A Grid computing project has successfully simulated part of the complex folding process that a typical protein molecule undergoes to achieve its unique, three-dimensional shape, an achievement that could lead to breakthroughs in the study of protein-folding diseases like Alzheimer's, Parkinson's and Creutzfeldt-Jakob disease, the human equivalent of "Mad Cow" disease.
Folding@home scientists Christopher Snow and Vijay Pande of Stanford University reported their findings in the journal Nature. Their findings were confirmed in the laboratory of Houbi Nguyen and Martin Gruebele of the University of Illinois at Urbana-Champaign, who co-authored the Nature study.
Every protein molecule consists of a chain of amino acids that must assume a specific three-dimensional shape to function normally, according to a Stanford release.
"The process of protein folding remains a mystery," Pande, assistant professor of chemistry and of structural biology at Stanford, said in a statement. "When proteins misfold, they sometimes clump together, forming aggregates in the brain that have been observed in patients with Alzheimer's, Parkinson's and other diseases."
How proteins fold into their ideal conformation is a question that has puzzled scientists for decades. To try to solve that problem, Stanford researchers have turned to computer simulation via a massive volunteer computing Grid.
"One reason that protein folding is so difficult to simulate is that it occurs amazingly fast," Pande said. "Small proteins have been shown to fold in a timescale of microseconds, but it takes the average computer one day just to do a one-nanosecond folding simulation."
Two years ago, Pande launched Folding@home, a distributed computing project that so far has enlisted the aid of more than 200,000 PC owners, whose screensavers are dedicated to simulating the protein-folding process, similar to the better-known SETI@home project.
For the Nature study, Pande and Snow, a biophysics graduate student, asked volunteer PCs to resolve the folding dynamics of two mutant forms of a protein called BBA5. Each computer was assigned a specific simulation pattern based on its speed.
With the use of 30,000 computers, Pande and Snow performed 32,500 folding simulations and accumulated 700 microseconds of folding data. The simulations tested the folding rate of the protein on a 5-, 10- and 20-nanosecond timescale under different temperatures, Stanford said. Using the data, the scientists were able to predict the folding rate and trajectory of the average molecule.
To confirm their predictions, the Stanford team asked Gruebele and Nguyen to conduct laser temperature-jump experiments at their Illinois lab. In this technique, an unfolded protein is pulsed with a laser, which heats the molecule just enough to cause it to bend into its native state, Stanford said. A fluorescent amino acid imbedded inside the molecule grows dimmer as the protein folds. Researchers use the changing fluorescence to measure folding events as they occur.
The results of the laser experiments were in "excellent agreement" with the Folding@home predictions, Pande and his colleagues concluded. The computers predicted that one experimental protein would fold in 6 microseconds, while laboratory observations revealed an actual folding time of 7.5 microseconds.
"These experiments represent a great success for distributed computing," Pande said. "Understanding how proteins fold will likely have a great impact on understanding a wide range of diseases."
The Nature study was supported by the National Institutes of Health, the American Chemical Society, Intel and the Howard Hughes Medical Institute.
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