Assay and Drug Development Technologies - 14

GIULIANO ET AL.
targets. By querying terms associated with mechanisms of
toxicity, a list of corresponding terms was produced that
contained potential toxicity assay targets. Figure 3 displays
the results of a query that quantifies associations between the
toxic mechanism terms in the left column and the cellular
function terms in the right column. The likelihood that the
terms co-occur in the scientific literature (articles in >600
MEDLINE journals are probed) is displayed as a color-coded
line connecting the term boxes. Clicking on any one of the
connecting lines allows the user to view the list of literature
references that contain the co-occurring terms. CellSpace
therefore allowed us to quickly build a panel of assays for our
high content profile of toxic compounds (see the legend of
Fig. 3 legend for details).
Once a list ofassay targets was assembled for the profile, we
completed a screening campaign that combined multiple targets
in multiple cell types with a compound library, automated
liquid handling, and HCS reagents, BioApplications software,
and the ArrayScan HCS Reader. Figure 4 shows a summary of
the campaign for compounds exhibiting hits in the greatest
FIG. 6. The CellSpace KnowledgeMiner tool provides a context in which to explore high content profiling data. The high content profiling
data presented in Figs. 4 and 5 are consistent with the stress kinase pathways and the activation of transcription factors being key cellular
responses to toxic insult (center column of molecule boxes). When these targets were queried against some of the compounds in the
library we tested, we found that drugs affecting the cytoskeleton (cytochalasin D, colchicine, nocodazole, and vinblastine), diacylglycerol
signal transduction (phorbol myristate acetate), and protein synthesis (cycloheximide) showed moderate to high likelihoods of cooccurrence
in the scientific literature. It is interesting to note that the MAP kinases (MAPK) did not have a high likelihood of co-occurrence
when queried against mechanisms of toxicity (Fig. 3). Furthermore, the toxicological agents in our screen that had a hit in at least one of
the stress kinase activation assays (gramicidin, hexetidine, and thimerosal) exhibited a low likelihood of co-occurrence with the stress
pathway targets. Therefore, the CellSpace data miner is not only valuable in building potential target panels for assay development, but it
is also useful in taking screening results to the next level of sophistication by revealing and building on physiological connections made by
others as well as discovering new ones.
14 ASSAY and Drug Development Technologies
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Assay and Drug Development Technologies

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