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Receptor-based virtual screening Lab version 2

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Page 1: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Receptor-based virtual screening

Lab version 2

Page 2: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Virtual screening

• Goal: identify ligands that tightly bind to a protein

• Requirements: a computer database of random potential ligands and a structure of the target protein

• Repetitively dock new ligands to protein• Score how tightly each ligand may bind• Keep best ‘hits’; discard other ligands

Page 3: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Find the best

Page 4: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Ligand database

• Often databases of commercially available compounds are used – up to 2 million compounds

• These take some time to analyze• We will use an NCI diversity set of about 1800

diverse compounds available from the National Cancer Institute

• This database contains many interesting compounds but is not exhaustive

Page 5: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Protein target

• We need a structure to serve as a target for ligand binding

• This can be an X-ray crystallographic structure or a high-quality homology model

• We need some idea of where the binding site for ligands is as well

• If the protein has multiple conformations, choose the appropriate one

Page 6: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Scoring

• To find the best ligands we must score the docked complexes

• Vina does this, giving a G score• Other scoring methods are available such as

X-score and DrugScore

Page 7: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Automation

• Virtual screening involves docking new ligands repetitively

• We will dock with Vina and automate the docking with a Perl script

• Automation includes selecting a new ligand from the database, running Vina, recording the docking score etc.

Page 8: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Output

• You will get a list of hits (ligand numbers)• You can select in advance how many hits you

want to look at – for a database of 2000, maybe 20 hits is a reasonable number

• You can recover these hits as PDB files from the (docked_pdb folder) and view them docked to your protein

Page 9: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Set up

• Patience!• We are trying to emulate much more

functional systems• Expect delays

Page 10: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Preparing your computer

• In the C: directory, copy the folder VirtualScreen2

• VirtualScreen2 contains most of the files you will need and many of the folders

Page 11: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Installing Perl

• Google ‘CPAN’ (the site for Perl)• Download a ‘binary’ for Perl• For PCs this will probably be ActivePerl• Install Perl• Test Perl; get a ‘Command Prompt’ from

start;Programs;accessories;CommandPrompt• Type: perl –v• You should get information about perl version

Page 12: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Look at a PDBQT file

• Ligands have torsion (twist and bend) features• Look in the database folder db_pdbqt• Look at ligand1.pdbqt• Open file by right-clicking and using ‘open

with, wordpad’• ‘BRANCH’ data indicates where ligand1 can

rotate (3 places)

Page 13: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Check Vina

• Test files are present in \lm\VirtualScreen• These are for a receptor and drug ligand• 2rhnh.pdbqt, carh.pdbqt, config2.txt• To run Vina type at command prompt:• \lm\downloads\vina.exe --config config2.txt• The program takes a minute or so to run• Test_vina.txt should give a list of energies for

9 alternative docked conformations

Page 14: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Check ligand database

• Go to VirtualScreen2\db_pdbqt directory• NCI diversity set = about 1800 chemicals• Parent DB from NCI is called Ncidiv_p0.0• These are chemicals available from NCI for

testing• We have about 1800 .pdbqt files, one per

chemical

Page 15: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Target protein

• Much of VirtualScreen2 relies on the target protein for binding

• A single name (ideally the PDB code) should be used throughout

• Any name variation will stop the program

Page 16: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Prepare target

• In VirtualScreen2• Make a new directory with a one_word name of

your target protein –example 2rht_a• In your target directory place two PDB files:• rech.pdbqt = your receptor/protein; must be

called ‘rech.pdbqt’ • xtal-lig.pdb = a reference ligand that will be used

to define the binding site• Look in folder 2rht_a to see example

Page 17: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Making rech.pdbqt

• Start with your receptor/protein without any ligand

• Make a copy of the PDB file and delete lines referring to your ligand 3-letter code

• Save

Page 18: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Making your rech.pdbqt file

• Add hydrogens• There are two methods• Open your protein in DS Viewer• -- click on ‘tools’ then ‘hydrogens’, ‘add’• You should see H’s added• Or use OpenBabel on the Command Line• Babel.exe –ipdb 2nht.pdb –opdb 2nhtH.pdb -h• (substitute the name of your protein)

Page 19: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Making your rech.pdbqt file

• Now convert the PDB file to PDBQT, adding hydrogen bonding information

• Use MGLtools (AutoDock tools)• Install if you do not have it• Start program; you will get a window• In the middle of the lower bar is ‘Grid’• Click ‘Macromolecule’ on the menu and open your

pdb+hydrogens file.• Then choose ‘output’ and save as a .pdbqt file

Page 20: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Making your rech.pdbqt file

• The file should be ready at this point• Check that file contains hydrogens (only polar

Hydrogens are included)• Check that file has hydrogen bonding info on

the right margin with entries like HD (indicating hydrogen donor) or OA (oxygen hydrogen bond acceptor) or C, doing nothing

Page 21: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Reference ligand

• The reference ligand PDB file serves only one purpose:

• It defines the region of the protein that Vina will search

• If the ligand is in the wrong place, Vina will search the wrong place.

• Copy the ligand from a trusted protein-ligand complex file

Page 22: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Editing the Virtual2.pl script

• Information on how the virtual screen should run is included in the script

• You must tell the script what to do• At runtime this information is used

Page 23: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

VS adjustable features

• Edit Virtual2.pl • You can adjust:• Target_name – must match a folder name• Filenum (file number) – use new number to

avoid deleting previous experiments• Number of ligands to screen – use ‘stop’ and

‘start’

Page 24: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Target_name

• $target_name defines the target for analysis• It should = the name of the folder that holds

rech.pdbqt• E.g. $target_name = “2rht_a”; • For the example search• There is a folder called 2rht_a that matches

and has the files needed for the search

Page 25: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Number of ligands

• You can adjust the start and stop point for searching the database

• – do only 5 to start… 1800 may take days on your machine (21 hours on my machine)

• Time the length of time needed to do 5 ligands and multiply by 360 to calculate the time required for the whole database

• The database can be split up using ‘stop’ and ‘start’ and run at different times

Page 26: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Editing the script

• Right click on virtual.pl and choose open with Wordpad

• At the top of the script is information• The section labeled for editing can be changed • If you are going to make big changes, save a copy

of the original script• You must enter the name of your protein exactly

as the folder is named• Edit carefully, do not delete #’s or ;’s

Page 27: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Before you begin VS

• Have you set the number of ligands to 5? (0-5)• This should take 3 – 30 minutes (you should

time it)• If something goes wrong the first time (it

usually does) no harm done.• To stop the program, use ctrl-C (repeat if

necessary)

Page 28: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Running VS

• Get a command prompt (start;programs;accessories;command prompt)

• Type: cd \virtualscreen2 • (this gets you to the right directory if needed)• Type: virtual2.pl• The program should run and stop in less than an

hour if you are doing 5 ligands (2-10 minutes is likely)

Page 29: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Looking at the results

• The results are in the vs_log folder (\virtualscreen2\vs_log)

• The output file has the file numbers of the hits, ranked from best to worst.

• Results files are marked with filenum to avoid overwriting

• Sample file: 2rht_a_results2.txt

Page 30: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Looking at hits

• Open your hits results file or open the example file 2rht_a_results.txt

• The predicted G of binding is shown and the ligand number

• A more negative G indicates tighter binding• The average G for all ligands is shown• For my data, ligand 438 is best

Page 31: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Looking at one ligand

• We can look at the best hit from 2rht_a• In db_pdb look for ligand438.pdb the best hit

for the example• (db_pdb contains un-docked molecules)• Look at this file with RasMol• It has a symmetric set of fused rings – this

type of molecule is usually an artefact, it binds to everything – other hits may be better

Page 32: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Looking for a good pose

• A ‘pose’ is a ligand conformation bound to a protein

• To view the conformation of a docked ligand after VS, look in the docked_pdb folder

• These files can also be added to a protein file to view docking

• Save molecules you like, because they can be overwritten

Page 33: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Viewing complexes

• The ligand .pdb file contents can be spliced onto the end of a copy of the receptor file used in virtual screening

• The complex can be viewed in RasMol• Especially note what receptor residues the

ligand contacts

Page 34: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

Ligand – protein contacts

• Splice ligand onto receptor in PDB file• Ligand should be named LIG in PDB file• Run contact12.pl script• Example: • contact12.pl 2rht_lig438.pdb LIG• Contacts appear on screen and in file

‘contact_output.txt’

Page 35: Receptor-based virtual screening Lab version 2. Virtual screening Goal: identify ligands that tightly bind to a protein Requirements: a computer database

The role of good judgment

• The value of virtual screening is that one can go from thousands or millions of candidate drugs with 0.01% - 0.1% leads to tens or hundreds of hits with 1% -10% leads

• Hits are not leads• They are a step toward getting leads