GlucoKinaseDB

GlucoKinaseDB provides a curated database of 1,723 experimentally derived glucokinase (GK) modulators with structural, bioactivity, molecular descriptor, and 3D-structure data to support pharmacophore, QSAR/QSPR and machine-learning studies of GK-mediated glucose sensing and hepatic glycogen regulation.

Key Features:

• Dataset scope: Contains 1,723 experimentally derived glucokinase modulators, including allosteric activators (GKAs) and GK–GKRP disruptors.
• Structural and bioactivity data: Provides detailed structural information and experimentally measured bioactivity values for each modulator.
• Molecular descriptors: Includes comprehensive molecular descriptors for cheminformatics and quantitative modeling.
• 3D structures: Supplies downloadable 3D structures of modulators in multiple file formats.
• Downloadable datasets: Enables bulk download of bioactivity data and molecular descriptors per modulator or for the full dataset.
• Cross-references: Includes links to original references and external databases for source provenance.
• Curation: Entries are curated to preserve experimental provenance and annotation consistency.

Scientific Applications:

• Pharmacophore modeling: Support development of pharmacophore hypotheses for GK modulators.
• QSAR/QSPR modeling: Enable construction of quantitative structure–activity and structure–property relationship models.
• Machine-learning prediction: Provide training data for predictive machine-learning models of GK activity.
• Antihyperglycemic drug discovery: Facilitate exploration of GK modulators as potential safer antihyperglycemic agents.
• Antiparasitic research: Support investigation of GK modulators' potential antiparasitic activities.

Methodology:

Entries were compiled through a manual curation process from experimental sources, and the system is implemented using PHP with a MySQL database backend.