Latest News
September 19, 2005
Volume 83, Number 38
p. 7
COMPUTATIONAL CHEMISTRY

Protein Structure FromScratch
Method to generate high-resolution
protein structures is best so far
Celia Henry

COURTESY OF DAVID BAKER

PROTEIN FOLDERS Misura (from left), Bradley, andBaker developed a new computational method to predict
the structure of small proteins.

Scientists have known for more than 40 years that the aminoacid sequence of a protein dictates its structure. Therefore, it
should be possible to forecast how a protein will fold just byknowing the sequence. Yet scientists are still searching formethods that will accurately predict a protein structure fromscratch. Now, biochemistry professor David Baker andpostdocs Philip Bradley and Kira M. S. Misura of theUniversity of Washington, Seattle, have developed what they
believe is the best method so far for generating highresolution protein structures from the amino acid sequence(Science 2005, 309, 1868).
Predicting protein structure involves two key challenges:
calculating the protein's energy accurately and identifying
which among the myriad of conformations has the minimum
energy. The assumption--usually a good one--is that thenative structure is the lowest-energy conformation. Because
trying all possible conformations is computationallyimpossible, "you have to have a search that is focused on
the regions where the global energy minimum might lie,"
Baker says.
Baker and his coworkers have devised a two-step method tofind the lowest-energy conformation of an amino acidsequence. First, they do a low-resolution search of theenergy landscape using only the backbones of the target
protein, as well as those of 15-50 homologous proteins withsimilar sequences. The other protein sequences are key inthe folding simulation, because they allow the method toexplore other parts of the energy landscape and locate lowenergy conformations that are different but similar to thosethat the target protein sequence reveals, Baker says. "It's away of making this initial low-resolution sampling broader."Then, the low-energy regions found are used in a high-resolution energy search using only the target protein but
with all of its atoms.
The team used the method to predict the structures of 16
small proteins. Among them is the structure of a protein-from Thermus thermophilus--used in a competition called theSixth Critical Assessment of Techniques for Protein
Structure Prediction. The team predicted its folded structurewith a resolution of 1.6 Å without prior knowledge. The result"showed the best accuracy by far for an ab initio prediction in
the competition's 10-year history," says competition
organizer Tim Hubbard of the Wellcome Trust Sanger
Institute in Hinxton, England.
The method is far from perfect: It could predict the structure
accurately for only six of 16 proteins the team tried to solve.
The problem, Baker says, is one of sampling rather thanenergy calculation. "Sampling is a major bottleneck to being
able to predict structure more generally."
Baker is continuing to improve the accuracy of the method.
"Before the method is really ready for prime-time generaluse, it's got to be more accurate and more consistent," hesays. "It's not a replacement for real structural biology like
NMR spectroscopy or X-ray crystallography until essentiallyevery time you build a model and take your lowest-energy
structure, it's correct."
The method so far is limited to proteins with fewer than 85
amino acids, but Baker is optimistic. "It's not a conceptual
problem with larger proteins," he says. "With morecomputing power and maybe better algorithms, it should bepossible."COURTESY OF DAVID BAKER

PREDICTION The computational method devised byBaker and coworkers predicted the structure of aThermus thermophilus protein with 1.6-Å resolution. The
backbone trace is shown on the left, and the core side
chains are shown on the right.
Chemical & Engineering News
ISSN 0009-2347
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