Protein Kinase Inhibitors

Application of parallel artificial membrane permeability assay technique and chemometric modeling for blood-brain barrier permeability prediction of protein kinase inhibitors.

Future medicinal chemistry 38639375

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 ...

Blood-Brain Barrier Humans Membranes, Artificial Permeability Protein Kinase Inhibitors Quantitative Structure-Activity Relationship Support Vector Machine

View on PubMed DOI

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 38642491

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...

Antineoplastic Agents Breast Neoplasms Deep Learning Drug Discovery Female Humans Protein Kinase Inhibitors Quantitative Structure-Activity Relationship Receptor Protein-Tyrosine Kinases Signal Transduction

View on PubMed DOI

A multimodal Transformer Network for protein-small molecule interactions enhances predictions of kinase inhibition and enzyme-substrate relationships.

PLoS computational biology 38768223

The activities of most enzymes and drugs depend on interactions between proteins and small molecules. Accurate prediction of these interactions could greatly accelerate pharmaceutical and biotechnological research. Current machine learning models des...

Amino Acid Sequence Computational Biology Deep Learning Humans Machine Learning Protein Binding Protein Kinase Inhibitors Protein Kinases Proteins Small Molecule Libraries Substrate Specificity

View on PubMed DOI

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

Journal of chemical information and modeling 38751014

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 ...

Drug Discovery Ligands Machine Learning Molecular Docking Simulation Neural Networks, Computer Phosphotransferases Protein Binding Protein Conformation Protein Kinase Inhibitors Protein Kinases

View on PubMed DOI

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 38713612

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...

Deep Learning Drug Discovery ErbB Receptors Humans Machine Learning Neural Networks, Computer Protein Kinase Inhibitors

View on PubMed DOI

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 38704786

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...

Adenocarcinoma of Lung Adult Aged Aged, 80 and over Deep Learning ErbB Receptors Female Fluorodeoxyglucose F18 Humans Lung Neoplasms Male Middle Aged Molecular Targeted Therapy Mutation Positron-Emission Tomography Prognosis Protein Kinase Inhibitors Retrospective Studies

View on PubMed DOI

Discovery of a Novel and Potent LCK Inhibitor for Leukemia Treatment via Deep Learning and Molecular Docking.

Journal of chemical information and modeling 38847742

The lymphocyte-specific protein tyrosine kinase (LCK) plays a crucial role in both T-cell development and activation. Dysregulation of LCK signaling has been demonstrated to drive the oncogenesis of T-cell acute lymphoblastic leukemia (T-ALL), thus p...

Animals Antineoplastic Agents Cell Line, Tumor Cell Proliferation Deep Learning Drug Discovery Humans Lymphocyte Specific Protein Tyrosine Kinase p56(lck) Mice Molecular Docking Simulation Protein Kinase Inhibitors

View on PubMed DOI

From Deep Learning to the Discovery of Promising VEGFR-2 Inhibitors.

ChemMedChem 38726553

Vascular endothelial growth factor receptor 2 (VEGFR-2) stands as a prominent therapeutic target in oncology, playing a critical role in angiogenesis, tumor growth, and metastasis. FDA-approved VEGFR-2 inhibitors are associated with diverse side effe...

Antineoplastic Agents Cell Line, Tumor Cell Proliferation Deep Learning Dose-Response Relationship, Drug Drug Discovery Drug Screening Assays, Antitumor Humans Molecular Docking Simulation Molecular Structure Protein Kinase Inhibitors Structure-Activity Relationship Vascular Endothelial Growth Factor Receptor-2

View on PubMed DOI

An ensemble machine learning model generates a focused screening library for the identification of CDK8 inhibitors.

Protein science : a publication of the Protein Society 38723187

The identification of an effective inhibitor is an important starting step in drug development. Unfortunately, many issues such as the characterization of protein binding sites, the screening library, materials for assays, etc., make drug screening a...

Cyclin-Dependent Kinase 8 Drug Evaluation, Preclinical Humans Machine Learning Molecular Docking Simulation Protein Kinase Inhibitors Small Molecule Libraries

View on PubMed DOI

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 38697440

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...

Binding Sites Chronic Disease G-Protein-Coupled Receptor Kinase 5 Humans Ligands Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Pharmacophore Protein Binding Protein Kinase Inhibitors Quantitative Structure-Activity Relationship Thermodynamics

View on PubMed DOI

AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Application of parallel artificial membrane permeability assay technique and chemometric modeling for blood-brain barrier permeability prediction of protein kinase inhibitors.

Exploratory drug discovery in breast cancer patients: A multimodal deep learning approach to identify novel drug candidates targeting RTK signaling.

A multimodal Transformer Network for protein-small molecule interactions enhances predictions of kinase inhibition and enzyme-substrate relationships.

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

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.

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.

Discovery of a Novel and Potent LCK Inhibitor for Leukemia Treatment via Deep Learning and Molecular Docking.

From Deep Learning to the Discovery of Promising VEGFR-2 Inhibitors.

An ensemble machine learning model generates a focused screening library for the identification of CDK8 inhibitors.

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.

Popular Topics

Recent Journals