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2211: cAMP Ligand Binder Design

Closed since over 3 years ago

Intermediate Overall Design

Summary


Created
October 12, 2022
Expires
Max points
100
Description

Design a binding pocket for the cAMP ligand! This puzzle enables AlphaFold predictions for your binder design, so you can upload your solution for AlphaFold using the AlphaFold prediction tool. AlphaFold will predict the structure of your binder only (i.e. in the absence of the ligand). If you load this prediction, then Foldit will attempt to align the prediction with your solution. We are looking for designs where the raw AlphaFold prediction has a binding pocket that fits the ligand!

Cyclic AMP (cAMP) is a secondary signaling molecule found within the cell. We typically think of signaling molecules as things that bind to surface receptors on the outside of the cell. Often these surface receptors produce secondary signals inside the cell membrane; these spread throughout the cell so that interior machinery can respond to the original surface signal. cAMP is extremely polar, which makes it a very difficult binding target! A good binder will need to make lots of H-bonds with the cAMP ligand in order to satisfy all of the polar atoms.

This puzzle starts with the backbone from a natural cAMP binder, with the ligand placed roughly in the correct position in the binding pocket. However, players may completely redesign the protein or reposition the ligand within the binding pocket. Try to design a binding pocket with high Contact Surface and zero BUNS! See the puzzle comments for Objective details.

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Comments


bkoep Staff Lv 1

Objectives

Contact Surface Metric (max +2000)
Measures how much of your binder surface is in close contact with the target protein. The goal Contact Surface is 200 or more.

Buried Unsats (max +500)
Penalizes 100 points for each polar atom that cannot make any hydrogen bonds.

Neural Net (max +0)
Achieve an AlphaFold prediction confidence of 80% or more.

spvincent Lv 1

AlphaFold doesn't seem to like this starting structure at all. Maybe it's just me but all the scores I'm getting are in the 30-40% range for both confidence and similarity.