AI Medical Compendium Topic

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

Cyclin-Dependent Kinase 2

Showing 1 to 7 of 7 articles

Clear Filters

Supervised machine learning techniques to predict binding affinity. A study for cyclin-dependent kinase 2.

Biochemical and biophysical research communications 29017921
Here we report the development of a machine-learning model to predict binding affinity based on the crystallographic structures of protein-ligand complexes. We used an ensemble of crystallographic structures (resolution better than 1.5 Å resolution) ...
Antineoplastic Agents Cyclin-Dependent Kinase 2 Databases, Protein Datasets as Topic Drug Design Humans Inhibitory Concentration 50 Ligands Molecular Docking Simulation Protein Kinase Inhibitors ROC Curve Supervised Machine Learning Thermodynamics
View on PubMed DOI

Machine Learning to Predict Binding Affinity.

Methods in molecular biology (Clifton, N.J.) 31452110
Recent progress in the development of scientific libraries with machine-learning techniques paved the way for the implementation of integrated computational tools to predict ligand-binding affinity. The prediction of binding affinity uses the atomic ...
Algorithms Cyclin-Dependent Kinase 2 Databases, Protein HIV Protease Humans Ligands Machine Learning Models, Statistical Molecular Docking Simulation Molecular Dynamics Simulation Proteins Software Supervised Machine Learning Web Browser
View on PubMed DOI

Reaction-Based Enumeration, Active Learning, and Free Energy Calculations To Rapidly Explore Synthetically Tractable Chemical Space and Optimize Potency of Cyclin-Dependent Kinase 2 Inhibitors.

Journal of chemical information and modeling 31404495
The hit-to-lead and lead optimization processes usually involve the design, synthesis, and profiling of thousands of analogs prior to clinical candidate nomination. A hit finding campaign may begin with a virtual screen that explores millions of comp...
Cyclin-Dependent Kinase 2 Drug Design Drug Discovery Humans Machine Learning Models, Molecular Protein Kinase Inhibitors Small Molecule Libraries Thermodynamics
View on PubMed DOI

Identification of novel CDK2 inhibitors by a multistage virtual screening method based on SVM, pharmacophore and docking model.

Journal of enzyme inhibition and medicinal chemistry 31760818
Cyclin-dependent kinase 2 (CDK2) is the family of Ser/Thr protein kinases that has emerged as a highly selective with low toxic cancer therapy target. A multistage virtual screening method combined by SVM, protein-ligand interaction fingerprints (PLI...
A549 Cells Antineoplastic Agents Cell Proliferation Cyclin-Dependent Kinase 2 Dose-Response Relationship, Drug Drug Evaluation, Preclinical Drug Screening Assays, Antitumor HCT116 Cells Humans Molecular Docking Simulation Molecular Structure Protein Kinase Inhibitors Structure-Activity Relationship Support Vector Machine
View on PubMed DOI

Application of Machine Learning Techniques to Predict Binding Affinity for Drug Targets: A Study of Cyclin-Dependent Kinase 2.

Current medicinal chemistry 31729287
BACKGROUND: The elucidation of the structure of cyclin-dependent kinase 2 (CDK2) made it possible to develop targeted scoring functions for virtual screening aimed to identify new inhibitors for this enzyme. CDK2 is a protein target for the developme...
Cyclin-Dependent Kinase 2 Humans Ligands Machine Learning Molecular Docking Simulation Pharmaceutical Preparations Protein Binding Supervised Machine Learning
View on PubMed DOI

Ensemble learning from ensemble docking: revisiting the optimum ensemble size problem.

Scientific reports 35013496
Despite considerable advances obtained by applying machine learning approaches in protein-ligand affinity predictions, the incorporation of receptor flexibility has remained an important bottleneck. While ensemble docking has been used widely as a so...
Binding Sites Crystallography, X-Ray Cyclin-Dependent Kinase 2 Ligands Machine Learning Molecular Docking Simulation Protein Binding Protein Conformation Structure-Activity Relationship Support Vector Machine
View on PubMed DOI

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

Journal of chemical information and modeling 40167386
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...
Allosteric Regulation Cyclin-Dependent Kinase 2 Deep Learning Drug Design Ligands Molecular Docking Simulation Protein Conformation Protein Kinase Inhibitors
View on PubMed DOI
Popular Topics
Recent Journals