Over the past decade, Baker and his colleagues have made steady progress in developing computer algorithms to predict how a string of amino acids will fold into a given proteins characteristic shape. This intricate folding is molded by the complex molecular side chains that project from the backbone of the protein and can interact in myriad ways, making such predictions far from straightforward. Among the teams chief computational tools is a program called Rosetta that calculates which of a proteins potential shapes is most efficient, or lowest in energy.
One of the thorniest problems Baker and his colleagues have faced with their algorithm is that folding proteins can get stuck in partially folded structures. Predicting protein structure involves finding a structure that has lower energy than any other structures the protein could adopt. We might have developed a protein structure that is close to the right structure, but not quite there, said Baker. You might think we could just wiggle the structure around and shake it computationally, but sometimes the energy barriers are so high that the protein just gets stuck in that shape. So, thats where we were stymied in our technique.
In the Nature article, Baker and colleagues reported a new strategy of targeted rebuilding and refining to overcome this hurdle. In this method, Rosetta identifies the regions most likely to give rise to misleading interim structures and isolates them for targeted rebuilding.
Its as if you have this complex coil of rope, and there is a section that you think just doesnt behave the way it should, explained Baker. So you just cut it out, reconnect the ends, and computationally explore different conformations of just that section until you have a better model of its behavior.
If a single round of this rebuilding and refinement does not produce the lowest-energy structure of a folded protein, the researchers repeat
|Contact: Jim Keeley|
Howard Hughes Medical Institute