A-glucosidase, Homology Modeling And Molecular Docking Studies

The thesis studies onα-glucoside glycohydrolase and its andrographolide analogues inhibitors. Homology modeling, molecular docking, quantitive structure-activity relationship (QSAR) and evolutionary trace analysis had been applied.Firstly, Using oligo-l,6-glucosidase as a structural template, the 3D structure ofα-glucoside glycohydrolase was built with homology modeling method. Rational analysis of the modelled structure was performed. The putative binding site in theα-glucoside glycohydrolase was searched and identified by Insight II/ Binding site analysis. It was found that His111, Asp214, Glu276, His348 and Asp349 play a major role in catalysis ofα-glucoside glycohydrolase. Subsequently, seventeen andrographolide analogues were selected for docking study. To explore the binding mode of andrographolide analogues with the active site ofα-glucoside glycohydrolase and guide further structural optimization, flexible molecular docking methods (Cerius~2/LigandFit and Insight II/Affinity) were used to investigate the interaction between them. While, different docking patterns had been researched, some rational explanations were provided for the different activities of these inhibitors. Hydrophobic interaction, electrostatic interaction, hydrogen-bonding and Van Der Waals interaction were found to play an important role in substrate recognition and orientation by the study. Thus allowing the rational design of specific inhibitors to the target enzyme and the discovery of novel antidiabetic agents with broad spectrum.Secondly, the andrographolide analogues were studied by the molecular field analysis. Variation of grid spacing was used during the optimization of the MFA model. It was found that the results of MFA is good, cross-validation coefficient (q~2) and linear correlation coefficient (r~2) equal to 0.761 and 0.996,respectively. In order to test the 3D-QSAR model, two inhibitors with certain experimental inhibitory activity value were selected to calculate, the result shows that there exists a good correlation between the calculated inhibitory activity value and the experimental inhibitory activity value. This result all indicates that the model is successful. The 3D-QSAR model showed strong predictive ability on both test set and training set.Thirdly, multiple sequence alignments were performed on the Glycosyl hydrolase 13 family and thus evolutionary trace was constructed. The important functional residues of Glycosyl hydrolase 13 family were identified by the ET analysis. From the ET results, the important residues confirmed by biological experiments, such as His111, Asp214, His348 and Asp349 of the active site inα-glucoside glycohydrolase, were identified successfully. Because these residues in the active site ofα-glucoside glycohydrolase have been confirmed important for the enzymatic activity and inhibitor binding by biological experiments, the trace residues identified by ET analysis are of great importance to study the structure-function relationship and also design specific inhibitors.