Model Organisms in Drug Discovery

As described above, the extensive information around C. elegans presenilin
suggests a viable entry point for high-throughput compound screening for
potential leads in Alzheimer’s disease. The presenilin proteins sel-12 and hop-1
in C. elegans process Notch by similar mechanisms to those of mammalian
Notch and APP processing. Lead compounds were tested that inhibit
presenilin enzyme activity and these compounds behave as partial loss of
Notch function, suggesting that affected tissues in C. elegans are accessible to
compounds (Figure 6.2). Genetic mutations in sel-12 are partial loss of
presenilin function and in the sel-12;hop-1 double mutant are complete loss of
presenilin function. Because C. elegans presenilin mutant phenotypes are easy
to score, a compound screen could be devised to screen for drug-induced sel-
12;hop1 phenotypes in a sel-12 mutant background. To allow large numbers
of compounds to be screened, automated sorting machines are available that
dispense worms and Drosophila embryos or larvae in a multiwell format
(Furlong et al., 2001).
The S2 cell-based system is also amenable to compound screens and, when
compared to whole-organism approaches, has the advantage of miniaturization
and high-throughput formatting. In Figure 6.7 we show that parthenolide
inhibits a NF-kB pathway very similar to that of humans and the drug’s
transcriptional profiling signature closely matches that of an NF-kB (Relish)
RNAi treatment. One could consider automated screening of compounds that
inhibit NF-kB transcriptional activation of a reporter construct. In some
cases, the lack of pathway redundancy in Drosophila and C. elegans may work
to their advantage in screening technologies.
Lead compound discovery may be aided by evaluating transcriptional
profiling. The specificity of the candidate drug can be tested by matching drug
treatment patterns to gene expression profiles of RNAi directed to the
validated target. An antagonist that is specific to the intended target should
produce an expression profile similar to that of target RNAi. Suboptimal
drugs will interact with non-intended targets. Many off-site targets in model
organisms will likely translate to many off-site targets in humans.
6.10 Future perspectives
FUTURE PERSPECTIVES 177
It is clear from our work in the pharmaceutical industry that there will
continue to be a strong demand to understand how drugs work at the
molecular level. Only recently has the MOA of acetaminophen – one of the
most widely used drugs available for decades – come to light (Chandrasekharan
et al., 2002). The massive information-driven growth in fields such as
computational chemistry, structural biology and bioinformatics is leading to
unparalleled opportunities in drug design and empowered drug discovery. The
strength of the chemical genetic approach stems from the ability of mutations