Rosetta algorithm allows ab initio protein folding prediction from sheer amino acid sequence

Chevy Chase 12 February 2001Rosetta, a computational method developed by Howard Hughes Medical Institute investigator David A. Baker and his colleagues at the University of Washington, has proven quite successful in predicting the three-dimensional structure of a folded protein from its linear sequence of amino acids during the fourth Critical Assessment of Techniques for Protein Structure Prediction (CASP4).

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In the CASP4 experiment, which began in April 2000, over 100 research groups generated three-dimensional structures for 40 candidate proteins. A candidate protein, or target, was considered to be eligible for CASP4 if its three-dimensional structure had been deduced via structural analysis but not yet published by researchers or made public in a protein structure database. Each research group was given the amino acid sequence of the target proteins, and they were asked to develop three-dimensional models of the folded proteins. The results of CASP4 were presented and discussed at a conference in Asilomar, California, in early December.

Even a few years ago, according to researcher David A. Baker, success in predicting how proteins assume their intricate three-dimensional forms was considered very unlikely if there was no related protein of known structure. For those proteins whose sequence resembles a protein of known structure, the three-dimensional structure of the known protein can be used as a "template" to deduce the unknown protein structure. About 60 percent of protein sequences arising from the genome sequencing projects however have no homologues of known structure.

Despite the lack of past success, researchers have pursued the problem of predicting three-dimensional protein structure only from the amino acid sequence, which is called ab initio prediction, because it is one of the central problems in computational molecular biology. Recently, the problem has taken on more importance as human gene sequencing efforts have provided researchers with massive amounts of raw gene sequence data.

"One of the problems with structure prediction is that it is all too easy to produce a programme that correctly predicts the structure of a protein if you know the correct structure in advance", David Baker explained. "By challenging researchers to produce models before knowing the right answer, the CASP experiments have provided an invaluable boost to the field." The Rosetta computer algorithm for predicting protein folding draws on experimental studies of protein folding by David Baker's laboratory and many others.

"During folding, each local segment of the chain flickers between a different subset of local conformations", commented David Baker. "Folding to the native structure occurs when the conformations adopted by the local segments and their relative orientations allow burial of the hydrophobic residues, pairing of the beta strands, and other low energy features of native protein structures. In the Rosetta algorithm, the distribution of conformations observed for each short sequence segment in known protein structures is taken as an approximation of the set of local conformations that sequence segment would sample during folding. The programme then searches for the combination of these local conformations which has the lowest overall energy."

The results reported utilising Rosetta at the CASP4 meeting revealed that enormous progress has been made in ab initio structure prediction, as David Baker added. "For example, four years ago, at the CASP2 meeting, there were few reasonable ab initio structure predictions. In contrast, in the CASP4 experiment, analysis of the predicted structures showed that for the majority of proteins with no homology to proteins of known structure, we had produced reasonable low-resolution models for large fragments of up to about 90 amino acids."

"Interestingly, some of our predicted structures were quite similar to structures of proteins that had already been solved, and which turned out to have similar functions to the target protein, even though there was no significant sequence similarity. Thus, our predicted structures provided clues about function which could not be obtained by traditional sequence comparison methods", David Baker continued.

Peter Kollman, an expert in computational molecular modelling at the University of California, San Francisco, who participated in the CASP4 experiment, gives some additional perspective. "The evaluators of the structures for the ab initio predictions gave two points for a structure which was among the very best, one point for a structure that was pretty good and zero if the structure was reasonably far from the correct one. The amazing thing is that David Baker's group had 31 points and the next best group had 8 points. Nonetheless, there is still some way to go in predicting these structures to experimental accuracy but all of us are hopeful this will advance also."

David Baker concurred: "While these three-dimensional structures are not detailed enough, for example, for structure-based drug design, they can yield invaluable insights into the function of unknown proteins. So, our aim consists in using our ab initio structure prediction method to produce three-dimensional models for proteins of unknown function. Using those models, we can search the database of protein structures to determine whether they are similar to proteins of known function. From this similarity, it might be possible to draw functional inferences about what those proteins do."

"We are very excited now about trying to do this on a large scale, to make functional inferences for the large fraction of proteins about which one cannot currently say anything at all", stated David Baker. "The power of these methods is that, since no information is needed other than the amino acid sequence, one can conceive of going through a genome and generating structures and possibly functional insights for every protein."


Leslie Versweyveld

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