Difference between revisions of "2017 Denovo refine tutorial with PDB 1BJU"

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(De novo Refinement Run)
(De novo Refinement Run)
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  simplex_grow_tors_premin_iterations                          0
  simplex_grow_tors_premin_iterations                          0
  simplex_random_seed                                          0
  simplex_random_seed                                          0
  simplex_restraint_min                                        no
  simplex_restraint_min                                        yes
  atom_model                                                  all
  atom_model                                                  all
  vdw_defn_file                                                {PATH_TO_FILE}/vdw_AMBER_parm99.defn
  vdw_defn_file                                                {PATH_TO_FILE}/vdw_AMBER_parm99.defn

Latest revision as of 12:15, 3 May 2021

2017 De novo refinement tutorial with PDB 1BJU

The De novo Refinement module of DOCK constructs new ligand molecules by adding side chains to any atom of a reference molecule. The side chains are taken from a library of fragments that will be specified as an input by the user. The atom at which the side chain will be added needs to be specified as a 'dummy' atom. This is done by opening the pdb file and modifying the atom type to "Du" (column 6).

Make sure to complete the 2016 Dock tutorial with Beta Trypsin. Some of the output files generated from that tutorial will be required below.

In the previous dock tutorial directory, create a directory for the de novo refinement run named "04.denovo_refinment".

The Files Needed For De novo Refinement

To run the de novo refinement code with single grid scoring you need these files:

From dock tutorial:


New files:


The first four files are in a fragment library directory called "gen-frags-12" which can be generated by the user here: Fragment Library Generation. The bottom three files are typical parameter files contained in the parameters directory in DOCK6.

Preparing The Files

Start a Chimera session and click Open and Select the 1BJU.rec.mol2 to open the receptor file. Show surface by clicking Actions->Surface->show. Display charge distribution on surface by Actions->Color->by heteroatom. Open ligand file 1BJU.lig.mol2. To select an atom to act as a dummy for side chains attachment, find an atom in a position that allows addition of molecular groups, in other words, not inside binding pocket and not tightly packed against receptor atoms. Here, we select H12 to be our dummy atom (see figure).

Copy the ligand file 1BJU.lig.mol2 into 1BJU.lig.dummyH.mol2. Open 1BJU.lig.dummyH.mol2 with vi and modify the type of atom 28 H12 to Du (in column 6). Make sure the spacing after the modification stays aligned with the other columns. Save file.

Beta trypsin in complex with GP6 inhibitor (cyan) showing the hydrogen atom at which the side chains will be attached.

De novo Refinement Run

Make input file by typing: touch dnref.in Copy the following commands into this file. Alternatively, one can create this file interactively by calling dock with the empty dnref.in file. Dock will ask for each input specification one by one. We are using the generic fragment library provided in the dock6 distribution in the parameters directory.

Make sure to include the correct paths to the files for the fragment library and the Dock parameter files.

conformer_search_type                                        denovo
dn_fraglib_scaffold_file                                     {PATH_TO_FILE}/gen-frags-12/fraglib_scaffold.mol2
dn_fraglib_linker_file                                       {PATH_TO_FILE}/gen-frags-12/fraglib_linker.mol2
dn_fraglib_sidechain_file                                    {PATH_TO_FILE}/gen-frags-12/fraglib_sidechain.mol2
dn_user_specified_anchor                                     yes
dn_fraglib_anchor_file                                       ../01.dockprep/1BJU.lig.dummyH.mol2
dn_use_torenv_table                                          yes
dn_torenv_table                                              {PATH_TO_FILE}/gen-frags-12/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                                         750
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                                           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                                          yes
dn_write_orients                                             no
dn_write_growth_trees                                        no
dn_output_prefix                                             1BJU.lig.dummyH.dnref
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
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
ph4_score_primary                                            no
ph4_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_grid_score_rep_rad_scale                          1
descriptor_grid_score_vdw_scale                              1
descriptor_grid_score_es_scale                               1
descriptor_grid_score_grid_prefix                            ../03.box-grid/grid
descriptor_weight_grid_score                                 1
gbsa_zou_score_secondary                                     no
gbsa_hawkins_score_secondary                                 no
SASA_descriptor_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                                        yes
atom_model                                                   all
vdw_defn_file                                                {PATH_TO_FILE}/vdw_AMBER_parm99.defn
flex_defn_file                                               {PATH_TO_FILE}/flex.defn
flex_drive_file                                              {PATH_TO_FILE}/flex_drive.tbl

This calculation should be done quickly, and upon finishing you will have three output files:


The first file contains the resulting 14 molecules. The last two files are empty since we have added only one layer (those files would be used as restart files for subsequent additions in multilayer runs).

Open Chimera to view results, use ViewDock from Tools/Surface/Binding-Analysis to check resulting molecules and rank them.

Beta trypsin in complex with GP6 inhibitor (cyan) and the best grid scoring molecule from denovo refinement (pink).

Note: If one desires to add more layers, modify the parameter of the command "dn_max_grow_layers" in the "dnref.in" input file.