Design a protein with the help of the new Neural Net Objective! The Neural Net Objective can help identify parts of your protein that should be mutated to improve AlphaFold prediction confidence. After you use the AlphaFold tool to get a prediction, click "Show Neural Net Objective" to color your protein based on local distogram analysis. To improve AlphaFold prediction confidence, try mutating residues that are colored red by the Neural Net Objective. Players should aim for an AlphaFold confidence and similarity of 80% or more.
We are especially interested to see what creative new folds players might come up with. There are no additional 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.
I noticed that the higher my foldit points, the higher the AF confidence.
It's disappointing because this doesn't help me to select early designs with higher confidence. On end play, the AF doesn't help to select and finish with high confidence solutions (because most of them are high, and if a high score isn't, I still shall end with this for pure competition).
I think that a small bonus related to confidence (once you stop mutating) could help to align high score with confidence.
It would be great to be able to share a bit more to scientists - especially for these kind of puzzles which are designed to try a multitude of different approaches. Thx!
