Research article

A simple click by click protocol to perform docking: AutoDock 4.2 made easy for non-bioinformaticians

Syed Mohd. Danish Rizvi1, Shazi Shakil2[*], Mohd. Haneef2

1Department of Biosciences, Integral University, Lucknow, India-226026

2Department of Bio-engineering, Integral University, Lucknow, India-226026

EXCLI J 2013;12:Doc831

 

Abstract

Recently, bioinformatics has advanced to the level that it allows almost accurate prediction of molecular interactions that hold together a protein and a ligand in the bound state. For instance, the program AutoDock has been developed to provide a procedure for predicting the interaction of small molecules with macromolecular targets which can easily separate compounds with micromolar and nanomolar binding constants from those with millimolar binding constants and can often rank molecules with finer differences in affinity. AutoDock can be used to screen a variety of possible compounds, searching for new compounds with specific binding properties or testing a range of modifications of an existing compound. The present work is a detailed outline of the protocol to use AutoDock in a more user-friendly manner. The first step is to retrieve required Ligand and Target.pdb files from major databases. The second step is preparing PDBQT format files for Target and Ligand (Target.pdbqt, Ligand.pdbqt) and Grid and Docking Parameter file (a.gpf and a.dpf) using AutoDock 4.2. The third step is to perform molecular docking using Cygwin and finally the results are analyzed. With due confidence, this is our humble claim that a researcher with no previous background in bioinformatics research would be able to perform molecular docking using AutoDock 4.2 program by following stepwise guidelines given in this article.

Keywords: computer aided docking, free offline docking, non-bioinformaticians, AutoDock, drug discovery, enzyme-ligand interaction

Introduction

Computer-aided docking is an important tool for gaining understanding of the binding interactions between a ligand (small molecule) and its target receptor (enzyme) (Anderson, 2003[1]; Schneider, 2010[6]) and has emerged as a reliable, cost-effective and time-saving technique for the discovery of lead compounds (Walters et al., 1998[8]; Schneider and Böhm, 2002[7]; Waszkowycz et al., 2001[10]). In recent years, the virtual screening approach for docking small molecules into a known protein structure is a powerful tool for drug design and has become an integral part of the drug discovery process. Computational tools like AutoDock offer the advantage of delivering new drug candidates more quickly and at a lower cost (Gilbert, 2004[2]; Warren et al., 2006[9]). AutoDock is an excellent non-commercial docking program that is widely used. Further, it employs a stochastic Lamarckian genetic algorithm for computing ligand conformations and simultaneously minimizing its scoring function which approximates the thermodynamic stability of the ligand bound to the target protein (Morris et al., 1998[4], 2009[5]). The use of complementary experimental and informatics techniques increases the chance of success in many stages of the discovery process. Theoretically the application of AutoDock in virtual screening is constrained only by the chemical compounds features that can be calculated and the relation between these features and the target (Lazarova, 2008[3]). But the problem arises in practical implementation of AutoDock in virtual screening of compounds which requires several considerations. Thus, this paper provides an easier protocol for the use of AutoDock for molecular docking purposes and will hopefully help in practically implementing AutoDock and AutoDock tools for the virtual screening purposes. To make it easier to understand, an example of experiment of the docking of Imipenem-hydrolyzing enzyme beta-lactamase SME-1 with Imipenem as ligand was made using AutoDock 4.2/ADT.

Requirements

1. Windows XP or Windows 7

Freely available software’s for non-commercial uses:

2. MGL tools
http://mgltools.scripps.edu/downloads

3. Cygwin
http://www.cygwin.com/install.html
(Click setup-x86.exe for 32-bits version while setup-x86_64.exe for 64-bits version)

4. Discovery Studio Visualizer
http://accelrys.com/products/discovery-studio/visualization-download.php

5. Binary files
http://autodock.scripps.edu/downloads/autodock-registration/autodock-4-0-1-and-autogrid-4-0.0
(Fig. 1)
Download and Extract autodocksuite-4.0.1-i86Cygwin.tar
Copy autodock4.exe and autogrid4.exe
(Fig. 2)
Paste in My computer\ C drive\ Cygwin\ bin

6. Java
http://www.java.com/en/download/index.jsp

Methods

1 Retrieving Required Ligand and Target .pdb files from major databases:

1.1 Retrieving Target.pdb files from major protein databases

http://www.rcsb.org/pdb/home/home.do

(Fig. 3)

(Fig. 4)

(Fig. 5)

(Fig. 6)

(Fig. 7)

(As both A and B chain are similar and Imipenemcan bind to anyone of the two chains)

(Fig. 8)

Save as Target.pdb

(Fig. 9)

1.2 Retrieving Ligand.pdb files from major ligand databases

http://www.drugbank.ca/ or

http://pubchem.ncbi.nlm.nih.gov/

(Fig. 10)

(Fig. 11)

(Fig. 12)

(Fig. 13)

(Fig. 14)

2 Preparing PDBQT format for Target and ligand (Target.pdbqt, Ligand.pdbqt), Grid and Docking Parameter file (a.gpf and a.dpf) using AutoDock 4.2

(Fig. 15)

(Fig. 16)

2.1 Preparation of Target.pdbqt file

(Fig. 17)

(Fig. 18)

Click Polar Only

Click OK

(Fig. 19)

(Fig. 20)

(*In short: save Target.pdbqt in C:\Cygwin\home\1 and after saving macromolecule gets coloured)

(Fig. 21)

2.2 Preparation of Ligand.pdbqt file

(Fig. 22)

(Fig. 23)

(Fig. 24)

(Fig. 25)

2.3 Preparation of Grid Parameter File (a.gpf)

(Fig. 26)

(*We have used X,Y,Z dimension as 60x60x60. Further X,Y,Zcenter (Center Grid Box) can be changed according to the requirements but we are taking them as Default)

(Fig. 27)

(Fig. 28)

2.4 Preparation of Docking Parameter File (a.dpf)

(Fig. 29)

(Fig. 30)

(Fig. 31)

(Fig. 32)

At last four files Target.pdbqt, Ligand.pdbqt, a.gpf and a.dpf are present in the C:\ Cygwin\ home\1

(Fig. 33)

3 Using Cygwin for Molecular Docking

Open Cygwin (*By clicking icon on the desktop)

Use these commands highlighted in brown font color by copy and paste in Cygwin and press enter after each command:

(cd..)cd<space>..

(ls)ls<space>

(cd 1) cd<space>1(or foldername)<space>

(ls)ls<space>

(autogrid4.exe -p a.gpf -l a.glg &)

autogrid(tab)<space>-p<space>a.gpf<space>-l<space>a.glg&

(Fig. 34)

(tail -f a.glg &) tail<space>-f<space>a.glg<space>&

(Fig. 35)

(autodock4.exe -p a.dpf -l a.dlg &)

autodock(tab)<space>-p<space>a.dpf<space>-l<space>a.dlg&

(tail -f a.dlg &) tail<space>-f<space>a.dlg<space>&

(Fig. 36)

(After Successful Completion)

(Fig. 37)

Copy Target.pdb file in C:\Cygwin\ home\1

(Fig. 38)

Copy and Paste the following commands in Cygwin Window and press enter after each command:

(grep '^DOCKED' a.dlg | cut -c9- >a.pdbqt)

(cut -c-66 a.pdbqt> a.pdb)

(catTarget.pdb a.pdb | grep -v '^END ' | grep -v '^END$' > complex.pdb)

(Fig. 39)

4 Analyzing results and Retrieving Ligand-Enzyme interaction complex .pdb

4.1 Analyzing Results

(Fig. 40)

Note the confirmation showing best down binding energy and inhibition constant

(*In our case 10 conformation was best with binding energy (ΔG) as -5.75 and inhibition constant (Ki) as 60.87 µM)

(Fig. 41)

4.2 Retrieving Ligand-Enzyme interaction complex .pdb

(Fig. 42)

Select all other complexes and delete them except the best

(*In our case Complex model 10 was best as conformation 10 was showing best results in our case).

(Fig. 43)

(Fig. 44)

(Fig. 45)

(Fig. 46)

Conclusion

AutoDock is a popular non-commercial docking program that docks a ligand to its target protein and performs well (accurate and computationally fast). In this paper we propose an easier user-friendly docking protocol for docking ligands with target protein that utilizes AutoDock and Cygwin for docking operations. Our protocol provides a detailed outline and advice for use of AutoDock, AutoDock Tools, its graphical interface and to analyze interaction complexes using computational docking. The example of a docking experiment between Imipenem-hydrolyzing beta-lactamase SME-1 (an enzyme) and Imipenem (a ligand) using AutoDock 4.2/ADT has been given. Our sincere aim is to spread knowledge and make scientific research accessible to researchers who could not afford to buy software or pay high subscription fees of online docking servers. With due confidence, this is our humble claim that a researcher with no previous background in bioinformatics research would be able to perform molecular docking using AutoDock 4.2 program by following stepwise guidelines given in this article.

Acknowledgements

The authors are thankful to all the scientists of this world who possess a burning desire to share their knowledge and skills with the entire world free of charge and solely for the benefit of mankind and expect its reward from Allah alone. We extend sincere thanks to the inventors of ‘AutoDock’.

 

References

1. Anderson AC. The process of structure-based drug design. Chem Biol. 2003;10:787–97.
2. Gilbert D. Software review: bioinformatics software resources. Brief Bioinform. 2004;5:300-4.
3. Lazarova M. Virtual screening-models, methods and software systems. International Scientific Conference Computer Science. 2008;55-60.
4. Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE, Belew RK, et al. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J Comput Chem. 1998;19:1639–62.
5. Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, et al. AutoDock 4 and AutoDockTools 4: automated docking with selective receptor flexibility. J Comput Chem. 2009;30:2785–91.
6. Schneider G. Virtual screening: an endless staircase? Nat Rev Drug Discov. 2010;9:273–6.
7. Schneider G, Böhm H. Virtual screening and fast automated docking methods: combinatorial chemistry. Drug Discov Today. 2002;7:64-70.
8. Walters W, Stahl M, Murcko M. Virtual screening - An overview. Drug Discov Today. 1998;3:160-78.
9. Warren G, Andrews C, Capelli A, Clarke B, LaLonde J, Lambert MH, et al. A critical assessment of docking programs and scoring functions. J Med Chem. 2006;49:5912-31.
10. Waszkowycz B, Perkins T, Sykes R, Li J. Large-scale virtual screening for discovering leads in the postgenomic Era. IBM Systems J. 2001;40:360-76.
 
 

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[*] Corresponding Author:

Dr., Assistant Professor, Shazi Shakil, Department of Bio-engineering, Integral University, Lucknow, UP, India-226026; Phone: 0522-2890812, 2890730, 3296117, 6451039; Fax: 0522-2890809; Mobile: +91-8004702899, eMail: shazibiotech@gmail.com