AUDocker LE: A GUI for virtual screening with AUTODOCK Vina
© Sandeep et al 2011
Received: 5 May 2011
Accepted: 25 October 2011
Published: 25 October 2011
AUTODOCK Vina is an open-source program which is steadfast and authentic to perform docking simulations. Though, Auto Dock Tools can help perform docking simulations with Vina, it largely remains as a platform for docking single molecule at a time.
"AUDocker LE" is designed with an aim to develop a software tool as a front end graphical interface with C# language to perform docking experiments in Windows based computers. It helps users to perform automated continuous docking of large ligand databases into a set of predefined protein targets. It will also help the user to analyze the results to select promising lead molecules.
AUDocker LE provides a straight forward graphical interface which can be used in a standard personal computer with Microsoft Windows XP or Windows 7 as the operating system where Autodock Vina, Python 2.5 and .net frame work are preinstalled.
Preparation of protein (rigid and flexible)
Defining the active site (Grid)
Vina does not require receptor files and GRID files as input, docking of a single molecule is made easy with command line instruction but virtual screening of larger databases is possible only, if the user is familiar with shell scripting.
PaDEL-ADV  is one of the cost-free available softwares for virtual screening with Vina, programmed on JAVA platform. Free version of VcPpt  software allows docking three ligands at a time. The authors could not find any open-handed software tool for docking larger database of molecules (Ligands) onto a panel of target proteins (Receptors) and determining the results.
In the last step, click the RUN tab to initiate docking.
The Progress of the experiment can be visualized in the text box given against "running receptor" and "running ligand" box which will reflect data on the number of files docked and the total number of files submitted for screening. A pop up window would appear on the screen, if the experiment is completed successfully.
Then the user can click "next" option to analyse of the results. The following is the methodology is used for analysis of the results.
Ligand efficiency is a parameter recently introduced for selection of useful lead molecules in virtual screening of large datasets of compounds. Ligands can be compared effectively by a parameter "ligand efficiency" which can be calculated by dividing the ΔG value (dock score) obtained in the docking experiment by number of non-hydrogen atoms present in the ligand [6, 7].
Where ΔG = RT In Kd and N is the number of non-hydrogen atoms.
Ligand selection is based on the conditions δLE > 1 or δLE ≥ m+3σ
Where m = average value of δLE for all the compounds for a given protein target σ = Standard deviation
Where V = New score value assigned to the ligand
Vo = Binding energy value obtained in docking simulations
ML = Average score value obtained for all the ligands for the respective protein
MR = Average score values obtained for the respective ligand in all the proteins
In this analysis, ligands with V value > 1 or V ≥ m+3σ were selected. Where m is the average of V values obtained for a given target protein and σ is the standard deviation.
A manual is also available for download along with files required for tutorial. The user is furnished with two datasets to get accustomed to the software. A dataset of 113 molecules (tutorial file 2) is obtained from the marine resources having protein kinase enzyme inhibitor activity are selected and docked against 21 kinases obtained from RCSB  website. The software can successfully identify potential ligands (kindly consult the tutorial file 2), in which one is considered as potential molecule for drug development .
Availability and requirements
Project name: AUDocker LE
Project homepage: https://sourceforge.net/projects/audocker/files/?
Operating system: Microsoft Windows XP and Windows 7
Programming language: C# on .net framework
Other requirements: Preinstallation of Python 2.5, Microsoft .net frame work, AutoDockTools (any latest version), Vina and PyMol. The user may consult manuals of ADT, .net framework and Python for successful installation and system compatibilities.
License: Free to use
Any restrictions to use by non-academics: None
We thank College of Pharmaceutical Sciences, Andhra University, Visakhapatnam for the computational facilities. We also thank the reviewers for their critical comments which helped us improve our program.
- Trott O, Olson AJ: AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading. J Comp Chem. 2010, 31: 455-461.Google Scholar
- AutoDockTools, the free GUI for AutoDock. [http://autodock.scripps.edu/resources/adt]
- Software to perform virtual screening with AutoDock Vina. [http://padel.nus.edu.sg/software/padeladv/index.html]
- Protein-ligand docking and in-silico virtual screening for windows. [http://biochemlabsolutions.com/Molecule_Docking.html]
- Tutorial for AutoDock Tools. [http://autodock.scripps.edu/faqs-help/tutorial]
- Abad-Zapatero C, Metz JT: Ligand efficiency indices as guideposts for drug discovery. Drug Discovery Today. 2005, 10: 464-469. 10.1016/S1359-6446(05)03386-6.PubMedView ArticleGoogle Scholar
- Andrew LH, Colin RG, Alexander A: Ligand efficiency: a useful metric for lead selection. Drug Discovery Today. 2004, 9: 430-431. 10.1016/S1359-6446(04)03069-7.View ArticleGoogle Scholar
- Gianluigi L, Adriana R, Raffaele R, Giuseppe B: Inverse Virtual Screening of Antitumor Targets: Pilot Study on a Small Database of Natural Bioactive Compounds. J Nat Prod. 2011, 74: 1401-1407. 10.1021/np100935s.View ArticleGoogle Scholar
- Biological Macromolecular Resource: [http://www.rcsb.org/pdb/home/home.do]
- Shyh-Ming Y, Ravi M, Lawrence JW, Rochelle A, Xin C, Cangming Y, Bingbing W, Druie C, William VM: Simplified staurosporine analogs as potent JAK3 inhibitors. Bioorganic & Medicinal Chemistry Letters. 2007, 17: 326-331. 10.1016/j.bmcl.2006.10.062.View ArticleGoogle Scholar