AIMC Topic: T-Lymphocytes, Cytotoxic

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Integrated structural proteomics and machine learning-guided mapping of a highly protective precision vaccine against mycoplasma pulmonis.

International immunopharmacology Aug 16, 2024
Mycoplasma pulmonis (M. pulmonis) is an emerging respiratory infection commonly linked to prostate cancer, and it is classified under the group of mycoplasmas. Improved management of mycoplasma infections is essential due to the frequent ineffectiven...
Mice Proteomics Bacterial Proteins Epitopes, T-Lymphocyte Molecular Docking Simulation Epitope Mapping T-Lymphocytes, Cytotoxic Mycoplasma Infections Antigens, Bacterial Epitopes, B-Lymphocyte Bacterial Vaccines Humans Machine Learning Animals
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Decoding CAR T cell phenotype using combinatorial signaling motif libraries and machine learning.

Science (New York, N.Y.) Dec 8, 2022
Chimeric antigen receptor (CAR) costimulatory domains derived from native immune receptors steer the phenotypic output of therapeutic T cells. We constructed a library of CARs containing ~2300 synthetic costimulatory domains, built from combinations ...
Signal Transduction Protein Domains T-Lymphocytes, Cytotoxic Humans Phenotype Machine Learning Receptors, Chimeric Antigen Peptide Library
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An in silico deep learning approach to multi-epitope vaccine design: a SARS-CoV-2 case study.

Scientific reports Feb 5, 2021
The rampant spread of COVID-19, an infectious disease caused by SARS-CoV-2, all over the world has led to over millions of deaths, and devastated the social, financial and political entities around the world. Without an existing effective medical the...
Allergens Solubility Immunogenicity, Vaccine RNA, Viral Molecular Dynamics Simulation Vaccines, Subunit T-Lymphocytes, Cytotoxic Codon Usage T-Lymphocytes, Helper-Inducer Protein Conformation Epitopes, B-Lymphocyte Deep Learning COVID-19 Vaccines Spike Glycoprotein, Coronavirus Computational Biology Models, Molecular Mutation Epitopes, T-Lymphocyte Molecular Docking Simulation Drug Design COVID-19 SARS-CoV-2 Humans
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Machine-Learning Prediction of Tumor Antigen Immunogenicity in the Selection of Therapeutic Epitopes.

Cancer immunology research Sep 12, 2019
Current tumor neoantigen calling algorithms primarily rely on epitope/major histocompatibility complex (MHC) binding affinity predictions to rank and select for potential epitope targets. These algorithms do not predict for epitope immunogenicity usi...
Algorithms Female Animals Male Neoplasms Epitopes, T-Lymphocyte Cancer Vaccines Mice, Inbred C57BL Histocompatibility Antigens Class II Antigens, Neoplasm Humans Peptide Fragments T-Lymphocytes, Cytotoxic Mice, Inbred BALB C Machine Learning Histocompatibility Antigens Class I Mice Computational Biology
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and cell-based analyses reveal strong divergence between prediction and observation of T-cell-recognized tumor antigen T-cell epitopes.

The Journal of biological chemistry May 23, 2017
Tumor exomes provide comprehensive information on mutated, overexpressed genes and aberrant splicing, which can be exploited for personalized cancer immunotherapy. Of particular interest are mutated tumor antigen T-cell epitopes, because neoepitope-s...
Mice, Knockout Peptide Fragments Epitopes Membrane Proteins T-Lymphocytes, Cytotoxic Models, Immunological Animals Neoplasm Proteins Protein Refolding Computational Biology Oligopeptides HLA-A2 Antigen Humans Cancer Vaccines Cells, Cultured Immunogenicity, Vaccine Protein Stability Antigens, Neoplasm Melanoma Artificial Intelligence Mice, Transgenic Expert Systems Vaccines, Synthetic Reproducibility of Results
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