Difference between revisions of "2021 Denovo tutorial 1 with PDBID 1HW9"
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= I. Focused De Novo Design = | = I. Focused De Novo Design = | ||
| − | In | + | In focused De Novo Design, we aim to generate a ligand that closely resembles Simvastatin in the binding pocket by connecting generated fragments from scratch. By putting the generated fragments back into the pocket through a variety of fragment assemblies, we can check how accurate simulation is in terms of the sampled ligand. |
---- | ---- | ||
| − | + | ||
= '''Fragment Libraries''' = | = '''Fragment Libraries''' = | ||
| − | First, a | + | First, a fragment library needs to be generated using the original ligand as the template. The generated fragments should build the same ligand seen in the crystalized structure. |
| − | + | Let us create a new directory for the fragment library, using the command: | |
mkdir 010_dn_fraglib | mkdir 010_dn_fraglib | ||
| − | Create a new input file for fragment generation, | + | Create a new input file for fragment generation, using the command: |
| − | + | vi fragment.in | |
| − | Use the following parameters to answer default questions from the | + | Use the following parameters to answer the default questions from the DOCK program (vi fragment.in, and place in the following parameters): |
conformer_search_type flex | conformer_search_type flex | ||
| Line 61: | Line 61: | ||
dock6 -i fragment.in -o fragment.out | dock6 -i fragment.in -o fragment.out | ||
| − | After the fragment library generation is complete, 6 files | + | After the fragment library generation is complete, 6 files shoulbe be seen in the current directory (fraglib_linker.mol2, fraglib_rigid.mol2, fraglib_scaffold.mol2, fraglib_sidechain.mol2, and fraglib_torenv.dat) |
| − | Using the | + | Using the grep command, we can check the number of fragments generated. Copy the mol2 files to your local computer and open the files in Viewdock using Chimera. Chimera can visualize the fragments and show how well they match with the original crystallized ligand. |
grep -wc MOLECULE *.mol2 | wc -l | grep -wc MOLECULE *.mol2 | wc -l | ||
| Line 71: | Line 71: | ||
= '''Focused Denovo Growth''' = | = '''Focused Denovo Growth''' = | ||
| − | + | Next, we'll be using the fragments generated in the last step to build new small molecules for our system. The fragments will connect with each other through a variety of specified constraints such as charge and molecular weight. | |
| − | Create a new directory for the fragment library, | + | Create a new directory for the fragment library, using the command: |
mkdir 011_dn_focus | mkdir 011_dn_focus | ||
| − | Create a new input file for | + | Create a new input file for small molecule generation, using the command: |
| + | |||
| + | vi dn_focus.in | ||
| − | + | Use the following parameters to answer the default questions from the dock program (Make sure to edit all appropriate paths): | |
| − | |||
conformer_search_type denovo | conformer_search_type denovo | ||
dn_fraglib_scaffold_file ../010_dn_fraglib/fraglib_scaffold.mol2 | dn_fraglib_scaffold_file ../010_dn_fraglib/fraglib_scaffold.mol2 | ||
| Line 165: | Line 166: | ||
flex_drive_file /gpfs/projects/AMS536/zzz.programs/dock6.9_release/parameters/flex_drive.tbl | flex_drive_file /gpfs/projects/AMS536/zzz.programs/dock6.9_release/parameters/flex_drive.tbl | ||
| − | Once the fragment.in | + | Once the fragment.in file is generated, run the dock6 program using fragment.in as the designated input file: |
dock6 -i dn_focus.in -o dn_focus.out | dock6 -i dn_focus.in -o dn_focus.out | ||
| − | After the de novo | + | After the de novo growth is complete, 8 .mol2 files and 1 .sh file will appear in the current directory. |
= '''Focused Denovo Rescore''' = | = '''Focused Denovo Rescore''' = | ||
| − | + | Even though we've generated and visualized these fragments, we want to rescore them based on numerous properties for better in vitro modeling. | |
| − | Create a new directory for the fragment library, | + | Create a new directory for the fragment library, using the command: |
mkdir 012_dn_focusrescore | mkdir 012_dn_focusrescore | ||
| − | Create a new input file for fragment generation, | + | Create a new input file for fragment generation, using the command: |
| − | + | vi rescore.in | |
| − | Use the following parameters to answer default questions from the dock program: | + | Use the following parameters to answer the default questions from the dock program: |
conformer_search_type rigid | conformer_search_type rigid | ||
| Line 278: | Line 279: | ||
rank_ligands no | rank_ligands no | ||
| − | Once the rescore.in | + | Once the rescore.in file is generated, run the dock6 program using rescore.in as the input file: |
dock6 -i rescore.in -o rescore.out | dock6 -i rescore.in -o rescore.out | ||
| − | After the rescore complete, | + | You may need to submit this as a slurm script depending on how long the job initially takes. |
| + | |||
| + | #!/bin/bash | ||
| + | #SBATCH --time=48:00:00 | ||
| + | #SBATCH --nodes=1 | ||
| + | #SBATCH --ntasks=28 | ||
| + | #SBATCH --job-name=dn_rescore | ||
| + | #SBATCH --output=dn_rescore.out | ||
| + | #SBATCH -p long-28core | ||
| + | |||
| + | cd $SLURM_SUBMIT_DIR | ||
| + | echo "starting Dock6.9 simulation" | ||
| + | /gpfs/projects/AMS536/zzz.programs/dock6.9_release/bin/dock6.mpi -i dn_rescore.in -o dn_rescore.out | ||
| + | |||
| + | After the rescore is complete, footprint and H-bond scored txt files are generated. The descriptor scored .mol2 files should also appear in the current directory. | ||
| + | |||
| + | [[File:viewdock descriptor.png|center|500px]] | ||
| − | + | The rescored highest descriptor score ligand viewed in Chimera. Purple is the original ligand while Brown is the rescored ligand in the binding site. | |
Latest revision as of 23:42, 1 April 2021
In this session, we are going to use the predetermined structures from the virtual screen tutorial to do de novo design
Contents
I. Focused De Novo Design
In focused De Novo Design, we aim to generate a ligand that closely resembles Simvastatin in the binding pocket by connecting generated fragments from scratch. By putting the generated fragments back into the pocket through a variety of fragment assemblies, we can check how accurate simulation is in terms of the sampled ligand.
Fragment Libraries
First, a fragment library needs to be generated using the original ligand as the template. The generated fragments should build the same ligand seen in the crystalized structure.
Let us create a new directory for the fragment library, using the command:
mkdir 010_dn_fraglib
Create a new input file for fragment generation, using the command:
vi fragment.in
Use the following parameters to answer the default questions from the DOCK program (vi fragment.in, and place in the following parameters):
conformer_search_type flex write_fragment_libraries yes fragment_library_prefix fraglib fragment_library_freq_cutoff 1 fragment_library_sort_method freq fragment_library_trans_origin no use_internal_energy yes internal_energy_rep_exp 12 internal_energy_cutoff 100.0 ligand_atom_file ../001.structure/1HW9_ligand_with_H.mol2 limit_max_ligands no skip_molecule no read_mol_solvation no calculate_rmsd no use_database_filter no orient_ligand yes automated_matching yes receptor_site_file ../002.surface_spheres/selected_spheres.sph max_orientations 1000 critical_points no chemical_matching no use_ligand_spheres no bump_filter no score_molecules no atom_model all vdw_defn_file /gpfs/projects/AMS536/zzz.programs/dock6.9_release/parameters/vdw_AMBER_parm99.defn flex_defn_file /gpfs/projects/AMS536/zzz.programs/dock6.9_release/parameters/flex.defn flex_drive_file /gpfs/projects/AMS536/zzz.programs/dock6.9_release/parameters/flex_drive.tbl ligand_outfile_prefix fragment.out write_orientations no num_scored_conformers 1 rank_ligands no
Once the fragment.in the file is generated, run the dock6 program using the fragment.in as the input file:
dock6 -i fragment.in -o fragment.out
After the fragment library generation is complete, 6 files shoulbe be seen in the current directory (fraglib_linker.mol2, fraglib_rigid.mol2, fraglib_scaffold.mol2, fraglib_sidechain.mol2, and fraglib_torenv.dat)
Using the grep command, we can check the number of fragments generated. Copy the mol2 files to your local computer and open the files in Viewdock using Chimera. Chimera can visualize the fragments and show how well they match with the original crystallized ligand.
grep -wc MOLECULE *.mol2 | wc -l
Focused Denovo Growth
Next, we'll be using the fragments generated in the last step to build new small molecules for our system. The fragments will connect with each other through a variety of specified constraints such as charge and molecular weight.
Create a new directory for the fragment library, using the command:
mkdir 011_dn_focus
Create a new input file for small molecule generation, using the command:
vi dn_focus.in
Use the following parameters to answer the default questions from the dock program (Make sure to edit all appropriate paths):
conformer_search_type denovo dn_fraglib_scaffold_file ../010_dn_fraglib/fraglib_scaffold.mol2 dn_fraglib_linker_file ../010_dn_fraglib/fraglib_linker.mol2 dn_fraglib_sidechain_file ../010_dn_fraglib/fraglib_sidechain.mol2 dn_user_specified_anchor no dn_use_torenv_table yes dn_torenv_table ../010_dn_fraglib/fraglib_torenv.dat dn_sampling_method graph dn_graph_max_picks 30 dn_graph_breadth 3 dn_graph_depth 2 dn_graph_temperature 100.0 dn_pruning_conformer_score_cutoff 100.0 dn_pruning_conformer_score_scaling_factor 1.0 dn_pruning_clustering_cutoff 100.0 dn_constraint_mol_wt 550.0 dn_constraint_rot_bon 15 dn_constraint_formal_charge 2.0 dn_heur_unmatched_num 1 dn_heur_matched_rmsd 2.0 dn_unique_anchors 1 dn_max_grow_layers 9 dn_max_root_size 25 dn_max_layer_size 25 dn_max_current_aps 5 dn_max_scaffolds_per_layer 1 dn_write_checkpoints yes dn_write_prune_dump no dn_write_orients no dn_write_growth_trees no dn_output_prefix dn_focus.out use_internal_energy yes internal_energy_rep_exp 12 internal_energy_cutoff 100.0 use_database_filter no orient_ligand yes automated_matching yes receptor_site_file ../002.surface_spheres/selected_spheres.sph max_orientations 1000 critical_points no chemical_matching no use_ligand_spheres no bump_filter no score_molecules yes contact_score_primary no contact_score_secondary no grid_score_primary yes grid_score_secondary no grid_score_rep_rad_scale 1 grid_score_vdw_scale 1 grid_score_es_scale 1 grid_score_grid_prefix ../003.gridbox/grid multigrid_score_secondary no dock3.5_score_secondary no continuous_score_secondary no footprint_similarity_score_secondary no pharmacophore_score_secondary no descriptor_score_secondary no gbsa_zou_score_secondary no gbsa_hawkins_score_secondary no SASA_score_secondary no amber_score_secondary no minimize_ligand yes minimize_anchor yes minimize_flexible_growth yes use_advanced_simplex_parameters no simplex_max_cycles 1 simplex_score_converge 0.1 simplex_cycle_converge 1.0 simplex_trans_step 1.0 simplex_rot_step 0.1 simplex_tors_step 10.0 simplex_anchor_max_iterations 500 simplex_grow_max_iterations 500 simplex_grow_tors_premin_iterations 0 simplex_random_seed 0 simplex_restraint_min no atom_model all vdw_defn_file /gpfs/projects/AMS536/zzz.programs/dock6.9_release/parameters/vdw_AMBER_parm99.defn flex_defn_file /gpfs/projects/AMS536/zzz.programs/dock6.9_release/parameters/flex.defn flex_drive_file /gpfs/projects/AMS536/zzz.programs/dock6.9_release/parameters/flex_drive.tbl
Once the fragment.in file is generated, run the dock6 program using fragment.in as the designated input file:
dock6 -i dn_focus.in -o dn_focus.out
After the de novo growth is complete, 8 .mol2 files and 1 .sh file will appear in the current directory.
Focused Denovo Rescore
Even though we've generated and visualized these fragments, we want to rescore them based on numerous properties for better in vitro modeling.
Create a new directory for the fragment library, using the command:
mkdir 012_dn_focusrescore
Create a new input file for fragment generation, using the command:
vi rescore.in
Use the following parameters to answer the default questions from the dock program:
conformer_search_type rigid use_internal_energy yes internal_energy_rep_exp 12 internal_energy_cutoff 100.0 ligand_atom_file ../011.dn_focus/dn_focus.out.denovo_build.mol2 limit_max_ligands no skip_molecule no read_mol_solvation no calculate_rmsd no use_database_filter no orient_ligand no bump_filter no score_molecules yes contact_score_primary no contact_score_secondary no grid_score_primary no grid_score_secondary no multigrid_score_primary no multigrid_score_secondary no dock3.5_score_primary no dock3.5_score_secondary no continuous_score_primary no continuous_score_secondary no footprint_similarity_score_primary no footprint_similarity_score_secondary no pharmacophore_score_primary no pharmacophore_score_secondary no descriptor_score_primary yes descriptor_score_secondary no descriptor_use_grid_score no descriptor_use_multigrid_score no descriptor_use_continuous_score no descriptor_use_footprint_similarity yes descriptor_use_pharmacophore_score yes descriptor_use_tanimoto yes descriptor_use_hungarian yes descriptor_use_volume_overlap yes descriptor_fps_score_use_footprint_reference_mol2 yes descriptor_fps_score_footprint_reference_mol2_filename ../004.dock/1hw9_lig_min_scored.mol2 descriptor_fps_score_foot_compare_type Euclidean descriptor_fps_score_normalize_foot no descriptor_fps_score_foot_comp_all_residue yes descriptor_fps_score_receptor_filename ../001.dockprep/1hw9_rec_prep.mol2 descriptor_fps_score_vdw_att_exp 6 descriptor_fps_score_vdw_rep_exp 12 descriptor_fps_score_vdw_rep_rad_scale 1 descriptor_fps_score_use_distance_dependent_dielectric yes descriptor_fps_score_dielectric 4.0 descriptor_fps_score_vdw_fp_scale 1 descriptor_fps_score_es_fp_scale 1 descriptor_fps_score_hb_fp_scale 0 descriptor_fms_score_use_ref_mol2 yes descriptor_fms_score_ref_mol2_filename ../004.dock/1hw9_lig_min_scored.mol2 descriptor_fms_score_write_reference_pharmacophore_mol2 no descriptor_fms_score_write_reference_pharmacophore_txt no descriptor_fms_score_write_candidate_pharmacophore no descriptor_fms_score_write_matched_pharmacophore no descriptor_fms_score_compare_type overlap descriptor_fms_score_full_match yes descriptor_fms_score_match_rate_weight 5.0 descriptor_fms_score_match_dist_cutoff 1.0 descriptor_fms_score_match_proj_cutoff 0.7071 descriptor_fms_score_max_score 20 descriptor_fingerprint_ref_filename ../004.dock/1hw9_lig_min_scored.mol2 descriptor_hms_score_ref_filename ../004.dock/1hw9_lig_min_scored.mol2 descriptor_hms_score_matching_coeff -5 descriptor_hms_score_rmsd_coeff 1 descriptor_volume_score_reference_mol2_filename ../04_dock/6UZW_lig_min_scored.mol2 descriptor_volume_score_overlap_compute_method analytical descriptor_weight_fps_score 1 descriptor_weight_pharmacophore_score 1 descriptor_weight_fingerprint_tanimoto -1 descriptor_weight_hms_score 1 descriptor_weight_volume_overlap_score -1 gbsa_zou_score_secondary no gbsa_hawkins_score_secondary no SASA_score_secondary no amber_score_secondary no minimize_ligand no atom_model all vdw_defn_file /gpfs/projects/AMS536/zzz.programs/dock6.9_release/parameters/vdw_AMBER_parm99.defn flex_defn_file /gpfs/projects/AMS536/zzz.programs/dock6.9_release/parameters/flex.defn flex_drive_file /gpfs/projects/AMS536/zzz.programs/dock6.9_release/parameters/flex_drive.tbl chem_defn_file /gpfs/projects/AMS536/zzz.programs/dock6.9_release/parameters/chem.defn pharmacophore_defn_file /gpfs/projects/AMS536/zzz.programs/dock6.9_release/parameters/ph4.defn ligand_outfile_prefix descriptor.output write_footprints yes write_hbonds yes write_orientations no num_scored_conformers 1 rank_ligands no
Once the rescore.in file is generated, run the dock6 program using rescore.in as the input file:
dock6 -i rescore.in -o rescore.out
You may need to submit this as a slurm script depending on how long the job initially takes.
#!/bin/bash #SBATCH --time=48:00:00 #SBATCH --nodes=1 #SBATCH --ntasks=28 #SBATCH --job-name=dn_rescore #SBATCH --output=dn_rescore.out #SBATCH -p long-28core
cd $SLURM_SUBMIT_DIR echo "starting Dock6.9 simulation" /gpfs/projects/AMS536/zzz.programs/dock6.9_release/bin/dock6.mpi -i dn_rescore.in -o dn_rescore.out
After the rescore is complete, footprint and H-bond scored txt files are generated. The descriptor scored .mol2 files should also appear in the current directory.
The rescored highest descriptor score ligand viewed in Chimera. Purple is the original ligand while Brown is the rescored ligand in the binding site.
