Large-scale template-based structural modeling of T-cell receptors with known antigen specificity reveals complementarity features.

Introduction: T-cell receptor (TCR) recognition of foreign peptides presented by the major histocompatibility complex (MHC) initiates the adaptive immune response against pathogens. While a large number of TCR sequences specific to different antigenic peptides are known to date, the structural data describing the conformation and contacting residues for TCR-peptide-MHC complexes is relatively limited. In the present study we aim to extend and analyze the set of available structures by performing highly accurate template-based modeling of these complexes using TCR sequences with known specificity. Methods: Identification of CDR3 sequences and their further clustering, based on available spatial structures, V- and J-genes of corresponding T-cell receptors, and epitopes, was performed using the VDJdb database. Modeling of the selected CDR3 loops was conducted using a stepwise introduction of single amino acid substitutions to the template PDB structures, followed by optimization of the TCR-peptide-MHC contacting interface using the Rosetta package applications. Statistical analysis and recursive feature elimination procedures were carried out on computed energy values and properties of contacting amino acid residues between CDR3 loops and peptides, using R. Results: Using the set of 29 complex templates (including a template with SARS-CoV-2 antigen) and 732 specificity records, we built a database of 1585 model structures carrying substitutions in either TCRα or TCRß chains with some models representing the result of different mutation pathways for the same final structure. This database allowed us to analyze features of amino acid contacts in TCR - peptide interfaces that govern antigen recognition preferences and interpret these interactions in terms of physicochemical properties of interacting residues. Conclusion: Our results provide a methodology for creating high-quality TCR-peptide-MHC models for antigens of interest that can be utilized to predict TCR specificity.

Evaluating performance of existing computational models in predicting CD8+ T cell pathogenic epitopes and cancer neoantigens.

T cell recognition of a cognate peptide-major histocompatibility complex (pMHC) presented on the surface of infected or malignant cells is of the utmost importance for mediating robust and long-term immune responses. Accurate predictions of cognate pMHC targets for T cell receptors would greatly facilitate identification of vaccine targets for both pathogenic diseases and personalized cancer immunotherapies. Predicting immunogenic peptides therefore has been at the center of intensive research for the past decades but has proven challenging. Although numerous models have been proposed, performance of these models has not been systematically evaluated and their success rate in predicting epitopes in the context of human pathology has not been measured and compared. In this study, we evaluated the performance of several publicly available models, in identifying immunogenic CD8+ T cell targets in the context of pathogens and cancers. We found that for predicting immunogenic peptides from an emerging virus such as severe acute respiratory syndrome coronavirus 2, none of the models perform substantially better than random or offer considerable improvement beyond HLA ligand prediction. We also observed suboptimal performance for predicting cancer neoantigens. Through investigation of potential factors associated with ill performance of models, we highlight several data- and model-associated issues. In particular, we observed that cross-HLA variation in the distribution of immunogenic and non-immunogenic peptides in the training data of the models seems to substantially confound the predictions. We additionally compared key parameters associated with immunogenicity between pathogenic peptides and cancer neoantigens and observed evidence for differences in the thresholds of binding affinity and stability, which suggested the need to modulate different features in identifying immunogenic pathogen versus cancer peptides. Overall, we demonstrate that accurate and reliable predictions of immunogenic CD8+ T cell targets remain unsolved; thus, we hope our work will guide users and model developers regarding potential pitfalls and unsettled questions in existing immunogenicity predictors.

SARS-CoV-2 Epitopes Are Recognized by a Public and Diverse Repertoire of Human T Cell Receptors.

Understanding the hallmarks of the immune response to SARS-CoV-2 is critical for fighting the COVID-19 pandemic. We assessed antibody and T cell reactivity in convalescent COVID-19 patients and healthy donors sampled both prior to and during the pandemic. Healthy donors examined during the pandemic exhibited increased numbers of SARS-CoV-2-specific T cells, but no humoral response. Their probable exposure to the virus resulted in either asymptomatic infection without antibody secretion or activation of preexisting immunity. In convalescent patients, we observed a public and diverse T cell response to SARS-CoV-2 epitopes, revealing T cell receptor (TCR) motifs with germline-encoded features. Bulk CD4+ and CD8+ T cell responses to the spike protein were mediated by groups of homologous TCRs, some of them shared across multiple donors. Overall, our results demonstrate that the T cell response to SARS-CoV-2, including the identified set of TCRs, can serve as a useful biomarker for surveying antiviral immunity.

MHC-II alleles shape the CDR3 repertoires of conventional and regulatory naïve CD4+ T cells.

T cell maturation and activation depend upon T cell receptor (TCR) interactions with a wide variety of antigenic peptides displayed in a given major histocompatibility complex (MHC) context. Complementarity-determining region 3 (CDR3) is the most variable part of the TCRα and -ß chains, which govern interactions with peptide-MHC complexes. However, it remains unclear how the CDR3 landscape is shaped by individual MHC context during thymic selection of naïve T cells. We established two mouse strains carrying distinct allelic variants of H2-A and analyzed thymic and peripheral production and TCR repertoires of naïve conventional CD4+ T (Tconv) and naïve regulatory CD4+ T (Treg) cells. Compared with tuberculosis-resistant C57BL/6 (H2-Ab) mice, the tuberculosis-susceptible H2-Aj mice had fewer CD4+ T cells of both subsets in the thymus. In the periphery, this deficiency was only apparent for Tconv and was compensated for by peripheral reconstitution for Treg We show that H2-Aj favors selection of a narrower and more convergent repertoire with more hydrophobic and strongly interacting amino acid residues in the middle of CDR3α and CDR3ß, suggesting more stringent selection against a narrower peptide-MHC-II context. H2-Aj and H2-Ab mice have prominent reciprocal differences in CDR3α and CDR3ß features, probably reflecting distinct modes of TCR fitting to MHC-II variants. These data reveal the mechanics and extent of how MHC-II shapes the naïve CD4+ T cell CDR3 landscape, which essentially defines adaptive response to infections and self-antigens.

Comprehensive analysis of structural and sequencing data reveals almost unconstrained chain pairing in TCRαß complex.

Antigen recognition by T-cells is guided by the T-cell receptor (TCR) heterodimer formed by α and ß chains. A huge diversity of TCR sequences should be maintained by the immune system in order to be able to mount an effective response towards foreign pathogens, so, due to cooperative binding of α and ß chains to the pathogen, any constraints on chain pairing can have a profound effect on immune repertoire structure, diversity and antigen specificity. By integrating available structural data and paired chain sequencing results we were able to show that there are almost no constraints on pairing in TCRαß complexes, allowing naive T-cell repertoire to reach the highest possible diversity. Additional analysis reveals that the specific choice of contacting amino acids can still have a profound effect on complex conformation. Moreover, antigen-driven selection can distort the uniform landscape of chain pairing, while small, yet significant, differences in the pairing can be attributed to various specialized T-cell subsets such as MAIT and iNKT T-cells, as well as other TCR sets specific to certain antigens.

The mechanism of a one-substrate transketolase reaction.

Transketolase catalyzes the transfer of a glycolaldehyde residue from ketose (the donor substrate) to aldose (the acceptor substrate). In the absence of aldose, transketolase catalyzes a one-substrate reaction that involves only ketose. The mechanism of this reaction is unknown. Here, we show that hydroxypyruvate serves as a substrate for the one-substrate reaction and, as well as with the xylulose-5-phosphate, the reaction product is erythrulose rather than glycolaldehyde. The amount of erythrulose released into the medium is equimolar to a double amount of the transformed substrate. This could only be the case if the glycol aldehyde formed by conversion of the first ketose molecule (the product of the first half reaction) remains bound to the enzyme, waiting for condensation with the second molecule of glycol aldehyde. Using mass spectrometry of catalytic intermediates and their subsequent fragmentation, we show here that interaction of the holotransketolase with hydroxypyruvate results in the equiprobable binding of the active glycolaldehyde to the thiazole ring of thiamine diphosphate and to the amino group of its aminopyrimidine ring. We also show that these two loci can accommodate simultaneously two glycolaldehyde molecules. It explains well their condensation without release into the medium, which we have shown earlier.

Biological Evaluation of a New Brassinosteroid: Antiproliferative Effects and Targeting Estrogen Receptor α Pathways.

Brassinosteroids (BS), a class of plant-specific steroid hormones, are considered as new potential anticancer agents for the treatment of tumors of different origin, including hormone-dependent cancers. Effects of a synthetic brassinosteroid BS4 ((22R,23R,24R)-22,23-dihydroxy-24-methyl-B-homo-7-oxa-5α-cholest-2-en-6-one ((3aS,7aR,7bS,9aS,10R,12aS,12bS)-10-[(2S,3R,4R,5R)-3,4-dihydroxy-5,6-dimethylheptan-2-yl]-7a,9a-dimethyl-1,3a,4,7,7a,7b,8,9,9a,10,11,12,12a,12b-tetradecahydro-3H-benzo[c]indeno[5,4-e]oxepin-3-one)) on hormone-dependent breast cancer cells and normal epithelial cells and its impact on the estrogen receptor signaling were evaluated. Cytotoxicity was assessed by MTT-test; expression of estrogen receptor α and survivin was measured by immunoblotting. Transactivation analysis of luciferase reporter gene was performed for ERα and AP-1 factors after the brassinosteroid treatment. Dock6 and Autodock Vina were used for molecular docking. BS4 revealed a significant antiproliferative effect towards the hormone-dependent breast cancer cells and was not active against normal epithelial cells. BS4 action on MCF-7 breast cancer cells was found to be complex: a decrease in ERα expression as well as in its transcription activity was accompanied by inhibition of ERα-related signaling pathways (AP-1 complex and survivin). BS4 binding mode to ERα ligand-binding domain was analyzed by molecular docking. The obtained results show that antiproliferative and antiestrogenic properties of the brassinosteroid BS4, as well as its ability to inhibit the anti-apoptotic protein survivin may be of interest for further development of anticancer agents.

Stability of the PHF10 subunit of PBAF signature module is regulated by phosphorylation: role of ß-TrCP.

The PBAF chromatin-remodeling complexes are multi-protein machines, regulating expression of genes involved in proliferation and differentiation. PHF10 is a subunit of the PBAF essential for its association with chromatin. Mammalian PHF10 is expressed as four ubiquitous isoforms, which are alternatively incorporated in the complex and differ by their influence on transcription of target genes. PHF10 have different domain structure and two of them (PHF10-S isoforms) lack C-terminal PHD domains, which enables their phosphorylation by CK-1. Here we have found that PBAF subunits have low turnover rate, except for PHF10 which has much lower half-life, and is degraded by ß-TrCP. The ß-TrCP knockdown stabilizes PBAF core subunits - BRG1 and BAF155 and specific subunits - PHF10, BAF200, BAF180 and BRD7. PHF10 isoforms contain two non-canonical ß-TrCP degrons and are degraded by ß-TrCP in a phospho-dependent manner. But phosphorylation of PHF10-S degrons by CK-1, contrary to previously described degrons, prevents their degradation. Targeted molecular docking demonstrated that phosphorylated forms of PHF10 bind to ß-TrCP with much lower affinity than non-phosphorylated ones, contrary to previously described degrons. This unorthodox mechanism proposes that phosphorylation of ß-TrCP degrons by CK-1 could not only degrade a set of proteins, but also stabilize a different set of targets.

Computer-aided design of aptamers for cytochrome p450.

Aptamers are short single-stranded DNA or RNA oligonucleotides that can bind to their targets with high affinity and specificity. Usually, they are experimentally selected using the SELEX method. Here, we describe an approach toward the in silico selection of aptamers for proteins. This approach involves three steps: finding a potential binding site, designing the recognition and structural parts of the aptamers and evaluating the experimental affinity. Using this approach, a set of 15-mer aptamers for cytochrome P450 51A1 was designed using docking and molecular dynamics simulation. An experimental evaluation of the synthesized aptamers using SPR biosensor showed that these aptamers interact with cytochrome P450 51A1 with Kd values in the range of 10(-6)-10(-7) M.