• 2022-05
  • 2022-04
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  • 2020-08
  • 2020-07
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  • 2019-11
  • 2019-10
  • 2019-09
  • 2019-08
  • 2019-07
  • br Table br Perturbation profiles of mitochondrial complex


    Table 2
    Perturbation profiles of mitochondrial complex inhibitors against each complex activity.
    Compounds MOA Substrates
    Malate/ Succinate Duroquinol TMPD/
    Rotenone Complex I + − − −
    Malonate Complex II − + − −
    Antimycin A Complex III + + + −
    KCN Complex IV + + + +
    Oligomycin A Complex V + + + +
    pyruvate but prevented that by succinate. Besides, antimycin A inhibits oxygen consumption by complexes I, II, and III, while KCN and 
    oligomycin A inhibits oxygen consumption all complexes. This de-monstrates that knowing the unique inhibition pattern against these complexes can help in determining the mode of action of a test com-pound (Table 2).
    Using the above reconstitution assay system, we next examined which complex is targeted by hit compounds (Fig. 6 and Fig. S7). As shown in Fig. 6A, unantimycin A drastically inhibited the respiratory activities driven by pyuvate/malate, succinate, and duroquinol at a concentration parallel to its inhibitory effect on OCR activity in the cell system; however, it did not inhibit the respiration activated by TMPD/ ascorbate. These perturbation profiles clearly BODIPY493 / 503 suggest that unantimycin A is similar to the an antimycin type of compound. Similar results were obtained when the BODIPY493 / 503 were treated with SW-163A (Fig. 6B). The data obtained indicate that unantimycin A and SW-163A act on complex III in the mitochondrial ETC.
    Meanwhile, NPL40330 selectively inhibited malate/pyruvate-driven respiration in that assay, indicating that it may be a complex I inhibitor (Fig. 6C). In order to verify this, we tested the effect of NPL40330 on in vitro NADH-CoQ reductase activity using isolated mi-tochondria. Our data showed that it significantly inhibits the activity of
    Fig. 6. The target of unantimycin A, SW-163A and NPL40330. Mitochondrial respiration (%) was calculated from Fig. S6 using the following equation: Mitochondrial respiration (%) = (state 3 OCR)DRUG/(state 3 OCR)DMSO × 100. Effects of (A) unantimycin A, (B) SW-163A and (C) NPL40330. The following reagents were used as positive controls for each activity test: rotenone (0.03 μM) for complex I, malonate (2 mM) for complex II, antimycin A (0.03 μM) for complex III, and KCN (20 mM) for complex IV. (D) In vitro NADH-CoQ reductase assay. Data are mean ± s.d. (n = 3 technical replicates) from one representative experiment out of two in-dependent experiments.
    4. Discussion
    To understand the cancer metabolic machinery in a chemical-biology approach, various small molecules that target specific proteins are needed. To this end, we constructed a natural product screening system integrating metabolomic and proteomic phenotypes of cancer. A proof-of-concept study was conducted using a representative set of well characterized compounds, which allows for the classification of anti-metabolic compounds. Nevertheless, the glutaminase inhibitor BPTES [38] did not show any significant phenotype in the HeLa cells (Fig. 2). We believe that under normoxic conditions, HeLa cells may not be suitable for the evaluation of glutamine metabolism because of the following reasons. A recent study has shown that the oncogenic tran-scription factor Myc regulates glutamine metabolism in human P-493 B lymphoma cells and PC3 prostate cancer cells by upregulating gluta-minase expression through the suppression of miR-23a/b expression [39]. In addition, it is reported that the importance of glutamine me-tabolism is maximized under hypoxic or nutrient (especially glucose)-deficient conditions [40]. However, Myc expression is not high in HeLa cells [41]. Taken together, these findings indicate that BPTES and other inhibitors of glutaminolysis may be active under certain experimental conditions. Thus, studies on the effects of nutrients and oxygen on the 
    proliferation of dozens of cancer cell lines are ongoing. ChemProteoBase is a proteomic profiling system that identifies the
    targets of compounds based on a simple comparison of changes in the expression of 296 spots in 2-D DIGE. Among the 296 spots, we identi-fied 276 spots and constructed a system to compare the extracted spots for target pathway analysis. Next, we analyzed the expression of en-zymes in the glycolytic pathway that participate in cancer metabolism. Mitochondrial respiratory inhibitors induced upregulation of the gly-colytic enzymes (Fig. 3B), which might compensate the mitochondrial function for energy production [42]. It is also reported that tyrosine kinases and mTOR upregulate the expression of glycolytic proteins [3, 43]. Our results showed unique proteomic patterns for inhibitors of the cancer metabolic pathway (Fig. 3B), and helped us identify un-antimycin A and NPL40330 as positive hit compounds (Fig. 4).