2017 Denovo design tutorial 2 with PDB 4QMZ
Contents
2017 De novo design tutorial 2 with PDB 4QMZ
The de novo module of DOCK6 is a relatively new feature as of Fall 2016 that constructs new ligand molecules inside a protein active site from a library of user-specified fragments. These novel ligand molecules are scored based on a number of unique scoring algorithms/criteria specified. The fragments used are common chemical functional groups -- or building blocks -- that are typically selected from a ZINC library of millions of compounds based off of their frequency of appearance. These fragments are classified as scaffolds, linkers, or side chains, according to the number of atomic positions that are permitted to seed growth: 3, 2, and 1 atoms, respectively. Thus, a scaffold could seed growth from three different atoms, having three linkers bonded to each position, and a linker could seed growth on two positions, and a side-chain on one position. Once the molecules are built within the active site, their interactions with the protein are scored using the user-specified method of scoring employed through DOCK6.
This tutorial will walk through the steps needed to run de novo growth on the 4QMZ system to build a novel chemically feasible ensemble of molecules from the 2017 DOCK6 tutorial. This method will utilize the multigrid scoring function (MGS), called through the descriptor score. Ensure you have all the folders and files necessary from running the 2017 tutorial. Users are encouraged to run through the traditional DOCK6 tutorial for the 4qmz system as many of the files are recycled for the denovo experiments. Before running the calculation, it's worth looking through the "Things to Keep in Mind" section at the bottom for some good pieces of information.
Additional Files Needed
To run the de novo code with multigrid scoring you need these files:
fraglib_scaffold.mol2 <-- [Fragment Library Generation]
fraglib_linker.mol2 <-- [Fragment Library Generation]
fraglib_sidechain.mol2 <-- [Fragment Library Generation]
anchor_library.mol2 <-- User defined anchor mol2 file with all attachment points written as "Du"
fraglib_torenv.dat <-- [Fragment Library Generation]
selected_spheres.sph <-- Generated through sphgen
primary_residues_multigrid.bmp / .nrg <-- Generated through DOCK6 for each of the primary residues
multigrid_minimized_ligand.mol2 <-- Generated through docking and minimizng the reference molecule
vdw_AMBER_parm99.defn <-- Located in the parameter file of DOCK6
flex.defn <-- Located in the parameter file in DOCK6
flex_drive.tbl <-- Located in the parameter file in DOCK6
The fragment libraries must be generated ([Fragment Library Generation]) or obtained prior to the de novo calculation:
/PATH/denovo/trial_denovo/000.fraglib
Everything else is generated through this tutorial, prior to running the de novo code.
Preparing The Files
Before running de novo on 4QMZ, please ensure you have gone through the DOCK6 2017 tutorial and have all the resulting files. The tutorial can be accessed through here. You should have these files in your directory:
4qmz.pdb
4qmz.lig.mol2
4qmz.rec.clean.mol2
4qmz.rec.noH.mol2
selected_spheres.sph
Additionally, you will also need these parameter files found in the parameters directory of DOCK6:
vdw_AMBER_parm99.defn
flex.defn
flex_drive.tbl
In order to run de novo with multigrid scoring, we must first go through several steps:
1). Create a primary residue text file and a reference text file -- determine the primary residues of interest and score the interactions with the reference ligand.
2). Make a multigrid file for each specified residue -- forms a grid for each residue specified in previous step.
3). Minimizes ligand mol2 file using multigrids from previous step (it is not necessary for the ligand to be minimized in multigrid, singlegrid would suffice).
4). Rescores ligand on multigrid to yield a minimized ligand .mol2 file. This serves as the reference ligand for de novo growth.
There is one script for each step, but we will only use the simple input files for DOCK6.
DOCK Specifying Primary Residues
Create a directory within your working directory titled 008.footprint_rescore. This is where all pertinent files from this step will go, and where we will run our calculation from. The input file for this step should be titled 4qmz.footprint_rescore.in, and should look like (substitute your own directory path ~/your/own/directory/01.dockprep/4qmz.lig.mol2) :
conformer_search_type rigid use_internal_energy no ligand_atom_file /PATH/dock_tutorial/01.dockprep/4qmz.lig.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 yes footprint_similarity_score_secondary no fps_score_use_footprint_reference_mol2 yes fps_score_footprint_reference_mol2_filename /PATH/dock_tutorial/01.dockprep/4qmz.lig.mol2 fps_score_foot_compare_type Euclidean fps_score_normalize_foot no fps_score_foot_comp_all_residue no fps_score_choose_foot_range_type threshold fps_score_vdw_threshold 1 fps_score_es_threshold 0.5 fps_score_hb_threshold 0.5 fps_score_use_remainder yes fps_score_receptor_filename /PATH/dock_tutorial/01.dockprep/4qmz.rec.mol2 fps_score_vdw_att_exp 6 fps_score_vdw_rep_exp 12 fps_score_vdw_rep_rad_scale 1 fps_score_use_distance_dependent_dielectric yes fps_score_dielectric 4.0 fps_score_vdw_fp_scale 1 fps_score_es_fp_scale 1 fps_score_hb_fp_scale 0 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 no atom_model all vdw_defn_file /PATH/DOCK6/parameters/vdw_AMBER_parm99.defn flex_defn_file /PATH/DOCK6/parameters/flex.defn flex_drive_file /PATH/DOCK6/parameters/flex_drive.tbl ligand_outfile_prefix output write_footprints yes write_hbonds no write_orientations no num_scored_conformers 1 rank_ligands no
This calculation should be very quick (~10 seconds) and result in three output files:
4qmz.footprint_rescore.out output_footprint_scored.txt output_scored.mol2
Now, we must declare the primary residues in the active site and generate a grid file for each. Create a new file in the text editor named 4qmz.primary_residues.sh and write this inside of it (copied from Brian's script *.fpsrescore.qsub.sh):
#!/bin/bash
grep -A 1 "range_union" footprintrescore.out |
grep -v "range_union" |
grep -v "\-" |
sed -e '{s/,/\n/g}' |
sed -e '{s/ //g}' |
sed '/^$/d' |
sort -n |
uniq > temp.dat
for i in `cat temp.dat`; do printf "%0*d\n" 3 $i; done > 4qmz.primary_residues.dat
for RES in `cat temp.dat`
do
grep " ${RES} " output_footprint_scored.txt |
awk -v temp=${RES} '{if ($2 == temp) print $0;}' |
awk '{print $1 " " $3 " " $4}' >> reference.txt
done
grep "remainder" output_footprint_scored.txt |
sed -e '{s/,/ /g}' |
tr -d '\n' |
awk '{print $2 " " $3 " " $6}' >> reference.txt
mv reference.txt 4qmz.reference.txt
rm temp.dat
Run the script and you should have two new files:
4qmz.primary_residues.dat 4qmz.reference.txt
These are our primary residues! Now we need to generate a grid for each one.
Generating the Grids
We must now generate a grid file for each residue. We need to generate two input files for DOCK6 which will be called upon by the script. Create a file named 4qmz.multigrid.in inside your 007.multigrid folder with the following inside it:
compute_grids yes grid_spacing 0.4 output_molecule yes contact_score no chemical_score no energy_score yes energy_cutoff_distance 9999 atom_model a attractive_exponent 6 repulsive_exponent 9 distance_dielectric yes dielectric_factor 4 bump_filter yes bump_overlap 0.75 receptor_file temp.mol2 box_file ../03.box-grid/4qmz.box.pdb vdw_definition_file /PATH/DOCK6/parameters/vdw_AMBER_parm99.defn chemical_definition_file /PATH/DOCK6/parameters/chem.defn score_grid_prefix temp.rec receptor_out_file temp.rec.grid.mol2
Additionally, create a file named 4qmz.reference_multigrid.in:
conformer_search_type rigid use_internal_energy yes internal_energy_rep_exp 12 internal_energy_cutoff 100.0 ligand_atom_file /PATH/dock_tutorial/01.dockprep/4qmz.lig.mol2 limit_max_ligands no skip_molecule no read_mol_solvation no calculate_rmsd yes use_rmsd_reference_mol yes rmsd_reference_filename /PATH/dock_tutorial/01.dockprep/4qmz.lig.mol2 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 yes multigrid_score_secondary no multigrid_score_rep_rad_scale 1 multigrid_score_vdw_scale 1 multigrid_score_es_scale 1 multigrid_score_number_of_grids 19 multigrid_score_grid_prefix0 ../10.multigrid/4qmz.resid_017 multigrid_score_grid_prefix1 ../10.multigrid/4qmz.resid_018 multigrid_score_grid_prefix2 ../10.multigrid/4qmz.resid_019 multigrid_score_grid_prefix3 ../10.multigrid/4qmz.resid_026 multigrid_score_grid_prefix4 ../10.multigrid/4qmz.resid_039 multigrid_score_grid_prefix5 ../10.multigrid/4qmz.resid_071 multigrid_score_grid_prefix6 ../10.multigrid/4qmz.resid_087 multigrid_score_grid_prefix7 ../10.multigrid/4qmz.resid_088 multigrid_score_grid_prefix8 ../10.multigrid/4qmz.resid_089 multigrid_score_grid_prefix9 ../10.multigrid/4qmz.resid_090 multigrid_score_grid_prefix10 ../10.multigrid/4qmz.resid_091 multigrid_score_grid_prefix11 ../10.multigrid/4qmz.resid_093 multigrid_score_grid_prefix12 ../10.multigrid/4qmz.resid_097 multigrid_score_grid_prefix13 ../10.multigrid/4qmz.resid_100 multigrid_score_grid_prefix14 ../10.multigrid/4qmz.resid_139 multigrid_score_grid_prefix15 ../10.multigrid/4qmz.resid_279 multigrid_score_grid_prefix16 ../10.multigrid/4qmz.resid_280 multigrid_score_grid_prefix17 ../10.multigrid/4qmz.resid_283 multigrid_score_grid_prefix18 /PATH/dock_tutorial/10.multigrid/4qmz.resid_remaining multigrid_score_fp_ref_mol no multigrid_score_fp_ref_text yes multigrid_score_footprint_text /PATH/dock_tutorial/09.footprint_rescore/4qmz.reference.txt multigrid_score_use_euc yes multigrid_score_use_norm_euc no multigrid_score_use_cor no multigrid_vdw_euc_scale 1 multigrid_es_euc_scale 1 dock3.5_score_secondary no continuous_score_secondary no footprint_similarity_score_secondary no ph4_score_secondary no descriptor_score_secondary no gbsa_zou_score_secondary no gbsa_hawkins_score_secondary no SASA_descriptor_score_secondary no amber_score_secondary no minimize_ligand yes simplex_max_iterations 1000 simplex_tors_premin_iterations 0 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_random_seed 0 simplex_restraint_min yes simplex_coefficient_restraint 5.0 atom_model all vdw_defn_file /PATH/DOCK6/parameters/vdw_AMBER_parm99.defn flex_defn_file /PATH/DOCK6/parameters/flex.defn flex_drive_file /PATH/DOCK6/parameters/flex_drive.tbl ligand_outfile_prefix output write_orientations no num_scored_conformers 1 rank_ligands no
Now that we have our input files, we can form the script that will call upon them to generate the grid files for each specified residue. Create a blank file named 4qmz.make_multigrids.qsub.sh in your 007.multigrid folder. Then transcribe into it:
cd /PATH/dock_tutorial/09.footprint_rescore
export PRIMARY_RES=` cat 4qmz.primary_residues.dat | sed -e 's/\n/ /g' `
export DOCKHOME="/gpfs/projects/AMS536/zzz.programs/dn_dock.6.7/"
python /PATH/DOCK6/bin/multigrid_fp_gen.py 4qmz.rec.mol2 4qmz.resid 4qmz.multigrid.in ${PRIMARY_RES}
rm temp.mol2
rm 4qmz.resid_*.rec.grid.mol2
/PATH/DOCK6/bin/dock6.dn -i 4qmz.reference_multigridmin.in -o 4qmz.reference_multigridmin.out
mv output_scored.mol2 4qmz.lig.multigridmin.mol2
cp 4qmz.lig.multigridmin.mol2 ../10.multigrid
Change the path to DOCK6 and your primary residue file if necessary, and ensure you are using a version of DOCK6 with the de novo code. If you get an error that says something like "cannot stat *.nrg / *.bmp" etc, check to make sure your directories are all pointing to the right places in your two input files. After running this script, you should be given a plethora of different files. If you are running on the 4qmz system, you should have 19 different residues: 18 individual residues, and a 19th file containing the grid for the rest of the residues. You will have four files for each residue: a .bmp file, a .mol2 file, a .nrg file, and a .out file (for each residue!). Additionally you should have two other files: 4qmz.lig.multigridmin.mol2, 4qmz.reference_multigridmin.out. Check your output file for any errors and to make sure everything ran to completion. Visualize your ligand in Chimera to make sure it contains atoms and looks like a real chemical structure. You should have something that looks like this:
In addition to ensuring the ligand still seems reasonable, it may be worthwhile and interesting to visualize the ligand with the primary residues to create a distilled down active site like this (ligand is highlighted green for ease of visualization):
Minimizing Ligand on the Grids
We're resoring the reference in grid space. Create an input file named 4qmz.parents_multigridmin.in with this inside it:
conformer_search_type rigid use_internal_energy yes internal_energy_rep_exp 12 internal_energy_cutoff 100.0 ligand_atom_file /PATH/dock_tutorial/01.dockprep/4qmz.lig.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 yes multigrid_score_secondary no multigrid_score_rep_rad_scale 1 multigrid_score_vdw_scale 1 multigrid_score_es_scale 1 multigrid_score_number_of_grids 19 multigrid_score_grid_prefix0 4qmz.resid_017 multigrid_score_grid_prefix1 4qmz.resid_018 multigrid_score_grid_prefix2 4qmz.resid_019 multigrid_score_grid_prefix3 4qmz.resid_026 multigrid_score_grid_prefix4 4qmz.resid_039 multigrid_score_grid_prefix5 4qmz.resid_071 multigrid_score_grid_prefix6 4qmz.resid_087 multigrid_score_grid_prefix7 4qmz.resid_088 multigrid_score_grid_prefix8 4qmz.resid_089 multigrid_score_grid_prefix9 4qmz.resid_090 multigrid_score_grid_prefix10 4qmz.resid_091 multigrid_score_grid_prefix11 4qmz.resid_093 multigrid_score_grid_prefix12 4qmz.resid_097 multigrid_score_grid_prefix13 4qmz.resid_100 multigrid_score_grid_prefix14 4qmz.resid_139 multigrid_score_grid_prefix15 4qmz.resid_279 multigrid_score_grid_prefix16 4qmz.resid_280 multigrid_score_grid_prefix17 4qmz.resid_283 multigrid_score_grid_prefix18 4qmz.resid_remaining multigrid_score_fp_ref_mol no multigrid_score_fp_ref_text yes multigrid_score_footprint_text 4qmz.reference.txt multigrid_score_foot_compare_type Euclidean multigrid_score_normalize_foot no multigrid_score_vdw_euc_scale 1.0 multigrid_score_es_euc_scale 1.0 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 simplex_max_iterations 1000 simplex_tors_premin_iterations 0 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_random_seed 0 simplex_restraint_min yes simplex_coefficient_restraint 5.0 atom_model all vdw_defn_file /PATH/DOCK6/parameters/vdw_AMBER_parm99.defn flex_defn_file /PATH/DOCK6/parameters/flex.defn flex_drive_file /PATH/DOCK6/parameters/flex_drive.tbl ligand_outfile_prefix output write_footprints no write_orientations no num_scored_conformers 1 rank_ligands no
After running this with DOCK6 you should have an output file (which should be checked for errors, as always) and a .mol2 file named output_scored.mol2. Rename this to 4qmz.parents_multigridmin.mol2, and visualize it in Chimera, to ensure you still have a realistic molecule. This is the mol2 file of the ligand minimized using the multigrid scoring. This will serve as our reference molecule for guided growth!
Running de novo
We can now run de novo growth! Rejoice! Compared to the previous steps, this part is fairly straight forward. Simply create the input file, and create a script to submit it to the cluster.
Creating the Input File
Create a folder named 010.denovo. Then, inside this directory, create an input file with the following inside it:
conformer_search_type denovo dn_fraglib_scaffold_file /PATH/dock_tutorial/000.fraglib/fraglib_scaffold.mol2 dn_fraglib_linker_file /PATH/dock_tutorial/000.fraglib/fraglib_linker.mol2 dn_fraglib_sidechain_file /PATH/dock_tutorial/000.fraglib/fraglib_sidechain.mol2 dn_user_specified_anchor yes dn_fraglib_anchor_file anchor1.mol2 dn_use_torenv_table yes dn_torenv_table /PATH/dock_tutorial/000.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 dn_pruning_conformer_score_cutoff 100.0 dn_pruning_conformer_score_scaling_factor 2.0 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 3 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 yes dn_write_orients no dn_write_growth_trees no dn_output_prefix 4qmz.final 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 ../02.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 ph4_score_primary no ph4_score_secondary no descriptor_score_primary yes descriptor_score_secondary no descriptor_use_grid_score no descriptor_use_multigrid_score yes descriptor_use_pharmacophore_score no descriptor_use_tanimoto no descriptor_use_hungarian no descriptor_multigrid_score_rep_rad_scale 1.0 descriptor_multigrid_score_vdw_scale 1.0 descriptor_multigrid_score_es_scale 1.0 descriptor_multigrid_score_number_of_grids 19 descriptor_multigrid_score_grid_prefix0 ../09.footprint_rescore/4qmz.resid_017 descriptor_multigrid_score_grid_prefix1 ../09.footprint_rescore/4qmz.resid_018 descriptor_multigrid_score_grid_prefix2 ../09.footprint_rescore/4qmz.resid_019 descriptor_multigrid_score_grid_prefix3 ../09.footprint_rescore/4qmz.resid_026 descriptor_multigrid_score_grid_prefix4 ../09.footprint_rescore/4qmz.resid_039 descriptor_multigrid_score_grid_prefix5 ../09.footprint_rescore/4qmz.resid_071 descriptor_multigrid_score_grid_prefix6 ../09.footprint_rescore/4qmz.resid_087 descriptor_multigrid_score_grid_prefix7 ../09.footprint_rescore/4qmz.resid_088 descriptor_multigrid_score_grid_prefix8 ../09.footprint_rescore/4qmz.resid_089 descriptor_multigrid_score_grid_prefix9 ../09.footprint_rescore/4qmz.resid_090 descriptor_multigrid_score_grid_prefix10 ../09.footprint_rescore/4qmz.resid_091 descriptor_multigrid_score_grid_prefix11 ../09.footprint_rescore/4qmz.resid_093 descriptor_multigrid_score_grid_prefix12 ../09.footprint_rescore/4qmz.resid_097 descriptor_multigrid_score_grid_prefix13 ../09.footprint_rescore/4qmz.resid_100 descriptor_multigrid_score_grid_prefix14 ../09.footprint_rescore/4qmz.resid_139 descriptor_multigrid_score_grid_prefix15 ../09.footprint_rescore/4qmz.resid_279 descriptor_multigrid_score_grid_prefix16 ../09.footprint_rescore/4qmz.resid_280 descriptor_multigrid_score_grid_prefix17 ../09.footprint_rescore/4qmz.resid_283 descriptor_multigrid_score_grid_prefix18 ../09.footprint_rescore/4qmz.resid_remaining descriptor_multigrid_score_fp_ref_mol yes descriptor_multigrid_score_footprint_ref ../09.footprint_rescore/4qmz.parents_multigridmin.mol2 descriptor_multigrid_score_use_euc yes descriptor_multigrid_score_use_norm_euc no descriptor_multigrid_score_use_cor no descriptor_multigrid_vdw_euc_scale 1.0 descriptor_multigrid_es_euc_scale 1.0 descriptor_weight_multigrid_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 no atom_model all vdw_defn_file /PATH/DOCK6/parameters/vdw_AMBER_parm99.defn flex_defn_file /PATH/DOCK6/parameters/flex.defn flex_drive_file /PATH/DOCK6/parameters/flex_drive.tbl
There are a few things to note here: you must specify a .mol2 file for the scaffold, linker, and sidechain libraries; you must specify your anchor library, which must be tailored prior to the calculation to include the specific anchors you would like to seed from; finally, even though we call upon the descriptor score, we only do so to call our multigrid scoring function -- we are not using descriptor grid score. This would be the same as running with descriptor_score = no and multigrid_score = yes, but it is standard protocol to call any and all scoring functions through descriptor score, regardless of if you're using it or not.
Creating a script to submit to Seawulf
Now we want to generate a script that will call DOCK6 to run the input file we just generated. Why do we need to make a script instead of submitting it directly to DOCK6? De novo generic growth take a good amount of time (approximately 5-10 hrs per anchor) and can get very computationally expensive, thus we will want to submit it to a cluster using qsub. Generate a script (denote.sh) with the following inside it:
#!/bin/bash #PBS -l walltime=48:00:00 #PBS -l nodes=1:ppn=24 #PBS -q long #PBS -N 4qmz.denovo #PBS -V cd $PBS_O_WORKDIR /gpfs/projects/AMS536/zzz.programs/dn_dock.6.7/bin/dock6.dn -i denovo.in -o 4qmz.denovo_mg.out
Submit this to the queue by typing:
qsub denovo.sh
Monitor the output file to see which anchor/layer the calculation is at. Run this calculation from your 010.denovo directory.
Viewing the Results
After the calculation has (successfully) finished, you should have in your directory a large amount of new files. These files take the form 4qmz.final_anchor_*.prune_dump_layer_*.mol2 and 4qmz.final_anchor_*.root_layer_*.mol2. For each anchor, you will have a number of both of these files equal to the number of molecules per layer you specified in the input file. Additionally, you will have an output file (which, of course, should be checked for errors), and a file named 4qmz.final.denovo_build.mol2 -- this is your final output file containing all of the constructed and scored molecules. We are going to open this in Chimera using ViewDock. First, in Chimera, open your 4qmz.parents.multigridmin.mol2 file, then on top of that open the cleaned receptor file. Then click Tools > Surface/Binding Analysis > ViewDock and open the 4qmz.final.denovo_build.mol2 file. This file can have upwards of a thousand different molecules in it, depending on how many anchors and layers you used, and can take a little while to open. Once you select the file in ViewDock and click open, most likely Chimera will freeze, and you won't be able to do anything. It must load all the molecules at once, so give it a good five or ten minutes to load before you decide to quit the program. It will open, you just have to be patient. Once it has loaded you can arrange your molecules based on various parameters contained in the mol2 file. Descriptor (multigrid) score, Mol. weight, and chain/fragment sequence are a few useful metrics for visualizing the newly created molecules in the receptor's active site.
Top descriptor score hits along with fragment strings. Identifies families of related compounds:
Related family of molecules:
Related family of compounds with varying active site conformation:
Related family with conserved binding pocket pose:
Top descriptor scores vs. cognate ligand in red:
Things to Keep in Mind
When running de novo for the first time, it is strongly encouraged that you run it through interactive mode first: that is, generate an empty input file, and run the code inputting the parameters manually for each question. This will give you a good idea of what it wants, what it's doing, and where any potential errors you may come across are originating from.
The de novo code takes anywhere from 4-8 hours per anchor for 15 molecules per layer depending on a myriad of factors: the anchor being used, the specific system, the number of grids, the scoring function, etc.
If you submit an anchor library containing more anchors than you will use (ex: library has 100 anchors, you're only using five) the de novo code will automatically pick the largest anchors! Thus, if you do not specify your anchors, upon finishing your calculation and reviewing your structures, you will notice a disturbing amount of large ring structures. To get around this, be sure to use an anchor library which you have personally compiled and be aware which order it will run the calculation in (it chooses the largest molecular weight anchor first).
It has been determined that the de novo code is sequence independent. Meaning that the results do not depend on the order of their calculation. For example, if you have in your anchor library file anchors A, B, and C for a de novo calculation, you will receive the same results (molecules, conformations, and scores) as if you had run the calculation for A, B, and C individually, with each structure in their own anchor file.
For multigrid scoring, you do not need to specify a dummy atom, or use the corresponding dummy_H parameter file. For other types of scoring functions you will have to specify in your anchor files which atoms are the dummy atoms.
Dock can be finicky about paths. Sometimes it doesn't want full paths (i.e. originating from the top directory, /gpfs), but other times it wants the explicit path in its entirety. If you keep receiving an error about a file location, and you are positive you have entered the correct path, try either reducing the path as much as possible (starting from your home directory, ~/ ) or try including the full path if you have not.
If DOCK6 does not accept "denovo" as a conformer_search_type then you are not running a version of DOCK6 that contains the de novo code.
Length of Denovo Calculations
The de novo code can take a large amount of time, especially as the number of anchors and layers is increased. To give an idea of how long the de novo calculations take, below are some details from different runs on the 4qmz system (the .out file from the de novo code has the total calculation time in seconds at the bottom):
1.) Single anchor (Methylene): ~3.92 hours
dn_max_grow_layers 9
dn_max_root_size 25
dn_max_layer_size 25
2.) Single Anchor (Carbonyl): ~6.3 hours
dn_max_grow_layers 9
dn_max_root_size 25
dn_max_layer_size 25
3.) Single Anchor (Amine): ~4.99 hours
dn_max_grow_layers 9
dn_max_root_size 25
dn_max_layer_size 25
4.) Single anchor (Methylene): not calculated
dn_max_grow_layers 9
dn_max_root_size 100
dn_max_layer_size 100
5.) Single Anchor (Methylene): ~18.1 hours
dn_max_grow_layers 9
dn_max_root_size 100
dn_max_layer_size 25
6.) Single Anchor (Methylene): ~24.2 hours
dn_max_grow_layers 9
dn_max_root_size 25
dn_max_layer_size 100
Make Unique Script to prune de novo results
I was able to test a couple of scripts that would filter through resulting mol2 libraries from de novo runs to collect unique results and omit any repeated molecules. This process uses two scripts, zzz.002.makeunique_new_sub.sh and split_on_tanimoto_new.py. It is imperative that the tanimoto score is included in the original de novo calculation in order to execute these scripts. Otherwise results from a de novo run can be rescored using the tanimoto scoring function without a problem. split_on_tanimoto takes the full de novo mol2 output and compares the tanimotos to a reference ligand. It is easiest to use the cognate ligand from your docking trials however any reference should be appropriate. From here many "bins" containing molecules with the same tanimoto to some reference. From here, zzz.002.makeunique_new_sub.sh compares the tanimoto of the first molecule in the bin (the highest scoring molecule) with the rest of the molecules in the same bin. If there are any tanimoto scores of 1, those molecules are deleted. This process continues until each molecule has been tested. At this point the output should contain a single copy of each of the best scoring molecules generated by a de novo calculation.
