期刊
COMPUTATIONAL BIOLOGY AND CHEMISTRY
卷 59, 期 -, 页码 91-97出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.compbiolchem.2015.07.007
关键词
Systems biology; Metabolic modeling; Homology modeling; Drug repositioning; Mycoplasma genitalium; Thymidylate kinase
资金
- Polish National Science Centre [UMO-2013/09/B/NZ2/00121, 2014/15/B/ST6/05082]
- Wroclaw Centre for Networking and Supercomputing [255]
- European Cooperation in Science and Technology [BM1405, BM1408]
- Medical University of Bialystok
- European Social Fund
- National Science Foundation Graduate Fellowship
- James S. McDonnell Foundation Postdoctoral Fellowship Award in Studying Complex Systems
- University of Virginia Health System
- Direct For Biological Sciences
- Div Of Molecular and Cellular Bioscience [1548123] Funding Source: National Science Foundation
Bacteria are increasingly resistant to existing antibiotics, which target a narrow range of pathways. New methods are needed to identify targets, including repositioning targets among distantly related species. We developed a novel combination of systems and structural modeling and bioinformatics to reposition known antibiotics and targets to new species. We applied this approach to Mycoplasma genitalium, a common cause of urethritis. First, we used quantitative metabolic modeling to identify enzymes whose expression affects the cellular growth rate. Second, we searched the literature for inhibitors of homologs of the most fragile enzymes. Next, we used sequence alignment to assess that the binding site is shared by M. genitalium, but not by humans. Lastly, we used molecular docking to verify that the reported inhibitors preferentially interact with M. genitalium proteins over their human homologs. Thymidylate kinase was the top predicted target and piperidinylthymines were the top compounds. Further work is needed to experimentally validate piperidinylthymines. In summary, combined systems and structural modeling is a powerful tool for drug repositioning. (C) 2015 Elsevier Ltd. All rights reserved.
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