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Decoding proteins using your very own super computer

Welcome to the latest edition of Biomed Bites, a weekly feature that introduces readers to some of Stanford's most innovative researchers. 

A quick review: DNA codes for RNA, which directs the formation of proteins, the body's teensy building blocks and messengers. But like individual widgets, proteins still aren't ready for prime time as soon as they pop off the assembly line.

First they must be folded, partnered with other proteins and crafted into a three-dimensional shapes. Then, they can go about the work of life.

Stanford biochemist Vijay Pande, PhD, has been studying proteins for quite some time, and early on he realized that experimentally, proteins aren't that easy to examine. They're small and they rely on precise environmental cues. Once stripped from the cell, proteins behave and assemble differently, perhaps even not at all.

"So we take a very different approach," Pande says in the video above:

We’ve been pioneering new simulation methods to not just be able to look at the problem experimentally, but to use large-scale computer simulations to understand why proteins would fold correctly, or why they would not fold correctly such as in the case with disease.

By using a very unusual approach where we get people around the world to donate computer time to us, we assembled the most powerful supercomputer in the world to tackle problems like protein folding and protein misfolding.

More than 183,000 computers now contribute to Pande's project, Folding@home. Perhaps yours will be 183,001.

Learn more about Stanford Medicine’s Biomedical Innovation Initiative and about other faculty leaders who are driving biomedical innovation here.

Previously: Using a smartphone and the Folding@home app to advance disease research, What computation tells us about how our bodies work and Nobel winner Michael Levitt's work animates biological processes

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