Computer Aided Kinase Inhibitor Design And Modeling

With the successful application of anticancer drug imatinib (trade name Gleevec), developing protein kinase inhibitor has gained heightened concern in the field of drug development. Ten protein kinase inhibitors have been approved and used for clinicals. There are now more than 200 kinase inhibitors in clinical development, which shed light on the treatment of some major diseases. As the important technology and tool for drug design, computer-aided drug design (CADD) has been applied to PKI discovery. Molecular modeling approaches, such as quantitative structure-activity relationship (QSAR), molecular modeling, pharmacophore, molecular dynamic simulation and binding free energy calculation have been applied to PKI design and discovery.Based on the structure of kinase and inhibitors, this dissertation uses several techniques (QSAR, molecular docking, molecular dynamic simulation and binding free energy calculation) to correlate molecular structure features to their bioactivity, to study the interaction mode between the targeted protein and their inhibitors and to investigate the selectivity mechanism of some inhibitors. We aim at gaining insights into the key structural features affecting activity, and the interaction mechanism for inhibitor-protein binding and selectivity, guiding the design, structural modification and activity prediction of PKI and to aid the design and synthesize of highly effective inhibitors targeted PK.In Chapter 1, we present a general introduction of protein kinase and its inhibitors, including protein kinase classification, structure, kinase inhibitor structure and classification etc. A brief introduction of the computer-aided drug design method was also given, such as QSAR, molecular docking, molecular dynamic simulation and binding free energy calculation. We also describe and overview the recent progress in the study of protein and protein inhibitors.In Chapter 2, multiple molecular modeling methods were applied to predict the inhibitory activity and binding free energy of Chkl inhibitors. In the first work, a series of 5,10-dihydro-dibenzo[b,e][1,4]diazepin-11-ones as inhibitor of Chk1, were taken as the research object, we focus on an important issues overlooked in traditional QSAR study, the selection of active conformation. The accurate molecular docking program—Glide was employed to dock all the studied compounds into the active site of Chk1, and then reliable complex structure was obtained. Structural descriptors, descriptors related to ADME and the ligand-receptor binding free energy were calculated to characterize compounds. Genetic algorithm was used to select the important descriptors influencing on inhibitory activity. At the same time, MLR model was constructed. The CoMFA model was constructed to find some key structural feature affecting activity. Both GA-MLR and CoMFA models are reliable, robust and predictive. In the second work, by considering the important issues including protein flexibility, water molecules and the effect of polarization, multiple docking methods were employed to investigate the binding mode between a series of quinolones and Chk1. Prime/MM-GBSA simulation based on the docked complex is employed to predict the binding free energy of these Chk1 inhibitors. The docking combined with Prime/MM-GBSA simulation can not only be employed to rapidly and accurately predict the binding free energy, but also provide a novel strategy for lead discovery and optimization of Chk1.In Chapter 3, we applied the computer-aided drug design methods to design the novel JNK inhibitors and study the related mechanism. In the first work, based on a set of isoquinolones as inhibitors of c-Jun N-terminal kinase 1, molecular docking was employed to explore the binding mode of this inhibitor at the active site of JNK 1. GA-MLR and CoMFA models were constructed and gained insight into the key structural factors affecting the bioactivity of these inhibitors. According to the results of QSAR study, we designed a series of novel compounds with high JNK1 inhibition activity. In the second work, we studied the selectivity mechanism of two aminopyrazole inhibitors (SR3576 and SR3451) for JNK3 over p38 on molecular level using the combined molecular modeling method. Molecular docking was employed to explore the binding mode of these inhibitors at the active site of JNK3 and p38. A long time molecular dynamic simulation was performed for sampling, MM-GBSA method based on the molecular dynamic simulation trajectories was employed to get insight to the binding and selectivity of them. The key residues responsible for the high selectivity were identified and all these findings can be utilized in the design of new potent selective JNK3 inhibitors.In chapter 4, based on a series of VEGFR-2 (KDR) inhibitors, molecular modeling was performed using 3D-QSAR and docking approach. Docking study was performed to explore the binding mode between all of the compounds and the KDR, which produced the bioactive conformer of the whole data set. CoMFA and CoMSIA, were applied to these inhibitors to gain insights into the key structural factors affecting the bioactivity of these inhibitors. To construct more reasonable 3D-QSAR models, we adopted two different conformer-based alignment methods. The results indicated that the models based on the docked conformer performed better than that based on the co-crystallized conformer. According to the results of QSAR study, we designed a series of novel compounds with high VEGFR kinase inhibition activity.In Chapter 5, a series of agonist of thyroid hormone receptorβwas taken as the research object. Molecular docking was employed to explore the binding mode of the compound at the active site of TRβ.CoMFA and CoMSIA models were constructed based on the docking conformation. The obtained 3D contour maps suggest that the bulky and electropositive substituents at the meta position of the A ring are favorable for the inhibitory activity. The bulky substituents the ortho position of the B ring will enhance the activity. This information is very useful for futher structural modification.