The Screening For Agricultural Bactericidal Active Compounds Based On The Genomic Information Of Erwinia Carotovora

Erwinia is an important plant pathogen, which can infect a wide range of host species, thus causes serious economic losses worldwide. In this study, we built the metabolic network of Erwinia carotovora subsp. atroseptica SCRI1043. Through the analysis of network topology structure and flow balance, several important nodes with no homologs in host species and the metabolic flux not equal to zero, were selected in the network. Upps was selected to further screen agricultural bactericidal in the compounds database Specs, and73hit compounds was obtained. The purpose of this study is to find new kinds of bactericidal compounds for the foundation of developing new kinds of green bactericide in agriculture. This study and the results are as follows:(1) Using MODEL SEED, a metabolic network reconstruction tool, we built the metabolic network of Erwinia carotovora subsp. atroseptica, and then correct the reaction direction and removing common metabolite. The metabolic networks can be visualized in cytoscape. Through analyzing the metabolic network, it is shown that the metabolic network model has the feature of "small world" and "scale-free ", which is the typical feature of metabolic networks.(2)Through the analysis of Erwinia metabolic network and the network topology, we filtered out the key node of the network. Taking sequence alignment to the sequence of the central nodes and targets in the TTD target database,44potential targets of Erwinia were screened. Subsequently,6targets were left by using flux balance analysis (FBA) for these targets. Finally, consider the biological function of these targets, and homology with the host plant, isoprene pyrophosphatase (Upps) was selected for the further screening for agricultural bactericidal active compounds.(3) Three-dimensional structure of the target Upps was constructed and optimized through homology modeling. PROCHECK is performed to evaluate the result of the modeling, and the result of modeling is reasonable. Finally, high-throughput virtual screening for the target was performed in the compound database Specs. Then we took visual screening to the400compounds which are the top in the comprehensive scoring. At last, we got73kinds of hit compounds, which can be used for further experiments to check their bactericidal activity.