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Biochimica Et Biophysica Acta.... Nov 2021Protective antigen channel is the central component of the deadly anthrax exotoxin responsible for binding and delivery of the toxin's enzymatic lethal and edema factor... (Review)
Review
Protective antigen channel is the central component of the deadly anthrax exotoxin responsible for binding and delivery of the toxin's enzymatic lethal and edema factor components into the cytosol. The channel, which is more than three times longer than the lipid bilayer membrane thickness and has a 6-Å limiting diameter, is believed to provide a sophisticated unfoldase and translocase machinery for the foreign protein transport into the host cell cytosol. The tripartite toxin can be reengineered, one component at a time or collectively, to adapt it for the targeted cancer therapeutic treatments. In this review, we focus on the biophysical studies of the protective antigen channel-forming activity, small ion transport properties, enzymatic factor translocation, and blockage comparing it with the related clostridial binary toxin channels. We address issues linked to the anthrax toxin channel structural dynamics and lipid dependence, which are yet to become generally recognized as parts of the toxin translocation machinery.
Topics: Antigens, Bacterial; Bacterial Toxins; Hydrogen-Ion Concentration; Lipid Bilayers; Protein Conformation; Protein Transport
PubMed: 34332985
DOI: 10.1016/j.bbamem.2021.183715 -
Scientific Reports Jun 2022Binding of peptides to Human Leukocyte Antigen (HLA) receptors is a prerequisite for triggering immune response. Estimating peptide-HLA (pHLA) binding is crucial for...
Binding of peptides to Human Leukocyte Antigen (HLA) receptors is a prerequisite for triggering immune response. Estimating peptide-HLA (pHLA) binding is crucial for peptide vaccine target identification and epitope discovery pipelines. Computational methods for binding affinity prediction can accelerate these pipelines. Currently, most of those computational methods rely exclusively on sequence-based data, which leads to inherent limitations. Recent studies have shown that structure-based data can address some of these limitations. In this work we propose a novel machine learning (ML) structure-based protocol to predict binding affinity of peptides to HLA receptors. For that, we engineer the input features for ML models by decoupling energy contributions at different residue positions in peptides, which leads to our novel per-peptide-position protocol. Using Rosetta's ref2015 scoring function as a baseline we use this protocol to develop 3pHLA-score. Our per-peptide-position protocol outperforms the standard training protocol and leads to an increase from 0.82 to 0.99 of the area under the precision-recall curve. 3pHLA-score outperforms widely used scoring functions (AutoDock4, Vina, Dope, Vinardo, FoldX, GradDock) in a structural virtual screening task. Overall, this work brings structure-based methods one step closer to epitope discovery pipelines and could help advance the development of cancer and viral vaccines.
Topics: Epitopes; HLA Antigens; Histocompatibility Antigens Class I; Histocompatibility Antigens Class II; Humans; Peptides; Protein Binding
PubMed: 35750701
DOI: 10.1038/s41598-022-14526-x -
Proteomics Dec 2021T cells play an important role in the adaptive immune response to a variety of infections and cancers. Initiation of a T cell mediated immune response requires antigen... (Review)
Review
T cells play an important role in the adaptive immune response to a variety of infections and cancers. Initiation of a T cell mediated immune response requires antigen recognition in a process termed MHC (major histocompatibility complex) restri ction. A T cell antigen is a composite structure made up of a peptide fragment bound within the antigen-binding groove of an MHC-encoded class I or class II molecule. Insight into the precise composition and biology of self and non-self immunopeptidomes is essential to harness T cell mediated immunity to prevent, treat, or cure infectious diseases and cancers. T cell antigen discovery is an arduous task! The pioneering work in the early 1990s has made large-scale T cell antigen discovery possible. Thus, advancements in mass spectrometry coupled with proteomics and genomics technologies make possible T cell antigen discovery with ease, accuracy, and sensitivity. Yet we have only begun to understand the breadth and the depth of self and non-self immunopeptidomes because the molecular biology of the cell continues to surprise us with new secrets directly related to the source, and the processing and presentation of MHC ligands. Focused on MHC class I molecules, this review, therefore, provides a brief historic account of T cell antigen discovery and, against a backdrop of key advances in molecular cell biologic processes, elaborates on how proteogenomics approaches have revolutionised the field.
Topics: Histocompatibility Antigens Class I; Histocompatibility Antigens Class II; Ligands; Mass Spectrometry; Proteomics; T-Lymphocytes
PubMed: 34310018
DOI: 10.1002/pmic.202000143 -
Molecular Immunology Feb 2021MR1 is an MHC class I-like molecule with unique structural and biological features that make it an important member among the molecules involved in antigen presentation...
MR1 is an MHC class I-like molecule with unique structural and biological features that make it an important member among the molecules involved in antigen presentation to T cells. Distinctive features include ubiquitous expression of the MR1 gene and its monomorphism. Another relevant property is that the MR1 protein appears at very low levels on the plasma membrane and its surface expression is regulated by antigen binding. Finally, the nature of presented antigens differs from those that bind other presenting molecules and includes small metabolites of microbial and self-origin, small drugs and tumor-associated antigens. This opinion paper describes in detail some of those features and discusses recent literature in the field.
Topics: Antigen Presentation; Antigens, Bacterial; Histocompatibility Antigens Class I; Humans; Ligands; Lymphocyte Activation; Minor Histocompatibility Antigens; Protein Binding; Protein Structure, Tertiary; T-Cell Antigen Receptor Specificity; T-Lymphocytes
PubMed: 33358568
DOI: 10.1016/j.molimm.2020.12.016 -
Frontiers in Immunology 2023Adoptive cell therapy (ACT) with tumor-specific T cells has been shown to mediate durable cancer regression. Tumor-specific T cells are also the basis of other... (Review)
Review
Adoptive cell therapy (ACT) with tumor-specific T cells has been shown to mediate durable cancer regression. Tumor-specific T cells are also the basis of other therapies, notably cancer vaccines. The main target of tumor-specific T cells are neoantigens resulting from mutations in self-antigens over the course of malignant transformation. The detection of neoantigens presents a major challenge to T cells because of their high structural similarity to self-antigens, and the need to avoid autoimmunity. How different a neoantigen must be from its wild-type parent for it to induce a T cell response is poorly understood. Here we review recent structural and biophysical studies of T cell receptor (TCR) recognition of shared cancer neoantigens derived from oncogenes, including p53, KRAS, KRAS, HHAT, and PIK3CA. These studies have revealed that, in some cases, the oncogenic mutation improves antigen presentation by strengthening peptide-MHC binding. In other cases, the mutation is detected by direct interactions with TCR, or by energetically driven or other indirect strategies not requiring direct TCR contacts with the mutation. We also review antibodies designed to recognize peptide-MHC on cell surfaces (TCR-mimic antibodies) as an alternative to TCRs for targeting cancer neoantigens. Finally, we review recent computational advances in this area, including efforts to predict neoepitope immunogenicity and how these efforts may be advanced by structural information on peptide-MHC binding and peptide-MHC recognition by TCRs.
Topics: Humans; T-Lymphocytes; Proto-Oncogene Proteins p21(ras); Antigens, Neoplasm; Neoplasms; Receptors, Antigen, T-Cell; Peptides; Autoantigens
PubMed: 38045695
DOI: 10.3389/fimmu.2023.1303304 -
Journal For Immunotherapy of Cancer Dec 2022CD73 is widely expressed on immune cells playing a critical role in immunomodulatory functions including cell adhesion and migration, as a costimulatory molecule for T...
BACKGROUND
CD73 is widely expressed on immune cells playing a critical role in immunomodulatory functions including cell adhesion and migration, as a costimulatory molecule for T cells and in production of adenosine. The function of CD73 expressed on B cells has not been fully characterized. Mupadolimab is an anti-human CD73 antibody that activates B cells. We evaluated the characteristics of this antibody and its effects on immune cells in vitro and in vivo.
METHODS
Mupadolimab binding to CD73, inhibition of CD73 enzymatic activity, and effects on lymphocyte activation were evaluated in vitro by measuring changes in immunophenotype by flow cytometry. Cryogenic-transmission electron microscopy was used to determine epitope binding. Effects on human B cells in vivo were evaluated in immunodeficient NSG-SGM3 mice immunized with SARS-CoV-2 and influenza viral antigens. Safety and immune effects were evaluated in the completed dose escalation portion of a phase 1 trial conducted in patients with cancer.
RESULTS
Mupadolimab binds to a unique epitope on CD73 B cells resulting in their activation and differentiation through B cell receptor signaling pathways. Mupadolimab induces expression of CD69, CD83, CD86 and MHC class II on B cells along with morphological transformation into plasmablasts and expression of CD27, CD38 and CD138. These effects are independent of adenosine. Mupadolimab binds to the N-terminal of CD73 in the closed position and competitively inhibits substrate binding. Mupadolimab enhanced antigen specific antibody response to SARS-CoV-2 spike protein and influenza hemagglutinin in humanized mouse models. Mupadolimab was evaluated as a monotherapy in a phase 1 trial (NCT03454451) in 34 patients with advanced cancer and demonstrated binding to CD73 circulating cells and transient reduction in the number of B cells, with return of CD73 B cells with memory phenotype. No dose-limiting toxicities or changes in serum immunoglobulins were seen.
CONCLUSIONS
Mupadolimab activates B cells and stimulates the production of antigen specific antibodies. The effects in patients with cancer suggest that activated, CD69 B cells redistribute to lymphoid tissues. Minor tumor regression was observed in several patients. These results support further investigation of mupadolimab as an immunotherapy for cancer and its potential use as a vaccine adjuvant.
TRIAL REGISTRATION NUMBER
NCT03454451.
Topics: Animals; Humans; Mice; Adenosine; Antibodies, Monoclonal; Antigens, Viral; B-Lymphocytes; Epitopes; Immunity, Humoral; Neoplasms
PubMed: 36600561
DOI: 10.1136/jitc-2022-005802 -
Biosensors & Bioelectronics Sep 2019The ability of influenza viruses to rapidly evolve has caused significant challenges in viral surveillance, diagnosis, and therapeutic development. Molecular sequencing... (Review)
Review
The ability of influenza viruses to rapidly evolve has caused significant challenges in viral surveillance, diagnosis, and therapeutic development. Molecular sequencing methods, though powerful tools for monitoring influenza evolution at the genetic level, are not able to fully characterize the antigenic properties of influenza viruses. Understanding influenza virus antigenicity is critical to vaccine development and disease prevention. Traditional immunoassays which have been widely used for evaluating influenza antigenicity have limited throughput. To alleviate these problems, new bioanalytical tools to investigate influenza antigenicity by measuring antibody-antigen binding are an active area of research. Herein, we review immunosensor technologies from the aspects of various sensing principles, while highlighting recent developments in multiplex, label-free detection strategies. Highlighted technologies include electrochemical immunosensors relying on impedimetric detection; these demonstrate simple design and cost effectiveness for mass production. Antibody arrays implemented on an optical interferometric sensor system allow systematic characterization of influenza antigenicity. Quartz microbalance immunosensors are highly sensitive but have yet to be explored for multiplex sensing. Immunosensors made on lateral flow strips have shown promise in rapid diagnosis of influenza subtypes. We anticipate that these and other technologies discussed in the review will facilitate advances in the study of influenza, and other viral pathogens.
Topics: Animals; Antigens, Viral; Biosensing Techniques; Equipment Design; Humans; Immunoassay; Influenza, Human; Alphainfluenzavirus; Orthomyxoviridae; Orthomyxoviridae Infections
PubMed: 31272058
DOI: 10.1016/j.bios.2019.111476 -
Advanced Science (Weinheim,... Sep 2023Antigen delivery based on non-virus-like particle self-associating protein nanoscffolds, such as Aquifex aeolicus lumazine synthase (AaLS), is limited due to the...
Antigen delivery based on non-virus-like particle self-associating protein nanoscffolds, such as Aquifex aeolicus lumazine synthase (AaLS), is limited due to the immunotoxicity and/or premature clearance of antigen-scaffold complex resulted from triggering unregulated innate immune responses. Here, using rational immunoinformatics prediction and computational modeling, we screen the T epitope peptides from thermophilic nanoproteins with the same spatial structure as hyperthermophilic icosahedral AaLS, and reassemble them into a novel thermostable self-assembling nanoscaffold RP that can specifically activate T cell-mediated immunity. Tumor model antigen ovalbumin T epitopes and the severe acute respiratory syndrome coronavirus 2 receptor-binding domain are loaded onto the scaffold surface through the SpyCather/SpyTag system to construct nanovaccines. Compared to AaLS, RP -constructed nanovaccines elicit more potent cytotoxic T cell and CD4 T helper 1 (Th1)-biased immune responses, and generate less anti-scaffold antibody. Moreover, RP significantly upregulate the expression of transcription factors and cytokines related to the differentiation of type-1 conventional dendritic cells, promoting the cross-presentation of antigens to CD8 T cells and Th1 polarization of CD4 T cells. RP confers antigens with increased stability against heating, freeze-thawing, and lyophilization with almost no antigenicity loss. This novel nanoscaffold offers a simple, safe, and robust strategy for boosting T-cell immunity-dependent vaccine development.
Topics: Humans; CD8-Positive T-Lymphocytes; COVID-19; Immunity, Cellular; T-Lymphocytes, Cytotoxic; Antigens, Neoplasm
PubMed: 37395451
DOI: 10.1002/advs.202303049 -
Journal of Translational Medicine Oct 2022Aberrant sialoglycans on the surface of tumor cells shield potential tumor antigen epitopes, escape recognition, and suppress activation of immunocytes. α2,3/α2,6Gal-...
BACKGROUND
Aberrant sialoglycans on the surface of tumor cells shield potential tumor antigen epitopes, escape recognition, and suppress activation of immunocytes. α2,3/α2,6Gal- and α2,6GalNAc (Gal/GalNAc)-linked sialic acid residues of sialoglycans could affect macrophage galactose-type lectins (MGL) mediated-antigen uptake and presentation and promote sialic acid-binding immunoglobulin-like lectins (Siglecs) mediated-immunosuppression. Desialylating sialoglycans on tumor cells could present tumor antigens with Gal/GalNAc residues and overcome glyco-immune checkpoints. Thus, we explored whether vaccination with desialylated whole-cell tumor vaccines (DWCTVs) triggers anti-tumor immunity in ovarian cancer (OC).
METHODS
Sialic acid (Sia) and Gal/GalNAc residues on OC A2780, OVCAR3, and ID8 cells treated with α2-3 neuraminidase (α2-3NA) and α2-6NA, and Sigec-9 or Siglec-E and MGL on DCs pulsed with desialylated OC cells were identified using flow cytometry (FCM); RT-qPCR determined IFNG expression of T cells, TRBV was sequenced using Sanger sequencing and cytotoxicity of αβ T cells was measured with LDH assay; Anti-tumor immunity in vivo was validated via vaccination with desialylated whole-cell ID8 vaccine (ID8 DWCTVs).
RESULTS
Gal/GalNAc but not Sia residues were significantly increased in the desialylated OC cells. α2-3NA-modified DWCTV increased MGL but decreased Siglec-9 or Siglec E expression on DCs. MGL/Siglec-9 DCs significantly up-regulated IFNG expression and CD4/CD8 ratio of T cells and diversified the TCR repertoire of αβ T-cells that showed enhanced cytotoxic activity. Vaccination with α2-3NA-modified ID8 DWCTVs increased MGL/Siglec-E DCs in draining lymph nodes, limited tumor growth, and extended survival in tumor-challenged mice.
CONCLUSION
Desialylated tumor cell vaccine could promote anti-tumor immunity and provide a strategy for OC immunotherapy in a clinical setting.
Topics: Humans; Mice; Animals; Female; Cancer Vaccines; Epitopes; N-Acetylneuraminic Acid; Cell Line, Tumor; Apoptosis; Ovarian Neoplasms; Sialic Acid Binding Immunoglobulin-like Lectins; Antigens; Galactose
PubMed: 36316782
DOI: 10.1186/s12967-022-03714-y -
Frontiers in Immunology 2022One of the primary tasks in vaccine design and development of immunotherapeutic drugs is to predict conformational B-cell epitopes corresponding to primary antibody...
One of the primary tasks in vaccine design and development of immunotherapeutic drugs is to predict conformational B-cell epitopes corresponding to primary antibody binding sites within the antigen tertiary structure. To date, multiple approaches have been developed to address this issue. However, for a wide range of antigens their accuracy is limited. In this paper, we applied the transfer learning approach using pretrained deep learning models to develop a model that predicts conformational B-cell epitopes based on the primary antigen sequence and tertiary structure. A pretrained protein language model, ESM-1v, and an inverse folding model, ESM-IF1, were fine-tuned to quantitatively predict antibody-antigen interaction features and distinguish between epitope and non-epitope residues. The resulting model called SEMA demonstrated the best performance on an independent test set with ROC AUC of 0.76 compared to peer-reviewed tools. We show that SEMA can quantitatively rank the immunodominant regions within the SARS-CoV-2 RBD domain. SEMA is available at https://github.com/AIRI-Institute/SEMAi and the web-interface http://sema.airi.net.
Topics: Antigens; COVID-19; Epitopes, B-Lymphocyte; Humans; Immunodominant Epitopes; Machine Learning; SARS-CoV-2; Vaccines
PubMed: 36189325
DOI: 10.3389/fimmu.2022.960985