A brief message about the Rosetta Energy Function
I just wanted to show an example of the Rosetta energy function that is used in Foldit.
We have evidence that the Rosetta energy function is able to pick out the native conformation when compared to many other models.
In the attached plot, the y-axis is the Rosetta score (negative is better here) and on the x-axis is how far off the model is from the native (so closer to the left is better). The wiggled native proteins are shown in blue on the very bottom left with all the black dots representing Rosetta predictions.
If you were to look at all models with a Rosetta score of exactly -170 (draw a line horizontally across the graph at -170) you can see that these models are very different from one another. If you look at the most successful predictions (shown by the red arrow) you can see that they have the best Rosetta score and are closest to the correct native structure. Based on this, we believe that our energy function is good at picking out folds that are similar to the native.
You'll notice that most of the Rosetta predictions on this graph are far from the native structure.
We are hoping that Foldit players will be able to more efficiently make accurate models of protein structures, because the automated methods are essentially random searches.
This figure is taken from the Science article:
"Toward High-Resolution de Novo Structure Prediction for Small Proteins"
Philip Bradley, Kira M. S. Misura, and David Baker
Science 16 September 2005: 1868-1871.