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Several inhibitors of the large regulatory enzyme glycogen phosphorylase (GP) have been studied in crystallographic and kinetic experiments. GP catalyses the first step in the phosphorylysis of glycogen to glucose-l-phosphate, which is utilized via glycolysis to provide energy to sustain muscle contraction and in the liver is converted to glucose. α-D-Glucose is a weak inhibitor of glycogen phosphorylase form b (GPb, Ki = 1.7 mM) and acts as a physiological regulator of hepatic glycogen metabolism. Glucose binds to phosphorylase at the catalytic site and results in a conformational change that stabilizes the inactive T state of the enzyme, promoting the action of protein phosphatase 1 and stimulating glycogen synthase. It has been suggested that in the liver, glucose analogues with greater affinity for glycogen phosphorylase may result in a more effective regulatory agent. Several N-acetyl glucopyranosylamine derivatives have been synthesized and tested in a series of crystallographic and kinetic binding studies with GPb. The structural results of the bound enzyme–ligand complexes have been analysed together with the resulting affinities in an effort to understand and exploit the molecular interactions that might give rise to a better inhibitor. Comparison of the N-methylacetyl glucopyranosylamine (N-methylamide, Ki = 0.032 mM) with the analogous β-methylamide derivative (C-methylamide, Ki = 0.16 mM) illustrate the importance of forming good hydrogen bonds and obtaining complementarity of van der Waals interactions. These studies also have shown that the binding modes can be unpredictable but may be rationalized with the benefit of structural data and that a buried and mixed polar/non-polar catalytic site poses problems for the systematic addition of functional groups. Together with previous studies of glucose analogue inhibitors of GPb, this work forms the basis of a training set suitable for three-dimensional quantitative structure–activity relationship studies. The molecules in the training set are void of problems and potential errors arising from the alignment and bound conformations of each of the ligands since the coordinates were those determined experimentally from the X-ray crystallographic refined ligand–enzyme complexes. The computational procedure described in this work involves the use of the program GRID to describe the molecular structures and the progam GOLPE to obtain the partial least squares regression model with the highest prediction ability. The GRID/GOLPE procedure performed using 51 glucose analogue inhibitors of GPb has good overall predictivity [standard deviation of error predictions (SDEP) = 0.98 and Q2 = 0.76] and has shown good agreement with the crystallographic and kinetic results by reliably selecting regions that are known to affect the binding affinity.
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