DISI - User contributions [en]

How to do parameter scanning

2020-05-29T18:02:29Z

Rstein:

== Manually Generating ES/LD Combinations ==

written by Reed Stein, updated 12/2019 so users can specify different low dielectric and ligand desolvation sphere radii

To generate different sized low dielectric and ligand desolvation thin sphere combinations, you must first run blastermaster on your protein/ligand of interest. Once this is finished, make a new directory. Change into the new directory
and run the following command:

python ~rstein/zzz.scripts/DOCK_prep_scripts/new_0001_generate_ES_LD_generation.py -p {FULL_ORIGINAL_BLASTERMASTER_PATH}

The full path to your original blastermaster path is the only required argument. However, you can modify other default values including:
1) Radius of low dielectric spheres you want to run: use the -es flag.
Default radius for electrostatic spheres is [1.0, 1.3, 1.5, 1.7, 1.9]
2) Radius of ligand desolvation spheres you want to run: use the -ld flag.
Default radius for ligand desolvation spheres is [0.1, 0.2, 0.3, 0.4, 0.5]
3) DMS density: use the -d flag. Default is 10.0 to ensure that the surface is sufficiently coated with spheres when using
a smaller sphere radii (typically <0.5 Å). This can be reduced to 1.0 if only larger sphere radii are used.
4) Distance from crystallographic ligand: use the -xd flag. Default is 2 Å.

If you wanted to change all, you could use:

python ~rstein/zzz.scripts/DOCK_prep_scripts/new_0001_generate_ES_LD_generation.py -p {FULL_ORIGINAL_BLASTERMASTER_PATH}
-es 1.1 1.2 1.3 -ld 0.1 0.3 -d 10 -xd 4

This script will submit ligand desolvation jobs to the queue. This should take 15-30 minutes. Once finished, check your spheres and grids by following the steps here:

http://wiki.docking.org/index.php/Protein_Target_Preparation_Updated

Then run the following script to combine the ES/LD grids in all combinations:

python ~rstein/zzz.scripts/DOCK_prep_scripts/new_0002_combine_es_ld_grids_into_combos.py -p {FULL_ORIGINAL_BLASTERMASTER_PATH}

This will create a new directory called "combo_directories" with docking-ready directories inside. The directories will have the name format "es_{ES_sphere_radius}_ld_{LD_sphere_radius}". "def" refers to grids taken from your {FULL_ORIGINAL_BLASTERMASTER_PATH} directory.

These directories are now ready for docking.

== Blastermaster Parameter Scanning ==

Written by Jiankun Lyu, 2017/01/18

4/16/2019 - this needs to be updated and will result in discontinuous thin spheres at low radii!
Use the tutorial above instead. Or use this link to run blastermaster manually:

http://wiki.docking.org/index.php/Using_thin_spheres_in_DOCK3.7

The hierarchy of the directories:

thin_spheres_parameter_scanning----- std_dockprep
|
|------ dockfiles
| |
| |----- working
| |
| ------ rec.pdb, xtal-lig.pdb, INDOCK and other files generated balstermaster.py
|
------- script ------ dockprep_thin_spheres_in_batches.csh
|
|------ submit_dockprep_thin_spheres.csh
|
|------ dockprep_thin_spheres.csh
|
|------ lig-decoy_enrichment.csh
|
|------ combineScoresAndPoses.csh
|
|------ AUCplot_of-lig-decoys.csh
|
|------ mk_matrix_logAUC.py
|
|------ sph_lib.py
|
|------ pdb_lib.py
|
------- close_sph.py

1) Make those directories above.
mkdir thin_spheres_parameter_scanning
cd thin_spheres_parameter_scanning
mkdir std_dockprep
mkdir script

2) Run blastermaster.py in std_dockprep. This will generate two directories: working and dockfiles

3) Download sph_lib.py, pdb_lib.py and close_sph.py files into the script directory
cd script
curl http://docking.org/~tbalius/code/for_dock_3.7/sph_lib.py > sph_lib.py
curl http://docking.org/~tbalius/code/for_dock_3.7/pdb_lib.py > pdb_lib.py
curl http://docking.org/~tbalius/code/for_dock_3.7/close_sph.py > close_sph.py

4) Copy scripts from my path, and modify as necessary.

cd script

cp /mnt/nfs/ex5/work/jklyu/large_scale_docking/DRD2/struct_20180322/A122I_add_polarH_mini_HID/thin_spheres_parameter_scanning/scripts/*dockprep* .

cp /mnt/nfs/reshwork/jklyu/D2R/scripts/lig-decoy_enrichment_submit.csh .
cp /mnt/nfs/reshwork/jklyu/D2R/scripts/combineScoresAndPoses.csh .
cp /mnt/nfs/reshwork/jklyu/D2R/scripts/mk_matrix_logAUC.py .

5) Run parameter scanning.
cd ../ # go back to thin_spheres_parameter_scanning folder
csh /path/to/script/dockprep_thin_spheres_in_batches.csh /path/to/script/ /path/to/std_dockprep

Note:- you can edit dockprep_thin_spheres_in_batches.csh to include more CPUs in Job Bound

6) make the following subfolders

mkdir ligands-decoys
cd ligands-decoys
mkdir ligands
mkdir decoys

now copy your decoys.db2.gz to decoys
now copy your ligands.db2.gz to ligands
now copy decoys.smi to the folder
now copy ligands.smi to the folder

7) Submit DOCK and enrichment calculation.
csh /path/to/script/lig-decoy_enrichment.csh

8) Combine and analyze the docking results.
csh /path/to/script/combineScoresAndPoses.csh #1st change the path inside the script to your own dir
csh /path/to/script/AUCplot_of-lig-decoys.csh #1st change the path inside the script to your own dir

9) Visualize the logAUC by heatmap.
python /path/to/script/mk_matrix_logAUC.py

2020-05-21T18:24:11Z

Rstein: /* Prepare Receptor */

= About =

DOCK 3.7 the current version in the [[DOCK 3]] series of docking programs developed and used by the [[Shoichet Lab]]. Please read and cite the DOCK 3.7 paper
[http://www.plosone.org/article/info:doi/10.1371/journal.pone.0075992 Coleman, Carchia, Sterling, Irwin & Shoichet, PLOS ONE 2013.]

DOCK 3.7 is written in Fortran and some C. It is an update of [[DOCK 3.6]] with many improved features. DOCK 3.7 comes with all the tools necessary to prepare a
protein for docking and some tools necessary to build ligands, though some tools must be obtained externally. It uses new Flexibase/DB2 files found in [[ZINC15]]. It includes tools to prepare receptors, and several auxiliary scripts.

DOCK 3.7 is available at [http://dock.compbio.ucsf.edu/DOCK3.7/ http://dock.compbio.ucsf.edu/DOCK3.7/].

{{TOCright}}

= Start here =
* [[So you want to set up a lab]] - only if you don't already have hardware ready.
* [[Install DOCK 3.7]]
* [[DOCK 3.7 2014/09/25 FXa Tutorial]]
* [[DOCK 3.7 2015/04/15 abl1 Tutorial]] superseded
* [[DOCK 3.7 2018/06/05 abl1 Tutorial]]
* [[DOCK 3.7 2016/09/16 Tutorial for Enrichment Calculations (Trent & Jiankun)]]
* [[DOCK 3.7 tutorial (Anat)]]
* [[DOCK 3.7 with GIST tutorials]]
* [[DOCK 3.7 tutorial based on Webinar 2017/06/28]]
* [[Getting started with DOCK 3.7]]
* [[Blastermaster]] - Prepare input for and then run [[DOCK 3.7]].
* [[Ligand preparation 3.7]] - Create dockable databases for [[DOCK 3.7]].
* [[Ligand preparation]] - different version.
* [[Ligand prep Irwin Nov 2016]] - John's current version
* [[Mol2db2 Format 2]] - details on the database formate.
* [[Running docking 3.7]] - how to actually run docking.
* [[DOCK 3.7 Development]] - for software developers
* [[prepare a receptor with a cofactor for docking]]
=== For DOCKovalent, start here ===
* [[DOCKovalent_3.7]]
* [[DOCKovalent lysine inhibitor design tutorial]]
* [[DOCKovalent cysteine inhibitor design tutorial]]

= Prepare Receptor =
* [[Protein Target Preparation]]
* [[Protein Target Preparation Updated]]
* [[Using_thin_spheres_in_DOCK3.7]]
*[[Matching Sphere Scan]]
*[[Removing Spheres (The Chase Method)]]
* [[Adding Static Waters to the Protein Structure]]
* [[Flexible Docking]]
* [[Visualize docking grids]]
* [[Minimize protein-ligand complex with AMBER]]
* [[Minimize protein-covalent ligand complex with AMBER]]

= Prepare Screening Library =
* [[mol2db2]] is the program that creates [[mol2db2 format]] database files which are read by [[DOCK 3.7]]
* [[ligand preparation 3.7]]
* [[generating decoys (Reed's way)]]
* [[generating extrema set]]

= Running Docking =
* [[Running docking 3.7]] - JJI currently working on this.
* [[Running DOCK 3.7]] - this seems to be slightly dated.
* [[INDOCK 3.7]] - file format used by [[DOCK 3.7]]
* [[DOCK3.7_INDOCK_Minimization_Parameter]] - How to run DOCK 3.7.1rc1 (and latter versions) with the minimization.
* Interpreting the [[OUTDOCK 3.7]] file.

= Analysis =
* [[Analyzing DOCK Results]]
* [http://autodude.docking.org/ Auto-DUD-E Test Set] (external site)
* [[Other Useful Stuff]]
* [[Bootstrap AUC]]
* [[another getposes.py]]
* [[Converting SMILES to Kekule Format]]
* Viewing results using [[ViewDock]]

= Post Docking Clustering=
* [[How to process results from a large-scale docking]]
* [[Large-scale SMILES Requesting and Fingerprints Converting]]
* [[ECFP4 Best First Clustering]]
* [[Bemis-Murcko Scaffold Analysis]]

= Post Docking Filters=
* [[Large-scale TC Calculations]]
* [[Whole Library TC to Knowns Calculations]]
* [[Filtering ligands for novelty]]
* [[Strain Filtering]]
* [[Interaction Filtering]]
* [[Torsion against CSD visualize with Maestro]]

= Redocking with Enhanced Sampling =
*[[Sample Additional Ring Puckers ]]
= Rescoring =
*[[Rescoring_with_DOCK_3.7]]

= Available Libraries =
* [[ZINC Subset DB2 file locations]]
* how to get db2 files from zinc15.docking.org

= Analog by Catalog=
* [[Substructure searching]]
* [[TC analog searching in ZINC]]

= Previous verisons and compatibility =
DOCK 3.7 is part of the [[DOCK 3]] series. It differs substantially from its immediate predecessor [[DOCK 3.6]],
which uses a different format of database files that cannot be read by [[DOCK 3.7]], and vice versa.

= How to Cite =
To cite the DOCK 3.7 paper, please use
[http://www.plosone.org/article/info:doi/10.1371/journal.pone.0075992 Coleman, Carchia, Sterling, Irwin & Shoichet, PLOS ONE 2013.]

= How to Download =
DOCK 3.7 is available at [http://dock.compbio.ucsf.edu/DOCK3.7/ http://dock.compbio.ucsf.edu/DOCK3.7/].

= Implementation =
DOCK 3.7 is written in Fortran and some C. Scripts are mostly in [[python]] and [[perl]].

{{Template:CC-BY-SA-30}}
{{Template:Coleman}}

[[Category:DOCK 3.7]]
[[Category:Software]]
[[Category:Freecom]]

Generating decoys (Reed's way)

2020-05-19T01:23:34Z

Rstein:

Written by Reed Stein on April 3, 2018.

updated 5/3/2019

updated 8/15/2019

updated 3/6/2020

updated 5/18/2020

This pipeline will generate property-matched decoys for a set of ligand SMILES. To build ligands yourself, see "ligand prep" in:
http://wiki.docking.org/index.php/DOCK_3.7_tutorial_%28Anat%29

All scripts for this tutorial can be found in:
/mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/

Before running any scripts, make sure to source the current version of Python
source /nfs/soft/python/envs/complete/current/env.csh

Additionally, JChem needs to be sourced in your ~/.cshrc file with the command:
source /nfs/soft/jchem/current/env.csh

== Querying ZINC for Protomers ==

This procedure generates decoys for your input ligands by searching through 3D conformers that are already built in ZINC. This procedure is advised if you want decoys to be charge-matched to ligands.

=== Step 1) Setting up directories for Protomers ===

Before starting, you need a SMILES file with the format (SMILES first, unique ID second):
S(Nc1c(O)cc(C(=O)O)cc1)(c2c(scc2)C(=O)O)(=O)=O 116

You also need an input file named "decoy_generation.in" with the following lines:

PROTONATE YES
MWT 0 125
LOGP 0 3.6
RB 0 5
HBA 0 4
HBD 0 3
CHARGE 0 2
LIGAND TC RANGE 0.0 0.35
MINIMUM DECOYS PER LIGAND 20
DECOYS PER LIGAND 50
MAXIMUM TC BETWEEN DECOYS 0.8
TANIMOTO YES

If your input ligand SMILES file is already protonated as you want it, set "PROTONATE NO".

If you want your input ligand SMILES protonated, only protomer SMILES with unique properties will be kept for generating decoys. Therefore, if you have one ligand that exists in 4 tautomers, all of which have identical molecular weight, cLogP, # rotatable bonds, # H-bond acceptors and donors, and net charge, only one will be maintained for decoy matching. This doesn't apply if you set "PROTONATE NO".

This file specifies that for each ligand protomer, at least 20 decoys will be retrieved with the following properties:
- within +/- 125 Daltons
- within +/- 3.6 logP
- within +/- 5 rotatable bonds
- within +/- 4 hydrogen bond acceptors
- within +/- 3 hydrogen bond donors
- within +/- 2 charge
- 0.35 or less Tanimoto
- minimum 20 decoys per ligand protomer, if available
- preferred 50 decoys per ligand protomer, if available
- the maximum TC between decoy molecules should be 0.8
- "TANIMOTO" refers to whether a Tanimoto calculation should be performed - see step 3 for when this is necessary

These are arbitrary, and you can input your desired minimum and maximum values that decoys can differ by, relative to the ligands.

Once you have created this file, run the following command to create the decoy generation directory:

python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0000_protonate_setup_dirs.py {SMILES_FILE} {NEW_DIR_NAME}

Provide a directory name that you want in place of {NEW_DIR_NAME}. This will create the directory with subdirectories named
"ligand_${number}" for each of the ligands in the SMILES file you input.

=== Step 2) Retrieving protomer decoys from ZINC15 ===

If you have edited the "decoy_generation.in" file which is now located in {NEW_DIR_NAME} as you want, you can run the following command:

python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0001_qsub_generate_decoys.py {NEW_DIR_NAME}

This should take 15 minutes to an hour, depending on how many ligands you input.

=== Step 3) Assigning accepted protomer decoys to each ligand protomer ===

We can assign the property-matched decoys to the ligand protomers. Make sure you have the "decoy_generation_input.in" file from before in {NEW_DIR_NAME}.

To filter the decoys, run the following command:
python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0002_qsub_filter_decoys.py {NEW_DIR_NAME}

This will run on the queue. A log file called "FILTER_DECOYS.log" will be generated in {NEW_DIR_NAME} with information and any errors.

If you don't get enough decoys, the "decoy_generation.in" file can be modified by changing "MAXIMUM TC BETWEEN DECOYS", "MINIMUM DECOYS PER LIGAND", etc.
To not run the time-consuming Tanimoto calculation between all decoys again, simply add/change this in the "decoy_generation.in" file:

TANIMOTO NO

If you set Tanimoto to "NO", make sure that your {NEW_DIR_NAME} still has the original files:

"test_ligdecoy_smiles.smi"
"cluster_head.list"

Otherwise, this step will not run.

If these original files still remain, this will skip the Tanimoto calculation step, and filter property matched decoys based on the new parameters in the "decoy_generation.in" file.

If this has completed successfully, you should see files in your {NEW_DIR_NAME} with the format "{LIGAND_ID}_final_property_matched_decoys.txt". These files contain the ligands and their properties, as well as property-matched decoys that have been assigned to them. These files have the format "SMILES", "ZINC ID", "logP", "#Rotatable Bonds", "# Hydrogen Bond Donors", "# Hydrogen Bond Acceptors", "Charge", "Protomer SMILES", and "Tanimoto Coefficient to Ligand".

There should also be files with the format "{LIGAND_ID}_replacements.txt", which include extra property-matched decoys that were assigned to that ligand.

If you still cannot get enough decoys for your ligands, consider reducing the number of ligands you have by clustering, for example, or using the SMILES decoy generation below, which is not limited to only molecules that are already built in ZINC15.

=== Step 4) Copying decoy .db2.gz files into your directories ===

To copy property-matched decoys into your own directory of choice, run the following command:

python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0003_copy_decoys_to_new_dir.py {NEW_DIR_NAME} {COPY_TO_DIR}

where {COPY_TO_DIR} is a new directory that will be created where your decoys will be copied into. In this directory, two subdirectories will be created:
"ligands" - this includes the input ligands for which there are X number property matched decoys (these are all ligands with "{LIGAND_ID}_final_property_matched_decoys.txt" files in {NEW_DIR_NAME})
"decoys" - this will include the decoy .db2.gz files for docking and "decoys.smi" which contains all the SMILES strings for property matched decoys

IMPORTANT: It is possible that all of your ligand protomers were not matched to property-matched decoys. The "ligands.smi" file in {COPY_TO_DIR} will not include these. Make
sure you do not dock these if you calculate enrichment values.

== Querying ZINC for SMILES ==

This procedure generates decoys for your input ligand SMILES by finding decoy SMILES in ZINC that are property-matched. This procedure will provide decoy SMILES that you can build yourself into 3D models for docking. If you would like to query ZINC for decoy SMILES so that you can build decoys yourself or if your ligands are >400 Da, start here. If not, go to "Querying ZINC for Protomers" to generate decoys that already have 3D models.

=== Step 1) Setting up SMILES directory ===

Before starting, you need a SMILES file with the format (SMILES first, ID second):
S(Nc1c(O)cc(C(=O)O)cc1)(c2c(scc2)C(=O)O)(=O)=O 116

You also need an input file named "decoy_generation.in" with the following lines:

SMILES YES
PROTONATE YES
MWT 0 125
LOGP 0 3.6
RB 0 5
HBA 0 4
HBD 0 3
CHARGE 0 2
LIGAND TC RANGE 0.0 0.35
MINIMUM DECOYS PER LIGAND 20
DECOYS PER LIGAND 50
MAXIMUM TC BETWEEN DECOYS 0.8
TANIMOTO YES
GENERATE DECOYS 750

If your input ligand SMILES file is already protonated as you want it, set "PROTONATE NO". "SMILES" tells the function you want to query ZINC for SMILES, not built protomers.

This file specifies that for each ligand protomer, {MINIMUM DECOYS PER LIGAND} to {DECOYS PER LIGAND} decoys will be retrieved with the following properties:
- within +/- 125 Daltons
- within +/- 3.6 logP
- within +/- 5 rotatable bonds
- within +/- 4 hydrogen bond acceptors
- within +/- 3 hydrogen bond donors
- within +/- 2 charge
- 0.35 or less Tanimoto

"GENERATE DECOYS" specifies how many potential decoys you want to check for property matching with your ligands. A smaller number results in faster decoy generation, but a smaller pool of potential decoys to compare your ligand against. A larger number results in slower decoy generation, and greater likelihood of property-matched decoys for all your ligands.

As with protomers, "MINIMUM DECOYS PER LIGAND" refers to the minimum number of decoys you want for each ligand protomer;

"DECOYS PER LIGAND" refers to your preferred number of decoys for each ligand protomer;

"MAXIMUM TC BETWEEN DECOYS" refers to the maximum Tc allowed between decoys (the lower, the more dissimilar your decoys will be);

and "TANIMOTO" refers to whether the ligand-decoy full Tc matrix should be calculated - this must be done at least once and should not be set to "NO" unless you are re-running step 3.

These are arbitrary, and you can input your desired minimum and maximum values that decoys can differ by, relative to the ligands.

Once you have created this file, run the following command to create the decoy generation directory:

python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0000_protonate_setup_dirs.py {SMILES_FILE} {NEW_DIR_NAME}

Provide a directory name that you want in place of {NEW_DIR_NAME}. This will create the directory with subdirectories named
"ligand_${number}" for each of the ligands in the SMILES file you input.

=== Step 2) Retrieving SMILES decoys from ZINC15 ===

If you have edited the "decoy_generation.in" file which is now located in {NEW_DIR_NAME} as you want, you can run the following command:

python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0001_qsub_generate_decoys.py {NEW_DIR_NAME}

Jobs will run for 15 minutes to 1-2 hours depending on how many ligands you input.

=== Step 3) Assigning decoys to ligands ===

To assign property matched decoys to your ligand protomers, run the following command:

python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0002_qsub_filter_decoys.py {NEW_DIR_NAME}

This will run on the queue. As with "Querying ZINC for Protomers":

If you don't get enough decoys, the "decoy_generation.in" file can be modified by changing "MAXIMUM TC BETWEEN DECOYS", "MINIMUM DECOYS PER LIGAND", etc.
To not run the time-consuming Tanimoto calculation between all ligands and decoys again, simply add/change this in the "decoy_generation.in" file:

TANIMOTO NO

If you set Tanimoto to "NO", make sure that your {NEW_DIR_NAME} still has the original files:

"test_ligdecoy_smiles.smi"
"cluster_head.list"

Otherwise, this step will not run.

If these original files still remain, this will skip the Tanimoto calculation step, and filter property matched decoys based on the new parameters in the "decoy_generation.in" file.

If this has completed successfully, you should see files in your {NEW_DIR_NAME} with the format "{LIGAND_ID}_final_property_matched_decoys.txt". These files have the format "SMILES", "ZINC ID", "logP", "#Rotatable Bonds", "# Hydrogen Bond Donors", "# Hydrogen Bond Acceptors", "Charge", "Protomer ID", and "Tanimoto Coefficient to Ligand".

These files contain the ligands and their properties, as well as property-matched decoys that have been assigned to them. There should also be files with the format "{LIGAND_ID}_replacements.txt", which include extra property-matched decoys that were assigned to that ligand.

=== Step 4) Setting up ligand/decoy directories for building SMILES ===

If you have queried ZINC for SMILES, you need to build the decoys yourself. To write the SMILES file, run the following command:

python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0003b_write_out_ligands_decoys.py {NEW_DIR_NAME} {COPY_TO_DIR}

This will create {COPY_TO_DIR} with two subdirectories, "ligands" and "decoys" as well as SMILES files for:

ligands.smi - this includes the input ligands for which there are X number property matched decoys (these are all ligands with "{LIGAND_ID}_final_property_matched_decoys.txt" files in {NEW_DIR_NAME})
decoys.smi - this includes the canonicalized property-matched decoy SMILES
decoy_protomers.smi - this includes the actual property-matched decoy protomer SMILES

SMILES for decoys can now be built.

For decoy building, use the following command:

setenv DOCKBASE /nfs/soft/dock/versions/dock37/DOCK-3.7-trunk
source /nfs/soft/dock/versions/dock37/DOCK-3.7-trunk/env.csh
${DOCKBASE}/ligand/generate/build_database_ligand.sh -H $ph decoy_protomers.smi --pre-tautomerized --no-db

If not all decoys successfully build, more property matched decoys can be taken from the "{LIGAND_ID}_replacements.txt" files. Additionally, you can build decoys without the --pre-tautomerized flag:

${DOCKBASE}/ligand/generate/build_database_ligand.sh -H $ph decoys.smi --no-db

This will produce all protomers of each decoy, including the property-matched decoy protomer.

== Visualizing Decoy Properties ==
=== Visualizing property distributions ===

To visualize the distributions of molecular properties of matched decoys relative to the ligands, run the following command:
python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0004_plot_properties.py {NEW_DIR_NAME}

There will be 6 images in {NEW_DIR_NAME} for molecular weight, logP, number of rotatable bonds, number of hydrogen bond donors, number of hydrogen bond acceptors, and net charge of ligands and decoys.

=== Visualizing decoy Tanimotos to ligands ===

To visualize how different the matched decoys are to the input ligands, run the following command:
python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0005_plot_tanimoto_to_lig.py {NEW_DIR_NAME}

There will be a box and whisker plot image in {NEW_DIR_NAME} showing the Tanimotos calculated between each ligand and all decoys.

Generating decoys (DUDE-Z)

2020-05-15T19:18:55Z

Rstein: Blanked the page

Blah

2020-05-15T19:18:28Z

Rstein: Blanked the page

Generating Decoys (DUDE-Z)

2020-05-15T19:18:11Z

Rstein: Blanked the page

DOCK 3.7

2020-05-15T19:17:16Z

Rstein: /* Prepare Screening Library */

= About =

DOCK 3.7 the current version in the [[DOCK 3]] series of docking programs developed and used by the [[Shoichet Lab]]. Please read and cite the DOCK 3.7 paper
[http://www.plosone.org/article/info:doi/10.1371/journal.pone.0075992 Coleman, Carchia, Sterling, Irwin & Shoichet, PLOS ONE 2013.]

DOCK 3.7 is written in Fortran and some C. It is an update of [[DOCK 3.6]] with many improved features. DOCK 3.7 comes with all the tools necessary to prepare a
protein for docking and some tools necessary to build ligands, though some tools must be obtained externally. It uses new Flexibase/DB2 files found in [[ZINC15]]. It includes tools to prepare receptors, and several auxiliary scripts.

DOCK 3.7 is available at [http://dock.compbio.ucsf.edu/DOCK3.7/ http://dock.compbio.ucsf.edu/DOCK3.7/].

{{TOCright}}

= Start here =
* [[So you want to set up a lab]] - only if you don't already have hardware ready.
* [[Install DOCK 3.7]]
* [[DOCK 3.7 2014/09/25 FXa Tutorial]]
* [[DOCK 3.7 2015/04/15 abl1 Tutorial]] superseded
* [[DOCK 3.7 2018/06/05 abl1 Tutorial]]
* [[DOCK 3.7 2016/09/16 Tutorial for Enrichment Calculations (Trent & Jiankun)]]
* [[DOCK 3.7 tutorial (Anat)]]
* [[DOCK 3.7 with GIST tutorials]]
* [[DOCK 3.7 tutorial based on Webinar 2017/06/28]]
* [[Getting started with DOCK 3.7]]
* [[Blastermaster]] - Prepare input for and then run [[DOCK 3.7]].
* [[Ligand preparation 3.7]] - Create dockable databases for [[DOCK 3.7]].
* [[Ligand preparation]] - different version.
* [[Ligand prep Irwin Nov 2016]] - John's current version
* [[Mol2db2 Format 2]] - details on the database formate.
* [[Running docking 3.7]] - how to actually run docking.
* [[DOCK 3.7 Development]] - for software developers
* [[prepare a receptor with a cofactor for docking]]
=== For DOCKovalent, start here ===
* [[DOCKovalent_3.7]]
* [[DOCKovalent lysine inhibitor design tutorial]]
* [[DOCKovalent cysteine inhibitor design tutorial]]

= Prepare Receptor =
* [[Protein Target Preparation]]
* [[Protein Target Preparation Updated]]
* [[Using_thin_spheres_in_DOCK3.7]]
*[[Matching Sphere Scan]]
* [[Adding Static Waters to the Protein Structure]]
* [[Flexible Docking]]
* [[Visualize docking grids]]
* [[Minimize protein-ligand complex with AMBER]]
* [[Minimize protein-covalent ligand complex with AMBER]]

= Prepare Screening Library =
* [[mol2db2]] is the program that creates [[mol2db2 format]] database files which are read by [[DOCK 3.7]]
* [[ligand preparation 3.7]]
* [[generating decoys (Reed's way)]]
* [[generating extrema set]]

= Running Docking =
* [[Running docking 3.7]] - JJI currently working on this.
* [[Running DOCK 3.7]] - this seems to be slightly dated.
* [[INDOCK 3.7]] - file format used by [[DOCK 3.7]]
* [[DOCK3.7_INDOCK_Minimization_Parameter]] - How to run DOCK 3.7.1rc1 (and latter versions) with the minimization.
* Interpreting the [[OUTDOCK 3.7]] file.

= Analysis =
* [[Analyzing DOCK Results]]
* [http://autodude.docking.org/ Auto-DUD-E Test Set] (external site)
* [[Other Useful Stuff]]
* [[Bootstrap AUC]]
* [[another getposes.py]]
* [[Converting SMILES to Kekule Format]]
* Viewing results using [[ViewDock]]

= Post Docking Clustering=
* [[How to process results from a large-scale docking]]
* [[Large-scale SMILES Requesting and Fingerprints Converting]]
* [[ECFP4 Best First Clustering]]
* [[Bemis-Murcko Scaffold Analysis]]

= Post Docking Filters=
* [[Large-scale TC Calculations]]
* [[Whole Library TC to Knowns Calculations]]
* [[Filtering ligands for novelty]]
* [[Strain Filtering]]
* [[Interaction Filtering]]
* [[Torsion against CSD visualize with Maestro]]

= Redocking with Enhanced Sampling =
*[[Sample Additional Ring Puckers ]]
= Rescoring =
*[[Rescoring_with_DOCK_3.7]]

= Available Libraries =
* [[ZINC Subset DB2 file locations]]
* how to get db2 files from zinc15.docking.org

= Analog by Catalog=
* [[Substructure searching]]
* [[TC analog searching in ZINC]]

= Previous verisons and compatibility =
DOCK 3.7 is part of the [[DOCK 3]] series. It differs substantially from its immediate predecessor [[DOCK 3.6]],
which uses a different format of database files that cannot be read by [[DOCK 3.7]], and vice versa.

= How to Cite =
To cite the DOCK 3.7 paper, please use
[http://www.plosone.org/article/info:doi/10.1371/journal.pone.0075992 Coleman, Carchia, Sterling, Irwin & Shoichet, PLOS ONE 2013.]

= How to Download =
DOCK 3.7 is available at [http://dock.compbio.ucsf.edu/DOCK3.7/ http://dock.compbio.ucsf.edu/DOCK3.7/].

= Implementation =
DOCK 3.7 is written in Fortran and some C. Scripts are mostly in [[python]] and [[perl]].

{{Template:CC-BY-SA-30}}
{{Template:Coleman}}

[[Category:DOCK 3.7]]
[[Category:Software]]
[[Category:Freecom]]

Blah

2020-05-15T19:15:26Z

Rstein: Rstein moved page Blah to Generating Decoys (DUDE-Z)

#REDIRECT [[Generating Decoys (DUDE-Z)]]

Generating Decoys (DUDE-Z)

2020-05-15T19:15:26Z

Rstein: Rstein moved page Blah to Generating Decoys (DUDE-Z)

Written by Reed Stein on April 3, 2018.

updated 5/3/2019

updated 8/15/2019

updated 3/6/2020

This pipeline will generate property-matched decoys for a set of ligand SMILES. To build ligands yourself, see "ligand prep" in:
http://wiki.docking.org/index.php/DOCK_3.7_tutorial_%28Anat%29

All scripts for this tutorial can be found in:
/mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/

Before running any scripts, make sure to source the current version of Python
source /nfs/soft/python/envs/complete/current/env.csh

Additionally, JChem needs to be sourced in your ~/.cshrc file with the command:
source /nfs/soft/jchem/current/env.csh

== Querying ZINC for Protomers ==

This procedure generates decoys for your input ligands by searching through 3D conformers that are already built in ZINC. This procedure is advised if you want decoys to be charge-matched to ligands.

=== Step 1) Setting up directories for Protomers ===

Before starting, you need a SMILES file with the format (SMILES first, ID second):
S(Nc1c(O)cc(C(=O)O)cc1)(c2c(scc2)C(=O)O)(=O)=O 116

You also need an input file named "decoy_generation.in" with the following lines:

PROTONATE YES
MWT 0 125
LOGP 0 3.6
RB 0 5
HBA 0 4
HBD 0 3
CHARGE 0 2
LIGAND TC RANGE 0.0 0.35
MINIMUM DECOYS PER LIGAND 20
DECOYS PER LIGAND 50
MAXIMUM TC BETWEEN DECOYS 0.8
TANIMOTO YES

If your input ligand SMILES file is already protonated as you want it, set "PROTONATE NO".

This file specifies that for each ligand protomer, at least 20 decoys will be retrieved with the following properties:
- within +/- 125 Daltons
- within +/- 3.6 logP
- within +/- 5 rotatable bonds
- within +/- 4 hydrogen bond acceptors
- within +/- 3 hydrogen bond donors
- within +/- 2 charge
- 0.35 or less Tanimoto
- minimum 20 decoys per ligand protomer, if available
- preferred 50 decoys per ligand protomer, if available
- the maximum TC between decoy molecules should be 0.8
- "TANIMOTO" refers to whether a Tanimoto calculation should be performed - see step 3 for when this is necessary

These are arbitrary, and you can input your desired minimum and maximum values that decoys can differ by, relative to the ligands.

Once you have created this file, run the following command to create the decoy generation directory:

python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0000_protonate_setup_dirs.py {SMILES_FILE} {NEW_DIR_NAME}

Provide a directory name that you want in place of {NEW_DIR_NAME}. This will create the directory with subdirectories named
"ligand_${number}" for each of the ligands in the SMILES file you input.

=== Step 2) Retrieving protomer decoys from ZINC15 ===

If you have edited the "decoy_generation.in" file which is now located in {NEW_DIR_NAME} as you want, you can run the following command:

python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0001_qsub_generate_decoys.py {NEW_DIR_NAME}

This should take 15 minutes to an hour, depending on how many ligands you input.

=== Step 3) Assigning accepted protomer decoys to each ligand protomer ===

We can assign the property-matched decoys to the ligand protomers. Make sure you have the "decoy_generation_input.in" file from before in {NEW_DIR_NAME}.

To filter the decoys, run the following command:
python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0002_qsub_filter_decoys.py {NEW_DIR_NAME}

This will run on the queue. A log file called "FILTER_DECOYS.log" will be generated in {NEW_DIR_NAME} with information and any errors.

If you don't get enough decoys, the "decoy_generation.in" file can be modified by changing "MAXIMUM TC BETWEEN DECOYS", "MINIMUM DECOYS PER LIGAND", etc.
To not run the time-consuming Tanimoto calculation between all decoys again, simply add/change this in the "decoy_generation.in" file:

TANIMOTO NO

If you set Tanimoto to "NO", make sure that your {NEW_DIR_NAME} still has the original files:

"test_ligdecoy_smiles.smi"
"cluster_head.list"

Otherwise, this step will not run.

If these original files still remain, this will skip the Tanimoto calculation step, and filter property matched decoys based on the new parameters in the "decoy_generation.in" file.

If this has completed successfully, you should see files in your {NEW_DIR_NAME} with the format "{LIGAND_ID}_final_property_matched_decoys.txt". These files contain the ligands and their properties, as well as property-matched decoys that have been assigned to them. These files have the format "SMILES", "ZINC ID", "logP", "#Rotatable Bonds", "# Hydrogen Bond Donors", "# Hydrogen Bond Acceptors", "Charge", "Protomer SMILES", and "Tanimoto Coefficient to Ligand".

There should also be files with the format "{LIGAND_ID}_replacements.txt", which include extra property-matched decoys that were assigned to that ligand.

If you still cannot get enough decoys for your ligands, consider reducing the number of ligands you have by clustering, for example, or using the SMILES decoy generation below, which is not limited to only molecules that are already built in ZINC15.

=== Step 4) Copying decoy .db2.gz files into your directories ===

To copy property-matched decoys into your own directory of choice, run the following command:

python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0003_copy_decoys_to_new_dir.py {NEW_DIR_NAME} {COPY_TO_DIR}

where {COPY_TO_DIR} is a new directory that will be created where your decoys will be copied into. In this directory, two subdirectories will be created:
"ligands" - this includes the input ligands for which there are X number property matched decoys (these are all ligands with "{LIGAND_ID}_final_property_matched_decoys.txt" files in {NEW_DIR_NAME})
"decoys" - this will include the decoy .db2.gz files for docking and "decoys.smi" which contains all the SMILES strings for property matched decoys

IMPORTANT: It is possible that all of your ligand protomers were not matched to property-matched decoys. The "ligands.smi" file in {COPY_TO_DIR} will not include these. Make
sure you do not dock these if you calculate enrichment values.

== Querying ZINC for SMILES ==

This procedure generates decoys for your input ligand SMILES by finding decoy SMILES in ZINC that are property-matched. This procedure will provide decoy SMILES that you can build yourself into 3D models for docking. If you would like to query ZINC for decoy SMILES so that you can build decoys yourself or if your ligands are >400 Da, start here. If not, go to "Querying ZINC for Protomers" to generate decoys that already have 3D models.

=== Step 1) Setting up SMILES directory ===

Before starting, you need a SMILES file with the format (SMILES first, ID second):
S(Nc1c(O)cc(C(=O)O)cc1)(c2c(scc2)C(=O)O)(=O)=O 116

You also need an input file named "decoy_generation.in" with the following lines:

SMILES YES
PROTONATE YES
MWT 0 125
LOGP 0 3.6
RB 0 5
HBA 0 4
HBD 0 3
CHARGE 0 2
LIGAND TC RANGE 0.0 0.35
MINIMUM DECOYS PER LIGAND 20
DECOYS PER LIGAND 50
MAXIMUM TC BETWEEN DECOYS 0.8
TANIMOTO YES
GENERATE DECOYS 750

If your input ligand SMILES file is already protonated as you want it, set "PROTONATE NO". "SMILES" tells the function you want to query ZINC for SMILES, not built protomers.

This file specifies that for each ligand protomer, {MINIMUM DECOYS PER LIGAND} to {DECOYS PER LIGAND} decoys will be retrieved with the following properties:
- within +/- 125 Daltons
- within +/- 3.6 logP
- within +/- 5 rotatable bonds
- within +/- 4 hydrogen bond acceptors
- within +/- 3 hydrogen bond donors
- within +/- 2 charge
- 0.35 or less Tanimoto

"GENERATE DECOYS" specifies how many potential decoys you want to check for property matching with your ligands. A smaller number results in faster decoy generation, but a smaller pool of potential decoys to compare your ligand against. A larger number results in slower decoy generation, and greater likelihood of property-matched decoys for all your ligands.

As with protomers, "MINIMUM DECOYS PER LIGAND" refers to the minimum number of decoys you want for each ligand protomer;

"DECOYS PER LIGAND" refers to your preferred number of decoys for each ligand protomer;

"MAXIMUM TC BETWEEN DECOYS" refers to the maximum Tc allowed between decoys (the lower, the more dissimilar your decoys will be);

and "TANIMOTO" refers to whether the ligand-decoy full Tc matrix should be calculated - this must be done at least once and should not be set to "NO" unless you are re-running step 3.

These are arbitrary, and you can input your desired minimum and maximum values that decoys can differ by, relative to the ligands.

Once you have created this file, run the following command to create the decoy generation directory:

python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0000_protonate_setup_dirs.py {SMILES_FILE} {NEW_DIR_NAME}

Provide a directory name that you want in place of {NEW_DIR_NAME}. This will create the directory with subdirectories named
"ligand_${number}" for each of the ligands in the SMILES file you input.

=== Step 2) Retrieving SMILES decoys from ZINC15 ===

If you have edited the "decoy_generation.in" file which is now located in {NEW_DIR_NAME} as you want, you can run the following command:

python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0001_qsub_generate_decoys.py {NEW_DIR_NAME}

Jobs will run for 15 minutes to 1-2 hours depending on how many ligands you input.

=== Step 3) Assigning decoys to ligands ===

To assign property matched decoys to your ligand protomers, run the following command:

python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0002_qsub_filter_decoys.py {NEW_DIR_NAME}

This will run on the queue. As with "Querying ZINC for Protomers":

If you don't get enough decoys, the "decoy_generation.in" file can be modified by changing "MAXIMUM TC BETWEEN DECOYS", "MINIMUM DECOYS PER LIGAND", etc.
To not run the time-consuming Tanimoto calculation between all ligands and decoys again, simply add/change this in the "decoy_generation.in" file:

TANIMOTO NO

If you set Tanimoto to "NO", make sure that your {NEW_DIR_NAME} still has the original files:

"test_ligdecoy_smiles.smi"
"cluster_head.list"

Otherwise, this step will not run.

If these original files still remain, this will skip the Tanimoto calculation step, and filter property matched decoys based on the new parameters in the "decoy_generation.in" file.

If this has completed successfully, you should see files in your {NEW_DIR_NAME} with the format "{LIGAND_ID}_final_property_matched_decoys.txt". These files have the format "SMILES", "ZINC ID", "logP", "#Rotatable Bonds", "# Hydrogen Bond Donors", "# Hydrogen Bond Acceptors", "Charge", "Protomer ID", and "Tanimoto Coefficient to Ligand".

These files contain the ligands and their properties, as well as property-matched decoys that have been assigned to them. There should also be files with the format "{LIGAND_ID}_replacements.txt", which include extra property-matched decoys that were assigned to that ligand.

=== Step 4) Setting up ligand/decoy directories for building SMILES ===

If you have queried ZINC for SMILES, you need to build the decoys yourself. To write the SMILES file, run the following command:

python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0003b_write_out_ligands_decoys.py {NEW_DIR_NAME} {COPY_TO_DIR}

This will create {COPY_TO_DIR} with two subdirectories, "ligands" and "decoys" as well as SMILES files for:

ligands.smi - this includes the input ligands for which there are X number property matched decoys (these are all ligands with "{LIGAND_ID}_final_property_matched_decoys.txt" files in {NEW_DIR_NAME})
decoys.smi - this includes the canonicalized property-matched decoy SMILES
decoy_protomers.smi - this includes the actual property-matched decoy protomer SMILES

SMILES for decoys can now be built.

For decoy building, use the following command:

setenv DOCKBASE /nfs/soft/dock/versions/dock37/DOCK-3.7-trunk
source /nfs/soft/dock/versions/dock37/DOCK-3.7-trunk/env.csh
${DOCKBASE}/ligand/generate/build_database_ligand.sh -H $ph decoy_protomers.smi --pre-tautomerized --no-db

If not all decoys successfully build, more property matched decoys can be taken from the "{LIGAND_ID}_replacements.txt" files. Additionally, you can build decoys without the --pre-tautomerized flag:

${DOCKBASE}/ligand/generate/build_database_ligand.sh -H $ph decoys.smi --no-db

This will produce all protomers of each decoy, including the property-matched decoy protomer.

== Visualizing Decoy Properties ==
=== Visualizing property distributions ===

To visualize the distributions of molecular properties of matched decoys relative to the ligands, run the following command:
python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0004_plot_properties.py {NEW_DIR_NAME}

There will be 6 images in {NEW_DIR_NAME} for molecular weight, logP, number of rotatable bonds, number of hydrogen bond donors, number of hydrogen bond acceptors, and net charge of ligands and decoys.

=== Visualizing decoy Tanimotos to ligands ===

To visualize how different the matched decoys are to the input ligands, run the following command:
python /mnt/nfs/home/rstein/zzz.scripts/new_DUDE_SCRIPTS/0005_plot_tanimoto_to_lig.py {NEW_DIR_NAME}

There will be a box and whisker plot image in {NEW_DIR_NAME} showing the Tanimotos calculated between each ligand and all decoys.

Generating decoys (DUDE-Z)

2020-05-15T19:14:42Z

Rstein: Rstein moved page Generating decoys (DUDE-Z) to Blah

#REDIRECT [[Blah]]

Generating Decoys (DUDE-Z)

2020-05-15T19:14:42Z

Rstein: Rstein moved page Generating decoys (DUDE-Z) to Blah

2020-05-15T17:57:13Z

Rstein:

This script generates some number of directories with perturbed matching spheres. This will randomly perturb non-crystallographic spheres generated by SPHGEN during blastermaster.

The original script was written by Trent Balius. Wrapper script is written by Reed Stein.

Usage:

python ~rstein/zzz.scripts/sphere_sets_scripts/generate_non_xtal_spheres_dirs.py {YOUR_DOCK_DIR} {# directories to generate} {maximum distance to perturb spheres}

So if you wanted to generate 100 new docking directories with 100 different perturbed matching sphere setups (randomly differing from the original matching spheres by at maximum 0.5 Å), use the command:

python ~rstein/zzz.scripts/sphere_sets_scripts/generate_non_xtal_spheres_dirs.py DOCK_DIR/ 100 0.5

Trent's original script is located here:

python ~tbalius/zzz.scripts/make_random_sph_non_ligand.py {INPUT_SPHERE_FILE} {maximum distance to perturb spheres} {OUTPUT_SPHERE_NAME}

Note that the "random spheres" in the original matching_spheres.sph file have a "0.000" in the fifth column. This is changed to 0.5 after perturbing the matching spheres. If you would like to perturb the matching spheres again after you have already run it, the fifth column with "0.500" needs to be changed back to "0.000"

Matching Sphere Scan

2020-05-15T17:48:22Z

Rstein: