| #!/bin/bash |
| cat << 'EOF' |
| ____ _ _ _ _ _ _ ____ _ _____ ____ _ _ ____ _ _ ____ _ ____ _ _ |
| ____ __ ____ _ ____ _ __ __ _ |
| / ___| _ _ _ __ / _| _ \ ___ ___| | __ | __ ) ___| |_ __ _ \ \ / /__ _ __ ___(_) ___ _ __ |
| \___ \| | | | '__| |_| | | |/ _ \ / __| |/ / | _ \ / _ \ __/ _` | \ \ / / _ \ '__/ __| |/ _ \| '_ \ |
| ___) | |_| | | | _| |_| | (_) | (__| < | |_) | __/ || (_| | \ V / __/ | \__ \ | (_) | | | | |
| |____/ \__,_|_| |_| |____/ \___/ \___|_|\_\ |____/ \___|\__\__,_| \_/ \___|_| |___/_|\___/|_| |_| |
| |
| |
| ____ _ _ _ _ _ _ ____ _ _____ ____ _ _ ____ _ _ ____ _ ____ _ _ |
| EOF |
| |
| # This script is used to run SurfDock on test samples |
| source ~/miniforge3/bin/activate SurfDock |
| path=$(readlink -f "$0") |
| SurfDockdir="$(dirname "$(dirname "$(dirname "$(dirname "$path")")")")" |
| SurfDockdir=${SurfDockdir} |
| echo SurfDockdir : ${SurfDockdir} |
| |
| temp="$(dirname "${SurfDockdir}")" |
| model_temp=${SurfDockdir} |
| |
| #------------------------------------------------------------------------------------------------# |
| #------------------------------------ Step1 : Setup Params --------------------------------------# |
| #------------------------------------------------------------------------------------------------# |
| |
| export precomputed_arrays="${temp}/precomputed/precomputed_arrays" |
| ## Please set the GPU devices you want to use |
| gpu_string="7" |
| echo "Using GPU devices: ${gpu_string}" |
| IFS=',' read -ra gpu_array <<< "$gpu_string" |
| NUM_GPUS=${#gpu_array[@]} |
| export CUDA_VISIBLE_DEVICES=${gpu_string} |
| ## Please set the main Parameters |
| main_process_port=2957${gpu_array[-1]} |
| ## Please set the project name |
| project_name='SurfDock_Screen_samples_skip_target_processed' |
| # /home/caoduanhua/NM_submit_code/SurfDock |
| # Set default value for target_have_processed if not already set |
| target_have_processed=${target_have_processed:-true} |
| ## Please set the path to save the surface file and pocket file |
| surface_out_dir=${temp}/Screen_result/processed_data/${project_name}/test_samples_8A_surface |
| ## Please set the path to the input data |
| data_dir=${SurfDockdir}/model/data/Screen_sample_dirs/test_samples |
| ## Please set the path to the output csv file |
| out_csv_dir=${temp}/Screen_result/processed_data/${project_name}/input_csv_files/ |
| out_csv_file=${out_csv_dir}/test_samples.csv |
| ## Please set the path to the esmbedding file |
| esmbedding_dir=${temp}/Screen_result/processed_data/${project_name}/test_samples_esmbedding |
| ## Please set the path to the Screen ligand library file |
| Screen_lib_path=${SurfDockdir}/model/data/Screen_sample_dirs/test_samples/1a0q/1a0q_ligand_for_Screen.sdf |
| ## Please set the path to the docking result directory |
| docking_out_dir=${temp}/Screen_result/docking_result/${project_name} |
| #------------------------------------------------------------------------------------------------# |
| # -----------------------Step1 : Processed Target Structure -------------------------------------# |
| #----------------(Set target_have_processed as true if you have done with your pipeline)---------# |
| #------------------------------------------------------------------------------------------------# |
| mkdir -p $surface_out_dir |
| if [ "$target_have_processed" = true ]; then |
| echo "Target structure has been processed, skipping this step." |
| else |
| echo "Processing target structure with OpenBabel..." |
| export BABEL_LIBDIR=~/miniforge3/envs/SurfDock/lib/openbabel/3.1.0 |
| command=` |
| python ${SurfDockdir}/model/comp_surface/protein_process/openbabel_reduce_openbabel.py \ |
| --data_path ${data_dir} \ |
| --save_path ${surface_out_dir}` |
| state=$command |
| fi |
| |
| #------------------------------------------------------------------------------------------------# |
| #----------------------------- Step2 : Compute Target Surface -----------------------------------# |
| #------------------------------------------------------------------------------------------------# |
| cd $surface_out_dir |
| command=` |
| python ${SurfDockdir}/model/comp_surface/prepare_target/computeTargetMesh_test_samples.py \ |
| --data_dir ${data_dir} \ |
| --out_dir ${surface_out_dir} \ |
| ` |
| state=$command |
| |
| #------------------------------------------------------------------------------------------------# |
| #-------------------------------- Step3 : Get Input CSV File -----------------------------------# |
| #------------------------------------------------------------------------------------------------# |
| |
| command=` python \ |
| ${SurfDockdir}/model/inference_utils/construct_csv_input.py \ |
| --data_dir ${data_dir} \ |
| --surface_out_dir ${surface_out_dir} \ |
| --output_csv_file ${out_csv_file} \ |
| --Screen_ligand_library_file ${Screen_lib_path} \ |
| ` |
| state=$command |
| |
| #------------------------------------------------------------------------------------------------# |
| #-------------------------------- Step4 : Get Pocket ESM Embedding ----------------------------# |
| #------------------------------------------------------------------------------------------------# |
| |
| esm_dir=${SurfDockdir}/model/esm |
| sequence_out_file="${esmbedding_dir}/test_samples.fasta" |
| protein_pocket_csv=${out_csv_file} |
| full_protein_esm_embedding_dir="${esmbedding_dir}/esm_embedding_output" |
| pocket_emb_save_dir="${esmbedding_dir}/esm_embedding_pocket_output" |
| pocket_emb_save_to_single_file="${esmbedding_dir}/esm_embedding_pocket_output_for_train/esm2_3billion_pdbbind_embeddings.pt" |
| # get faste sequence |
| command=`python ${SurfDockdir}/model/datasets/esm_embedding_preparation.py \ |
| --out_file ${sequence_out_file} \ |
| --protein_ligand_csv ${protein_pocket_csv}` |
| state=$command |
| # esm embedding preprateion |
| |
| command=`python ${esm_dir}/scripts/extract.py \ |
| "esm2_t33_650M_UR50D" \ |
| ${sequence_out_file} \ |
| ${full_protein_esm_embedding_dir} \ |
| --repr_layers 33 \ |
| --include "per_tok" \ |
| --truncation_seq_length 4096` |
| state=$command |
| |
| |
| # map pocket esm embedding |
| command=`python ${SurfDockdir}/model/datasets/get_pocket_embedding.py \ |
| --protein_pocket_csv ${protein_pocket_csv} \ |
| --embeddings_dir ${full_protein_esm_embedding_dir} \ |
| --pocket_emb_save_dir ${pocket_emb_save_dir}` |
| state=$command |
| |
| # save pocket esm embedding to single file |
| command=`python ${SurfDockdir}/model/datasets/esm_pocket_embeddings_to_pt.py \ |
| --esm_embeddings_path ${pocket_emb_save_dir} \ |
| --output_path ${pocket_emb_save_to_single_file}` |
| state=$command |
| |
| #------------------------------------------------------------------------------------------------# |
| #------------------------ Step5 : Start Sampling Ligand Confromers ----------------------------# |
| #------------------------------------------------------------------------------------------------# |
| |
| diffusion_model_dir=${model_temp}/weight/docking |
| confidence_model_base_dir=${model_temp}/weight/posepredict |
| protein_embedding=${pocket_emb_save_to_single_file} |
| test_data_csv=${out_csv_file} |
| cd ${SurfDockdir}/scripts/bash_scripts/test_scripts |
| mdn_dist_threshold_test=3.0 |
| version=6 |
| dist_arrays=(3) |
| for i in ${dist_arrays[@]} |
| do |
| mdn_dist_threshold_test=${i} |
| |
| command=`accelerate launch \ |
| --multi_gpu \ |
| --main_process_port ${main_process_port} \ |
| --num_processes ${NUM_GPUS} \ |
| ${SurfDockdir}/scripts/inference_accelerate.py \ |
| --data_csv ${test_data_csv} \ |
| --model_dir ${diffusion_model_dir} \ |
| --ckpt best_ema_inference_epoch_model.pt \ |
| --confidence_model_dir ${confidence_model_base_dir} \ |
| --confidence_ckpt best_model.pt \ |
| --save_docking_result \ |
| --mdn_dist_threshold_test ${mdn_dist_threshold_test} \ |
| --esm_embeddings_path ${protein_embedding} \ |
| --run_name ${confidence_model_base_dir}_test_dist_${mdn_dist_threshold_test} \ |
| --project ${project_name} \ |
| --out_dir ${docking_out_dir} \ |
| --batch_size 400 \ |
| --batch_size_molecule 10 \ |
| --samples_per_complex 40 \ |
| --save_docking_result_number 40 \ |
| --head_index 0 \ |
| --tail_index 10000 \ |
| --inference_mode Screen \ |
| --wandb_dir ${temp}/docking_result/test_workdir` |
| state=$command |
| done |
| #------------------------------------------------------------------------------------------------# |
| #---------------- Step6 : Start Rescoring the Pose For Screening -----------------# |
| #------------------------------------------------------------------------------------------------# |
| echo '---------------- Step4 : Start Rescoring the Pose For Screening -----------------' |
| # project_name='SurfDock_Screen_samples/repeat_zero' |
| |
| # surface_out_dir=${SurfDockdir}/model/data/Screen_sample_dirs/${project_name}/test_samples_8A_surface |
| # data_dir=${SurfDockdir}/model/data/Screen_sample_dirs/test_samples |
| out_csv_file=${out_csv_dir}/score_inplace.csv |
| |
| command=` python \ |
| ${SurfDockdir}/model/inference_utils/construct_csv_input.py \ |
| --data_dir ${data_dir} \ |
| --surface_out_dir ${surface_out_dir} \ |
| --output_csv_file ${out_csv_file} \ |
| --Screen_ligand_library_file ${Screen_lib_path} \ |
| --is_docking_result_dir \ |
| --docking_result_dir ${docking_out_dir} \ |
| ` |
| state=$command |
| |
| confidence_model_base_dir=${model_temp}/weight/screen |
| |
| test_data_csv=${out_csv_file} |
| |
| version=6 |
| dist_arrays=(3) |
| for i in ${dist_arrays[@]} |
| do |
| mdn_dist_threshold_test=${i} |
| echo mdn_dist_threshold_test : ${mdn_dist_threshold_test} |
| |
| command=`accelerate launch \ |
| --multi_gpu \ |
| --main_process_port ${main_process_port} \ |
| --num_processes 1 \ |
| ${SurfDockdir}/scripts/evaluate_score_in_place.py \ |
| --data_csv ${test_data_csv} \ |
| --confidence_model_dir ${confidence_model_base_dir} \ |
| --confidence_ckpt best_model.pt \ |
| --model_version version6 \ |
| --mdn_dist_threshold_test ${mdn_dist_threshold_test} \ |
| --esm_embeddings_path ${protein_embedding} \ |
| --run_name ${project_name}_test_dist_${mdn_dist_threshold_test} \ |
| --project ${project_name} \ |
| --out_dir ${docking_out_dir} \ |
| --batch_size 40 \ |
| --wandb_dir ${temp}/wandb/test_workdir` |
| state=$command |
| done |
| |
| cat << 'EOF' |
| ____ _ _ _ _ _ _ ____ _ _____ ____ _ _ ____ _ _ ____ _ ____ _ _ |
| ____ __ ____ _ ____ _ _ ____ _ |
| / ___| _ _ _ __ / _| _ \ ___ ___| | __ / ___| __ _ _ __ ___ _ __ | (_)_ __ __ _ | _ \ ___ _ __ ___| | |
| \___ \| | | | '__| |_| | | |/ _ \ / __| |/ / \___ \ / _` | '_ ` _ \| '_ \| | | '_ \ / _` | | | | |/ _ \| '_ \ / _ \ | |
| ___) | |_| | | | _| |_| | (_) | (__| < ___) | (_| | | | | | | |_) | | | | | | (_| | | |_| | (_) | | | | __/_| |
| |____/ \__,_|_| |_| |____/ \___/ \___|_|\_\ |____/ \__,_|_| |_| |_| .__/|_|_|_| |_|\__, | |____/ \___/|_| |_|\___(_) |
| |_| |___/ |
| ____ _ _ _ _ _ _ ____ _ _____ ____ _ _ ____ _ _ ____ _ ____ _ _ |
| EOF |
|
|
