The enzyme GSK-3 plays a central role in cells during the phosphorylation of various key regulatory proteins, and consequently pharmacological inhibitors of this enzyme potentially allow the treatment of diseases that include neurodegenerative and bipolar affective disorders, diabetes, and diseases caused by unicellular parasites. Today there is a huge number of reported empirical structure-activity relationships (SAR) that may guide a rational design of more potent and selective inhibitors. However, only a few studies based on Quantitative Structure-Activity Relationships (QSAR) are available for predicting the inhibitor potency against this specific kinase, and they involve mainly molecular modeling and 3D-QSAR. The present review deals with the recent search for a quantitative analysis of GSK-3 inhibition.
Keywords: QSAR Theory, Glycogen Synthase Kinase-3, Phosphorylation, CoMFA/CoMSIA, Partial Least Squares, Multivariable Linear Regression, Artificial Neural Network
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