Difference between revisions of "2022 DOCK tutorial 1 with PDBID 6ME2"
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And this will produce a PDF containing a visualization of the footprint, called '''footprint.out.pdf'''. Open this in a PDF viewer, and it appears as follows: | And this will produce a PDF containing a visualization of the footprint, called '''footprint.out.pdf'''. Open this in a PDF viewer, and it appears as follows: | ||
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= Virtual Screening = | = Virtual Screening = | ||
Revision as of 12:38, 21 March 2022
Contents
Required Software
UCSF Chimera, UCSF DOCK 6.9
Chimera
UCSF Chimera is a software which aids the interactive 3D visualization, editing, and analysis of biological macromolecules.
[insert screenshot of chimera]
Chimera will be used in this tutorial to prepare molecules for docking, as well as for simply exploring the structures of molecules of interest.
DOCK
UCSF DOCK is a molecular docking program, used to find the optimal orientation of a ligand binding to a receptor. DOCK can be used for a number of different molecular modeling/design tasks, such as testing binding affinities, virtual screening, and de novo design.
6ME2
6ME2 is the modeled structure of receptor MT1 of melatonin complexed with ramelteon (the ligand). Further details on the structure from the original researchers can be found at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6696938/
Seawulf: Getting Started
Basics of the Command Line/Terminal
There are some basic commands for the command line/terminal that are necessary to know in order to complete this tutorial effectively.
When one first opens a command line window, it will begin in their home directory. To change this directory to, say, Desktop, type:
cd ~/Desktop
To get to a folder, say folder_1, in Desktop, type
cd ~/Desktop/folder_1
To list out all of the directories/files contained within this current directory, type
ls
To change the directory to one folder in the hierarchy above the current, type
cd ../
to change directories a folder, say folder_2 inside the current directory, type
cd ./folder_2
To create a file in the current directory, called "file_example", using vim, type
vi filename_example
This will open up a prompt where one can type in, paste, or edit (if the file already exists in the current directory) the contents of the file. To edit the file once opened, type "i", which will change the environment to "INSERT" mode. "INSERT" is displayed at the bottom of the window when in this mode. To exit "INSERT" mode, press "Escape". If in "INSERT" mode, to save the file, press "Escape" and then type
:wq
which will save the file and open the terminal window back up to commands, in the current directory. If one types
ls
the newly created "file_example" should be visible in the outputted list of files.
To move files between directories, say "file_example" is the file of interest, from Directory_1 to Directory_2, type
mv /Directory_1/file_example /Directory_2/file_example
The name of file_example may also be changed (to "file_new_name") during this move:
mv /Directory_1/file_example /Directory_2/file_new_name
Note this should be used to rename directories--move the file to the same directory and change the name to rename the file.
To copy files between directories, type the following
cp /Directory_1/file_example /Directory_2/file_new_name
And one can copy directories as well, by typing
cp -R /Directory_1/sub_directory /Directory_2/sub_directory_new_name
Note that the "-R" flag specifies to copy over the sub_directory folder and all of its contents from Directory_1 to Directory_2.
To create a new directory, called "new_directory" for example, type
mkdir new_directory
To delete a file in the current directory, "file_example", type
rm file_example
To delete a directory called "directory_example", including all of its subdirectories and associated files, type
rm -r
Note that if one wishes to perform the same action on multiple files at once, this can be done on the same line by separating the filenames with a space. For example to delete the files filename_1 in Directory_1 and filename_2 in Directory_2, type
rm Directory_1/filename_1 Directory_2/filename_2
Important note: the action of deleting files with rm cannot be undone. Use extreme caution when removing files/directories as there is no Ctrl + Z in the terminal.
SeaWulf is the High Performance Computing (HPC) cluster which researchers and students at Stony Brook University can gain access to use for computationally intensive tasks. Note Stony Brook students often do not automatically have access to SeaWulf, but students can request access from IT or be given access by their labs/instructors. For help getting access to SeaWulf, or questions/problems encountered when using the cluster at any point, submit a ticket to IT at https://it.stonybrook.edu/help/kb/understanding-seawulf.
If one has access to SeaWulf, they can access the cluster by typing the following into their terminal
ssh -X NETID@login.seawulf.stonybrook.edu
Note that the flag -X enables visualizations when running programs in SeaWulf, and NETID is the user's assigned NETID username, used to sign into Blackboard and all associated Stony Brook University domains. The terminal will then prompt the user for the password associated with the entered NETID, and then will give a list of options to use DUO Authentication to grant access. After cooperating with DUO, the user will be in their SeaWulf home directory.
To navigate to the AMS 536 space within SeaWulf, type
cd /gpfs/projects/AMS536
To access a user's personal scratch space, which is where users can keep files and test programs (but note all files in this directory will be automatically deleted if not modified in over 30 days), type
cd /gpfs/scratch/NETID
File transfers to/from SeaWulf
To transfer files between the user's local machine and the SeaWulf cluster, this can be done using scp. For example, to transfer the file "file_1" from the directory Directory_1 on the user's local directory to the user's scratch space on SeaWulf, type the following into the user's local terminal window (not connected to SeaWulf):
scp Directory_1/file_1 NETID@login.seawulf.stonybrook.edu:/gpfs/scratch/NETID
Likewise, to transfer file_1 from the scratch space in SeaWulf back to a local directory, type the following into the local terminal window:
scp NETID@login.seawulf.stonybrook.edu:/gpfs/scratch/NETID/file_1 /Directory_1
Chimera: Getting Started
Searching for/Downloading files from the PDB
The RCSB Protein Data Bank is a useful tool for searching for and downloading files containing the 3D structures of biological macromolecules. One can search for a molecule by using an exact 4 letter code (such as "6ME2") or by searching for a short description (such as "melatonin with ramelteon complex"). Note that there may be many molecules that fit a given description, so one may need to scroll through results shown after the search to find the one of interest.
(insert picture of PDB w/ search bar, results below after searching)
After finding the page for the structure of interest, one can download it in PDB or Mol2 (or other) format by selecting the dark blue Download Files drop-down menu to the right of the page. Select the desired format, and the download will begin.
First-steps for visualizations in Chimera
Opening files in Chimera
Once one opens Chimera, they are met with a blue screen, and at the bottom right corner are two options called Browse... and Fetch.... If the structure of interest is downloaded already to a local computer, choose Browse...; it is possible to download the structure from the PDB directly in Chimera using the Fetch... option, but note this requires knowledge of the 4-digit code for the structure listed in the PDB.
Visual configurations
Chimera can be a helpful tool for producing publication-ready visualizations of molecules. When Chimera is first opened, the structure will be drawn against a black screen; if a different appearance is desired, click the Presets tab at the top, where there are a number of options. A recommended preset is Publication 1 (silhouette, rounded ribbons).
Selecting substructures
Note that it is possible to select portions of the current structure. To do so, click the Select tab at the top. Options will become visible to select by chain, residue, structure, and so on. One can also hit Control + Click to interactively select a small portion of the structure. If one presses the "up" arrow on their keyboard, this will select a larger substructure containing the initial selection. Hitting "up" again will select more, until the entire structure is selected. Alternatively, hitting the "down" arrow will go backwards in selection scope, until the initial small selection is restored.
Modifying selected substructures
One of the easiest ways to make a visualization in Chimera more clear is through color editing. If one is dealing with a protein-ligand complex, for example, it may be useful to color the two structures differently to contrast the two. To do this, select one of the structures (this can be done by interactively clicking and hitting the "up" arrow, or more easily by selecting by structure), then, while the substructure is selected, click the Actions tab, click Color, and make a color choice.
If one wishes to isolate specific parts of a structure from the rest, it is necessary to understand how to delete substructures. This can be done by selecting a substructure of interest, clicking "Actions", hovering over Atoms/Bonds, then under the shown options clicking delete at the bottom. This will remove the selected substructure, and cannot be immediately undone, so make sure that parts of the substructure have been colored to make their separation as clear as possible to avoid deleting any parts by accident.
Saving sessions
If one wishes to save an entire session, with all configurations (such as visual orientation, focus, coloring, etc. which cannot be captures by just saving as a Mol2 or PDB file), one can go to File -> Save Session As... and this will save the current configurations.
(put in a picture?)
Organizing File Directories
It is imperative to one's ability to keep and access records, for any purpose, by having a detailed and organized directory list wherein any necessary files may be kept. While following this docking tutorial, it is recommended to have the following directories on both the local machine as well as in the user's designated space on SeaWulf:
000_files 001_structure 002_surface_spheres 003_gridbox 004_dock 005_virtual_screen 006_virtual_screen_mpi 007_cartesian_min 008_rescore
Dock Prep
Initial investigation/preparation
First, download the 6ME2 file from the PDB, using either Mol2 or PDB format. Save this in 000_files. Then, open this structure using Chimera. It should look as follows:
[insert image of PL complex]
Inspect the structure of the complex. Note that other non-standard residues besides ramelteon (code "JEV") are present, and will be deleted. Note that to begin the docking preparation process, all solvent must be removed from the file. There is water present in this file, so go to Select -> Residue -> HOH, and click Actions -> Atoms/Bonds -> sphere then Actions -> Atoms/Bonds -> show, which will show the selected as red spheres, shown below
[insert image of HOH selected]
Next, hit Select -> Residue and select all non-standard residues outside of JEV. While these are selected, go to Actions -> Atoms/Bonds -> delete, leaving only the JEV ligand and receptor. Save this as a Mol2 file called 6me2_noH_noDetergents.mol2 in the 000_files directory.
[insert photo of ligand-protein complex without extra residues]
Isolating the ligand and receptor
To prepare the ligand and receptor for docking, it is necessary to have two separate files--one for the prepared ligand, and one for the prepared receptor, which will be used separately at points.
Isolating the receptor: Load the 6ME2 pdb into Chimera. Select and delete the OLA and PEG residues. There are non-standard residues (YCM) which need to be mutated to the closest structural analog, cysteine. Using Tools > Structure Editing > Rotamers, change YCM to the most probable rotamers of CYS. Use Tools > Surface/Binding analysis > DockPrep to add hydrogens to the receptor. Save this structure as a mol2 with File > Save mol2
Isolating ligand:
Select the ligand (JEV) in Chimera. Initially, the structure will present incorrectly with an sp2 carbon after adding hydrogens with the Tools > Structure Editing > AddH.
Caption: Incorrect structure of JEV ligand.
Select the incorrect atom. Go to Tools > Structure Editing > Build Structure. In the pop-up window, select “Modify structure”. Under the “Geometry” tab, select tetrahedral, and choose to leave the residue name unchanged, then choose “Apply”. Save this structure as jev_wH.mol2 with File > Save mol2.
Caption: Correct structure of JEV ligand
Surface Spheres
Generating DMS of receptor
Open the receptor_wH.mol2 in Chimera. In Chimera, go to Actions > Surface > Show to visualize the surface of the receptor.
Save this surface (without the ligand present) using Tools > Structure Editing > Write DMS > receptor_wH.dms. To visualize the binding pocket, load in the jev_wH.mol2 file, and show the ligand as a surface. For 6ME2, the binding pocket is in the interior of the protein.
Creating Surface Spheres
Next, the available space near the active site needs to be identified. These spaces represent possible binding sites for the ligand. DOCK6.9 provides many options here; the first line is the input .dms, the second line, R, tells DOCK to only look for space on the exterior surface of the protein. X indicates to DOCK to use all surface points. The 4th line, 0.0 is the extent of acceptable steric clash. Here, we don't accept any steric clashing, and set it to zero. The 5th and 6th lines, 4.0 and 1.4 are the maximum and minimum sphere radii, respectively. The final line in the input file is the output .sph, which contains all of the spheres identified by DOCK.
vi INSPH
6ME2_rec_surface.dms R X 0.0 4.0 1.4 6ME2_receptor_noH.sph
The following command will call spheregen and generate the spheres
sphgen -i INSPH -o OUTSPH
If we look at the output in Chimera, we see that there are many spheres generated.
Selecting Relevant Spheres
Most of these spheres aren't relevant for the ligand in question. Only the spheres that overlap well (within 10 Å) with the docked structure of the ligand are important in this context. To isolate these specific spheres,
sphere_selector 6ME2_receptor_noH.sph jev_wH.mol2 10.0
When opening selected_spheres.sph in Chimera, it can be see that most of the spheres have been erased, leaving only the spheres that are within 10 Å of the ligand.
Generating Box/Grid
In order to score the ligands upon docking, DOCK uses a grid - with its size defined by a box - to generate a series of points. Energetic contributions will be calculated at each of these points.
Box Generation
To create the box, run vi showbox.in The first line, Y tell the showbox "Yes, create a box". The second line is the distance (Å) from the spheres that the box should be created. The third line is the location of the selected_spheres.sph file, and the last line is the output, which contains the box.
Y 8.0 ../002_surface_spheres/selected_spheres.sph 1 6me2.box.pdb
To create the box, run showbox < showbox.in
Grid Generation
To make the grid, vi grid.in
compute_grids yes grid_spacing 0.4 output_molecule no contact_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 ../001_structure/jev_wH.mol2 box_file 6me2.box.pdb vdw_definition_file /gpfs/projects/AMS536/zzz.programs/dock6.9_release/parameters/vdw_AMBER_parm99.defn score_grid_prefix grid
Then run, grid -i grid.in -o gridinfo.out If the grid generation was successful, then there will now be gridinfo.out, grid.bmp, and grid.nrg in the directory.
Docking
Energy Minimization
The purpose of using DOCK for this tutorial is to find the most energetically favorable position of the ligand in the target site pocket. To get as good of a DOCK score as possible, it is pertinent to minimize the potential energy of the ligand itself.
Switch to the 004_dock directory by typing
cd ../004_dock
Then create an input file called min.in by typing
vi min.in
Then copy and paste the following into this file:
conformer_search_type rigid use_internal_energy yes internal_energy_rep_exp 12 internal_energy_cutoff 100.0 ligand_atom_file ../001_structure/6me2_ligand_wH.mol2 limit_max_ligands no skip_molecule no read_mol_solvation no calculate_rmsd yes use_rmsd_reference_mol yes rmsd_reference_filename ../001_structure/6me2_ligand_wH.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 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 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_tors_step 10.0 simplex_random_seed 0
simplex_restraint_min yes simplex_coefficient_restraint 10.0 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 6me2.ligand.min write_orientations no num_scored_conformers 1 rank_ligands no
Next, run the energy minimization by typing
dock6 -i min.in -o min.out
When the produced 6me2.ligand.min_scored.mol2 is visualized in Chimera, it looks as follows:
To view the RMSD of the minimized ligand conformation, vi into this file:
vi 6me2.ligand.min_scored.mol2
Rigid Docking
Note that there are multiple different docking protocols that this tutorial will utilize--rigid, fixed anchor, and flexible. The first this tutorial will utilize is rigid docking.
Make sure to still be in the 004_dock directory, and create a rigid docking input file as follows:
vi rigid.in
Copy and paste the following input parameters into the file:
conformer_search_type rigid use_internal_energy yes internal_energy_rep_exp 12 internal_energy_cutoff 100 ligand_atom_file 6me2.ligand.min_scored.mol2 limit_max_ligands no skip_molecule no read_mol_solvation no calculate_rmsd yes use_rmsd_reference_mol yes rmsd_reference_filename 6me2.ligand.min_scored.mol2 use_database_filter no orient_ligand yes automated_matching yes receptor_site_file ../002_surface_spheres/selected_spheres.sph max_orientations 2000 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 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 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 rigid.out write_orientations no num_scored_conformers 1 rank_ligands no
Now run the rigid docking protocol using this input file by typing:
dock6 -i rigid.in
Note this will produce the output file rigid.out_scored.mol2, which when opened in Chimera appears as the following:
[insert image]
Be sure to open the file and inspect the RMSD by typing:
vi rigid.out_scored.mol2
Fixed Anchor Docking
The next docking protocol used is the fixed anchor protocol, wherein the location of the ligand in the binding pocket is fixed but the rotatable bonds are moved during energy minimization. Make sure to still be in the 004_dock directory, and create the following input file
vi fixed.in
And copy and paste the following parameters into this file:
conformer_search_type flex write_fragment_libraries no user_specified_anchor no limit_max_anchors no min_anchor_size 5 pruning_use_clustering yes pruning_max_orients 10000 pruning_clustering_cutoff 100 pruning_conformer_score_cutoff 100.0 pruning_conformer_score_scaling_factor 1.0 use_clash_overlap no write_growth_tree no use_internal_energy yes internal_energy_rep_exp 12 internal_energy_cutoff 100.0 ligand_atom_file ../001_structure/6me2_ligand_wH.mol2 limit_max_ligands no skip_molecule no read_mol_solvation no calculate_rmsd yes use_rmsd_reference_mol yes rmsd_reference_filename ../001_structure/6me2_ligand_wH.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 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 simplex_trans_step 1 simplex_rot_step 0.1 simplex_tors_step 10 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 ligand_outfile_prefix 6me2_fad write_orientations no num_scored_conformers 100 write_conformations no cluster_conformations yes cluster_rmsd_threshold 2.0 rank_ligands no
And now run the docking protocol by typing:
dock6 -i fixed.in -o fixed.out
When the output file 6me2_fad_scored.mol2 is opened in Chimera, it appears as follows:
And be sure to check the RMSD value of the docked ligand by typing:
vi 6me2_fad_scored.mol2
Flexible Docking
The final docking protocol that will be performed in this tutorial is flexible docking. In this method, the ligand is completely free to move with all degrees of freedom being taken into account; because of the added number of possible conformations in this protocol, it is the most computationally intensive out of the three tested herein.
Be sure to remain in the 004_dock folder, and create the following input file:
vi flex.in
And paste the following parameters into this file:
conformer_search_type flex write_fragment_libraries no user_specified_anchor no limit_max_anchors no min_anchor_size 5 pruning_use_clustering yes pruning_max_orients 5000 pruning_clustering_cutoff 2500 pruning_conformer_score_cutoff 100.0 pruning_conformer_score_scaling_factor 1.0 use_clash_overlap no write_growth_tree no use_internal_energy yes internal_energy_rep_exp 12 internal_energy_cutoff 100.0 ligand_atom_file 6me2.ligand.min_scored.mol2 limit_max_ligands no skip_molecule no read_mol_solvation no calculate_rmsd yes use_rmsd_reference_mol yes rmsd_reference_filename 6me2.ligand.min_scored.mol2 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 ligand_outfile_prefix flex.out write_orientations yes num_scored_conformers 25 write_conformations yes cluster_conformations yes cluster_rmsd_threshold 2 rank_ligands no
Now run the flexible docking protocol with the input file by typing the following:
dock6 -i flex.in
When the output file flex.out_scored.mol2 is opened in Chimera it appears as follows:
[insert image]
Be sure to open up the file and check the RMSD by typing:
vi flex.out_scored.mol2
Calculating Molecular Footprint
The molecular footprint is a helpful tool to visually inspect and analyze the van der Waals and electrostatic interactions between the ligand and local amino acid residues, which can imply affinity of the ligand to the receptor on a per-residue basis. The footprint can also give clues to structural characteristics, such as the appearance of hydrogen bonds at peaks in the footprint graph, and thus can be used to find errors in the ligand conformation during energy minimization.
To calculate the molecular footprint, create an input file in the 004_dock directory as follows:
vi footprint.in
And paste the following into this file:
conformer_search_type rigid use_internal_energy no ligand_atom_file 6me2.ligand.min_scored.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 ../001.structure/6me2_ligand_wH.mol2 fps_score_foot_compare_type Euclidean fps_score_normalize_foot no fps_score_foot_comp_all_residue yes fps_score_receptor_filename ../001.structure/6me2_receptor_dockprep.mol2 fps_score_vdw_att_exp 6 fps_score_vdw_rep_exp 9 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 /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 footprint.out write_footprints yes write_hbonds yes write_orientations no num_scored_conformers 1 rank_ligands no
Now run the footprint calculation by typing the following:
dock6 -i footprint.in -o footprint.out
There will now be a python script created in the 004_dock folder, called plot_footprint_single_magnitude.py, which must be run to produce a visualization of the footprint calculation:
python plot_footprint_single_magnitude.py footprint.out_footprint_scored.txt 50
And this will produce a PDF containing a visualization of the footprint, called footprint.out.pdf. Open this in a PDF viewer, and it appears as follows:
Virtual Screening
Now that we have finished preparing both the ligand and receptor and verified that the ligand can be reasonably docked back into the receptor, we can now begin with the virtual screen. The idea behind virtual screening is that you can take a library of known molecules, dock them to a receptor, and then score how well those molecules are binding to the receptor. In this tutorial, our library is a file named "VS_library_5K.mol2", which contains 5,000 small molecules for us to dock to 6ME2. Let's begin by generating that library file of 5,000 molecules. Cd into the directory "005_virtual_screen" and copy the "VS_library_25K.mol2" file from "/gpfs/projects/AMS536/zzz.programs" into that directory with the following command:
cp /gpfs/projects/AMS536/zzz.programs/VS_library_25K.mol2 ./
Now we need to truncate this library for the top 5,000 molecules. We can do this with a very simple python script. Vi into "truncate_library.py" and write the following to that file (you can delete the comments, but they will give context to what is happening line-by-line if you don't know):
#Keep track of how many molecules have been copied over.
moleculenumber=0
#Create a list to hold each line being copied.
libraryfile = []
#Open the 25K library file, and number each line so it can be read line-by-line.
read_file = open("VS_library_25K.mol2")
lines = read_file.readlines()
#Add each individual line to the list.
for i, line in enumerate(lines):
libraryfile.append(line)
#Create the new library file so that molecules can be written to it.
with open("VS_library_5K.mol2", "w") as new_f:
#Copy over each line in the list for the first 5,000 molecules
for d in libraryfile:
new_f.write(d)
if "MOLECULE" in d:
moleculenumber += 1
if moleculenumber == 5001:
break
Once you have finished doing that, save and exit the file. To run this, type the following command into the terminal:
python truncate_library.py
Once you have your library of molecules, the next thing we want to do is write the input file. Vi into virtual.in and write the following to that file:
conformer_search_type flex write_fragment_libraries no user_specified_anchor no limit_max_anchors no min_anchor_size 5 pruning_use_clustering yes pruning_max_orients 1000 pruning_clustering_cutoff 100 pruning_conformer_score_cutoff 100.0 pruning_conformer_score_scaling_factor 1.0 use_clash_overlap no write_growth_tree no use_internal_energy yes internal_energy_rep_exp 12 internal_energy_cutoff 100.0 ligand_atom_file VS_library_5K.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 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 ligand_outfile_prefix virtual.out write_orientations no num_scored_conformers 1 rank_ligands no
Once you have finished doing that, save and exit the file. Now, we could try running the virtual screen similarly to previous steps, but it would be really slow. The best way to do this is to parallelize the task as many times as possible, and to do this we are going to use MPI.
Virtual Screening Using MPI
Running the virtual screen using MPI does not require us to change anything about in input file, but the submit file will look a little different than the previous one you made for the flexible docking step. To start, cd into the "006_virtual_screen_mpi" directory and copy over the 5,000 molecule library we generated. Vi into "virtualscreen.sh" and write the following to that file:
#!/bin/bash #SBATCH --time=48:00:00 #SBATCH --nodes=1 #SBATCH --ntasks=28 #SBATCH --job-name=6ME2_VS_min #SBATCH --output=6ME2_VS_min #SBATCH -p long-28core
cd $SLURM_SUBMIT_DIR
mpirun -np 28 dock6.mpi -i ../005_virtual_screen/virtual.in -o 6ME2.virtual.mpi.out
This will run the virtual screen across 28 cores which will significantly speed up the virtual screen process. To run this even faster, you can increase the number of nodes from one to up to 4, which would increase the total number of cores to either 56, 84, or 112. If you elect to try with more nodes, make sure to adjust both the number of nodes (line 3) and the total number of cores (line 11) in the submit file. To submit this simulation to the queue, type the following command into the terminal:
sbatch virtualscreen.sh
This will take awhile to finish, even with the MPI helping to speed things up. Once it's done, make sure to check that everything ran to completion per your output files. You should then, using Chimera, load the receptor and ligand files and see how the molecules from the virtual screen align with the ligand. The easiest way to do that is not to load in every molecule at once but to use a program in Chimera called ViewDock. ViewDock will let you visualize each molecule one at a time and order them based on parameters scuh as molecular weight or docking score. You can find ViewDock in (Tools -> Surface/Binding Analysis -> ViewDock). Select the output file from the virtual screen and from the next menu select "DOCK 4, 5, or 6" as we are using DOCK6. You can then scroll through the different molecules and see how well they align.
Cartesian Minimization of Docked Molecules
The structures you just looked at were the raw output from the virtual screen. It would be better, before making a conclusion on which of the 5,000 molecules bind the best, to run an energy minimization on each of those molecules and then rescore them based on any changes in their interactions with the receptor. Starting with the energy minimization, change directories to 007_cartesian_min. We will need to write an input and submit file for this simulation, so let's start with the input file and vi into cartmin.in. Write the following to that file:
conformer_search_type rigid use_internal_energy yes internal_energy_rep_exp 12 internal_energy_cutoff 100 ligand_atom_file ../006_virtualscreenmpi/virtual.out_scored.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 yes continuous_score_secondary no cont_score_rec_filename ../001_structure/6ME2.receptor_wH.mol2 cont_score_att_exp 6 cont_score_rep_exp 12 cont_score_rep_rad_scale 1 cont_score_use_dist_dep_dielectric yes cont_score_dielectric 4.0 cont_score_vdw_scale 1.0 cont_score_es_scale 1.0 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 1.0 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 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 6ME2.virtual_screen.min write_orientations no num_scored_conformers 1 rank_ligands no
Once you finish save and exit that file and then we can start to write the submit file. Vi into cartmin.sh and write the following to that file:
#!/bin/bash #SBATCH --time=48:00:00 #SBATCH --nodes=1 #SBATCH --ntasks=28 #SBATCH --job-name=mpi_6ME2_VS_AR #SBATCH --output=6ME2_VS_mpi.out #SBATCH -p long-28core
cd $SLURM_SUBMIT_DIR
mpirun -np 28 /gpfs/projects/AMS536/zzz.programs/dock6.9_release/bin/dock6.mpi -i cartmin.in -o cartmin.out
We are using mpi again to speed up the energy minimization, so if you choose to adjust the number of nodes being used to speed it up even further, adjust the file accordingly as mentioned in the virtual screen using MPI section. Once you are happy with the submit file, you can start it by typing the following command into the terminal:
sbatch cartmin.sh
Once this finishes running, check the output files to make sure everything ran smoothly. Once that is done, we can now move to rescore these molecules and then visualize them.
Rescoring Docked Molecules
Now that we have minimized all the molecules docked in the virtual screen, we can rescore them based on their new conformations. In order to do this, change directories to 008_rescore. We will need to start by creating the input and submit files, so vi into rescore.in and write the following to that file:
conformer_search_type rigid use_internal_energy yes internal_energy_rep_exp 12 internal_energy_cutoff 100 ligand_atom_file ../007_cartesian_min/6ME2.virtual_screen.min_scored.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 no 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/6ME2.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/6ME2.receptor_wH.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/6ME2.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 .7071 descriptor_fms_score_max_score 20 descriptor_hms_score_ref_filename ../004_dock/6ME2.lig.min_scored.mol2 descriptor_hms_score_matching_coeff -5 descriptor_hms_score_rmsd_coeff 1 descriptor_volume_score_reference_mol2_filename ../004_dock/6ME2.lig.min_scored.mol2 descriptor_volume_score_overlap_compute_method analytical descriptor_weight_fps_score 1 descriptor_weight_pharmacophore_score 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 you have finished, save and exit the file. Then vi rescore.sh and write the following to that file:
#!/bin/sh #SBATCH --partition=long-28core #SBATCH --time=48:00:00 #SBATCH --nodes=1 #SBATCH --ntasks=28 #SBATCH --job-name=6ME2-rescore #SBATCH --output=%x-%j.o
echo "starting DOCK6.9 Simulation" module load intel/mpi/64/2018/18.0.3
mpirun -np 28 dock6.mpi -i rescore.in -o rescore.out echo "done"
Again, we are using mpi so if you want to speed things up use for than one node and then adjust the submit file accordingly. Once you have finished, save and exit the file. Submit the job to the queue as described above. Once this has finished, check your input files to make sure everything ran smoothly. You will have generated multiple files named rescore.out.x, but every molecule described in the output files can also be found in the descriptor.output_scored.mol2 file.
Now, we can properly visualize the minimized and rescored molecules. Transfer the descriptor.output_scored.mol2 file to your computer and open Chimera. Load into Chimera the ligand and receptor files (6ME2.receptor_wH.mol2 and 6ME2.ligand_wH.mol2). Additionally, load in the the gridbox generated in showbox (6ME2.gridbox.pdb). Your screen should look as follows:
Now, using DockView as described above: load in the descriptor.output_scored.mol2 file and begin moving through different ligands one at a time. Which ligands have the highest molecular weight, or the best score from DOCK? Using the ViewDock panel, go to (Column -> Show -> Molecular Weight) and a new column will appear in the panel which you can use to sort the molecules on any number of properties listed in that submenu. Once you have finished analyzing your different ligands, you have finished this part of the DOCK tutorial for 6ME2. Congratulations!
