Design a protein that can bind to the BMPR target! Unlike in previous puzzles, this Neural Net Objective awards a 2000 pt. bonus for AlphaFold predictions with both high confidence and high similarity to the current solution. After an AlphaFold prediction is complete, load the original or predicted structure from the AlphaFold panel to receive the bonus. You can continue to work on this solution, but the bonus will disappear if the similarity drops. Note that the table in the AlphaFold panel only displays the similarity of the original solution; the true similarity of your current solution is recalculated by the Neural Net Objective as you change its structure.
Once you've designed a binder for the target, upload your solution for AlphaFold using the AlphaFold prediction tool. AlphaFold will predict the structure of your binder chain only (i.e. in the unbound state, in the absence of the target). If you load this prediction, then Foldit will attempt to align the prediction with your solution (i.e. in the bound state, making an interface with the target). If you continue working off of the AlphaFold prediction, you may need to make adjustments at the interface where the binder interacts with the target.
Bone morphogenic proteins (BMPs) are a type of signaling molecule that the body produces naturally to regulate tissue growth. When these molecules bind to a BMP receptor (BMPR) on the surface of a bone-producing osteoblast cells, this triggers the cell to generate new bone tissue. Synthetic BMPs are used in medicine to stimulate bone growth, especially for special procedures like spinal fusions. But synthetic BMPs bind to many off-target receptors in the body, and can cause unintended side effects. We'd like to design a protein that can bind specifically to BMPR without sticking to off-target receptors.
In this puzzle, we've presented a portion of the BMPR target that exposes its natural binding site. The backbone and most of the sidechains are frozen, except at the binding site, where flexible sidechains are shown in color. Players should design a new protein that can bind to these sidechains on the target. In order to bind the target, designs will need to make lots of hydrophobic contacts and satisfy any polar atoms that are buried at the interface. But designs will also need to have lots of secondary structure (helices or sheets) and a large core, so that they fold up correctly! See the puzzle comments for Objective details.
DDG Metric (max +2000)
The predicted binding energy of your design. The goal DDG is -40.0 or less.
Contact Surface (max +2000)
Measures how much of your binder surface is in close contact with the target protein. The goal Contact Surface is 500 or more.
Buried Unsats (max +500)
Penalizes 20 points for each polar atom that cannot make any hydrogen bonds.
Core Existence (max +1500)
Ensures that at least 25 percent of residues are buried in the core of the monomer unit.
Interaction Energy (max +500)
Monitors that all large PHE, TYR, and TRP residues are scoring well.
Ideal Loops (max +500)
Penalizes any loop region that does not match one of the Building Blocks in the Blueprint tool. Use "Auto Structures" to see which regions of your protein count as loops.
SS Design (max +500)
Disabled use of CYS residues.
Neural Net (max +2000)
Achieve an AlphaFold prediction confidence of 80% or more, and similarity to current solution is 80% or more.
Neural Net bonus doen't work in shared solutions (impossible to evolve: 2000+ points are needed).
Tip to surround this problem:
submit to AF
load original solution from AF
