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AlphaFold 3 on Lawrencium

AlphaFold 3 is a new AI model developed by Google DeepMind and Isomorphic Labs for generating 3D predictions of biological systems. The software package and the public database is now available ont the Lawrencium cluster.

Genetic Databases

The genetic database required for AlphaFold 3 is saved under the shared directory /clusterfs/collections/Alphafold3/public-db on the cluster.

Model Parameters

The model parameters are the result of training the AlphaFold model and required for inference pipeline of AlphaFold 3. The model parameters are distributed separately from the source code by Google DeepMind and subject to terms Model Parameters Terms of Use .

Lawrencium users interested in using AlphaFold 3 are required to abide to above terms. Users can request a personal copy of the model parameters directly from Google DeepMind by filling out this form. If you have any questions about fields of the form then you may send us an inquiry at hpcshelp@lbl.gov. Once you get response and directions from Google DeepMind on obtaining model parameters you may save the parameters file in your home directory or project directory (if you are sharing with your group members) inside directory model_param. The parameters file is a single file approximately 1GB in size.

Loading AlphaFold 3 module

module load ml/alphafold3

The ml/alphafold3 module defines various environment variables such as ALPHAFOLD_DIR and DB_DIR that can be used to run a job as shown below. Users will have to setup environment variable for MODEL_PARAMETERS_DIR before running the script or it can be setup directly in the job submission script as shown below.

Running

Note

  • Use python /app/alphafold/run_alphafold.py when using the alphafold3.sif image from the ml/alphafold3 module. This is different from the official instructions on the alphafold3 github page. See the sample slurm script below.

Below is a sample script to run alphafold3 after loading ml/alphafold3 module. It assumes the presence of fold_input.json in $HOME/af_input and saves output to $HOME/af_output. Please pay close attention to different options, path and variables and make changes as necessary.

#!/bin/bash
#SBATCH --account=<account>
#SBATCH --partition=es1
#SBATCH --gres=gpu:H100:1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=14
#SBATCH --nodes=1
#SBATCH --qos=es_normal
#SBATCH --time=1:30:00

module load ml/alphafold3

# export MODEL_PARAMETERS_DIR variable according to where they are saved
#If model parameters are saved in your home directory
export MODEL_PARAMETERS_DIR=/global/home/users/$USER/model_param

#If model parameters are saved in your group directory
export MODEL_PARAMETERS_DIR=/global/home/groups/<project_name>/model_param

apptainer exec --nv --bind $HOME/af_input:/root/af_input \
                    --bind $HOME/af_output:/root/af_output \
                    --bind $MODEL_PARAMETERS_DIR:/root/models \
                    --bind $DB_DIR:/root/public_databases \
                    $ALPHAFOLD_DIR/alphafold3.sif \
                    python /app/alphafold/run_alphafold.py \
                    --json_path=/root/af_input/fold_input.json \
                    --model_dir=/root/models \
                    --db_dir=/root/public_databases \
                    --output_dir=/root/af_output