Catching the bugs

NIAID-funded protein structure effort helps deCODE attack emerging diseases

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BAINBRIDGE ISLAND, Wash.—Mid-December saw the announcement by deCODE biostructures Inc., that it received a five-year, $13.5 million collaborative subcontract from the Seattle Biomedical Research Institute (SBRI) to establish the Seattle Structural Genomics Center for Infectious Diseases (SSGCID). This is part of an overall effort funded by the National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health, to spur research into therapies for emerging or re-emerging infectious diseases—including those that may be potential bioterrorism weapons.

The SSGCID is a Washington-based consortium including scientists not just from SBRI and deCODE biostructures but also the University of Washington in Seattle and Battelle Northwest in Richland. With funding from NIAID's 2007 New Research Initiatives, the SSGCID will generate a collection of experimentally determined structures of protein targets from various infectious disease pathogens. Just a few of the diseases of interest include influenza, drug-resistant tuberculosis, cholera and typhus.

"The NIAID is interested in having centers to go after the targets that aren't considered daily by drug companies and thus don't get much money thrown in their direction," says Dr. Lance Stewart, president of deCODE biostructures. "More than that, though, what we discover could be useful for more traditional antibiotic targets and general work in anti-infectives, because the targets we are looking at are homologues of known targets. So there are much broader implications for this work as well."

This research will be accomplished by employing a high-throughput gene-to-structure pipeline involving a multi-pronged serial escalation approach to protein expression in bacterial, wheat-germ cell-free translation, baculovirus, and mammalian systems, followed by structure solution using X-ray crystallography and nuclear magnetic resonance spectroscopy.

"The protein structures produced by the SSGCID should provide the three-dimensional information needed to facilitate the structure-guided development of new drugs, vaccines and diagnostics to combat deadly infectious diseases," says Dr. Peter Myler, the principal investigator of SSGCID and a member of SBRI.

Although the work of deCODE and its SSGCID collaborators is all focused in the Northwest, the researchers also have a strong connection to the Midwest, as NIAID funded a second, $30-million structural genomics center at Northwestern University in Illinois as part of the same program.

"This is a very coordinated effort, and we are working closely with the Northwestern-based center to make sure we are doing unique, distinct work and not attacking the same targets and research goals and thus creating redundancies," Stewart says.

The SSGCID collaboration will leverage deCODE's platform for high-throughput protein crystal structure determination, from the computer-aided synthetic gene engineering to the determination of high resolution ligand-bound protein X-ray crystal structures, he says, and the  SSGCID funding will enable deCODE to more than double its X-ray data collection throughput.

Target selection by SSGCID collaborators will be managed by SBRI in collaboration with the NIAID, and each year, high-impact targets will be chosen for a fragment-based drug lead discovery campaign within SSGCID. There is no quota as such for how many will be chosen, though Stewart says his goal is to produce at least two high-impact targets each year.

As part of this project, deCODE will apply its Fragments of Life library technology for fragment-based lead identification to selected well-diffracting crystallized targets of high biomedical relevance.

The resulting fragment-bound target co-crystal structures are expected to provide valuable ligand binding information as starting points for structure-based drug discovery, and the SSGCID will make its structures freely accessible to the worldwide scientific community through the Protein Data Bank.


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