This structure portrays the vibrational modes of conalbumin, a protein found in egg whites. Extraordinary Acoustic Raman (EAR) spectroscopy is an innovative method for characterizing such complex organic molecules as well as influencing their chemical action. Photo by: Tim DeWolf
As chemically intricate as proteins may be, understanding how they work may be a matter of listening very closely.
“Proteins are like little machines in your body,” says Reuven Gordon, an electrical and computer engineering professor at the University of Victoria. “They go around doing these jobs and it’s amazing what they can accomplish. But most of their functioning comes from large-scale macroscopic motion that allows them to do work,” Gordon says.
The study of this behaviour deals with normal mode analysis, an assessment of vibrational frequencies displayed by proteins. Gordon has extended this analysis so that these frequencies can be sampled and even adjusted using a variation of standard spectroscopic analysis. “These are in the range of 100 GHz acoustic vibrations,” he says, referring to this approach as Extraordinary Acoustic Raman (EAR) spectroscopy. Gordon’s research team outlined their accomplishment in a recent paper for Nature Photonics, as well as the more popular medium of YouTube, where visitors can hear these vibrations as a sound file.
EAR borrows the principle of electrostriction, which causes materials to change shape in an electric field, so that these vibrations can be isolated in samples as small as a single nanoparticle. Gordon’s lab has pioneered the use of paired nanoscale apertures to trap such samples optically; the amplitude modulation between two lasers of different frequencies effectively creates very fine tweezers for holding small particles.
Early this year, Gordon and his colleagues published a paper in Nanoscale introducing how they used these optical tweezers to assess the vibrational modes of DNA fragments. “The greatest potential for impact is in drug discovery and understanding biophysical processes — fundamental questions like allostery,” he says, referring to the subtle process by which biological molecules go about binding to one another. This approach could also determine the underlying causes of diseases like cystic fibrosis, which start with key proteins that do not fold in the right way.
Gordon emphasizes that EAR is a platform technology that could go in many directions. He is currently dedicated to refining its methodology for others to use, including the prospect of scaling it up for massively parallel drug discovery applications. “We are looking at several problems, such as drug discovery, protein analysis, allostery and virus particles,” he says. “But we haven’t zeroed in on just one.”