DOCK 3.7 tutorial based on Webinar 2017/06/28

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This tuturial expands on a webinar presentation to the SBGrid [1]

Find the Youtube video here: video

Scenario 1:

Use docking to predicted how Erlotinib (an approved drug) binds to the Epidermal Growth Factor Receptor

Search for Your Molecule in ZINC, Get Files for Docking from ZINC

Get the link from the zinc webpage and us wget to download:

wget http://files.docking.org/protomers/16/89/55/209168955.db2.gz

Put the path of the downloaded database into the split database index file (this file usually contain many db2 file):

ls /path/tutorial_for_webinar/dock3.7/209168955.db2.gz > ligands.sdi

Get the receptor structure from the PDB website

wget https://files.rcsb.org/download/1M17.pdb --no-check-certificate
Break Xtal into Receptor and Ligand Files

You may use a program like Chimera for this

Receptor file must be called: rec.pdb

Ligand file: xtal-lig.pdb


What if the crystal does not have a ligand:

Place atoms in the site were you want to dock. One way is to run sphgen and selecting spheres near residues in the site convert to pdb

Make the recptor file (remove alternative side chains):

grep "^ATOM" 1M17.pdb | grep -v ^................B > rec.pdb

Make ligand file:

grep AQ4 1M17.pdb | sed -e 's/HETATM/ATOM  /g' > xtal-lig.pdb

Run blastermaster: input rec.pdb, xtal-lig.pdb and makes all receptor file need for docking.

python $DOCKBASE/proteins/blastermaster/blastermaster.py --addhOptions=" -HIS -FLIPs "  -v

This command may take several minutes to run.

Here are the files that are produce:

 -rw-r--r--. 1 tbalius bks 3163 Jun 17 12:27 INDOCK
 
 dockfiles/:
 total 30388
 -rw-r--r--. 1 tbalius bks  1206051 Jun 17 12:27 ligand.desolv.heavy
 -rw-r--r--. 1 tbalius bks  1206051 Jun 17 12:27 ligand.desolv.hydrogen
 -rw-r--r--. 1 tbalius bks     3376 Jun 17 12:27 matching_spheres.sph
 -rw-r--r--. 1 tbalius bks   908086 Jun 17 12:27 trim.electrostatics.phi
 -rw-r--r--. 1 tbalius bks  3121095 Jun 17 12:27 vdw.bmp
 -rw-r--r--. 1 tbalius bks     1653 Jun 17 12:27 vdw.parms.amb.mindock
 -rw-r--r--. 1 tbalius bks 24660016 Jun 17 12:27 vdw.vdw

Modifying INDOCK File

The following parameter how much orienting to do:

 match_goal                    5000

Reduce 1000 if docking takes to long.

The following parameter specifies the number of poses to write out:

 number_save                   1
 number_write                  1

Consider writing out 100

Here are the minimization parameters:

 #                    MINIMIZATION
 minimize                      no
 sim_itmax                     500
 sim_trnstep                   0.2
 sim_rotstep                   5.0
 sim_need_to_restart           1.0
 sim_cnvrge                    0.1
 min_cut                       1.0e15
 iseed                         777

When these parameters are turned on, dock will minimize the 6 degrees of freedom (3 rotation, 3 translation) for the poses written out. All molecules written out will be minimized.

Make prepare docking directories.

$DOCKBASE/docking/setup/setup_db2_zinc15_file_number.py ./ ligand ligand.sdi 500 count

Submit jobs to queue (we use SGE queuing system):

$DOCKBASE/docking/submit/submit.csh

To analyze the results we need to combine the results and then get poses

$DOCKBASE/analysis/extract_all.py
$DOCKBASE/analysis/getposes.py

It is also possible to run dock locally:

$DOCKBASE/docking/DOCK/bin/dock64

Output: OUTDOCK and test.mol2.gz

Visualize poses in Chimera with Viewdock

open molecules and poses with Viewdock
compare best pre-minimized poses before and after minimization

Pose with and without minimization: Energy -37.79 -> -38.54

compare best minimized poses with xtal ligand

Best pose out of the top 100 after min: Energy -41.31


Scenario 2:

Use docking to test enrichment capabilities of Epidermal Growth Factor Receptor using 12 ligands and DUD-E property matched decoys

Get Known Ligands for Docking

https://www.ebi.ac.uk/chembl/target/inspect/CHEMBL203


Find your target on Chembl.

Get Known Ligands for Docking

Obtain smiles from Chembl.

Process the XLS file into the a smiles file called "ligands_12_from_chembl.smi" with the smiles in the first column and the name in the second column.

 cat bioactivity-17_20_35_00.xls | grep -v "CMPD_CHEMBLID" | head -12 | awk '{print $10 " " $1}' > ligands_12_from_chembl.smi

Generate Decoy Smiles File

http://dude.docking.org/generate


Generate property matched decoys from DUD-E webserver.


If the system is in DUD-E, You may download ready to dock databases here: http://autodude.docking.org/

Here I just used the first 12 ligands from Chembl

Generated decoys using DUD-E webserver Use the link in email:

wget http://dude.docking.org/generate/results/4094969748/dude-decoys.tar.gz
tar -xzvf dude-decoys.tar.gz
grep -v ligand dude-decoys/decoys/decoys.P*.picked | awk -F: '{print $2}' | awk '{print $1 " " $2}' > ! decoys.smi
${DOCKBASE}/ligand/generate/build_database_ligand.sh -H 7.4 ligands_12_from_chembl.smi
csh wraper_queue_build_smiles_ligand_mod_corina.csh decoys.smi

For more information see the page: Ligand_preparation_-_20170424


Make a list of all the databases:

ls /path/databases/ligands_12_from_chembl/CHEMBL*/*.db2.gz /path/databases/decoys/sgejob_*/finished/C*/*.db2.gz > ! ligands_decoys.sdi 
awk '{print $2}' databases/ligands_12_from_chembl.smi > databases/ligands_names.txt
awk '{print $2}' databases/decoys.smi > databases/decoys_names.txt

Make directories for docking:

$DOCKBASE/docking/setup/setup_db2_zinc15_file_number.py ./ ligands_decoys databases/ligands_decoys.sdi 100 count 

Submit docking jobs:

$DOCKBASE/docking/submit/submit.csh

Process results combining results and get the best poses:

$DOCKBASE/analysis/extract_all.py
$DOCKBASE/analysis/getposes.py

Calculate enrichments:

$DOCKBASE/analysis/enrich.py -i . -l databases/ligands_names.txt -d databases/decoys_names.txt
$DOCKBASE/analysis/plots.py -i . -l databases/ligands_names.txt -d databases/decoys_names.txt
Enrichment quanified using log-adjusted AUC curves.