model/ProteinMPNN/examples/submit_example_5.sh

#!/bin/bash
#SBATCH -p gpu
#SBATCH --mem=32g
#SBATCH --gres=gpu:rtx2080:1
#SBATCH -c 3
#SBATCH --output=example_5.out

source activate mlfold

folder_with_pdbs="../inputs/PDB_complexes/pdbs/"

output_dir="../outputs/example_5_outputs"
if [ ! -d $output_dir ]
then
    mkdir -p $output_dir
fi


path_for_parsed_chains=$output_dir"/parsed_pdbs.jsonl"
path_for_assigned_chains=$output_dir"/assigned_pdbs.jsonl"
path_for_fixed_positions=$output_dir"/fixed_pdbs.jsonl"
path_for_tied_positions=$output_dir"/tied_pdbs.jsonl"
chains_to_design="A C"
fixed_positions="9 10 11 12 13 14 15 16 17 18 19 20 21 22 23, 10 11 18 19 20 22"
tied_positions="1 2 3 4 5 6 7 8, 1 2 3 4 5 6 7 8" #two list must match in length; residue 1 in chain A and C will be sampled togther;

python ../helper_scripts/parse_multiple_chains.py --input_path=$folder_with_pdbs --output_path=$path_for_parsed_chains

python ../helper_scripts/assign_fixed_chains.py --input_path=$path_for_parsed_chains --output_path=$path_for_assigned_chains --chain_list "$chains_to_design"

python ../helper_scripts/make_fixed_positions_dict.py --input_path=$path_for_parsed_chains --output_path=$path_for_fixed_positions --chain_list "$chains_to_design" --position_list "$fixed_positions"

python ../helper_scripts/make_tied_positions_dict.py --input_path=$path_for_parsed_chains --output_path=$path_for_tied_positions --chain_list "$chains_to_design" --position_list "$tied_positions"

python ../protein_mpnn_run.py \
        --jsonl_path $path_for_parsed_chains \
        --chain_id_jsonl $path_for_assigned_chains \
        --fixed_positions_jsonl $path_for_fixed_positions \
        --tied_positions_jsonl $path_for_tied_positions \
        --out_folder $output_dir \
        --num_seq_per_target 2 \
        --sampling_temp "0.1" \
        --seed 37 \
        --batch_size 1