Learning about protein structure is especially relevant for treating illnesses that alter protein function, such as cancer.
Published in consecutive months of the Journal of Biomolecular NMR (nuclear magnetic resonance), Donald, a graduate student and a post-doctoral fellow present new algorithms that interpret NMR data to reveal a protein's shape and molecular architecture. NMR surveys a protein's molecular structure and uses tiny, spectroscopic protractors and rulers to generate a network of geometric measurements.
"In these papers, we discuss a new framework for thinking about how to solve these problems, and our algorithms are highly accurate," says Donald, the Joan P. and Edward J. Foley Jr. 1933 Professor of Computer Science and an Adjunct Professor of Chemistry and of Biological Sciences.
The first paper, published in June 2004, explains the work of Christopher Langmead, a doctoral student in Donald's laboratory who is now an assistant professor of computer science at Carnegie Mellon University. Langmead's algorithm introduced new techniques for assigning NMR measurements to specific molecular bonds. Most NMR experiments measure a protein, reporting distances between molecules and angles of chemical bonds, but the data doesn't indicate which atoms or bonds the measurements correspond to. "It's a little like taking all the heights and weights of everyone at a cocktail party, but you don't know which height goes with which person," says Donald. Langmead's
Contact: Sue Knapp