In Leder, P., Clayton, D. A. and Rubenstein, E. (Ed.), Scientific American: Introduction to Molecular Medicine (pp. 153-168). New York NY: Scientific American Inc. 1994.
Department of Biochemistry, Stanford University School of Medicine, Stanford California 94305-5307.
To reap the most benefit from the human genome we will have be
able to understand the meaning of the genetic sequences. The methods
currently available for interpreting DNA and protein sequences
largely utilize evolutionary homology. The consensus sequence method
looks for highly conserved amino acids or bases in specific
locations. The weight matrix or profile methods perform the same task
quantitatively. Sequence alignments even attempt to recapitulate
evolution by specifically postulating substitution, insertion and
deletion events that occurred during the evolutionary process. Using
these evolutionary based methods, this article has shown how much
hypothetical information can be gained from the study of a single
gene and protein molecule.
However, these evolutionary methods do not give much insight into the
flow of genetic information from genes to structure and to phenotype
as discussed in the introduction. What is truly needed are methods
that can predict structure and function based on physical and
chemical principles. Such methods will have to embody knowledge about
how proteins fold, how they mediate catalysis, how they interact and
how they determine phenotype. Research is ongoing along these lines.
Molecular dynamics hopes to predict the structure of DNA, RNA, and
proteins from physical principles. Automated learning methods
including those that utilize neural networks are directed at
discovering these physical principles based on the large amounts of
sequence information that we now have. Probabilistic networks and
other statistical methods may also reveal principles of physical
structure and function based on examples in the growing public
databases.
Even without these sophisticated informatic methods, we can still
gain much from the sequences contained in the human genome. At the
very least we will be able to design DNA diagnostic probes for many
if not all inherited disease. Using the genome sequences coupled with
recombinant DNA technology we will be able to synthesize and mass
produce any human proteins with therapeutic value. With the the
ability to decode the genetic information we will be able to
understand the nature of the disease state and design more rational
therapies in the short term and genetic therapies in the long
term.
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