3DQSAR And Virtual Screening Studies Azaindole Class Renin Inhibitor

Computer aided drug design (CADD) is a computer-based chemistry, which can simulate the interaction of small drug molecules and receptor protein with the help of computer, and do the inherent structure-activity relationship analysis to optimize screen and rationally design new lead compounds. CADD has gradually become one of the core technologies of innovative drug research.Hypertension can cause a variety of cardiovascular and renal diseases and the renin-angiotensin-aldosterone system (RAAS) has the function of maintaining normal blood pressure and fluid balance. There is a total of three ways for the inhibition of RAAS system. DRIs act directly on the RAAS rate-limiting step, reduce the contents of Ang Ⅰ and Ang Ⅱ from the source, and avoid the side effects of ACEIs and ARBs. Scheiper et al. explored the high activities of azaindole molecules, especially the excellence in S1and S3subsites.In the first chapter of the thesis, a review of CADD research, progress, and applications was presented.In the second chapter of the thesis, a series of azaindole class renin inhibitors were subjected to3D-QSAR study using Topomer CoMFA. The best splitting mode of such molecules was founded. The developed model was assessed by the external test set validation, Y-randomization test and date re-division to be reliable and robust. Six Topomer CoMFA models have similar statistical results and can be used to predict the activities of similar compounds. They indicated the Topomer CoMFA method can be used to the study of such renin inhibitors. Further explanation of the three-dimensional contour map can effectively improve the activity of the molecule and provide a theoretical basis for molecular design and activity prediction of more renin inhibitors.In the third chapter of the thesis, the methodology of fragment-based drug design (FBDD) to virtual screen specified database by using Topomer Search technology and the query was adopted. The Ri-group of the compound No.13with the highest activity was chosen as the basic scaffold, and its remaining R2-group acted as a query to screen142,025Leadlike molecules of ZINC database for similar fragments. The obtained30fragments with the highest R2-group contribution values were added to the basic scaffold respectively. Finally30new azaindole compounds were obtained, which were predicted high activities by using Topomer CoMFA model. Further the binding modes were studied by using Surflex-Dock. The docking results showed good binding interactions of the designed compounds with the renin protein, thus the rationality of this design was further verified from the perspective of the renin receptor.In the fourth chapter of the thesis, pharmacophore studies were done for a series of92azaindole renin inhibitors by using GALAHAD method. Firstly,20molecules with high activities were chosen as the training set to build model, and MODEL001showed good results. MODEL001included four cyan hydrophobic groups (HY), two green hydrogen bond acceptors (AA) and one red positive nitrogen (NP). Then align all the92molecules on MODEL001. There was some correlation between the established pharmacophore model parameters and biological activities.This research was summed up as follows:(1) A series of azaindole class renin inhibitors were subjected to3D-QSAR study using Topomer CoMFA, and the developed model was assessed by three methods to be reliable and robust;(2) The methodology of fragment-based drug design (FBDD) to virtual screen specified database by using Topomer Search technology was adopted. Finally30new azaindole compounds by fragment combination were obtained, and the binding modes were studied by using Surflex-Dock;(3) The reliable pharmacophore model of azaindole renin inhibitors was established, and provided a theoretical basis for more renin inhibitors’molecular design and activity prediction.