Big data helps scientists solve protein puzzles

Protein models
The molecular diagram at left is a representation of a protein molecule known as DMT superfamily transporter YddG, generated by Rosetta@Home software. The diagram at right is a representation of the molecule as determined by experiments. (Sergei Ovchinnikov et al. / UW via AAAS / Science)

Molecular biologists have enlisted cutting-edge trends in genomics and big data to get a grip on one of the grand challenges of biotech: figuring out how protein molecules fold.

But they couldn’t have done it without the help of tens of thousands of volunteers.

The fruits of all that crowdsourced computer labor went public today in the journal Science. Researchers from the University of Washington and other institutions say they’ve solved more than 600 protein-folding mysteries – which represents a fair proportion of the estimated 5,200 protein families whose molecular structure was unknown.

Still more solutions are in the works, and solving those puzzles could lead to new types of medicines and synthetic molecular machinery.

Get the full story on GeekWire.

By Alan Boyle

Mastermind of Cosmic Log, contributor to GeekWire and Universe Today, author of "The Case for Pluto: How a Little Planet Made a Big Difference," past president of the Council for the Advancement of Science Writing.

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