In this ongoing quest, a group of Scripps Research Institute scientists, along with colleagues from the University of California, San Diego, (UCSD) have borrowed from physics to deliver one of those research raritiesan unmitigated success. The group has devised a computational method that, with remarkable accuracy, predicts how bacterial proteins fold and interact.
In the short term, this new capability, described in this week's Early Edition of the Proceedings of the National Academy of Sciences, should allow development of new antibiotics that target and block newly identified protein interactions vital to the survival of pathogenic bacteria. In the longer term, as the collective body of genomics data for humans and other animals grows, some version of the new technique may allow similar protein predictive capabilities for higher organisms, spawning a wealth of new and highly effective drug discovery options.
"I think it's a quantum leap," says team leader James Hoch, a professor at The Scripps Research Institute, of the work, "This is one thing I really am proud of."
Ever since genomic data has been available, researchers have been looking for ways to understand protein interactions, but no method has proven even close to sufficient. "It's really the last frontier in proteins," says Hoch, "figuring out who they interact with and the structures they make."
One way to study proteins is to actually image their interactions using x-ray crystallography. This has provided invaluable, but very limited, information, because the method is fraught with drawbacks including extreme labor intensity and great difficulty in actually capturing the intended protein interactions. Assistant Professor Hendrik Szurmant, another leader of the project from Scripps Research, says the process is so difficult with x-ray crystallography that it only rarely works for transient interactions.
Another available means for studying protein
|Contact: Keith McKeown|
Scripps Research Institute