Medicinal Chemistry

fly by studying a single frozen goose stacked amongst other frozen geese in a grocery
store freezer.) NMR spectroscopy at least permits solution-phase structural studies, but
still does not supply the detailed data provided by either X-ray or quantum pharmacol-
ogy studies. Quantum pharmacology calculations are inexpensive, fast, and do not
require that the compound has already been synthesized. Thus, quantum pharmacology
calculations may be used in a predictive manner to determine which molecules should
next be synthesized. Furthermore, many theoretical chemists would argue that current
quantum mechanics calculations provide structural data on small drug molecules that is
equivalent to an X-ray structure; others might dispute this assertion.

1.6.7 Bioinformatics and Cheminformatics

Bioinformatics and cheminformatics are significant, new, rapidly evolving techniques
focused upon the management of information. They are exerting an important influence
on the future of medicinal chemistry, drug design, and quantum pharmacology calcula-
tions. Bioinformaticsrefers to the tools and techniques (usually computational) for
storing, handling, and communicating the massive and seemingly exponentially increas-
ing amounts of biological data emerging mainly from genomics research but also from
other areas of biological research. Bioinformatics has the goal of enabling and accelerat-
ing biological and pharmacological research. It encompasses a diverse range of activities
including data capture, automated data recording, data storage, data access, data analysis,
data visualization, and the use of search engines and query tools for probing multiple
databases. Bioinformatics also endeavors to draw correlations between biological data
from multiple sources in an attempt to identify novel information that may have utility in
drug design; the use of bioinformatics in drug design is now ubiquitous and all pervasive.
Bioinformatics attempts to combine data from the following three principal types
of study:

1. Gene discovery studies
   
   
   • High-throughput genetic sequencing
   
   
   • Genetic linkage studies
   
   
   • Genetic maps
   
   
   • Polymorphism studies
   
   
   
   


2. Gene function studies
   
   
   • Gene chips and microarrays
   
   
   • Gene expression profiles
   
   
   • Functional genomics
   
   
   • Proteomics
   
   
   • Metabolic pathways
   
   
   
   


3. Clinical trial studies
   
   
   • Clinical trial efficacy data
   
   
   • Pharmacokinetic studies
   
   
   • Pharmacogenetics
   
   
   • Pharmacogenomics
   
   
   • Toxicology studies
   
   
   • Patient data
   
   
   
   

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