Difference between revisions of "2024 Denovo tutorial 1 with PDBID 2ITO"

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==Setting up the dummy atom==
 
==Setting up the dummy atom==
  
For the ligand from #4s0v, we will be removing a terminal ring and looking at what DOCK suggests to replace it with. The steps to do this are: 
 
*Open the ligand minimized mol2 file we generated in the previous tutorial into Chimera.
 
*Open the protein into the same session
 
*Examine the binding site and choose a residue on the ligand that's pointing towards the inside of the binding site.  For our protein this detailed section looks like:
 
 
[[File: ligandInSite.png|thumb|center]]
 
 
We see an imidazole ring pointing towards the binding site so will choose to work with that.  Select the protein and hide it from view: 
 
 
*Place your mouse over the atom connecting the ring to the rest of the ligand and note the atom and number.  In this case it's N4.
 
[[File: atomnumber.png|center]]
 
 
*Delete all the atoms from N4 to the end.  Your ligand should now look something like:
 
[[File: DeletedRing.png|center]]
 
 
*Save a .mol2 file of your ligand in this configuration.  Make sure to give it a new filename such as 4s0v_denovoRefinement.mol2
 
*Open the .mol2 file.  If you're on a UNIX system, you can use vi; if you're on a PC, you can use textedit.  Locate the atom that will now be changed to a dummy atom:
 
[[File: Originalmol2.png|center]]
 
 
*Change the atom type to 'Du1' and the bond type to 'Du':
 
[[File: Modifiedmol2.png|center]]
 
and save the file.
 
 
*Open a new session in Chimera and load the modified mol2 file.  The "dummy" atom should now be purple:
 
[[File: dummyatom.png|thumb|center]]
 
 
*scp 4s0v_denovoRefinement.mol2 over to Seawulf and into the 012.denovoRefinement directory.  From this point on we will be working on the command line.
 
  
 
==Running DeNovo Refinement==
 
==Running DeNovo Refinement==

Revision as of 19:42, 26 April 2024

Introduction

DeNovo Design aims to create a new ligand from scratch. It is incrementally designed bad added known structures of bioacitve compounds. The end result will hopefully produce a new ligand that can bind more tightly to a protein receptor than the current ligand can. There are three methods that will be introduced in this tutorial:

  1. Generic DeNovo Design
  2. Focused Fragment Design
  3. DeNovo Refinement

We will do denovo design with PDB: 2ITO.


Setting Up Your Environment

We will add more directories to the ones we used from the traditional virtual screening.

 009_deNovoRefinement
 010a_fragLib   
 010b_focusGrowth
 010c_focusReScore
 011_genericDeNovo

DeNovo Refinement

DeNovo Refinement can be used to assess the effects upon ligand and protein interactions by chaning a portion of the molecule. We can experiment with an interesting piece of the ligand and delete the remaining portion. This deleted portion needs to be replaced with a dummy atom. Dock will then find which fragments can be placed in this position that will have the least energy.

Setting up the dummy atom

Running DeNovo Refinement

Viewing New Molecules

Focused DeNovo Design

Fragment Library Generation

DeNovo Design

ReScoring Designed Molecules

Generic DeNovo Design

For generic denovo design, we are not limiting DOCK to build new molecules using fragments present in the original ligand. Instead, we will be taking fragments from a fragment library.

Create the input file:

 vi 2ito_generic.in

The file should contain these lines:

 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_torenv_table                                              /gpfs/projects/AMS536/zzz.programs/dock6.10/parameters/fraglib_torenv.dat
 dn_name_identifier                                           2ito_generic
 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                                   550.0
 dn_lower_constraint_mol_wt                                   0.0
 dn_mol_wt_std_dev                                            35.0
 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                                             2ito_generic
 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                                           /gpfs/projects/AMS536/2024/students/group_1_2ITO/002_surface_spheres/2ITO.sph
 max_orientations                                             1000
 critical_points                                              no
 chemical_matching                                            no
 use_ligand_spheres                                           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                                       /gpfs/projects/AMS536/2024/students/group_1_2ITO/003_gridbox/grid
 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                                  250
 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

Create a slurm file to run this:

 #!/bin/bash
 #SBATCH --job-name=2ito_generic
 #SBATCH --ntasks=28
 #SBATCH --nodes=1
 #SBATCH --time=48:00:00
 #SBATCH -p long-28core
 dock6 -i 2ito_generic.in

After the program has run, you can use the following command to see how many ligands has been generated. The program has made 368 potential ligands.

 grep MOLECULE 2ito_generic.denovo_build.mol2 | wc -l


The output file we are going to move to our local computer is 2ito_generic.denovo_build.mol2. We can see the ligands the program has created.

Go into Chimera and open the molecule on ViewDock. (Tools >> Surface/Binding Analysis >> ViewDock)

Use Column >> Show >> Grid_Score to find the ligand with the lowest energy.

The ligand with the lowest score has a score of -93.318.

We can compare this with the energy minimized ligand and see how it is positioned differently compared to the generated ligand. This original energy minimized ligand has a grid score of -71.423.

We can also observe how the designed ligand and the original ligand interact with the receptor.