AIMC Topic: Protein Kinase Inhibitors

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Guided Docking as a Data Generation Approach Facilitates Structure-Based Machine Learning on Kinases.

Journal of chemical information and modeling May 15, 2024
Drug discovery pipelines nowadays rely on machine learning models to explore and evaluate large chemical spaces. While including 3D structural information is considered beneficial, structural models are hindered by the availability of protein-ligand ...
Phosphotransferases Ligands Protein Conformation Protein Kinase Inhibitors Neural Networks, Computer Machine Learning Protein Binding Protein Kinases Molecular Docking Simulation Drug Discovery
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GraphEGFR: Multi-task and transfer learning based on molecular graph attention mechanism and fingerprints improving inhibitor bioactivity prediction for EGFR family proteins on data scarcity.

Journal of computational chemistry May 7, 2024
The proteins within the human epidermal growth factor receptor (EGFR) family, members of the tyrosine kinase receptor family, play a pivotal role in the molecular mechanisms driving the development of various tumors. Tyrosine kinase inhibitors, key c...
Humans Neural Networks, Computer Machine Learning Protein Kinase Inhibitors Drug Discovery Deep Learning ErbB Receptors
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Prognostic value of combining clinical factors, F-FDG PET-based intensity, volumetric features, and deep learning predictor in patients with EGFR-mutated lung adenocarcinoma undergoing targeted therapies: a cross-scanner and temporal validation study.

Annals of nuclear medicine May 5, 2024
OBJECTIVE: To investigate the prognostic value of F-FDG PET-based intensity, volumetric features, and deep learning (DL) across different generations of PET scanners in patients with epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma...
Humans Prognosis Retrospective Studies Adenocarcinoma of Lung Lung Neoplasms Adult Male Mutation ErbB Receptors Middle Aged Positron-Emission Tomography Protein Kinase Inhibitors Deep Learning Fluorodeoxyglucose F18 Female Molecular Targeted Therapy Aged Aged, 80 and over
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Unveiling G-protein coupled receptor kinase-5 inhibitors for chronic degenerative diseases: Multilayered prioritization employing explainable machine learning-driven multi-class QSAR, ligand-based pharmacophore and free energy-inspired molecular simulation.

International journal of biological macromolecules Apr 30, 2024
GRK5 holds a pivotal role in cellular signaling pathways, with its overexpression in cardiomyocytes, neuronal cells, and tumor cells strongly associated with various chronic degenerative diseases, which highlights the urgent need for potential inhibi...
Molecular Docking Simulation Protein Binding Chronic Disease Molecular Dynamics Simulation Humans Machine Learning Binding Sites Thermodynamics Pharmacophore G-Protein-Coupled Receptor Kinase 5 Ligands Quantitative Structure-Activity Relationship Protein Kinase Inhibitors
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Application of parallel artificial membrane permeability assay technique and chemometric modeling for blood-brain barrier permeability prediction of protein kinase inhibitors.

Future medicinal chemistry Apr 19, 2024
This study aims to investigate the passive diffusion of protein kinase inhibitors through the blood-brain barrier (BBB) and to develop a model for their permeability prediction. We used the parallel artificial membrane permeability assay to obtain ...
Membranes, Artificial Permeability Humans Quantitative Structure-Activity Relationship Protein Kinase Inhibitors Blood-Brain Barrier Support Vector Machine
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Exploratory drug discovery in breast cancer patients: A multimodal deep learning approach to identify novel drug candidates targeting RTK signaling.

Computers in biology and medicine Apr 16, 2024
Breast cancer, a highly formidable and diverse malignancy predominantly affecting women globally, poses a significant threat due to its intricate genetic variability, rendering it challenging to diagnose accurately. Various therapies such as immunoth...
Receptor Protein-Tyrosine Kinases Signal Transduction Quantitative Structure-Activity Relationship Female Protein Kinase Inhibitors Breast Neoplasms Drug Discovery Antineoplastic Agents Humans Deep Learning
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Ligand-based pharmacophore modeling and machine learning for the discovery of potent aurora A kinase inhibitory leads of novel chemotypes.

Molecular diversity Mar 6, 2024
Aurora-A (AURKA) is serine/threonine protein kinase involved in the regulation of numerous processes of cell division. Numerous studies have demonstrated strong association between AURKA and cancer. AURKA is overexpressed in many cancers, such as col...
Quantitative Structure-Activity Relationship Protein Kinase Inhibitors Pharmacophore Aurora Kinase A Machine Learning Drug Discovery Models, Molecular Ligands Humans
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A deep learning model of tumor cell architecture elucidates response and resistance to CDK4/6 inhibitors.

Nature cancer Mar 5, 2024
Cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6is) have revolutionized breast cancer therapy. However, <50% of patients have an objective response, and nearly all patients develop resistance during therapy. To elucidate the underlying mechanisms, ...
Female Breast Neoplasms Humans Drug Resistance, Neoplasm Mice Protein Kinase Inhibitors Pyridines Animals Cyclin-Dependent Kinase 4 Piperazines Deep Learning Cyclin-Dependent Kinase 6 Xenograft Model Antitumor Assays Cell Line, Tumor
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Computational discovery of novel FYN kinase inhibitors: a cheminformatics and machine learning-driven approach to targeted cancer and neurodegenerative therapy.

Molecular diversity Feb 28, 2024
In this study, we explored the potential of novel inhibitors for FYN kinase, a critical target in cancer and neurodegenerative disorders, by integrating advanced cheminformatics, machine learning, and molecular simulation techniques. Our approach inv...
Protein Kinase Inhibitors Cheminformatics Proto-Oncogene Proteins c-fyn Neurodegenerative Diseases Molecular Dynamics Simulation Piperidines Humans Machine Learning Drug Discovery Neoplasms Antineoplastic Agents Molecular Docking Simulation
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A deep learning-based theoretical protocol to identify potentially isoform-selective PI3Kα inhibitors.

Molecular diversity Feb 2, 2024
Phosphoinositide 3-kinase alpha (PI3Kα) is one of the most frequently dysregulated kinases known for their pivotal role in many oncogenic diseases. While the side effects linked to existing drugs against PI3Kα-induced cancers provide an avenue for fu...
Protein Kinase Inhibitors Phosphoinositide-3 Kinase Inhibitors Humans Protein Binding Class I Phosphatidylinositol 3-Kinases Phosphatidylinositol 3-Kinases Ligands Molecular Docking Simulation Drug Design Deep Learning
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