Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 program), Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
Mol Syst Biol. 2011 Jan 18;7:460. doi: 10.1038/msb.2010.115.
Although the genomes of many microbial pathogens have been studied to help identify effective drug targets and novel drugs, such efforts have not yet reached full fruition. In this study, we report a systems biological approach that efficiently utilizes genomic information for drug targeting and discovery, and apply this approach to the opportunistic pathogen Vibrio vulnificus CMCP6. First, we partially re-sequenced and fully re-annotated the V. vulnificus CMCP6 genome, and accordingly reconstructed its genome-scale metabolic network, VvuMBEL943. The validated network model was employed to systematically predict drug targets using the concept of metabolite essentiality, along with additional filtering criteria. Target genes encoding enzymes that interact with the five essential metabolites finally selected were experimentally validated. These five essential metabolites are critical to the survival of the cell, and hence were used to guide the cost-effective selection of chemical analogs, which were then screened for antimicrobial activity in a whole-cell assay. This approach is expected to help fill the existing gap between genomics and drug discovery.
尽管已经研究了许多微生物病原体的基因组,以帮助确定有效的药物靶点和新药,但这些努力尚未取得圆满成功。在这项研究中,我们报告了一种系统生物学方法,该方法能够有效地利用基因组信息进行药物靶标和发现,并将其应用于机会性病原体创伤弧菌 CMCP6。首先,我们对创伤弧菌 CMCP6 基因组进行了部分重测序和完全重新注释,并相应地重建了其基因组规模的代谢网络 VvuMBEL943。然后,使用代谢物必需性的概念以及其他筛选标准,使用经过验证的网络模型系统地预测药物靶标。与五个必需代谢物相互作用的酶编码靶基因最终被实验验证。这五个必需代谢物对细胞的存活至关重要,因此被用于指导具有成本效益的化学类似物的选择,然后在全细胞测定中筛选这些类似物的抗菌活性。这种方法有望有助于弥合基因组学和药物发现之间的现有差距。