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Recipe: 933 Secondary Structure from Contacts
Created by Susume 82 171
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Name: 933 Secondary Structure from Contacts
ID: 49562
Created on: Tue, 07/08/2014 - 11:22
Updated on: Tue, 07/08/2014 - 18:27
Description:

For CASP Ts802 (puzzle 933) or CASP Tc802 only! SS based on contact map. More hints about protein shape in script comments (view in script editor).



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Joined: 09/24/2012
Groups: Go Science
thanks for doing this !

I don't understand how you deduce structure from contact, but it seems heart and I use your structures

LociOiling's picture
User offline. Last seen 4 hours 25 min ago. Offline
Joined: 12/27/2012
Groups: Beta Folders
output from Contact Cement may help

Contact Cement (http://fold.it/portal/recipe/49061 or http://fold.it/portal/recipe/49437) prints the contact info in spreadsheet friendly CSV format, for example:

Contact Cement v1.00
106 contacts with non-zero heat found
seg1,seg2,heat
8,27,1
9,27,1
10,25,1
12,22,1
12,23,1
12,60,1
13,21,1
...

The format is segment 1, segment 2, contact heat.

In this short example, there's segment 1:

8 - 9 - 10 - [11] - 12 - 13

and segment 2:

27 - [26] - 25 - [24] - 23 - 22 - 21.

Even though there are gaps like [11], [26], and [24], the contacts suggest two sheets in an antiparallel alignment, where the lower-numbered end of one sheet is adjacent to the higher-numbered end of the other sheet.

The contact 12,60 indicates contact with another part of the protein.

On the other hand, there's

57,61,1
58,60,1
59,61,1
59,62,1
60,62,1
61,63,1
62,64,1
63,116,1
65,68,1

Again there's an outlier at 63,116. The rest of the points have one segment in contact with another two to four segments away. A couple of points like this probably indicate a turn, but a longer list of points tends to indicate a helix.

So one technique is to paste the output from Contact Cement into a spreadsheet and manually group the contacts.

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Developed by: UW Center for Game Science, UW Institute for Protein Design, Northeastern University, Vanderbilt University Meiler Lab, UC Davis
Supported by: DARPA, NSF, NIH, HHMI, Amazon, Microsoft, Adobe, RosettaCommons