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576: CASP10 Refinement Puzzle: TR661

Closed since over 10 years ago

Intermediate Overall Prediction


June 14, 2012
Max points

This target was originally 215 residues, but has been trimmed down to 185. We have been told that almost 80% of this model matches the native, so we are also giving you the template that was used to generate this model. Hopefully by moving the alignment around with the Alignment Tool you'll be able to completely match the native! Please read the puzzle comments for more on this.

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beta_helix Staff Lv 1

Here is the CASP link for this Refinement target:

Here is the sequence logo predicted by the SAM server.

H = helix
E = sheet
C = loop (or coil)

The taller the letter at each position, the higher the probability of that specific secondary structure for that amino acid.

For example, the Leucines at residues 18-19, 22, 40 & 82 are highly predicted to be in a helix. However, the Leucine at residue 131 is predicted to be in a sheet.

Note that we are giving you over 8 days to work on this one, because it's a large protein and TR688 will have to be due on the same day (they gave us less than 3 weeks to work on that one).

beta_helix Staff Lv 1

The model that the CASP organizers have given us for this Refinement Target is actually a RosettaServer model (generated using Rosetta@home).

The trouble with this (as we learned in CASP9, which you can read about here: is that this model is already minimized with Rosetta so it will be very hard to move that model out of its local energy minimum.

So for the starting model, we have given you the closest non-Rosetta server model (that is only 1.2 Angstroms RMSD away from the model chosen by the CASP organizers) so that you will be able to find high-scoring solutions that are slightly different than the ~80% correct starting structure.

In addition, we are providing you with the exact template and alignment that Rosetta used to generate that model, so you should be able to end up with the same structure as Rosetta (but without having it being heavily minimized). We also hope that by moving the alignment around you are able to increase the model accuracy from 80% to 100%.