People have only 20,000 to 30,000 genes (the number is hotly contested), but they use those genes to make more than 2 million proteins. It's the protein molecules that domost of the work in the human cell. After all, the word protein comes from the Greek prota, meaning "of primary importance."
Proteins are created as chains of amino acids, and these chains of usually fold spontaneously into what is called their "native form" in milliseconds or a few seconds.
A protein's function depends sensitively on its shape. For example, enzymes and the molecules they alter are often described as fitting together like a lock and key. By the same token, misfolded proteins are behind some of the most dreaded neurodegenerative diseases, such as Alzheimer's, Parkinson's and mad cow disease.
Scientists can't match the speed with which proteins fold. Predicting how chains of amino acids will fold from scratch requires either powerful supercomputers or cloud sourcing (harnessing the pattern recognition power of thousands of people by means of games such as Folding@home).
Either way, prediction is time-consuming and often inaccurate, so much so that the protein-structure bottleneck is slowing the exploitation of DNA sequence data in medicine and biotechnology.
A clever way of watching proteins fold and unfold may finally provide the kind of detail needed to improve protein structure predictions.
In a recent issue of the online version of the Journal of the American Chemical Society three scientists, led by Michael L. Gross, PhD, professor of chemistry in Arts & Sciences and of medicine and immunology in the School of Medicine at Washington University in St. Louis, describe a proof-of-principle study in which they use the new approach to watch the folding of a small protein called barstar.
What they do is roughly analogous to filming flying bullets or bursing balloons with a stroboscope and a fast camera. The
|Contact: Diana Lutz|
Washington University in St. Louis