Scientists devise innovative method to profile and predict the behavior of proteins

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Posted August 9, 2013

An enzyme is a tiny, well-oiled machine. A class of proteins that are made up of multiple, interlocking molecular components, enzymes perform a variety of tasks inside each cell. However, precisely how these components work together to complete these tasks has long eluded scientists. But now, a team of researchers has found a way to map an enzyme’s underlying molecular machinery, revealing patterns that could allow them to predict how an enzyme behaves—and what happens when this process disrupted.


In the latest issue of the journal Cell, a team of scientists led by Gladstone Institutes and University of California, San Francisco (UCSF) Investigator Nevan Krogan, PhD, Texas A&M University’s Craig Kaplan, PhD, and UCSF Professor Christine Guthrie, PhD, describe a new technique—called the point mutant E-MAP (pE-MAP) approach—that gives researchers the ability to pinpoint and map thousands of interactions between each of an enzyme’s many moving parts.

The researchers focused on a well-known enzyme—called RNA polymerase II (RNAPII)—and used the single-cellular yeast species S. cerevisiae as a model. Researchers had previously mapped the physical structure of RNAPII, but not how various parts of the enzyme work with other proteins within the cell to perform vital functions.

“Scientists know RNAPII’s physical structure, but this large enzyme has many distinct regions that each perform distinct functions” said Dr. Kaplan, who is also a scientist at Texas A&M AgriLife. “We wanted to connect the dots between these regions and their function.”

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