3D-QSAR Studies Of HIV-1Integrase Inhibitors

AIDS is defined as a clinical syndrome, which mechanism is that the human immunodeficiency virus infection leads to defects in the body defense function, and thus prone to opportunistic infections and tumors. Belonging to the subgenus of primate immunodeficiency virus of ribodeoxy virus and lentivirus, Human immunodeficiency virus is the pathogen which provokes the spreading of AIDS. Since the first case of HIV infection occurred in1981, people have gained a large development on making great progress in the cause, treatment and prevention of AIDS by the cost of large money and time. However, no effective drug has been created to cure this disease so far. HIV is divided into HIV-1and HIV-2, HIV-1is the pathogen which caused the global AIDS. HIV-1’s life cycle depends on the enzymes: transcriptase, protease and integrase. And the suppression of any of them can block HIV-1’s replication cycle. Integrase is widely considered as a potential target, because there is no integrase and its analogues in human cells.HIV-1integrase catalyzes the integration of proviral DNA into the genome of the host cell, an essential step for viral replication, thus inhibition of integrase catalytic activity represents a rational strategy for the treatment of HIV-1infection. At present, a lot of HIV-1integrase inhibitors have been designed and synthesized, one of them named Raltegravir (MK-0518, Isentress) has been applied to clinical and some others are studied currently in clinical trials. In a view of chemical structure, most of the HIV-1integrase inhibitors are reported belong to the class of diketo acids or their bioisosters. HIV integrase inhibitors have emerged as a new class of drugs for the treatment of AIDS. In this paper, we treat integrase inhibitors as the research target to understand the relationship between structure and function with3D-QSAR.(1)3D-QSAR analysis on styrylquinoline derivatives as integrase inhibitorsIntegrase inhibitors of styrylquinoline derivatives were analyzed by the Comparative Molecular Field Analysis (CoMFA), Comparative Molecular Similarity Induces Analysis (CoMSIA) and Topomer CoMFA methods. Firstly,77compounds were selected to form the training and test sets. Secondly, predictive models were constructed with CoMFA, CoMSIA and Topomer CoMFA method, respectively. And all models are reliable by performing good external and internal consistency. The CoMFA method yielded the best model with cross-validated q2of0.758and non-cross-validated r2of0.988, the CoMSIA model has q2=0.701and r2of0.986, while the Topomer CoMFA model has q2of0.661and r2of0.966. Analysis from the outcome parameters and the contour maps of three models could provide reciprocal explanations to each other and thus help us as an instructive tool to universally realize the key physicochemical features affecting binding affinity. These results provide a helpful contribution to the design of novel highly active HIV-1integrase inhibitors. The model established in our work could be used to guide the screening of new drugs, and could design new drugs which have efficient treatment of AIDS.(2) Quantitative Structure-Activity Relationships of HIV-1Integrase Inhibitors of Diketo acidsThis paper choose189Diketo acids inhibitors using quantitative structure-activity relationship (QSAR) methods to analyze its structure and inhibitory activity relationship. We try to establish a QSAR model based on molecular descriptors. In order to establish the QSAR model, we use the dione acid inhibitor data provided by the papers of Merck Research Laboratory. These data are divided into multiple training set、test set and one external validation set. We choose to use the Random Forest method to build QSAR models. After tested, the external validation set to high sensitivity and high specificity of the model is retained. Because of the output r2of external validation set is0.606, greater than the critical conditions of0.6, the model is proved to be an effective prediction model.In this thesis, ligand-based CADD methods are used to attain detailed information for drug design targeting to HIV-1intergrase inhibitors which are crucial for viral entry. Through analyzing of existing integrase inhibitors, we expect to get more effective structure in inhibiting HIV-1Infection. This work may help to further developed of HIV-1inhibitors which can prevent the integration process.