Boltz-1 is the state-of-the-art open-source model to predict biomolecular structures containing combinations of proteins, RNA, DNA, and other molecules. It also supports modified residues, covalent ligands and glycans, as well as conditioning the prediction on specified interaction pockets or contacts. Boltz-2 is the first deep learning model to approach the accuracy of physics-based free-energy perturbation (FEP) methods, while running 1000x faster — making accurate in silico screening practical for early-stage drug discovery.
--cache /data/$USER/boltz
Allocate an interactive session and run the program.
Sample session (user input in bold):
[user@biowulf]$ sinteractive --gres=lscratch:30,gpu:a100:1 -c 8 --mem=20g
salloc.exe: Pending job allocation 46116226
salloc.exe: job 46116226 queued and waiting for resources
salloc.exe: job 46116226 has been allocated resources
salloc.exe: Granted job allocation 46116226
salloc.exe: Waiting for resource configuration
salloc.exe: Nodes cn3144 are ready for job
[user@cn3144 ~]$ module load boltz
[user@cn3144 ~]$ cd /data/$USER/
[user@cn3144 ~]$ cp -r {$BOLTZ_EXAMPLES:-none} .
[user@cn3144 ~]$ boltz predict ./examples/ligand.yaml --cache /data/$USER/boltz
Create a batch input file (e.g. boltz.sh). For example:
#!/bin/bash set -e module load boltz boltz predict ./examples/ligand.yaml --cache /data/$USER/boltz
Submit this job using the Slurm sbatch command.
sbatch --cpus-per-task=6 --mem=20g --gres=lscratch:30,gpu:a100:1 --partition=gpu boltz.sh