Structural analysis of the adenovirus type 2 E3/19K protein using mutagenesis and a panel of conformation-sensitive monoclonal antibodies

The E3/19K protein of human adenovirus type 2 (Ad2) was the first viral protein shown to interfere with antigen presentation. This 25 kDa transmembrane glycoprotein binds to major histocompatibility complex (MHC) class I molecules in the endoplasmic reticulum (ER), thereby preventing transport of newly synthesized peptide–MHC complexes to the cell surface and consequently T cell recognition. Recent data suggest that E3/19K also sequesters MHC class I like ligands intracellularly to suppress natural killer (NK) cell recognition. While the mechanism of ER retention is well understood, the structure of E3/19K remains elusive. To further dissect the structural and antigenic topography of E3/19K we carried out site-directed mutagenesis and raised monoclonal antibodies (mAbs) against a recombinant version of Ad2 E3/19K comprising the lumenal domain followed by a C-terminal histidine tag. Using peptide scanning, the epitopes of three mAbs were mapped to different regions of the lumenal domain, comprising amino acids 3–13, 15–21 and 41–45, respectively. Interestingly, mAb 3F4 reacted only weakly with wild-type E3/19K, but showed drastically increased binding to mutant E3/19K molecules, e.g. those with disrupted disulfide bonds, suggesting that 3F4 can sense unfolding of the protein. MAb 10A2 binds to an epitope apparently buried within E3/19K while that of 3A9 is exposed. Secondary structure prediction suggests that the lumenal domain contains six β-strands and an α-helix adjacent to the transmembrane domain. Interestingly, all mAbs bind to non-structured loops. Using a large panel of E3/19K mutants the structural alterations of the mutations were determined. With this knowledge the panel of mAbs will be valuable tools to further dissect structure/function relationships of E3/19K regarding down regulation of MHC class I and MHC class I like molecules and its effect on both T cell and NK cell recognition

Potential interaction between presenilin and metacaspase on the Mechanism of Programed Cell Death in Leishmania infantum.

Proteases have been considered as promising targets for anti-parasitic agents, these enzymes occur in all organisms from prokaryotes to eukaryotes to viruses. The aim of the present study was to provide, through bioinformatics techniques, potential promising targets related to the apoptosis mechanism, in order to develop a vaccine and new anti-parasitic drugs.For the identifying of the hydrophobic regions, the Kyte and Doolittle methodology was utilized. The nine hydrophobic regions identified in the presenilin, based on the physicochemical properties, suggested the occurrence of transmembrane regions that were confirmed as helices scattered in the membrane by THMM. In the metacaspase structure of L. chagasi, besides the occurrence of four hydrophobic regions, the THMM analyses predicted just one helix, placed in the N-terminal portion. The analyzes of hydrophilicity through B-EpiPred Server, indicated the occurrence of several residues localized in external regions, showing that both molecules have significant numbers of fragments with high antigenic propensity. The prediction of epitopes on the tertiary structure was obtained by the I-TASSER server.In the present paper we are suggesting potential availability of a hybrid peptide originated from the presenilin and metacaspase of the Leishmania for the developing of new drugs or vaccine

Efficient processing of an antigenic sequence for presentation by MHC class I molecules depends on its neighboring residues in the protein

Processing of endogenously synthesized proteins generates short peptides that are presented by MHC class I molecules to CD8 T lymphocytes. Here it is documented that not only the sequence of the presented peptide but also the residues by which it is flanked in the protein determine the efficiency of processing and presentation. This became evident when a viral sequence of proven antigenicity was inserted at different positions into an unrelated carrier protein. Not different peptides, but different amounts of the antigenic insert itself were retrieved by isolation of naturally processed peptides from cells expressing the different chimeric proteins. Low yield of antigenic peptide from an unfavorable integration site could be overcome by flanking the insert with oligo-alanine to space it from disruptive neighboring sequences. Notably, the degree of protection against lethal virus disease related directly to the amount of naturally processed antigenic peptide

Peptide Binding Classification on Quantum Computers

We conduct an extensive study on using near-term quantum computers for a task in the domain of computational biology. By constructing quantum models based on parameterised quantum circuits we perform sequence classification on a task relevant to the design of therapeutic proteins, and find competitive performance with classical baselines of similar scale. To study the effect of noise, we run some of the best-performing quantum models with favourable resource requirements on emulators of state-of-the-art noisy quantum processors. We then apply error mitigation methods to improve the signal. We further execute these quantum models on the Quantinuum H1-1 trapped-ion quantum processor and observe very close agreement with noiseless exact simulation. Finally, we perform feature attribution methods and find that the quantum models indeed identify sensible relationships, at least as well as the classical baselines. This work constitutes the first proof-of-concept application of near-term quantum computing to a task critical to the design of therapeutic proteins, opening the route toward larger-scale applications in this and related fields, in line with the hardware development roadmaps of near-term quantum technologies

T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges

Atomistic Molecular Dynamics provides powerful and flexible tools for the prediction and analysis of molecular and macromolecular systems. Specifically, it provides a means by which we can measure theoretically that which cannot be measured experimentally: the dynamic time-evolution of complex systems comprising atoms and molecules. It is particularly suitable for the simulation and analysis of the otherwise inaccessible details of MHC-peptide interaction and, on a larger scale, the simulation of the immune synapse. Progress has been relatively tentative yet the emergence of truly high-performance computing and the development of coarse-grained simulation now offers us the hope of accurately predicting thermodynamic parameters and of simulating not merely a handful of proteins but larger, longer simulations comprising thousands of protein molecules and the cellular scale structures they form. We exemplify this within the context of immunoinformatics

Computational modelling approaches to vaccinology

Excepting the Peripheral and Central Nervous Systems, the Immune System is the most complex of somatic systems in higher animals. This complexity manifests itself at many levels from the molecular to that of the whole organism. Much insight into this confounding complexity can be gained through computational simulation. Such simulations range in application from epitope prediction through to the modelling of vaccination strategies. In this review, we evaluate selectively various key applications relevant to computational vaccinology: these include technique that operates at different scale that is, from molecular to organisms and even to population level

Integrating In Silico and In Vitro Analysis of Peptide Binding Affinity to HLA-Cw*0102: A Bioinformatic Approach to the Prediction of New Epitopes

Background: Predictive models of peptide-Major Histocompatibility Complex (MHC) binding affinity are important components of modern computational immunovaccinology. Here, we describe the development and deployment of a reliable peptide-binding prediction method for a previously poorly-characterized human MHC class I allele, HLA-Cw*0102. Methodology/Findings: Using an in-house, flow cytometry-based MHC stabilization assay we generated novel peptide binding data, from which we derived a precise two-dimensional quantitative structure-activity relationship (2D-QSAR) binding model. This allowed us to explore the peptide specificity of HLA-Cw*0102 molecule in detail. We used this model to design peptides optimized for HLA-Cw*0102-binding. Experimental analysis showed these peptides to have high binding affinities for the HLA-Cw*0102 molecule. As a functional validation of our approach, we also predicted HLA-Cw*0102-binding peptides within the HIV-1 genome, identifying a set of potent binding peptides. The most affine of these binding peptides was subsequently determined to be an epitope recognized in a subset of HLA-Cw*0102-positive individuals chronically infected with HIV-1. Conclusions/Significance: A functionally-validated in silico-in vitro approach to the reliable and efficient prediction of peptide binding to a previously uncharacterized human MHC allele HLA-Cw*0102 was developed. This technique is generally applicable to all T cell epitope identification problems in immunology and vaccinology

A rare cryptic translation product is presented by Kb major histocompatibility complex class I molecule to alloreactive T cells.

The identity of allogeneic peptide/major histocompatibility complex (MHC) complexes that elicit vigorous T cell responses has remained an interesting problem for both practical and theoretical reasons. Although a few abundant MHC class I-bound peptides have been purified and sequenced, identifying the unique T cell-stimulating peptides from among the thousands of existing peptides is still a very difficult undertaking. In this report, we identified the antigenic peptide that is recognized by an alloreactive bm1 anti-B6 T cell clone using a novel genetic strategy that is based upon measurement of T cell receptor occupancy in single T cells. Using lacZ-inducible T cells as a probe, we screened a splenic cDNA library in transiently transfected antigen-presenting cells (APCs) and isolated a cDNA clone that allowed expression of the appropriate peptide/Kb MHC complex in APC. The antigenic octapeptide (SVVEFSSL) exactly matched the consensus Kb MHC motif, but was surprisingly encoded by a non-ATG defined translation reading frame. Furthermore, the abundance of the naturally processed analog in untransfected cells was estimated to be <10 copies per cell. These results illustrate a novel strategy for identifying T cell-stimulating antigens in general and directly show that alloreactive T cells can respond to rather rare peptide/MHC complexes. These results also suggest that the total pool of processed peptides expressed on the APC surface may include those generated by cryptic translation of normally expressed transcripts