25 research outputs found

    Abacavir inhibits but does not cause self-reactivity to HLA-B*57:01-restricted EBV specific T cell receptors

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    Pre-existing pathogen-specific memory T cell responses can contribute to multiple adverse outcomes including autoimmunity and drug hypersensitivity. How the specificity of the T cell receptor (TCR) is subverted or seconded in many of these diseases remains unclear. Here, we apply abacavir hypersensitivity (AHS) as a model to address this question because the disease is linked to memory T cell responses and the HLA risk allele, HLA-B*57:01, and the initiating insult, abacavir, are known. To investigate the role of pathogen-specific TCR specificity in mediating AHS we performed a genome-wide screen for HLA-B*57:01 restricted T cell responses to Epstein-Barr virus (EBV), one of the most prevalent human pathogens. T cell epitope mapping revealed HLA-B*57:01 restricted responses to 17 EBV open reading frames and identified an epitope encoded by EBNA3C. Using these data, we cloned the dominant TCR for EBNA3C and a previously defined epitope within EBNA3B. TCR specificity to each epitope was confirmed, however, cloned TCRs did not cross-react with abacavir plus self-peptide. Nevertheless, abacavir inhibited TCR interactions with their cognate ligands, demonstrating that TCR specificity may be subverted by a drug molecule. These results provide an experimental road map for future studies addressing the heterologous immune responses of TCRs including T cell mediated adverse drug reactions

    The histone deacetylase inhibitor, romidepsin, as a potential treatment for pulmonary fibrosis

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    Idiopathic pulmonary fibrosis (IPF) is a progressive disease that usually affects elderly people. It has a poor prognosis and there are limited therapies. Since epigenetic alterations are associated with IPF, histone deacetylase (HDAC) inhibitors offer a novel therapeutic strategy to address the unmet medical need. This study investigated the potential of romidepsin, an FDA-approved HDAC inhibitor, as an anti-fibrotic treatment and evaluated biomarkers of target engagement that may have utility in future clinical trials. The anti-fibrotic effects of romidepsin were evaluated both in vitro and in vivo together with any harmful effect on alveolar type II cells (ATII). Bronchoalveolar lavage fluid (BALF) from IPF or control donors was analyzed for the presence of lysyl oxidase (LOX). In parallel with an increase in histone acetylation, romidepsin potently inhibited fibroblast proliferation, myofibroblast differentiation and LOX expression. ATII cell numbers and their lamellar bodies were unaffected. In vivo, romidepsin inhibited bleomycin-induced pulmonary fibrosis in association with suppression of LOX expression. LOX was significantly elevated in BALF of IPF patients compared to controls. These data show the anti-fibrotic effects of romidepsin, supporting its potential use as novel treatment for IPF with LOX as a companion biomarker for evaluation of early on-target effects

    Big data biology - just the next big hype?

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    The Ba−Eu (Barium-Europium) system

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    The Ba−Yb (Barium-Ytterbium) system

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    Relaxation dynamics in suspensions of ferromagnetic particles

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    We have studied the relaxation dynamics of a dilute assembly of ferromagnetic particles in suspension. A formalism based on the Smoluchowski equation, describing the evolution of the probability density for the directions of the magnetic moment and of the axis of easy magnetization of the particles, has been developed. We compute the rotational viscosity from a Green-Kubo formula and give an expression for the relaxation time of the particles which comes from the dynamic equations of the correlation functions. Concerning the relaxation time for the particles, our results agree quite well with experiments performed on different samples of ferromagnetic particles for which the magnetic energy, associated with the interaction between the magnetic moments and the external field, or the energy of anisotropy plays a dominant role

    AI-guided pipeline for protein-protein interaction drug discovery identifies an SARS-CoV-2 inhibitor

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    Protein–protein interactions (PPIs) offer great opportunities to expand the druggable proteome and therapeutically tackle various diseases, but remain challenging targets for drug discovery. Here, we provide a comprehensive pipeline that combines experimental and computational tools to identify and validate PPI targets and perform early-stage drug discovery. We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays or AlphaFold-Multimer predictions. Using the quantitative assay LuTHy together with our machine learning algorithm, we identified high-confidence interactions among SARS-CoV-2 proteins for which we predicted three-dimensional structures using AlphaFold-Multimer. We employed VirtualFlow to target the contact interface of the NSP10-NSP16 SARS-CoV-2 methyltransferase complex by ultra-large virtual drug screening. Thereby, we identified a compound that binds to NSP10 and inhibits its interaction with NSP16, while also disrupting the methyltransferase activity of the complex, and SARS-CoV-2 replication. Overall, this pipeline will help to prioritize PPI targets to accelerate the discovery of early-stage drug candidates targeting protein complexes and pathways
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