Foldit design update - Part 1
It's been a long time since our last update on Foldit protein design! Here we lay out some recent progress and highlight the latest improvements in proteins designed by Foldit players.
Local Backbone Quality
Unlike designed α-helical bundles, which Foldit players have mastered with relative ease, the design of α/β folds has proven to be more problematic. For some time, we've suspected that the crux of the problem lies in unfavorable local backbone conformations. In particular, we found that the α/β proteins designed by Foldit players seemed to have loops that are never observed in natural proteins.
The Ideal Loop Filter, which was introduced last June, has helped Foldit designs remarkably. And in subsequent updates spanning the last several months we've seen further improvement in the backbone quality of Foldit-designed proteins. The box plot below shows the average local deviation from natural protein backbones in top-scoring Foldit designs. (Imagine breaking up each designed protein into 9-residue fragments, for each fragment searching natural proteins for a fragment with a similar backbone, and then measuring the RMSD to the closest match. If every backbone fragment of a design has a close match in a natural protein, that design should have a low mean RMSD; if there are regions of the design that have an unusual backbone, the design will have a higher mean RMSD.)
You can see that backbone quality in Foldit designs improved significantly after imposing the Ideal Loop Filter; disabling Rebuild; adjusting the IdealizeSS torsions; and introducing the Blueprint Panel. The dotted line marks a reference value from successful Baker lab designs; all designed proteins from Koga et al. fall below that line. In the latest design puzzles with the Blueprint Panel, we see that most high-ranking Foldit designs also fall below that line.
Rosetta@home Folding Funnels
The improvement in Foldit backbones is reflected in other types of analysis. With the improved backbones, Rosetta@home is better able to predict the structure of Foldit designs from their amino acid sequences (explained here).
Below is a set of 14 Foldit player designs that were successfully folded by Rosetta@home—all but one originate from puzzles using the Ideal Loop Filter. The strong "funnel" shape of each plot indicates not only that Rosetta is able to sample the intended fold (note the numerous red points with RMSD < 2 Å), but also that Rosetta predicts the intended structure to be the most stable. Compare these folding funnels to those of earlier α/β designs.
mimi, Mark- (Contenders) — Puzzle 1245
Bletchley Park, Mark- (Contenders) — Puzzle 1248
tokens, Galaxie (Anthropic Dreams) — Puzzle 1251
tokens, Galaxie (Anthropic Dreams) — Puzzle 1257
tokens (Anthropic Dreams) — Puzzle 1257
dcrwheeler — Puzzle 1263
fiendish_ghoul — Puzzle 1285
gitwut(Contenders) — Puzzle 1290
Bletchley Park, Cyberkashi, Mark- (Contenders) — Puzzle 1294
Hollinas, Bruno Kestemont, Scopper (Go Science) — Puzzle 1294
tokens (Anthropic Dreams) — Puzzle 1294
fiendish_ghoul — Puzzle 1297
fiendish_ghoul — Puzzle 1299
retiredmichael (Beta Folders)— Puzzle 1299
Each of the designs above has been reverse-transcribed into synthetic DNA, which is inserted into E. coli and expressed in our lab for further testing (read more about lab testing here). However, in the list above I've omitted four particularly promising designs that are already showing encouraging results. Next week we'll post a follow-up with more information about those designs, alongside some brand new experimental data.
A big thank you is due to all the Foldit players who have been designing proteins every week! We're learning a lot about protein design from your contributions, and credit goes to all participants—not just to those players acknowledged above. We appreciate your patience and persistence as we experiment with new tools and filters. Keep up the great folding!( Posted by bkoep 79 1027 | Tue, 02/28/2017 - 19:34 | 7 comments )