Molecular fingerprints  pg. 7

“What this is going to take is all aspects of humanity, if you will, working together. It’s going totake the physicists, it’s going to take the mathematicians, computer scientists, biologists, chemists – you can go down the line. We as humans have to network before we can understand protein networks.”
Richard Caprioli, Ph.D. Stanley Cohen Professor of Biochemistry
Photo by Dean Dixon
“However, the one thing I do believe in is the value of these initiatives (to develop) high throughput technologies,” Chazin says. That’s the ability to accelerate the research process and generate huge amounts of data essentially overnight.”

The new technologies, in fact, are opening up a new way to conduct research (see “Discovery Science.”)

The traditional approach, exemplified by Stanley Cohen’s Nobel Prize-winning work at Vanderbilt four decades ago, is to begin with a biological observation. For example, Cohen noticed that an extract of mouse salivary glands causes newborn mice to open up their eyes earlier than normal.

That observation led to the discovery of epidermal growth factor (EGF) and, later, to the identification of the receptor through which it acts. Hypotheses were formulated to explain the phenomena that were observed, and experiments were designed to test them.

Meanwhile, certain cancers were found to have abnormally high levels of the EGF receptor. Technological advances enabled scientists to determine the three-dimensional structure of the protein, and to synthesize molecules that can block its activity. Cohen’s body of work, beginning with an incidental observation, helped lead to a new field of cancer research and drug development.

The tried-and-true hypothesis approach hasn’t been abandoned. But increasingly, scientists are first mining the genome and now the proteome for all the data they can. Rather than studying a car by kicking the tires, they’re taking the entire vehicle apart—including the engine—then fiddling with each part to see what it does.

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