Computer Aided Anti-cancer Drug Design And Homology Modeling

The traditional methods of drug design are time-consuming and labor-intensive, and have a certain degree of randomness and blindness, lacking of rationality. With the rapid development of automation platform, computational chemistry and biology, drug design has been gradually direction to computer-aided drug design. In our work, we used computer-aided drug design approach to the study of coumarin and novobiocin's anti-cancer drug activity and bovine serum albumin interactions with fluoroquinolones compounds.In Chapter 1, outline the theoretical background of computer-aided drug design. Describe the quantitative structure-activity relationship (including two and three-dimensional quantitative structure activity relationship), molecular docking and homology modeling methods in detail. And finally introduces the work of this paper.In Chapter 2, study on the anticancer activity of coumarin derivatives by QSAR and docking. Protein kinase 2 (CK2) is a potential target for the development of novel anticancer agents. The coumarins, natural substances present in several foods derived from plants, were identified as an attractive CK2 inhibitor scaffold. In this study, two models (CoMFA and CoMSIA) were established, and the reliabilities were supported by their statistical parameters. The results obtained from molecular modeling techniques not only provide the models to predict the activity of inhibitors but also lead to a better understanding of interactions between inhibitors and CK2, which will be very helpful for drug design.In Chapter 3, design higher active anticancer drugs based on three-dimensional quantitative structure-activity relationship. Heat shock protein 90 (Hsp90) takes part in the development of several cancers such as breast cancer. Novobiocin, a typically C-terminal inhibitor for Hsp90, is probably to be used as an anticancer drug in the future. We explored the valuable information and designed new novobiocin derivatives based on three-dimensional quantitative structure-activity relationship.The CoMFA and CoMSIA models with high predictive capability were established, and their statistical parameters indicate that the models are reliable. Based on the several important influence factors obtained from thees models, six novel novobiocin derivatives with higher activities were designed, and supported by the molecular simulation with our models, which provides the potential anticancer drugs for further research.In Chapter 4, study the interaction between fluoroquinolone compounds and bovine serum albumin (BSA). Fluoroquinolone compound, a quinolone nalidixic acid variant, is a Gram-positive bacteria and gram-negative bacteria antibiotics. As these compounds have antibacterial, high activity, low toxicity and clinical efficiency characteristics, they have become a star in clinical treatment. The rich and cheap BSA has important research value in separation science, proteomics, and other aspects. To explore the mechanism between bovine serum protein and fluoroquinolones, we intend to use the computer simulation of molecular docking method to study it. Since there is no bovine serum albumin present three-dimensional crystal structure, we first constructed using homology modeling to build three-dimensional structure of bovine serum albumin, and then used Autodock docking to study the binding mode of bovine serum albumin and fluoroquinolones compounds. And the docking results were compared with the experimental results. Building the 3D structure of BSA by homology modeling can provide reference for the theoretical study. Exploring the mechanism between bovine serum protein and fluoroquinolones also provides useful reference.