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Sept.
23, 2002 |
Decoding the Protein Language
Mohammed Zaki, assistant professor of computer
science, and Chris Bystroff, assistant professor of biology, are
creating a faster, more efficient data-mining technique to determine
basic rules of how proteins form.
Researchers can identify a protein's biological
function, and therefore its specific role in disease, if they
know the 3-D structure of a protein given its amino-acid sequence.
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| The researchers reduce a 3-D image of a protein
to a simpler 2-D representation, called a "contact map."
The contact map reveals the chemical and other interactions
among amino acids that are difficult to extract from the more
complex 3-D images. |
Twenty simple amino acids make up the "language"
that forms the thousands of complex proteins in the human body.
The idea is to discover how amino acids, or "letters,"
lead to "words" or common patterns to form proteins.
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"The ability to predict protein structure
from the amino acid sequence is revolutionizing molecular
biology."
—Mohammed Zaki —
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With that in mind, Zaki and Bystroff's approach
involves creating a 3-D image of each known protein already recorded
in the worldwide Protein Data Bank. The researchers then reduce
the image to a simpler 2-D representation, called a "contact
map." The 2-D map reveals the chemical and other interactions
among amino acids-data that is difficult to extract from the more
complex 3-D images.
The data is mined from the contact map is then
transferred into a knowledge bank of "contact rules"
and used to predict unknown proteins and even how novel proteins
might form.
"The ability to predict protein structure
from the amino acid sequence is revolutionizing molecular biology,"
Zaki said.
The research is funded under an Early Career Principal
Investigator Award from the U.S. Department of Energy. The three-year,
$333,928 grant to decode the protein language was a result of
work conducted under Rensselaer's Exploratory
Research Seed Program.
A primary goal of that program is to fund new
interdisciplinary research projects in areas of strategic interests
and build new opportunities in disciplines that have a high probability
of leading to major externally sponsored research programs.
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