Protein Kinase Inhibitors - AI Medical Compendium

Discovery and Characterization of Novel Receptor-Interacting Protein Kinase 1 Inhibitors Using Deep Learning and Virtual Screening.

ACS chemical neuroscience Apr 3, 2025

Receptor-interacting protein kinase 1 (RIPK1) serves as a critical mediator of cell necroptosis and represents a promising therapeutic target for various human neurodegenerative diseases and inflammatory diseases. Nonetheless, the RIPK1 inhibitors cu...

Drug Evaluation, Preclinical HT29 Cells Protein Kinase Inhibitors Drug Discovery Deep Learning Necroptosis Receptor-Interacting Protein Serine-Threonine Kinases Humans Molecular Docking Simulation

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A Specialized and Enhanced Deep Generation Model for Active Molecular Design Targeting Kinases Guided by Affinity Prediction Models and Reinforcement Learning.

Journal of chemical information and modeling Apr 2, 2025

Kinases are critical regulators in numerous cellular processes, and their dysregulation is linked to various diseases, including cancer. Thus, protein kinases have emerged as major drug targets at present, with approximately a quarter to a third of g...

Models, Molecular Protein Kinases Protein Kinase Inhibitors Drug Design Deep Learning

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Can Deep Learning Blind Docking Methods be Used to Predict Allosteric Compounds?

Journal of chemical information and modeling Apr 1, 2025

Allosteric compounds offer an alternative mode of inhibition to orthosteric compounds with opportunities for selectivity and noncompetition. Structure-based drug design (SBDD) of allosteric compounds introduces complications compared to their orthost...

Cyclin-Dependent Kinase 2 Allosteric Regulation Molecular Docking Simulation Ligands Drug Design Protein Conformation Deep Learning Protein Kinase Inhibitors

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Discovery and characterization of novel FAK inhibitors for breast cancer therapy via hybrid virtual screening, biological evaluation and molecular dynamics simulations.

Bioorganic chemistry Mar 26, 2025

Focal adhesion kinase (FAK) is a critical drug target implicated in various disease pathways, including hematological malignancies and breast cancer. Therefore, identifying FAK inhibitors with novel scaffolds could offer new opportunities for develop...

Dose-Response Relationship, Drug Drug Screening Assays, Antitumor Structure-Activity Relationship Drug Discovery Antineoplastic Agents Humans Cell Proliferation Female Protein Kinase Inhibitors Breast Neoplasms Focal Adhesion Kinase 1 Molecular Docking Simulation Focal Adhesion Protein-Tyrosine Kinases Molecular Structure Molecular Dynamics Simulation Drug Evaluation, Preclinical

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Insights into phosphorylation-induced influences on conformations and inhibitor binding of CDK6 through GaMD trajectory-based deep learning.

Physical chemistry chemical physics : PCCP Mar 26, 2025

The phosphorylation of residue T177 produces a significant effect on the conformational dynamics of CDK6. Gaussian accelerated molecular dynamics (GaMD) simulations followed by deep learning (DL) are applied to explore the molecular mechanism of the ...

Thermodynamics Cyclin-Dependent Kinase 6 Deep Learning Protein Binding Humans Phosphorylation Molecular Dynamics Simulation Protein Conformation Protein Kinase Inhibitors

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In silico discovery of novel compounds for FAK activation using virtual screening, AI-based prediction, and molecular dynamics.

Computational biology and chemistry Mar 25, 2025

Focal Adhesion Kinase (FAK) is a non-receptor tyrosine kinase that plays a crucial role in cell proliferation, migration, and signal transduction. FAK is overexpressed in metastatic and advanced-stage cancers, where it is considered a key kinase in c...

Humans Artificial Intelligence Molecular Docking Simulation Drug Discovery Drug Evaluation, Preclinical Molecular Structure Protein Kinase Inhibitors Molecular Dynamics Simulation Focal Adhesion Protein-Tyrosine Kinases

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Ontology-driven identification of inconsistencies in clinical data: A case study in lung cancer phenotyping.

Journal of biomedical informatics Mar 21, 2025

OBJECTIVE: To illustrate the use of an ontology in evaluating data quality in the medical field, focusing on phenotyping lung cancers.

ErbB Receptors Protein Kinase Inhibitors Data Warehousing Mutation Data Accuracy Biological Ontologies Humans Anaplastic Lymphoma Kinase Phenotype Lung Neoplasms

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Artificial intelligence system for predicting hand-foot skin reaction induced by vascular endothelial growth factor receptor inhibitors.

Scientific reports Mar 21, 2025

Hand-foot skin reaction (HFSR) is a common adverse effect of vascular endothelial growth factor receptor (VEGFR) inhibitors that significantly impacts patients' quality of life. Prevention and management of HFSR require individualized approaches, but...

Protein Kinase Inhibitors Receptors, Vascular Endothelial Growth Factor Hand-Foot Syndrome Adult Female Male Risk Factors Middle Aged Aged Humans Artificial Intelligence

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Computational discovery of novel PI3KC2α inhibitors using structure-based pharmacophore modeling, machine learning and molecular dynamic simulation.

Journal of molecular graphics & modelling Mar 15, 2025

PI3KC2α is a lipid kinase associated with cancer metastasis and thrombosis. In this study, we present a novel computational workflow integrating structure-based pharmacophore modeling, machine learning (ML), and molecular dynamics (MD) simulations to...

Humans Machine Learning Molecular Docking Simulation Drug Discovery Protein Binding Phosphatidylinositol 3-Kinases Phosphoinositide-3 Kinase Inhibitors Molecular Dynamics Simulation Pharmacophore Ligands Protein Kinase Inhibitors

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Identification of Novel Fourth-Generation Allosteric Inhibitors Targeting Inactive State of EGFR T790M/L858R/C797S and T790M/L858R Mutations: A Combined Machine Learning and Molecular Dynamics Approach.

The journal of physical chemistry. B Mar 7, 2025

Targeted therapy with an allosteric inhibitor (AIs) is an important area of research in patients with epidermal growth factor receptor (EGFR) mutations. Current treatment of nonsmall cell lung cancer patients with EGFR mutations using orthosteric inh...

Quantitative Structure-Activity Relationship ErbB Receptors Protein Kinase Inhibitors Allosteric Regulation Machine Learning Mutation Molecular Dynamics Simulation Humans

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AIMC Topic: Protein Kinase Inhibitors

Discovery and Characterization of Novel Receptor-Interacting Protein Kinase 1 Inhibitors Using Deep Learning and Virtual Screening.

A Specialized and Enhanced Deep Generation Model for Active Molecular Design Targeting Kinases Guided by Affinity Prediction Models and Reinforcement Learning.

Can Deep Learning Blind Docking Methods be Used to Predict Allosteric Compounds?

Discovery and characterization of novel FAK inhibitors for breast cancer therapy via hybrid virtual screening, biological evaluation and molecular dynamics simulations.

Insights into phosphorylation-induced influences on conformations and inhibitor binding of CDK6 through GaMD trajectory-based deep learning.

In silico discovery of novel compounds for FAK activation using virtual screening, AI-based prediction, and molecular dynamics.

Ontology-driven identification of inconsistencies in clinical data: A case study in lung cancer phenotyping.

Artificial intelligence system for predicting hand-foot skin reaction induced by vascular endothelial growth factor receptor inhibitors.

Computational discovery of novel PI3KC2α inhibitors using structure-based pharmacophore modeling, machine learning and molecular dynamic simulation.

Identification of Novel Fourth-Generation Allosteric Inhibitors Targeting Inactive State of EGFR T790M/L858R/C797S and T790M/L858R Mutations: A Combined Machine Learning and Molecular Dynamics Approach.

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AIMC Topic: Protein Kinase Inhibitors

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