HOUSTON, Oct. 3, 2005 -- In unprecedented new research, scientists at Rice University have combined theory and experiment for the first time to both predict theoretically and verify experimentally the protein-folding dynamics of a large, complex protein.
The interdisciplinary research appears this week in two back-to-back papers in the Proceedings of the National Academy of Sciences.
"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.
The research was funded by the National Science Foundation, the National Institutes of Health, the Texas Advanced Technology Program and the Welch Foundation.
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