AlphaFold
AlphaFold is Google DeepMind's protein structure prediction software that uses deep learning to minimize energy potential by modifying torsion angles.
AlphaFold's primary component is a CNN trained off of protein samples to predict distances between atoms within pairs of residues of a protein. Given an amino acid sequence, it produces a discrete probability distribution for every residue pair within a 64 by 64 area in the distance matrix. These local predictions can be combined to create a full set of predictions and a distance histogram (a matrix view of the distances between any two residues).
SIDENOTE: Network also outputs confidence for each prediction
Proteins were parameterized via torsion angles of each residue the coordinates for structure were generated via "differential models of protein geometry".
Hyperparameters/Details
- Dropout (keep prob 0.85)
- Parallelized SGD (batch sz 4)
- Activation function: ELU
- Learning rate: 0.06
- Learning rate decay (halved at 150000, 200000, 250000, 350000 steps)
- 5 days training time