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Computation as a Tool for Glycogen Phosphorylase Inhibitor Design

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Auteur
Hayes, J. M.; Leonidas, D. D.
Date
2010
Sujet
Docking
free energy perturbation (FEP)
glycogen phosphorylase
modeling
MM-GBSA
pharmacophore
QM/MM
QSAR
GLUCOSE ANALOG INHIBITORS
GENETIC NEURAL-NETWORKS
POTENTIAL
ANTIDIABETIC DRUG
PROTEIN-LIGAND COMPLEXES
MOLECULAR
SIMILARITY-MATRICES
TYPE-2 DIABETES THERAPY
RECEPTOR SURFACE MODELS
BINDING FREE-ENERGY
OF-THE-ART
ALLOSTERIC SITE
Chemistry, Medicinal
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Résumé
Glycogen phosphorylase is an important therapeutic target for the potential treatment of type 2 diabetes. The importance of computation in the search for potent, selective and drug-like glycogen phosphorylase inhibitors which may eventually lead to antihyperglycemic drugs is now firmly established. Acting solo or more effectively in combination with experiment in a multidisciplinary approach to structure based drug design, current day modeling methods are an effective means of reducing the time and money spent on costly experimental procedures. Glycogen phosphorylase is an allosteric protein with five different ligand binding sites, hence offering multiple opportunities for modulation of enzyme activity. However, the binding sites have their own individual characteristics, so that different modeling approaches may be more effective for each. This review is focused on advances in the modeling and design of new inhibitors of the enzyme aimed towards providing the reader with some useful hints towards more successful computer-aided inhibitor (drug) design targeting glycogen phosphorylase.
URI
http://hdl.handle.net/11615/28485
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