Last week, as the 2014 Big Data in Biomedicine conference came to a close, a related story about the importance of computing across disciplines posted on the Stanford University homepage. The article describes research making use of the new Stanford Research Computing Center, or SRCC (which we blogged about here). We're now running excerpts from that piece about the role computation, as well as big data, plays in medical advances.
As you sip your morning cup of coffee, the caffeine makes its way to your cells, slots into a receptor site on the cells' surface, and triggers a series of reactions that jolt you awake. A similar process takes place when Zantac provides relief for stomach ulcers, or when chemical signals produced in the brain travel cell-to-cell through your nervous system to your heart, telling it to beat.
In each of these instances, a drug or natural chemical is activating a cell's G-protein coupled receptor (GPCR), the cellular target of roughly half of all known drugs, says Vijay Pande, PhD, a professor of chemistry and, by courtesy, of structural biology and computer science at Stanford. This exchange is a complex one, though. In order for caffeine or any other molecule to influence a cell, it must fit snuggly into the receptor site, which consists of 4,000 atoms and transforms between an active and inactive configuration. Current imaging technologies are unable to view that transformation, so Pande has been simulating it using his Folding@Home distributed computer network.
So far, Pande's group has demonstrated a few hundred microseconds of the receptor's transformation. Although that’s an extraordinarily long chunk of time compared to similar techniques, Pande is looking forward to accessing the SRCC to investigate the basic biophysics of GCPR and other proteins. Greater computing power, he says, will allow his team to simulate larger molecules in greater detail, simulate folding sequences for longer periods of time, and visualize multiple molecules as they interact. It might even lead to atom-level simulations of processes at the scale of an entire cell. All of this knowledge could be applied to computationally design novel drugs and therapies.
“Having more computer power can dramatically change every aspect of what we can do in my lab,” says Pande, who is also a Stanford Bio-X affiliate. “Much like having more powerful rockets could radically change NASA, access to greater computing power will let us go way beyond where we can go routinely today.
Previously: Computing our evolution, Learning how to learn to read, Personal molecular profiling detects diseases earlier, New computing center at Stanford supports big data and Nobel winner Michael Levitt’s work animates biological processes
Photo by Toshiyuki IMIA
