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Stanford and Google team up to simulate key drug receptor

ate; receptors naturally change configurations, and their intermediate forms might also have medical potential.

When developing a drug, scientists will often run a computer program, known as a docking program, that predicts how well the atomic structure of a proposed drug will fit into the known receptor.

In the case of GPCRs, for example, the X-ray crystallography techniques have detailed teceptors' "on" and "off" configurations; many medications have been specifically designed to fit into these sites. Scientists expect, however, that other fruitful configurations exist. Many drugs engage with GPCR sites, even though computational models suggest that they don't fit either of the two defined reaction site configurations.

Computer simulations of a GPCR's shape as it morphs from "on" to "off" could create a thicker catalog of reaction site profiles, Pande said, and provide scientists a better jumping-off point for computational drug design and more discoveries.

A cloud-based attack

To simulate the GPCR alternatives at the same atom-level accuracy of X-ray crystallography, however, would take too long using traditional computing methods.

"The computational burden of a model that is faithful to atomic details is very high," Pande said. "A very fast computer processor can compute a billionth of a second of this reaction in one computer day. So if you want to simulate a full reaction on a millisecond time scale, it's going to take millions of days."

Instead, Pande and his colleagues tapped the power of Google's Exacycle cloud computing system, which harnesses a distributed network of computers to process data in parallel.

The B2AR simulation consists of almost 60,000 atoms. Each Exacycle system simulated tens of thousands of random trajectories that these atoms could take as the protein shifted its shape, generating about 250,000 molecular structures per simulated system.

The research

Contact: Bjorn Carey
Stanford University

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