When Science published a breakthrough in the quest to predict how chains of amino acids fold up into proteins this January, it caught the attention of program managers at the U.S. Department of Energy.
The research, spearheaded by David Baker, a biochemist at the University of Washington in Seattle, included contributions from the DOE Joint Genome Institute, a DOE Office of Science User Facility at Lawrence Berkeley National Laboratory. DNA encodes the amino acid sequences of proteins. Baker’s team needed information on natural sequence variation for their prediction algorithm.
“With a lot of sequence data, it turns out we can predict protein structures more accurately,” said Baker.
DOE JGI provided Baker and his colleagues access to a database with 5 billion metagenome sequences derived from microbial communities found in diverse habitats across the globe.
Terry Law is the User Program Services manager at EMSL, the Environmental Molecular Sciences Laboratory, a DOE Office of Science User Facility at Pacific Northwest National Laboratory. When she read about Baker’s research and DOE JGI’s contribution, she paused. The prediction algorithm, called Rosetta, sounded familiar.