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The birth of combinatorial chemistry in the early 1990s held out the promise that scientists would soon synthesize trillions of compounds at a time and screen up to a million a day, revolutionizing the process of drug discovery. But synthesizing a vast library of compounds is just the first step in the historically painstaking process of determining whether a compound has the desired effect on a target. In addition to an ever-growing library of candidate therapeutic compounds, advances in genome analysis have produced a growing list of potential drug targets - drowning drug researchers in an excess of riches.
In the open-access journal PLoS Biology, Kevan Shokat and colleagues report a high-throughput screening method that substantially narrows the field of candidate therapeutic agents. Their approach takes advantage of a recently developed automated system (called Cytometrix) that combines advanced imaging and bioinformatics approaches to classify cells according to small-molecule-induced changes in cell size, shape, and structure (morphology). Their analysis identified a novel compound with promising potential as an anticancer agent.
From the library of screened compounds, Shokat and colleagues identified a molecule (hydroxy-PP) that, though structurally related to a known kinase inhibitor, induced morphological changes distinct from any known kinase inhibitor. What does hydroxy-PP target? An enzyme, called carbonyl reductase 1 (CBR1), that acts on xenobiotics like anticancer drugs and is thought to cause the heart damage associated with daunorubicin chemotherapy.
The authors then solved the structure of hydroxy-PP and CBR1 bound together and used their structural analysis to increase hydroxy-PP's inhibition of CBR1 in cell culture so they could further explore the enzyme's biological function. These experiments revealed a previously uncharacterized role for CBR1 in programmed cell death.
Given the enzyme's suspected role in chemotherapy-related cardiotoxicity, inhibiting CBR1 activity might enhance the efficacy of chemotherapy treatments by reducing their debilitating side effects-a possibility that future studies can explore. But for now, Shokat and colleagues have demonstrated the power of using high-throughput image-based screening to identify small molecules both for probing cell biology and for identifying promising drug candidates.
Citation: Tanaka M, Bateman R, Rauh D, Vaisberg E, Ramachandani S, et al. (2005) An unbiased cell morphology-based screen for new, biologically active small molecules. PLoS Biol 3(5): e128.
CONTACT:
Kevan Shokat
University of California, San Francisco
Genentech Hall
600 16th St.
San Francisco, CA USA 94143-2280
+1-415-514-0472
shokat@cmp.ucsf.edu
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PLoS Biology