(313c) Metabolite-Centric Approach for Drug Targeting and Discovery Against Microbial Pathogens | AIChE

(313c) Metabolite-Centric Approach for Drug Targeting and Discovery Against Microbial Pathogens

Authors 

Kim, H. U. - Presenter, Korea Advanced Institute of Science and Technology (KAIST)
Lee, S. Y. - Presenter, Korea Advanced Institute of Science and Technology (KAIST)
Kim, T. Y. - Presenter, Korea Advanced Institute of Science and Technology (KAIST)


Extensive genomic knowledge on microbial pathogens has become available from a-decade-long efforts, yet there still exists a gap to fill in between genomics and actual drug discovery. Prompted by this biomedical issue, we developed a metabolite-centric approach for effective drug targeting and discovery against microbial pathogens, and, in particular, in this study, this approach was applied to an opportunistic human pathogen Vibrio vulnificus CMCP6 as a demonstration. This drug targeting method aims at predicting so called essential metabolites whose absence disrupts cell growth using a genome-scale metabolic network model of the target organism. For this, we first reconstructed the genome-scale metabolic network of V. vulnificus CMCP6, named VvuMBEL943, using its newly updated genomic information. Then, essential metabolites were predicted by implementing constraints-based flux analysis, which is an optimization-based simulation technique. This initial set of the predicted essential metabolites was screened with additional criteria of organism specificity and maximal disruptive damage to the cell. Essentiality of final five essential metabolites survived from the filtering was experimentally validated by gene knockout experiments. Finally, structural analogs of the final five essential metabolites were selected out of large chemical compound library, and employed for whole-cell screening to identify the most effective antibacterial candidate compound. This systematic approach should facilitate initial stage of drug discovery for antibiotics as well as other human diseases.

[This work was supported by the Korean Systems Biology Research Project (20100002164) and World Class University program (R322009000101420) of the Ministry of Education, Science and Technology through the National Research Foundation of Korea.]