Docking and Virtual Screening Using the BMI cluster

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Docking and Virtual Screening Using the BMI
cluster
Jacek Biesiada Cincinnati, 2008
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The Docking Problem
Finding the geometry and strength of ligand
binding to a receptor.
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High Throuput Docking and Virtual Screening for
Drug Design

• Definition of Virtual Screening
• Use of high-performance computing to analyze
  large database of chemical compounds in order to
  indetify possible drug candidates.
• W.P. Walters, M.T. Stahl and M.A. Murcko,
  Virtual Screening-An Overview, Drug Discovery
  Today, 3, 160-178 (1998)
• Virtual Screening is also known as
• High-Throughput Docking
• High-Throughput Virtual Screening

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Why Use Virtual Screening ?

• VS is a computational filter
• Reduces the size of a chemical library to be
  screened experimentaly 106 to 103 Saves time
  money
• ZINC library version 2007, only drug-like
  compounds 2.2 106
• Expected ZINC version 2008 about 4 106
  compounds
• May improve likelihood of finding interesting
  compounds
• As oppoesed to random screening
• Enhance hit rates
• VS can
• Evaluate virtual combinatorial libraries before
  synthesized
• VS can be usefull tool for discovering new
  targets
• in post-genomic era
• Examples of aplications Design of inhibitors
  for Norovirus and Glycoprotein IV
• (collaboration with Jason Jiang, CCHMC and
• Andrew B. Herr UC College of Medicine )

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Autodock

• AutoDock has been widely-used and there are many
  examples of its successful application in the
  literature
• (First clinicaly-approved HIV Integrase
  Inhibitor Autodock used during the research
  prof. Andrew McCammon)
• Citation Index showed more than 1100 publications
  have cited the primary AutoDock methods papers.
• It is very fast, provides high quality
  predictions of ligand conformations, and good
  correlations between predicted inhibition
  constants and experimental ones.
• Very well calibrated force fieled (188 known
  protein)
• Autodock is free software and version 4 is
  distributed under the GNU General Public License

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Screening Pipeline Scripts to Run Autodock on
BMI Cluster

• Adscr.pl input Receptor.cfg adscr.cfg
  Ligand_info1-N_CPU
• output _ki, _cl. _bestlig,
  _currentlig, _errors
• Que.pl - input Number_of_CPU Receptor.cfg
  Ligand_info_all
• Best.pl - input File with results (_ki)
• Restart.pl building new Ligand_info_all file in
  case of restart of
• calculation
• Ligand_info_all (Ligand_info) example
• 862418 862450 ZINC00041309 3_p0.0.pdbqt
• 2 862453 862484 ZINC00041344 3_p0.0.pdbqt
• 3 862487 862528 ZINC00041448 3_p0.0.pdbqt
• ...................... 2200000 line
  ................................

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Preparing Receptor and Ligand for Docking
Simulations

• Prepare_receptor.pl input Receptor.pdb 3(4)
• Prepare_gpf.pl - input Receptor.pdb Ligand.pdb
  3(4)
• binding site, grid box
• Autogrid.pl input Receptor.pdb Ligand.pdb 3(4)
• Configure Receptor.cfg
• adscr.cfg
• - Read the Tutorial connected to prepared
  scripts all details connected with Virtual
  Screening

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Our Library of Compounds

• Library in directory
• ZINC offer four formats
• sdf, mol2, Smail and flexibase
• /database/Zinc/ (version from 2007)
• /mol2
• /sdf /sdf_index
• /pdb /pdb_index
• /pdbq /pdbq_index (Autodock v.3)
• /pdbqt /pdbqt_index (Autodock v.4)

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Virtual Screening is CPU Intensive Some
Estimates Using BMI Cluster

• 2.2 mln compounds
• On average 1 min for one docking (depends of grid
  map and several search parameter with default
  value)
• 50 CPU
• ((2200000/50)/ 60min)/ 24h 30 day
• About 30 days 1th screeaning

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Validation and Analysis of Docking Results

• Similarity compounds
• molprint2d http//www.molprint.com (free)
• Method based on MOLecular fingerPRINT
• ADME (absorption, distribution, metabolism,
  excretation)
• Paramaters like Molecular weight, LogP,
  LogD, pKa , number of H-bond donor/acceptor,
  PSA, ,... (15-16 parameters)
• ALOGS http//www.vcclab.org/lab/alogps
  (free)
• JChem (MARVIN, JCLUSTOR)
• http//www.chemaxon.com/ (free for
  academic research)

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Future Work

• Testing scripts
• Increase library of compounds
• Writing good Tutorial for users
• Gold standard similarity and ADME ?
• Improve scripts for finall-automatic analisys of
  docking, similarity and ADME.

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• THANK YOU