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by factoring in and refining important drug properties concurrently with the optimization of drug affinity
and specificity for a specific molecular receptor. This objective is achieved by integrating assays and
computational models that relate to important drug development issues (e.g., oral absorption, optimal
pharmacokinetics, minimal toxicity, etc.) directly into the iterative design process.
V. Chemi-Informatics
The development of methods that can optimize the parallel refinement of drug potency and
pharmacological properties is a key objective in enhancing the efficiency and productivity of drug
discovery. To address this problem and to handle the dramatic increase in experimental data generated
using robotic synthesis and assay methodologies, advanced informatics systems are required to collect
and exploit data relating to the properties of the chemicals being produced. These systems will amplify
the synergy between structure-based design and combinatorial chemistry and provide a means for
reducing the aggregate failure rate of development candidates.
The poor success rate for preclinical development candidates (about 1 in 20) results from our limited
ability to predict such drug properties as intestinal absorption, excretion, metabolism, toxicity, efficacy,
and side effects. Rendering the prediction more difficult is the certainty that these drug properties are
composite properties that result from the operation of many biological processes. Recently, progress has
been made towards understanding the underlying molecular basis for some of the individual components
that contribute to the observed drug properties. For instance, the absorption of compounds into Caco-2
cells in culture may be predictive of intestinal absorption [29–31]. Retention times of compounds during
artificial membrane chromatography has also been correlated with oral absorption [32]. Recently,
molecular transporters have been identified, cloned, and characterized that are responsible for the
absorption of dipeptides and the excretion of organic cations [33,34]. The enzymatic basis for the
metabolism of xenobiotics (cytochrome P450, glutathione transferase, etc.) has been known for some
time, at least in part. In fact, many of the individual components of the composite biological processes
can be developed into high-throughput assays, providing the opportunity to collect SAR data and
develop SAR models.
These observations, together with the integrated structure-based design and combinatorial chemical
technology described here, define a comprehensive new strategy for drug discovery that has the
potential to reduce the aggregate failure rate for development candidates (Figure 4). The creation of
virtual libraries of compounds that are readily accessible through the use of automated
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