characterization of the complexities of cellular protein–protein interactions will afford a
robust understanding of the integrated networks that drive cellular function. Furthermore,
many human diseases, including cancer and neurodegenerative diseases, seem to arise
from aberrant protein–protein association mechanisms. Interaction proteomics seeks to
elucidate the complete set of interactions that define protein–protein associations.
Even when the technologies of structural proteomics and interaction proteomics have
evolved to maturity, the pathway to the awaiting plethora of drugs is still not paved and
perfect. Drugs are small organic molecules. Obtaining these drug molecules will require
yet another step in the “from genomics–to proteomics–to disease” cascade. Just as pro-
teomics is a crucial bridge uniting genomics to disease, so too will an equally crucial
bridge be needed to unite proteomics with therapeutics. Hopefully, the bioinformatics/
cheminformatics spectrum will be that bridge.
3.2.7.3 Bioinformatics and Cheminformatics in Lead Compound Discovery
Bioinformatics and cheminformatics constitute an in silico science that endeavors to
predict the phenomenology of cellular physiology and pharmacology at a molecular level
using computational methods. Using databases of compounds and other theoretical mol-
ecular design techniques, bioinformatics and cheminformatics will attempt to identify
novel molecules to alter the function of various proteins defined by the genome-based
proteome. Bioinformatics/cheminformatics will apply knowledge-discovery and pattern-
recognition algorithms to the genome-wide and proteome-wide experimental data,
thereby facilitating drug design. If structural proteomics has identified the functional
portion of an important protein, cheminformatics will search large databases of drug-like
molecules to identify one that has the right shape and properties to dock with the pro-
tein. Because of the importance of bioinformatics and cheminformatics to the future of
drug design, these topics are discussed in greater detail in chapter 1.
An interesting and recent advance in cheminformatics is chemogenomics. In conven-
tional cheminformatics, a single drug is designed for a single protein target; in
chemogenomics, multiple drugs will be designed to target multiple-gene families. Data
gleaned for one protein can be applied to structurally similar proteins coded by the same
gene family. Chemogenomics represents a new conceptual approach to target identifi-
cation and drug development.
3.2.8 Pharmacogenomics and the Future of Lead Compound DiscoveryThe spectrum of genomics/proteomics/bioinformatics/cheminformatics is defining the
future of lead compound discovery and drug design; pharmacogenomics is defining the
future beyond that! Conventional drug design attempts to discover drugs to treat par-
ticular diseases; pharmacogenomics attempts to design individualized drugs to treat
particular people with particular diseases. On the basis of a variety of genetic testing, a
physician would be able to predict how an individual patient would respond to a spe-
cific drug and if this patient will experience any specific side effects. On the basis of
person-to-person variability in pharmacokinetics and pharmacodynamics, pharmacoge-
nomics will study how genetic variations affect the ways in which particular people
respond to specific drug molecules. Traditionally, drug design has developed drugs for
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