AlphaFold Latent Flooding: Zero-shot Prediction of Protein Conformational Ensemble

Zilin Song (song.zilin@outlook.com)

Installation

If you have a working AF2 environment, install the following packages depends on your JAX/JAXLIB version in the environment. For more info, see the corresponding GitHub repos and find a compatible release.

optax

If installing from scratch, the following provides a non-Docker approach, depends on your cuda version (below are for CUDA 11.2):

conda create -n aftools python=3.9
conda activate aftools
conda install -y -c conda-forge openmm==7.5.1 cudatoolkit=11.2 pdbfixer
pip install -r requirements.txt --no-cache-dir
pip install --upgrade --no-cache-dir jax==0.3.25 jaxlib==0.3.25+cuda11.cudnn805 optax==0.1.7 -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html

For unit tests, install the following:

conda install parameterized

Example with TEM-1

For AFLF checkpoint modeling:

python test_chkp.py

For AFLF inference modeling:

python test2_tem1.py

File descriptions

./afmisc/ Miscellaneous files from AlphaFold repository;
./aftools/ Implements the AFLF algorithm and helper functions;
./alphafold/ The AlphaFold source code;
./test2_tem1/ The working directory for the TEM-1 example;
./featureizer.* Customized scripts that executes the native AlphaFold featurization pipeline, generate features.pkl;
./test_chkp.py Executes the AFLF checkpoint modeling for TEM-1;
./test2_tem1.py Executes the AFLF inference modeling for TEM-1;
./prep2_tem1.py Preprocessing file for region definitions for AFLF inference modeling for TEM-1 (requires MDAnalysis), generates ./test2_tem1/prep.pkl;
./LICENSE The AlphaFold license.