The new W family reconstructs the evolution of MHC genes

Dichotomy in TCR V-domain dynamics binding the opposed inclined planes of pMHC-II and pMHC-I α-helices

Ligand recognition by the human α/β T-cell antigen receptor (TCR) heterodimer protein, unlike the surface immunoglobulin (sIg) B-cell receptor, is not governed by relative binding affinity. Its interaction with the peptide (p) plus major histocompatibility complex (MHC) protein (abbrev. pMHC) likely involves some different molecular mechanism linking pMHC binding to T-cell functions. Recent analytical geometry of TCR:pMHC-II solved crystallographic structures (n = 40) revealed that each variable (V)-domain is bound in similar, yet mathematically unique orientations to its target pMHC groove. The relative position of the central cysteine of each V-domain was examined by multivariable calculus in spherical coordinates, where a simple volume element (dV) was found to describe clonotypic geometry with pMHC-II. Here, the study was expanded to include TCR:pMHC-I structures, and to model a physical mechanism, specifically involving the two directionally opposed inclined planes (IP) manifest by the two major α-helices prominent in both MHC-I and MHC-II proteins. Calculations for rotational torque of each V-domain, together with acceleration up and down the slopes of both MHC α-helices were used to estimate the time a given V-domain spends sliding down its cognate MHC IP. This V-domain rotation/sliding mechanism appears to be quantitatively unique for each TCR:pMHC V-domain (n = 40). However, there is an apparent and common dichotomy between the mobility of each V-domain with respect to the two classes of MHC proteins. Evolutionary motifs in the MHC helices support that the V-domains negotiate the opposed inclined planes of pMHC ligands in clonotypic fashion. Thus, this model is useful in understanding how mechanical forces are linked to TCR function.

Some thoughts about what non-mammalian jawed vertebrates are telling us about antigen processing and peptide loading of MHC molecules

The major histocompatibility complex (MHC) of mammals encodes highly polymorphic classical class I and class II molecules with crucial roles in immune responses, as well as various nonclassical molecules encoded by the MHC and elsewhere in the genome that have a variety of functions. These MHC molecules are supported by antigen processing and peptide loading pathways which are well-understood in mammals. This review considers what has been learned about the MHC, MHC molecules and the supporting pathways in non-mammalian jawed vertebrates. From the initial understanding from work with the chicken MHC, a great deal of diversity in the structure and function has been found. Are there underlying principles?

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The genomic organisation of the MHC varies enormously across jawed vertebrates.

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Total numbers of MHC genes vary among vertebrates, with only a few classical MHC genes.

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Some nonclassical MHC and classical pathway genes appear earlier than others.

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Obvious co-evolution within MHC pathways occurs in some species, but not others.

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The promiscuity of interactions may correlate with differences in genomic organisation.

Immunogenomics of Killer Cell Immunoglobulin-Like Receptor (KIR) and HLA Class I: Coevolution and Consequences for Human Health

Interactions of killer cell immunoglobin-like receptors (KIR) with human leukocyte antigens (HLA) class I regulate effector functions of key cytotoxic cells of innate and adaptive immunity. The extreme diversity of this interaction is genetically determined, having evolved in the ever-changing environment of pathogen exposure. Diversity of KIR and HLA genes is further facilitated by their independent segregation on separate chromosomes. That fetal implantation relies on many of the same types of immune cells as infection control places certain constraints on the evolution of KIR interactions with HLA. Consequently, specific inherited combinations of receptors and ligands may predispose to specific immune-mediated diseases, including autoimmunity. Combinatorial diversity of KIR and HLA class I can also differentiate success rates of immunotherapy directed to these diseases. Progress toward both etiopathology and predicting response to therapy is being achieved through detailed characterization of the extent and consequences of the combinatorial diversity of KIR and HLA. Achieving these goals is more tractable with the development of integrated analyses of molecular evolution, function, and pathology that will establish guidelines for understanding and managing risks. Here, we present what is known about the coevolution of KIR with HLA class I and the impact of their complexity on immune function and homeostasis.

PANDORA: A Fast, Anchor-Restrained Modelling Protocol for Peptide: MHC Complexes

Deeper understanding of T-cell-mediated adaptive immune responses is important for the design of cancer immunotherapies and antiviral vaccines against pandemic outbreaks. T-cells are activated when they recognize foreign peptides that are presented on the cell surface by Major Histocompatibility Complexes (MHC), forming peptide:MHC (pMHC) complexes. 3D structures of pMHC complexes provide fundamental insight into T-cell recognition mechanism and aids immunotherapy design. High MHC and peptide diversities necessitate efficient computational modelling to enable whole proteome structural analysis. We developed PANDORA, a generic modelling pipeline for pMHC class I and II (pMHC-I and pMHC-II), and present its performance on pMHC-I here. Given a query, PANDORA searches for structural templates in its extensive database and then applies anchor restraints to the modelling process. This restrained energy minimization ensures one of the fastest pMHC modelling pipelines so far. On a set of 835 pMHC-I complexes over 78 MHC types, PANDORA generated models with a median RMSD of 0.70 Å and achieved a 93% success rate in top 10 models. PANDORA performs competitively with three pMHC-I modelling state-of-the-art approaches and outperforms AlphaFold2 in terms of accuracy while being superior to it in speed. PANDORA is a modularized and user-configurable python package with easy installation. We envision PANDORA to fuel deep learning algorithms with large-scale high-quality 3D models to tackle long-standing immunology challenges.