2024 Denovo tutorial 3 with PDBID 1Y0X
From Rizzo_Lab
Contents
Introduction
Continuing from Virtual Screening tutorial, we have the De Novo design tutorial. De Novo means from the beginning, thus, in this tutorial, we are learning to design the molecule that can bind to our protein from scratch. There are 3 different algorithms for the De Novo Design:
- Generic DeNovo Design
- Focused Fragment Design
- DeNovo Refinement
Setting Up Your Environment
Creating new directories in your workspace like the similar:
De Novo Refinement
This algorithm allows us to refine an existing molecule by deleting part of the molecule and let DOCK6 decide what chemical group can be regrow from the deleted area to fit with the protein pocket. Hear is how you can perform it:
Set up your dummy atom
- Open the protein and ligand in chimera
- Choose a chemical group inside the binding pocket that you want to delete
- Get the name of the first atom connecting the chemical group to the rest of the compound by placing the mouse on top of the structure
- Delete all other atoms after that first atom that you located
- Save the .mol2 file of the ligand and open it in a text editor program
- Change the name of the Atom to "DU1" and the atom type to "Du"
- Save the .mol2 file again
Running De Novo Refinement
Locate to 012 directory and scp the .mol2 file into the directory. Make an input file for DOCK with the following input:
conformer_search_type denovo dn_fraglib_scaffold_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/fraglib_scaffold.mol2 dn_fraglib_linker_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/fraglib_linker.mol2 dn_fraglib_sidechain_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/fraglib_sidechain.mol2 dn_user_specified_anchor yes dn_fraglib_anchor_file ligand_dummy.mol2 dn_torenv_table /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/fraglib_torenv.dat dn_name_identifier 1y0x_denovo 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 2.0 dn_pruning_clustering_cutoff 100.0 dn_mol_wt_cutoff_type soft dn_upper_constraint_mol_wt 1000.0 dn_lower_constraint_mol_wt 0.0 dn_mol_wt_std_dev 35.0 dn_constraint_rot_bon 15 dn_constraint_formal_charge 5 dn_heur_unmatched_num 1 dn_heur_matched_rmsd 2.0 dn_unique_anchors 1 dn_max_grow_layers 1 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 denovo_output use_internal_energy yes internal_energy_rep_exp 12 internal_energy_cutoff 100.0 use_database_filter no orient_ligand no bump_filter no score_molecules yes contact_score_primary no grid_score_primary yes grid_score_rep_rad_scale 1 grid_score_vdw_scale 1 grid_score_es_scale 1 grid_score_grid_prefix ../003.gridbox/grid minimize_ligand yes minimize_anchor no minimize_flexible_growth yes use_advanced_simplex_parameters no simplex_max_cycles 1 simplex_score_converge 0.1 simplex_cycle_converge 1 simplex_trans_step 1 simplex_rot_step 0.1 simplex_tors_step 10 simplex_grow_max_iterations 250 simplex_grow_tors_premin_iterations 0 simplex_random_seed 0 simplex_restraint_min yes simplex_coefficient_restraint 10 atom_model all vdw_defn_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/vdw_de_novo.defn flex_defn_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/flex.defn flex_drive_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/flex_drive.tbl
Run the Refinement by command:
dock6 -i denovo.in -o denovo.out
Once the job has completed you will see the following new files in your directory:
- denovo_output.anchor_1.root_layer_1.mol2
- denovo_output.denovo_build.mol2
- denovo.out
Opening the _build.mol2 molecule in Chimera using View Dock tool to look at the newly refined molecule.
=Focused De Novo Design In focused De Novo, a chemical group from our compound is selected as an anchor and the anchor can be sampled against the protein to find the most attractive position within the binding site. From there, the molecule is grown back from the anchor.
Fragment Library Generation
This is the library of chemical group fragments that dock will use as binding blocks to regrow the molecule. In this case, focused de novo design use only the fragments from the original ligand. Locate to your 013a. directory and create an input file using the following input:
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/H_charged_ligand.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/dock6.10/parameters/vdw_de_novo.defn flex_defn_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/flex.defn flex_drive_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/flex_drive.tbl ligand_outfile_prefix focused write_orientations no num_scored_conformers 1 write_conformations no cluster_conformations yes cluster_rmsd_threshold 2.0 rank_ligands no
And run the input file using command:
dock6 -i focused.in -o focused.out
Once the program has successfully run you'll see the following new files in your directory:
- focused_scored.mol2
- fragLib_linker.mol2
- fragLib_rigid.mol2
- fragLib_scaffold.mol2
- fragLib_sidechain.mol2
- fragLib_torenv.dat
De Novo Design
After constructing the fragment library, we can perform focused De Novo Design to grow the molecule. The input is as followed:
conformer_search_type denovo dn_fraglib_scaffold_file ../013a.fragLib/fragLib_scaffold.mol2 dn_fraglib_linker_file ../013a.fragLib/fragLib_linker.mol2 dn_fraglib_sidechain_file ../013a.fragLib/fragLib_sidechain.mol2 dn_user_specified_anchor no dn_use_torenv_table yes dn_torenv_table ../013a.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 2 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 yes dn_output_prefix focused 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/dock6.10/parameters/vdw_de_novo.defn flex_defn_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/flex.defn flex_drive_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/flex_drive.tbl
And execute the docking using the command:
dock6 -i focus.in -o focus.out
Once the run is done, you can see new files with the newly built molecules. The most important file is the
focused.denovo_build.mol2
Rescoring Designed Molecules
The molecules built can be then rescored to be compared against the crystallographic ligand in terms of interaction energy values. We can do that using the input file as followed:
conformer_search_type rigid use_internal_energy yes internal_energy_rep_exp 12 internal_energy_cutoff 100.0 ligand_atom_file ../013b.focusGrowth/focused.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.energy_min/protein.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.structure/H_charged_protein.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.energy_min/protein.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.energy_min/protein.lig.min_scored.mol2 descriptor_hms_score_ref_filename ../004.energy_min/protein.lig.min_scored.mol2 descriptor_hms_score_matching_coeff -5 descriptor_hms_score_rmsd_coeff 1 descriptor_volume_score_reference_mol2_filename ../004.energy_min/protein.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/dock6.10/parameters/vdw_de_novo.defn flex_defn_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/flex.defn flex_drive_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/flex_drive.tbl chem_defn_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/chem.defn pharmacophore_defn_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/ph4.defn ligand_outfile_prefix focus_rescore write_footprints yes write_hbonds yes write_orientations no num_scored_conformers 1 rank_ligands no
And execute the rescoring using the command:
dock6 -i rescore.in -o rescore.out
You will see the output contains 3 files:
- focus_rescore_footprint_scored.txt
- focus_rescore_hbond_scored.txt
- focus_rescore_scored.mol2
If we compare the best scoring molecule with the energy minimized ligand, the differences are minimal.
Generic De Novo Design
This type of algorithm performs the same kind of anchored fragment growth as observed in focused De Novo with the only difference of using the premade fragment library that contains various common fragments in thousands of drug molecules. After locating to 014. directory, you can use the input file as follow to carry out this docking:
conformer_search_type denovo dn_fraglib_scaffold_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/fraglib_scaffold.mol2 dn_fraglib_linker_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/fraglib_linker.mol2 dn_fraglib_sidechain_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/fraglib_sidechain.mol2 dn_user_specified_anchor no dn_use_torenv_table yes dn_torenv_table /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/fraglib_torenv.dat dn_sampling_method graph dn_graph_max_picks 30 dn_graph_breadth 3 dn_graph_depth 2 dn_graph_temperature 100 dn_pruning_conformer_score_cutoff 100 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 genericDenovo_output 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 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 yes descriptor_use_pharmacophore_score no descriptor_use_tanimoto no descriptor_use_hungarian no descriptor_use_volume_overlap no descriptor_grid_score_rep_rad_scale 1 descriptor_grid_score_vdw_scale 1 descriptor_grid_score_es_scale 1 descriptor_grid_score_grid_prefix ../003.gridbox/grid descriptor_weight_grid_score 1 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/dock6.10/parameters/vdw_de_novo.defn flex_defn_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/flex.defn flex_drive_file /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/flex_drive.tbl
Since the process may take long, it is a good idea to submit this job to the cluster using the script as followed:
#!/bin/bash # #SBATCH --job-name=genericLib #SBATCH --output=genericLib_output.txt #SBATCH --ntasks-per-node=28 #SBATCH --nodes=4 #SBATCH --time=48:00:00 #SBATCH -p long-28core mpirun -np 112 dock6 -i generic.in -o generic.out
The most important file in the result is genericDenovo_output.denovo_build.mol2, which can be viewed in Chimera using View Dock. You can check how many molecules were built using the command:
grep MOLECULE 4s0v_genericDenovo_output.denovo_build.mol2 | wc -l
You can compare the grid score as well as other interacting energy values to determine if generic De Novo Docking has provided better binding molecules than the crystallographic ligand.
