Protein Kinase Inhibitors

Discovery of novel ULK1 inhibitors through machine learning-guided virtual screening and biological evaluation.

Future medicinal chemistry 39145469

Build a virtual screening model for ULK1 inhibitors based on artificial intelligence. Build machine learning and deep learning classification models and combine molecular docking and biological evaluation to screen ULK1 inhibitors from 13 million co...

Autophagy-Related Protein-1 Homolog Drug Discovery Drug Evaluation, Preclinical Humans Intracellular Signaling Peptides and Proteins Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Molecular Structure Protein Kinase Inhibitors

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Unveiling Conformational States of CDK6 Caused by Binding of Vcyclin Protein and Inhibitor by Combining Gaussian Accelerated Molecular Dynamics and Deep Learning.

Molecules (Basel, Switzerland) 38893554

CDK6 plays a key role in the regulation of the cell cycle and is considered a crucial target for cancer therapy. In this work, conformational transitions of CDK6 were identified by using Gaussian accelerated molecular dynamics (GaMD), deep learning (...

Binding Sites Cyclin-Dependent Kinase 6 Deep Learning Humans Molecular Dynamics Simulation Normal Distribution Principal Component Analysis Protein Binding Protein Conformation Protein Kinase Inhibitors Thermodynamics

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Potential inhibitors of VEGFR1, VEGFR2, and VEGFR3 developed through Deep Learning for the treatment of Cervical Cancer.

Scientific reports 38858458

Cervical cancer stands as a prevalent gynaecologic malignancy affecting women globally, often linked to persistent human papillomavirus infection. Biomarkers associated with cervical cancer, including VEGF-A, VEGF-B, VEGF-C, VEGF-D, and VEGF-E, show ...

Deep Learning Female Humans Molecular Docking Simulation Protein Kinase Inhibitors Uterine Cervical Neoplasms Vascular Endothelial Growth Factor Receptor-1 Vascular Endothelial Growth Factor Receptor-2 Vascular Endothelial Growth Factor Receptor-3

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Molecular docking aided machine learning for the identification of potential VEGFR inhibitors against renal cell carcinoma.

Medical oncology (Northwood, London, England) 38981988

Renal cell carcinoma is a highly vascular tumor associated with vascular endothelial growth factor (VEGF) expression. The Vascular Endothelial Growth Factor -2 (VEGF-2) and its receptor was identified as a potential anti-cancer target, and it plays a...

Antineoplastic Agents Carcinoma, Renal Cell Drug Repositioning Humans Kidney Neoplasms Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Protein Kinase Inhibitors Vascular Endothelial Growth Factor Receptor-2

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Construction of IRAK4 inhibitor activity prediction model based on machine learning.

Molecular diversity 38970641

Interleukin-1 receptor-associated kinase 4 (IRAK4) is a crucial serine/threonine protein kinase that belongs to the IRAK family and plays a pivotal role in Toll-like receptor (TLR) and Interleukin-1 receptor (IL-1R) signaling pathways. Due to IRAK4's...

Humans Interleukin-1 Receptor-Associated Kinases Machine Learning Molecular Docking Simulation Protein Kinase Inhibitors

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Deriving general structure-activity/selectivity relationship patterns for different subfamilies of cyclin-dependent kinase inhibitors using machine learning methods.

Scientific reports 38961127

Cyclin-dependent kinases (CDKs) play essential roles in regulating the cell cycle and are among the most critical targets for cancer therapy and drug discovery. The primary objective of this research is to derive general structure-activity relationsh...

Cyclin-Dependent Kinases Drug Discovery Humans Machine Learning Neural Networks, Computer Protein Kinase Inhibitors Structure-Activity Relationship

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Scaffold-Hopped Compound Identification by Ligand-Based Approaches with a Prospective Affinity Test.

Journal of chemical information and modeling 38950192

Scaffold-hopped (SH) compounds are bioactive compounds structurally different from known active compounds. Identifying SH compounds in the ligand-based approaches has been a central issue in medicinal chemistry, and various molecular representations ...

Algorithms Humans Ligands Models, Molecular Protein Kinase Inhibitors Support Vector Machine

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Chemical analogue based drug design for cancer treatment targeting PI3K: integrating machine learning and molecular modeling.

Molecular diversity 39154146

Cancer is a generic term for a group of disorders defined by uncontrolled cell growth and the potential to invade or spread to other parts of the body. Gene and epigenetic alterations disrupt normal cellular control, leading to abnormal cell prolifer...

Antineoplastic Agents Class Ib Phosphatidylinositol 3-Kinase Drug Design Humans Ligands Machine Learning Models, Molecular Molecular Docking Simulation Molecular Dynamics Simulation Neoplasms Phosphatidylinositol 3-Kinases Phosphoinositide-3 Kinase Inhibitors Protein Binding Protein Kinase Inhibitors

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Identification of mycobacterial Thymidylate kinase inhibitors: a comprehensive pharmacophore, machine learning, molecular docking, and molecular dynamics simulation studies.

Molecular diversity 39152354

Thymidylate kinase (TMK) is a pivotal enzyme in Mycobacterium tuberculosis (Mtb), crucial for phosphorylating thymidine monophosphate (dTMP) to thymidine diphosphate (dTDP), thereby playing a critical role in DNA biosynthesis. Dysregulation or inhibi...

Antitubercular Agents Enzyme Inhibitors Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Mycobacterium tuberculosis Nucleoside-Phosphate Kinase Pharmacophore Protein Binding Protein Kinase Inhibitors

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Machine Learning Prediction of On/Off Target-driven Clinical Adverse Events.

Pharmaceutical research 39095534

OBJECTIVE: Currently, 90% of clinical drug development fails, where 30% of these failures are due to clinical toxicity. The current extensive animal toxicity studies are not predictive of clinical adverse events (AEs) at clinical doses, while current...

Animals Drug Development Drug-Related Side Effects and Adverse Reactions Humans Machine Learning Protein Kinase Inhibitors

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

Discovery of novel ULK1 inhibitors through machine learning-guided virtual screening and biological evaluation.

Unveiling Conformational States of CDK6 Caused by Binding of Vcyclin Protein and Inhibitor by Combining Gaussian Accelerated Molecular Dynamics and Deep Learning.

Potential inhibitors of VEGFR1, VEGFR2, and VEGFR3 developed through Deep Learning for the treatment of Cervical Cancer.

Molecular docking aided machine learning for the identification of potential VEGFR inhibitors against renal cell carcinoma.

Construction of IRAK4 inhibitor activity prediction model based on machine learning.

Deriving general structure-activity/selectivity relationship patterns for different subfamilies of cyclin-dependent kinase inhibitors using machine learning methods.

Scaffold-Hopped Compound Identification by Ligand-Based Approaches with a Prospective Affinity Test.

Chemical analogue based drug design for cancer treatment targeting PI3K: integrating machine learning and molecular modeling.

Identification of mycobacterial Thymidylate kinase inhibitors: a comprehensive pharmacophore, machine learning, molecular docking, and molecular dynamics simulation studies.

Machine Learning Prediction of On/Off Target-driven Clinical Adverse Events.

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