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Receptor-based virtual screening

Receptor-based virtual screening. Lab version 2. 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

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Receptor-based virtual screening

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  1. Receptor-based virtual screening Lab version 2

  2. 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

  3. Find the best

  4. 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

  5. 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

  6. Scoring • To find the best ligands we must score the docked complexes • Vina does this, giving a DG score • Other scoring methods are available such as X-score and DrugScore

  7. 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.

  8. 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

  9. Set up • Patience! • We are trying to emulate much more functional systems • Expect delays

  10. 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

  11. 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

  12. 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)

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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)

  19. 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

  20. 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

  21. 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

  22. 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

  23. 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’

  24. 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

  25. 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

  26. 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

  27. 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)

  28. 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)

  29. 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

  30. Looking at hits • Open your hits results file or open the example file 2rht_a_results.txt • The predicted DG of binding is shown and the ligand number • A more negative DG indicates tighter binding • The average DG for all ligands is shown • For my data, ligand 438 is best

  31. 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

  32. 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

  33. 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

  34. 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’

  35. 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

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