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Agammaglobulinaemia Tyrosine Kinase

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Design, synthesis and biological evaluation of 7H-pyrrolo[2,3-d]pyrimidin-4-amine derivatives as selective Btk inhibitors with improved pharmacokinetic properties for the treatment of rheumatoid arthritis.

European journal of medicinal chemistry 29324347
Bruton's tyrosine kinase (Btk) is a Tec family kinase with a well-defined role in the B cell receptor (BCR) and Fcγ receptor (FcR) signaling pathways, which makes it a uniquely attractive target for the treatment of autoimmune diseases, such as rheum...
Agammaglobulinaemia Tyrosine Kinase Animals Arthritis, Rheumatoid Cell Line Cell Proliferation Dogs Dose-Response Relationship, Drug Drug Design Haplorhini Humans Mice Microsomes, Liver Models, Molecular Molecular Structure Protein Kinase Inhibitors Protein-Tyrosine Kinases Pyrimidines Pyrroles Rats Rats, Sprague-Dawley Structure-Activity Relationship
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Bayesian machine learning to discover Bruton's tyrosine kinase inhibitors.

Chemical biology & drug design 31855311
Bruton's tyrosine kinase (BTK) has a crucial role in multiple cell signaling pathways including B-cell antigen receptor (BCR) and Fc receptor (FcR) signaling cascades, which has attracted much attention to find BTK inhibitors to treat autoimmune dise...
Agammaglobulinaemia Tyrosine Kinase Bayes Theorem Humans Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Protein Kinase Inhibitors Reproducibility of Results
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Machine learning-based classification models for non-covalent Bruton's tyrosine kinase inhibitors: predictive ability and interpretability.

Molecular diversity 37479824
In this study, we built classification models using machine learning techniques to predict the bioactivity of non-covalent inhibitors of Bruton's tyrosine kinase (BTK) and to provide interpretable and transparent explanations for these predictions. T...
Agammaglobulinaemia Tyrosine Kinase Algorithms Humans Machine Learning Neural Networks, Computer Protein Kinase Inhibitors Support Vector Machine Tyrosine Kinase Inhibitors
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Integrating machine learning algorithms and single-cell analysis to identify gut microbiota-related macrophage biomarkers in atherosclerotic plaques.

Frontiers in cellular and infection microbiology 38716195
OBJECTIVE: The relationship between macrophages and the gut microbiota in patients with atherosclerosis remains poorly defined, and effective biological markers are lacking. This study aims to elucidate the interplay between gut microbial communities...
Agammaglobulinaemia Tyrosine Kinase Algorithms Antigens, CD Antigens, Differentiation, Myelomonocytic Atherosclerosis Biomarkers CD68 Molecule Gastrointestinal Microbiome Gene Expression Profiling Gene Regulatory Networks Humans Interferon Regulatory Factors Machine Learning Macrophages Plaque, Atherosclerotic Receptors, CCR1 Single-Cell Analysis
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