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Protein Kinase Inhibitors

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Classification of FLT3 inhibitors and SAR analysis by machine learning methods.

Molecular diversity May 5, 2023
FMS-like tyrosine kinase 3 (FLT3) is a type III receptor tyrosine kinase, which is an important target for anti-cancer therapy. In this work, we conducted a structure-activity relationship (SAR) study on 3867 FLT3 inhibitors we collected. MACCS finge...
Humans Neural Networks, Computer Structure-Activity Relationship Protein Kinase Inhibitors fms-Like Tyrosine Kinase 3 Algorithms Support Vector Machine Machine Learning
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Strategy toward Kinase-Selective Drug Discovery.

Journal of chemical theory and computation Feb 23, 2023
Kinase drug selectivity is the ground challenge in cancer research. Due to the structurally similar kinase drug pockets, off-target inhibitor toxicity has been a major cause for clinical trial failures. The pockets are similar but not identical. Here...
Drug Discovery Protein Kinase Inhibitors Humans Computational Biology Artificial Intelligence
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A radiomics-based deep learning approach to predict progression free-survival after tyrosine kinase inhibitor therapy in non-small cell lung cancer.

Cancer imaging : the official publication of the International Cancer Imaging Society Jan 20, 2023
BACKGROUND: The epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are a first-line therapy for non-small cell lung cancer (NSCLC) with EGFR mutations. Approximately half of the patients with EGFR-mutated NSCLC are treated with...
Humans Deep Learning ErbB Receptors Protein Kinase Inhibitors Tyrosine Kinase Inhibitors Mutation Progression-Free Survival Disease-Free Survival Lung Neoplasms Carcinoma, Non-Small-Cell Lung
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Interpretable Machine Learning Models for Molecular Design of Tyrosine Kinase Inhibitors Using Variational Autoencoders and Perturbation-Based Approach of Chemical Space Exploration.

International journal of molecular sciences Sep 24, 2022
In the current study, we introduce an integrative machine learning strategy for the autonomous molecular design of protein kinase inhibitors using variational autoencoders and a novel cluster-based perturbation approach for exploration of the chemica...
Machine Learning Molecular Structure src-Family Kinases Protein Kinase Inhibitors Space Flight
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Discovery of moiety preference by Shapley value in protein kinase family using random forest models.

BMC bioinformatics Apr 15, 2022
BACKGROUND: Human protein kinases play important roles in cancers, are highly co-regulated by kinase families rather than a single kinase, and complementarily regulate signaling pathways. Even though there are > 100,000 protein kinase inhibitors, onl...
Protein Kinase Inhibitors Protein Kinases United States Food and Drug Administration Humans United States Pharmaceutical Preparations Machine Learning
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A novel graph convolutional neural network for predicting interaction sites on protein kinase inhibitors in phosphorylation.

Scientific reports Jan 7, 2022
Protein kinase-inhibitor interactions are key to the phosphorylation of proteins involved in cell proliferation, differentiation, and apoptosis, which shows the importance of binding mechanism research and kinase inhibitor design. In this study, a no...
Amino Acid Motifs Phosphorylation Neural Networks, Computer Protein Kinases Protein Kinase Inhibitors Machine Learning Algorithms
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Discovery of Pyrazolo[3,4-]pyridazinone Derivatives as Selective DDR1 Inhibitors via Deep Learning Based Design, Synthesis, and Biological Evaluation.

Journal of medicinal chemistry Nov 25, 2021
Alterations of discoidin domain receptor1 (DDR1) may lead to increased production of inflammatory cytokines, making DDR1 an attractive target for inflammatory bowel disease (IBD) therapy. A scaffold-based molecular design workflow was established and...
Drug Design Dextran Sulfate Humans Mice Mice, Inbred ICR Drug Screening Assays, Antitumor Drug Discovery Animals Colitis Deep Learning Mice, Inbred C57BL Molecular Structure Anti-Inflammatory Agents Pyridazines Discoidin Domain Receptor 1 Protein Kinase Inhibitors Pyrazolones
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Deep learning-driven scaffold hopping in the discovery of Akt kinase inhibitors.

Chemical communications (Cambridge, England) Oct 12, 2021
Scaffold hopping has been widely used in drug discovery and is a topic of high interest. Here a deep conditional transformer neural network, SyntaLinker, was applied for the scaffold hopping of a phase III clinical Akt inhibitor, AZD5363. A number of...
Pyrroles Protein Kinase Inhibitors Pyrimidines Deep Learning Molecular Structure Humans Proto-Oncogene Proteins c-akt Drug Discovery
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Kinase Inhibitor Scaffold Hopping with Deep Learning Approaches.

Journal of chemical information and modeling Sep 29, 2021
The protein kinase family contains many promising drug targets. Many kinase inhibitors target the ATP-binding pocket, leading to approved drugs in past decades. Scaffold hopping is an effective approach for drug design. The kinase ATP-binding pocket ...
Protein Binding Protein Kinases Protein Kinase Inhibitors Drug Design Deep Learning
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Interpretable deep recommender system model for prediction of kinase inhibitor efficacy across cancer cell lines.

Scientific reports Aug 6, 2021
Computational models for drug sensitivity prediction have the potential to significantly improve personalized cancer medicine. Drug sensitivity assays, combined with profiling of cancer cell lines and drugs become increasingly available for training ...
Computer Simulation Neoplasms Protein Kinase Inhibitors Humans Gene Expression Regulation, Neoplastic Tumor Cells, Cultured Prognosis Deep Learning Algorithms Biomarkers, Tumor
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