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"Researchers have successfully combined computer
modeling and experimental results in folding studies for small
proteins, but this is the first effective combination for a large,
multi-domain protein," said study co-author Kathleen Matthews, Dean of
the Wiess School of Natural Sciences and Stewart Memorial Professor of
Biochemistry. "Pioneering efforts were required to establish
comparable experimental and theoretical data, and the method worked
remarkably well. We expect others to adopt it in their own studies."
Proteins are the workhorses of biology. At any
given time, each cell in our bodies contains 10,000 or more of them.
Each of these proteins is a chain of amino acids strung end-to-end
like beads in necklace. For longer proteins, the chain can contain
hundreds of amino acids.
Thanks to modern genomics, scientists can use DNA
to decipher the amino acid sequence in a protein. But knowing the
sequence gives no clue to the protein's function, because function is
inextricably tied to shape, and every protein self-assembles into its
characteristic shape within seconds of being created.
"The folded, functional form of the protein is what
really matters, and our interest is in creating a folding roadmap of
sorts, a plot of the thermodynamic route that the protein follows as
it moves toward equilibrium," said co-author Cecilia Clementi, the
Norman Hackerman-Welch Young Investigator Assistant Professor of
Chemistry.
The Rice research team included Clementi,
Clementi's graduate student Payel Das, experimentalist Pernilla
Wittung-Stafshede, associate professor of biochemistry and cell
biology, Matthews and graduate student Corey Wilson of biochemistry
and cell biology.
"We know that misfolded proteins play a key but
mysterious role in Alzheimer's, Parkinson's, diabetes and a host of
other diseases, so mapping the normal route a protein takes – and
finding the off-ramps that might lead to misfolding – are vitally
important," Wittung-Stafshede said.
Rice's studies were carried out on monomeric
lactose repressor protein, or MLAc, a variant of the protein used by
E. coli to regulate expression of the proteins that transport and
metabolize lactose. MLAc contains about 360 amino acids.
While scientists know proteins containing 100 or
fewer amino acids fold in a very cooperative (all-or-none) fashion, it
is believed that larger proteins fold through the formation of
partially folded intermediate structures before settling into their
final state.
Simulating large-scale protein folding is too
complex for even the most powerful supercomputer. In developing a
theoretical approach that allows studying protein folding on a
computer, Clementi and Das relied on the techniques of statistical
mechanics, building up an overall picture of MLAc folding based upon
statistical approximations of molecular events.
On the experimental side, Wittung-Stafshede,
Matthews and Wilson prepared samples of MLAc and added urea to cause
them to unfold. The team then injected water into the solution very
fast, diluting the mixture and causing the proteins to fold. Using
spectroscopy, they captured fluorescence and ultraviolet polarization
patterns given off by the proteins as they folded.
"The novelty of this work is the direct and
quantitative comparison of the time-dependent simulation data with the
experimental measurements from circular dichroism and tryptophan
fluorescence," Das said. "The excellent agreement between experiment
and theory illustrates that the existence of a well-defined "folding
route", at least for large proteins, can be predicted within the
framework of free-energy landscape theory. This has been a very
controversial issue in the field of protein folding."
Study co-authors also included Giovanni Fossati,
assistant professor of physics and astronomy, who helped the team
analyze and interpret the simulation data. |
