Design a protein with the help of the new AlphaFold prediction tool! AlphaFold is an algorithm from the company DeepMind and can predict protein structures with incredible accuracy. We want to know if Foldit players can use feedback from AlphaFold to design new proteins! After you've designed a protein, you can upload your solution to the Foldit server and get back an AlphaFold prediction about how your design will actually fold up. Players should aim for an AlphaFold confidence and similarity of 80% or more. See the blog for more details about the AlphaFold prediction tool.
We are especially interested to see what creative new folds players might come up with. We already know that Foldit players can design simple helix bundles or ferredoxin-like ("surfing hotdog") proteins. We are hoping that AlphaFold will allow players to explore protein designs with all beta sheets, or folds with a recessed binding pocket where a ligand could fit. After this puzzle closes, we'll highlight our favorite designs in the next Lab Report video update on September 1.
In addition to the typical extended chain, this puzzle has four starting structures of designed proteins that you may like to use as a starting point. Reset the puzzle to cycle through the different starting structures. There are no Objectives, but we expect successful designs will still need lots of helices or sheets, with short minimal loops, as well as a closely-packed core of orange hydrophobic residues. AlphaFold predictions will not affect your score. Players may insert and delete residues to a maximum of 120 residues total. This special puzzle will remain online until August 31 at 23:00 GMT.
If I've reached agreement with AF on the topology (confidence >80), and AF and foldit are now duking it out about how big the voids will be or what angle the helix will lie against the sheet (similarity never quite reaching 80), is it really useful to keep pushing for them to agree, or can I call that one done and move on to something else?
And which version do scientists want to see? I guess if I upload mine you can always run AF on it yourself? But if you will discard it due to similarity < 80%, I'll be sad.
Please share your Foldit-optimized design (not the raw AlphaFold prediction)! We can easily run AlphaFold predictions for your shared designs, and we like to see a players' best attempts in Foldit.
. . . is it really useful to keep pushing for them to agree, or can I call that one done and move on to something else?
We are still uncertain about this. Among previous Foldit designs, we have seen that AlphaFold similarity is slightly better than AlphaFold confidence for predicting successful designs. That suggests that, yes, it's worth it to keep refining your Foldit solution until AlphaFold similarity is greater than 80%.
However, we don't know how well that holds if you are iteratively loading AlphaFold solutions, refining them in Foldit, resubmitting to AlphaFold, re-refining in Foldit, etc. . . . This kind of strategy might "artificially" boost your AlphaFold similarity value without making meaningful improvements to your design.
Either way, I would hope that you could eventually find a high-scoring Foldit solution that also has a high AlphaFold similarity. If the differences cannot be reconciled, that might suggest a deeper problem (so you should share examples with scientists!).
I'm seeing this too. Doesn't happen with all AF-generated solutions but when it does it crashes consistently. Scientist-shared solution t4_c, when fed to AF, generates a solution which crashes when you try to load it.
This is a multistart puzzle, which is explained in the last paragraph of the puzzle description, which I hadn't read until just now.
When I started the puzzle, I saw a straight "extended chain", so I assumed that was that….
Resetting the puzzle gives you a different structure. Structure 5 is the extended chain. You can reset by ctrl-r or Undo => Reset Puzzle. The first time you open the puzzle, Foldit picks a structure at random.
The structure number appears briefly in a pop-up when you reset. The segment information window also contains the structure number in the third line. To open the segment information window, hover over any segment and hit the tab key.
I used Jpred to search for matches to the primary structure (amino acid sequence) of structures 1 through 4. Jpred looks for matches to "solved" proteins in the PDB (Protein Data Bank, at rcsb.org), and also in the UniProt database of protein sequences. Unlike the PDB, entries in UniProt may not have a known 3D structure. (Maybe AlphaFold can get that sorted.) Jpred doesn't always find PDB matches.
The results were:
Structure 1 - length 43 - JPred finds no matches, but rscb.org finds PDB 5UOI
Structure 3 - length 106 - no PDB match, but lots of UniProt matches
Structure 4 - length 109 - matches PDB 6D0T (chains A and B)
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So three of the structures have been "solved", and structure 2 was designed by Foldit players in the first place.
Structure 3 shows UniProt matches, where you'll quickly see things like "Cluster: SnoaL-like domain-containing protein" and *Burkholderia pyrrocinia*, part of the Burkholderia genus. Interesting, but not as helpful as having a 3D view available. If you look up "SnoaL", you may find "the proteins in this family adopt a distorted alpha-beta barrel fold", and see PDB 1SJW as an example.
(Edit: search at rcsb.org found match for structure 1, Jpred is not perfect.)
