AIMC Topic: Cyclin-Dependent Kinase 2

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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...
Molecular Docking Simulation Drug Design Protein Kinase Inhibitors Cyclin-Dependent Kinase 2 Allosteric Regulation Deep Learning Ligands Protein Conformation
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Ensemble learning from ensemble docking: revisiting the optimum ensemble size problem.

Scientific reports Jan 10, 2022
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...
Molecular Docking Simulation Cyclin-Dependent Kinase 2 Protein Binding Machine Learning Protein Conformation Support Vector Machine Structure-Activity Relationship Binding Sites Ligands Crystallography, X-Ray
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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 Aug 22, 2019
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...
Small Molecule Libraries Cyclin-Dependent Kinase 2 Protein Kinase Inhibitors Thermodynamics Humans Drug Design Machine Learning Drug Discovery Models, Molecular
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Supervised machine learning techniques to predict binding affinity. A study for cyclin-dependent kinase 2.

Biochemical and biophysical research communications Oct 7, 2017
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) ...
Cyclin-Dependent Kinase 2 Protein Kinase Inhibitors Thermodynamics Molecular Docking Simulation Ligands Humans Drug Design ROC Curve Inhibitory Concentration 50 Databases, Protein Datasets as Topic Antineoplastic Agents Supervised Machine Learning
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Deciphering the mechanism of baicalein in cervical cancer via bioinformatics, machine learning and computational simulations: PIM1 and CDK2 are key target proteins.

International journal of biological macromolecules Jun 1, 2025
Cervical cancer is one of the leading causes of death among women worldwide. Current treatments are limited by chemoresistance and chemotherapeutic agents' adverse effects, prompting the search for better therapeutic alternatives. Baicalein, a natura...
Protein Binding Cyclin-Dependent Kinase 2 Female Computational Biology Uterine Cervical Neoplasms Proto-Oncogene Proteins c-pim-1 Humans Cell Proliferation Molecular Docking Simulation Molecular Dynamics Simulation Machine Learning Flavanones
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Application of Machine Learning Techniques to Predict Binding Affinity for Drug Targets: A Study of Cyclin-Dependent Kinase 2.

Current medicinal chemistry Jan 1, 2021
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...
Machine Learning Molecular Docking Simulation Protein Binding Humans Ligands Cyclin-Dependent Kinase 2 Pharmaceutical Preparations Supervised Machine Learning
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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 Dec 1, 2020
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...
Molecular Structure Drug Evaluation, Preclinical HCT116 Cells Structure-Activity Relationship A549 Cells Protein Kinase Inhibitors Cyclin-Dependent Kinase 2 Humans Molecular Docking Simulation Support Vector Machine Antineoplastic Agents Dose-Response Relationship, Drug Cell Proliferation Drug Screening Assays, Antitumor
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Machine Learning to Predict Binding Affinity.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2019
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 ...
Software Algorithms Molecular Docking Simulation Models, Statistical Proteins Databases, Protein Cyclin-Dependent Kinase 2 Humans Machine Learning Ligands Molecular Dynamics Simulation HIV Protease Supervised Machine Learning Web Browser
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