title: Ligand-based modeling followed by in vitro bioassay yielded new potent glucokinase activators.
abstract: Glucokinase (GK) has received recent interest as a valid antidiabetic target. With this in mind, we applied a computational workflow based on combining pharmacophore modeling and QSAR analysis followed by in silico screening toward the discovery of novel GK activators. Virtual screening identified 10 promising bioactivators from the National Cancer Institute (NCI) list of compounds. The most potent NCI hit illustrated 6.3-fold GK activation at 10 μM. These results demonstrated that our virtual screening protocol was able to identify novel GK activator leads for subsequent development into potential antidiabetic agents.
authors.affiliation: Drug Discovery Unit, Department of Pharmaceutical Sciences, Faculty of Pharmacy, The University of Jordan, Amman, Jordan. Electronic address: mutasem@ju.edu.jo.
authors.forename: Mutasem O
authors.initials: MO
authors.lastname: Taha
authors.affiliation: Department of Pharmaceutical Chemistry and Pharmacognosy, Faculty of Pharmacy, Applied Science University, Amman, Jordan.
authors.forename: Maha
authors.initials: M
authors.lastname: Habash
authors.affiliation: Department of Medical Laboratory Sciences, Faculty of Allied Health Sciences, The Hashemite University, Zarqa, Jordan.
authors.forename: Ma'mon M
authors.initials: MM
authors.lastname: Hatmal
authors.affiliation: Department of Medicinal Chemistry, Faculty of Pharmacy, Beni-Suef University, Beni-Suef, Egypt; Department of Pharmaceutical Chemistry, College of Pharmacy, Taif University, Taif, Saudi Arabia.
authors.forename: Ahmed H
authors.initials: AH
authors.lastname: Abdelazeem
authors.affiliation: Department of Medicinal Chemistry and Pharmacognosy, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid, Jordan; Department of Basic Pharmaceutical Sciences, College of Pharmacy, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia.
authors.forename: Amjad
authors.initials: A
authors.lastname: Qandil
mesh_terms: D020816:Amino Acid Motifs; D001665:Binding Sites; D062126:Databases, Chemical; D004789:Enzyme Activation; D020536:Enzyme Activators / Q000737:chemistry*; D005941:Glucokinase / Q000737:chemistry*; D057166:High-Throughput Screening Assays; D006801:Humans; D007700:Kinetics; D008024:Ligands; D062105:Molecular Docking Simulation; D008969:Molecular Sequence Data; D011485:Protein Binding; D021281:Quantitative Structure-Activity Relationship; D013816:Thermodynamics; D014584:User-Computer Interface
chemical_list: D020536:Enzyme Activators; D008024:Ligands; D005941:Glucokinase
keywords: Glucokinase enzyme; In vitro assay; In-silico screening; Pharmacophore modeling; Quantitative structure–activity relationship