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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.

Prediction of TCR-peptide interactions has great importance for therapy of cancer, infectious and autoimmune diseases, but remains a major challenge, particularly for unseen epitopes. We present a structure-based method that enables scoring of TCR-peptide interactions using an energy potential (TCRen) derived from statistics of TCR-peptide contacts in existing crystal structures. We show that TCRen has high performance in discriminating cognate/unrelated peptides and can facilitate the identification of cancer neoepitopes recognized by tumor-infiltrating lymphocytes.

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 -β 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 (T conv ) and naïve regulatory CD4 + T (T reg ) cells. Compared with tuberculosis-resistant C57BL/6 (H2-A b ) mice, the tuberculosis-susceptible H2-A j mice had fewer CD4 + T cells of both subsets in the thymus. In the periphery, this deficiency was only apparent for T conv and was compensated for by peripheral reconstitution for T reg . We show that H2-A j favors selection of a narrower and more convergent repertoire with more hydrophobic and strongly interacting amino acid residues in the middle of CDR3α and CDR3β, suggesting more stringent selection against a narrower peptide–MHC-II context. H2-A j and H2-A b mice have prominent reciprocal differences in CDR3α and CDR3β 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.

T cell recognition of a cognate peptide-MHC complex (pMHC) presented on the surface of infected or malignant cells, is of utmost importance for mediating robust and long-term immune responses. Accurate predictions of cognate pMHC targets for T Cell Receptors (TCR) would greatly facilitate identification of vaccine targets for both pathogenic diseases as well as personalized cancer immunotherapies. Predicting immunogenic peptides therefore has been at the centre 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 SARS-CoV-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 training data of the models seem 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 vs. cancer peptides. Overall, we demonstrate that accurate and reliable prediction of immunogenic CD8+ T cell targets remains unsolved, thus we hope our work will guide users and model developers regarding potential pitfalls and unsettled questions in existing immunogenicity predictors.

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.

Understanding the hallmarks of the adaptive immune response to SARS-CoV-2 is critical for fighting the COVID-19 pandemic. We assessed the antibody and T-cell reactivity in COVID-19 convalescent patients and healthy donors sampled both prior to and during the pandemic. The numbers of SARS-CoV-2-specific T cells were increased in healthy donors examined during COVID-19. Combined with the absence of symptoms and humoral response across that group, this finding suggests that some individuals might be protected by T-cell cross-reactivity. In convalescent patients we observed public and diverse T-cell response to SARS-CoV-2 epitopes, revealing T-cell receptor motifs with germline-encoded features. Bulk CD4+ and CD8+ T-cell responses to Spike glycoprotein were mediated by groups of homologous T-cell receptors, some of them shared across multiple donors. Overall, our results demonstrate that T-cell response to SARS-CoV-2, including the identified set of specific T-cell receptors, can serve as a useful biomarker for surveying viral exposure and immunity. Funding: Mikhail Shugay was supported by RFBR grant No 19-34-70011. Alexander Ivanov was supported by the Ministry of Science and Higher Education of the Russian Federation [Agreement No. 075-15-2019-1660]. Conflict of Interest: The authors declare no conflicts of interest. Ethical Approval: All donors signed the informed consent approved by the National Research Center for Hematology ethical committee before the enrollment. Additionally, 10 healthy hematopoietic stem cell donor samples and 10 healthy donor serum samples were obtained from the blood bank with the approval of the local ethical committee.

Highly mutable β‐lactamases are responsible for the ability of Gram‐negative bacteria to resist β‐lactam antibiotics. Using site‐directed mutagenesis technique, we have produced in vitro a number of recombinant analogs of naturally occurring TEM‐type β‐lactamases, bearing the secondary substitution Q39K and key mutations related to the extended‐spectrum (E104K, R164S) and inhibitor‐resistant (M69V) β‐lactamases. The mutation Q39K alone was found to be neutral and hardly affected the catalytic properties of β‐lactamases. However, in combination with the key mutations, this substitution resulted in decreased K M values towards hydrolysis of a chromogenic substrate, CENTA. The ability of enzymes to restore catalytic activity after exposure to elevated temperature has been examined. All double and triple mutants of β‐lactamase TEM‐1 bearing the Q39K substitution showed lower thermal stability compared with the enzyme with Q39 intact. A sharp decrease in the stability was observed when Q39K was combined with E104K and M69V. The key R164S substitution demonstrated unusual ability to resist thermal inactivation. Computer analysis of the structure and molecular dynamics of β‐lactamase TEM‐1 revealed a network of hydrogen bonds from the residues Q39 and K32, related to the N‐terminal α‐helix, towards the residues R244 and G236, located in the vicinity of the enzyme's catalytic site. Replacement of Q39 by lysine in combination with the key drug resistance mutations may be responsible for loss of protein thermal stability and elevated mobility of its secondary structure elements. This effect on the activity of β‐lactamases can be used as a new potential target for inhibiting the enzyme.

Synthesis of β-lactamases is one of the common mechanisms of bacterial resistance to β-lactam antibiotics such as penicillins and cephalosporins. The widespread use of antibiotics resulted in appearance of numerous extended-spectrum β-lactamase variants or inhibitor-resistant β-lactamases. In TEM type β-lactamases mutations of 92 residues have been described. Several mutations are functionally important and they determine the extended substrate specificity. However, roles of the most so-called associated mutations, located far from the active site, remain unknown. We have investigated the role of associated mutations in structure of β-lactamase TEM-72, which contains two key mutations (G238S, E240K) and two associated mutations (Q39K, M182T) by means of molecular dynamics simulation. Appearance of the key mutations (in 238 and 240 positions) caused destabilization of the protein globule, characterized by increased mobility of amino acid residues. Associated mutations (Q39K, M182T) exhibited opposite effect on the protein structure. The mutation M182T stabilized, while the mutation Q39K destabilized the protein. It appears that the latter mutation promoted optimization of the conformational mobility of β-lactamase and may influence the enzyme activity.

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.

β-lactamases are hydrolytic enzymes primarily responsible for occurrence and abundance of bacteria resistant to β-lactam antibiotics. TEM type β-lactamases are formed by the parent enzyme TEM-1 and more than two hundred of its mutants. Positions for the known amino acid substitutions cover ∼30% of TEM type enzyme's sequence. These substitutions are divided into the key mutations that lead to changes in catalytic properties of β-lactamases, and the secondary ones, which role is poorly understood. In this study, Residue Interaction Networks were constructed from molecular dynamic trajectories of β-lactamase TEM-1 and its variants with two key substitutions, G238S and E240K, and their combinations with secondary ones (M182T and Q39K). Particular attention was paid to a detailed analysis of the interactions that affect conformation and mobility of the Ω-loop, representing a part of the β-lactamase active site. It was shown that key mutations weakened the stability of contact inside the Ω-loop thus increasing its mobility. Combination of three amino acid substitutions, including the 182 residue, leads to the release of R65 promoting its new contacts with N175 and D176. As a result, Ω-loop is fixed on the protein globule. The second distal mutation Q39K prevents changes in spatial position of R65, which lead to the weakening of the effect of M182T substitution and the recovery of the Ω-loop mobility. Thus, the distal secondary mutations are directed for recovering the mobility of enzyme disturbed by the key mutations responsible for expansion of substrate specificity. AbbreviationsESBLextended spectrum beta-lactamasesIRinhibitor resistant beta-lactamasesMDmolecular dynamicsRINresidue interaction networksRMSDroot mean square deviationRMSFroot mean square fluctuations. extended spectrum beta-lactamases inhibitor resistant beta-lactamases molecular dynamics residue interaction networks root mean square deviation root mean square fluctuations. Communicated by Ramaswamy H. Sarma

The network description is widely used to analyze the topology and the dynamics of complex systems. Residue interaction network (RIN) represents three-dimensional structure of protein as a set of nodes (residues) with their connections (edges). Calculated topological parameters from RIN correlate with various aspects of protein structure and function. Here, we reviewed the applications of RIN for the analysis and prediction of functionally important residues and ligand binding sites, protein–protein interactions, allosteric regulation, influence of point mutations on structure and dynamics of proteins.

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 pre-existing 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 glycoprotein 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., Graphical Abstract, Highlights Healthy donors sampled in 2020 had an increased T cell response to SARS-CoV-2 SARS-CoV-2 glycoprotein S-specific TCR repertoire features public CDR3 motifs Two epitopes are recognized by the majority of the HLA-A2+ COVID-19 convalescents, Shomuradova et al. assessed the immune response to SARS-CoV-2 in convalescent patients and healthy donors. Antigen-specific T cells were increased in convalescents and in donors sampled during the pandemic. The work identified two public epitopes from S-glycoprotein. T cell receptor repertoire profiling of S-glycoprotein specific lymphocytes revealed public CDR3 motifs.

Synthesis of b-lactamases is one of the common mechanisms of bacterial resistance to b-lactam antibiotics including penicillins and cephalosporins. The widespread use of antibiotics results in appearance of numerous extended-spectrum b-lactamase variants or resistance to inhibitors. Mutations of 92 residues of TEM type were found. Several mutations are the key mutations that determine the extension of spectrum of substrates. However, roles of the most associated mutations, located far from active site, remain unknown. We have investigated the role of associated mutations in structure of b-lactamase TEM-72, which contain two key mutation (G238S, E240K) and two associated mutations (Q39K, M182T) by means of simulation of molecular dynamics. The key mutation lead to destabilization of the protein globule, characterized by increased mobility of amino acid residues at high temperature of modelling. Mutation M182T lead to stabilization protein, whereas mutation Q39K is destabilizing mutation. It seems that the last mutation serves for optimization of conformational mobility of b-lactamase and may influence on enzyme activity.Sintez b-laktamaz iavliaetsia odnim iz naibolee obshchikh mekhanizmov rezistentnosti bakteriĭ k b-laktamnym antibiotikam, takim kak penitsilliny i tsefalosporiny. Shirokoe ispol'zovanie antibiotikov privelo k vozniknoveniiu mnozhestva variantov b-laktamaz s rasshirennym spektrom deĭstviia ili ustoĭchivym k ingibitoram. U b-laktamaz TEM tipa uzhe opisany mutatsii 92 aminokislotnykh ostatkov. Riad mutatsiĭ iavliaiutsia funktsional'nymi i otvechaiut za rasshirenie spektra substratnoĭ spetsifichnosti. Odnako rol' bol'shinstva tak nazyvaemykh soputstvuiushchikh mutatsiĭ, raspolozhennykh vdali ot aktivnogo tsentra, ostaetsia neizuchennoĭ. V rabote metodom molekuliarnoĭ dinamiki issledovali rol' soputstvuiushchikh mutatsiĭ v strukture b-laktamaz TEM-72, kotoraia soderzhit dve kliuchevye mutatsii (G238S, E240K) i dve soputstvuiushchie (Q39K, M182T). Pokazano, chto poiavlenie kliuchevykh mutatsiĭ ostatkov 238 i 240 privodilo k destabilizatsii belkovoĭ globuly, chto vyrazhalos' v uvelichenii podvizhnosti aminokislotnykh ostatkov. Soputstvuiushchie mutatsii ostatkov 182 i 39 vliiali na strukturu belka protivopolozhnym obrazom. Mutatsiia M182T uvelichivala ustoĭchivost' belkovoĭ globuly, a mutatsiia Q39K okazyvala destabiliziruiushchiĭ éffekt. Éta mutatsiia, po-vidimomu, sposobstvuet optimizatsii konformatsionnoĭ podvizhnosti b-laktamazy i mozhet vliiat' na rabotu fermenta.