR) activation: An enduring enigma

T cells are critical for protective immune responses to pathogens and tumors. The T-cell receptor (TCR)-CD3 complex is composed of a diverse αβ TCR heterodimer noncovalently associated with the invariant CD3 dimers CD3ϵγ, CD3ϵδ, and CD3ζζ. The TCR mediates recognition of antigenic peptides bound to MHC molecules (pMHC), whereas the CD3 molecules transduce activation signals to the T cell. Whereas much is known about downstream T-cell signaling pathways, the mechanism whereby TCR engagement by pMHC is first communicated to the CD3 signaling apparatus, a process termed early T-cell activation, remains largely a mystery. In this review, we examine the molecular basis for TCR activation in light of the recently determined cryoEM structure of a complete TCR-CD3 complex. This structure provides an unprecedented opportunity to assess various signaling models that have been proposed for the TCR. We review evidence from single-molecule and structural studies for force-induced conformational changes in the TCR-CD3 complex, for dynamically-driven TCR allostery, and for pMHC-induced structural changes in the transmembrane and cytoplasmic regions of CD3 subunits. We identify major knowledge gaps that must be filled in order to arrive at a comprehensive model of TCR activation that explains, at the molecular level, how pMHC-specific information is transmitted across the T-cell membrane to initiate intracellular signaling. An in-depth understanding of this process will accelerate the rational design of immunotherapeutic agents targeting the TCR-CD3 complex.

Introducing Patterns of Variability for Overcoming Compensatory Adaptation of the Immune System to Immunomodulatory Agents: A Novel Method for Improving Clinical Response to Anti-TNF Therapies

Primary lack of response and secondary loss of response (LOR) are major obstacles to the use of anti–tumor necrosis factor (TNF)-based therapies in patients with rheumatoid arthritis or inflammatory bowel disease. Here, we review the mechanisms and methods for predicting LOR and the currently used methods for overcoming the ineffectiveness of anti-TNFs. The complex functions of TNF and anti-TNF antibodies, which can promote both pro- or anti-inflammatory actions, and the factors that affect the induction of immune tolerance to their effects are presented. The lack of rules and the continuous dynamics of the immune processes partly underlie the unpredictability of the response to anti-TNFs. Variability is inherent to biological systems, including immune processes, and intra/inter-patient variability has been described in the response to drugs. This variability is viewed as a compensatory adaptation mechanism of the immune system in response to drugs and may contribute to treatment LOR. Dose reductions and drug holidays have been tested in patients treated with anti-TNFs. Regular dose-based regimens may be incompatible with physiological variability, further contributing to treatment inefficacy. We present the concept of overcoming immune system adaptation to anti-TNFs by introducing patient-tailored patterns of variability to treatment regimens.

The Role of Conformational Dynamics in Abacavir-Induced Hypersensitivity Syndrome

Abacavir is an antiretroviral drug used to reduce human immunodeficiency virus (HIV) replication and decrease the risk of developing acquired immune deficiency syndrome (AIDS). However, its therapeutic value is diminished by the fact that it is associated with drug hypersensitivity reactions in up to 8% of treated patients. This hypersensitivity is strongly associated with patients carrying human leukocyte antigen (HLA)-B*57:01, but not patients carrying closely related alleles. Abacavir’s specificity to HLA-B*57:01 is attributed to its binding site within the peptide-binding cleft and subsequent influence of the repertoire of peptides that can bind HLA-B*57:01. To further our understanding of abacavir-induced hypersensitivity we used molecular dynamics (MD) to analyze the dynamics of three different peptides bound to HLA-B*57:01 in the presence and absence of abacavir or abacavir analogues. We found that abacavir and associated peptides bind to HLA-B*57:01 in a highly diverse range of conformations that are not apparent from static crystallographic snapshots, but observed no difference in either the conformations, nor degree of flexibility when compared to abacavir-unbound systems. Our results support hypersensitivity models in which abacavir-binding alters the conformational ensemble of neopeptides, so as to favour exposed peptide surfaces that are no longer recognized as self by circulating CD8+ T cells, and are conducive to TCR binding. Our findings highlight the need to also consider the role of dynamics in understanding drug-induced hypersensitivities at the molecular and mechanistic level. This additional insight can help inform the chemical modification of abacavir to prevent hypersensitivity reactions in HLA-B*57:01+ HIV patients whilst retaining potent antiretroviral activity.

Is TCR/pMHC Affinity a Good Estimate of the T-cell Response? An Answer Based on Predictions From 12 Phenotypic Models

On the T-cell surface the TCR is the only molecule that senses antigen, and the engagement of TCR with its specific antigenic peptide (agonist)/MHC complex (pMHC) is determined by the biochemical parameters of the TCR-pMHC interaction. This interaction is the keystone of the adaptive immune response by triggering intracellular signaling pathways that induce the expression of genes required for T cell-mediated effector functions, such as T cell proliferation, cytokine secretion and cytotoxicity. To study the TCR-pMHC interaction one of its properties most extensively analyzed has been TCR-pMHC affinity. However, and despite of intensive experimental research, the results obtained are far from conclusive. Here, to determine if TCR-pMHC affinity is a reliable parameter to characterize T-cell responses, a systematic study has been performed based on the predictions of 12 phenotypic models. This approach has the advantage that allow us to study the response of a given system as a function of only those parameters in which we are interested while other system parameters remain constant. A little surprising, only the simple occupancy model predicts a direct relationship between affinity and response so that an increase in affinity always leads to larger responses. Conversely, in the others more elaborate models this clear situation does not occur, i.e., that a general positive correlation between affinity and immune response does not exist. This is mainly because affinity values are given by the quotient k _on/k _off where k _on and k _off are the rate constants of the binding process (i.e., affinity is in fact the quotient of two parameters), so that different sets of these rate constants can give the same value of affinity. However, except in the occupancy model, the predicted T-cell responses depend on the individual values of k _on and k _off rather than on their quotient k _on/k _off. This allows: a) that systems with the same affinity can show quite different responses; and b) that systems with low affinity may exhibit larger responses than systems with higher affinities. This would make affinity a poor estimate of T-cell responses and, as a result, data correlations between affinity and immune response should be interpreted and used with caution.