Stanford University researchers are seeking to make use of their distributed computing project to simulate the way proteins take shape. Protein-folding modeling can help evolve new therapeutic approaches, says Vijay Pande, the brain behind the group.
Proteins control nearly all of life's functions, but how they self-assemble, or fold, is an unsolved problem in biology. Understanding how folding goes awry could lead to cures for diseases caused by protein misfolding, like Alzheimer's and Parkinson's.
By modeling protein folding, group leader Vijay Pande says, "We hope to get exquisite detail and information that you might not be able to get from experiments."
Their [email protected]
uses processor time donated by millions of home computer and video game console users. It has advanced the field of molecular dynamics by cutting protein-folding simulation times from years to days. Recently, Pande's group used [email protected]
simulations to investigate new therapeutic approaches for Alzheimer's.
Thanks to the distributed computing project, people from throughout the world download and run software to band together to make one of the largest supercomputers in the world.
Now they have developed Copernicus, a new framework, in collaboration with the labs of Erik Lindahl at Sweden's KTH Royal Institute of Technology and Stockholm University and Peter Kasson at the University Virginia. It was presented this week at SC11, an international supercomputing conference, in Seattle.
"We're bringing [email protected]
to supercomputers," said Pande, a professor of chemistry.
The vast computing resources of [email protected]
have been available to Pande and his collaborators. With open-source Copernicus software, other researchers can run simulations, including molecular models, using processer time on multiple supercomputers or computing clusters, rather than home computers.
"It opens the door to huge crowds of people using these methods, which have matured with [email protected]
," Pande said.
With an interest in solving protein structures and having large computing clusters on hand, pharmaceutical companies are an example of one potential Copernicus user-group.
The advantage of Copernicus comes from how it uses the fast communication available between supercomputers, combined with statistical sampling techniques, to run parallel simulations within or between computing clusters or between supercomputers.
Copernicus allows for each additional processor in the system to aid the calculation to run faster and faster, something known as strong scaling. Previously, when using supercomputers to understand molecular dynamics, it has been very difficult to achieve strong scaling on a single machine.
"This method should be able to use any supercomputer on the planet completely," Pande said. "Strong scaling to these extremes is unusual." [email protected]
is useful for molecular simulations that take place on relatively long timescales. But Copernicus will be a tool for shorter problems where researchers want a quick solution.
Computationally, using Copernicus is like taking a Lamborghini to run out for milk. [email protected]
, on the other hand, "is kind of like a rocket. It takes a big deal to launch it and once you launch, it goes really far," Pande said. "You don't use it to go to the corner store."