All Platforms

Use the man command to look up commands in the manual. From a Terminal or shell, type:

      man man

Remember to press the < Enter > or < Return > key at the end of every command: otherwise the computer will not do anything. For example, the command ls is short for "list" and lists all the files and directories in the current directory, so typing:

      man ls

and pressing < Enter > or < Return > would give you the manual page for the list command, ls. The behaviour of commands can be changed by typing a so-called flag after the name of the command, for example to get a simple listing of files, you would type ls, but to get a long listing, use the -l flag like this:

      ls -l

If you don't know the name of the command, you can use the apropos command (or type man -k, where k is short for "keyword") to get a list of all the commands that match, e.g. apropos python would list all the commands that refer to the word "python".

Cygwin

• If you are experienced with Windows, there is a Quick Start Guide for those more experienced with Windows
• If you come from a UNIX background, there is a Quick Start Guide for those more experienced with UNIX
• Take a look at the manual that comes with Cygwin, which is available online and in PDF: Cygwin User's Guide

Linux

• There is a nice series of interactive tutorials on using Linux, called Linux Survival.

Mac OS X

• A gentle introduction to Mac OS X is available from Learning Mac OS X but this does not cover using the Terminal.
• O'Reilly is a very well-respected publisher of books about UNIX and open source technologies; their "MacDevCenter" has a great series of hands-on tutorials about Learning the Mac OS X Terminal

You can subscribe to the ADL by going to the ADL Info Page; you will need to give a valid email address, create a password, and decide if you want your messages to be sent as a daily digest or not.

About the AutoDock mailing list

This list is intended for novice and expert users of the ligand-protein and protein-protein docking software AutoDock, AutoGrid and ADT (AutoDockTools). This list will provide a forum for users to share experience, to ask questions about things not covered in the documentation, and hopefully, to get answers to these questions. Questions may range from technical to scientific, but should be about docking molecules using AutoDock and its associated programs and utilities. Suggestions for new features are also welcome. Announcements of new software versions and functionalities will be made on this list. In general, bugs should not be reported here but entered into our Bugzilla database. Just go to http://mgldev.scripps.edu/bugs/ and click on the "Open a new Bugzilla account" link.

Go to the AutoDock List archives, and type in your query. If your query has more than one word, choose either "Match ALL words" or "Match ANY word".

The MGL (Molecular Graphics Laboratory) has a special database called "Bugzilla" that we use to collect and track bug reports.

• Click "Search existing bug reports" to see if your bug has been reported by someone else. If it has, then you don't need to file a new bug report.
• If you have found a new bug, click on "Enter a new bug report" and select the appropriate "product", i.e. AutoGrid, AutoDock or "MGL Applications" for ADT (the AutoDockTools graphical user interface).
• If you don't have a Bugzilla account, you will need to create one. Click on "Open a new Bugzilla account" to make one; you will need a valid email address, and this will also be your login name. The account will be created, and its password will be mailed to you. You will not be able to log in until you receive the password.

Yes, it is called ADT (also known as AutoDockTools), and is produced by the Olson Laboratory, here at The Scripps Research Institute.  ADT builds on Michel Sanner's PMV (Python Molecule Viewer) and MGLTools.

There is also BDT (Blind Docking Tool) which is produced by Facultat de Química de Tarragona, Universitat Rovira i Virgili, in Spain.

See the Resources section for more information.

Since AutoGrid/AutoDock look for input files in current working directory (cwd), you need to make sure that your cwd includes all input files necessary. Start your command line shell and run ls (POSIX) or dir (Windows). If the input file mentioned in error message is not listed, you need to change directory (cd) or move required input file to cwd. Please note that AutoDock is a command line application and you need to be able to navigate your file system in order to troubleshoot potential problems. See, for instance, File Systems - Unix and Dos.

The above is also true if you launch AutoDock using AutoDockTools (ADT). If you changed your directory while saving or opening an input file then chances are that you need to change current working directory in ADT.

---

Which Python scripts are available?

In version 1.5.0 of MGLTools, these scripts include:

compute_AutoDock41_score.py
compute_consensus_maps_from_dlgs.py
compute_rms_between_methods.py
dpf3_to_dpf4.py
energy_average_maps.py
gpf3_to_gpf4.py
gpf4_to_gpf3.py
pdbq_to_pdbqt.py
pdbqs_to_pdbqt.py
pdbqt_to_pdb.py
pdbqt_to_pdbq.py
pdbqt_to_pdbqs.py
prepare_dpf.py
prepare_dpf4.py
prepare_flexreceptor4.py
prepare_gpf.py
prepare_gpf4.py
prepare_ligand.py
prepare_ligand4.py
prepare_ligand_dict.py
prepare_receptor.py
prepare_receptor4.py
repair_ligand4.py
rotate_molecule.py
summarize_docking_directory.py
summarize_results.py
summarize_results4.py
summarize_time.py
summarize_wcg_docking.py
superimpose_based_on_subset.py
write_all_complexes.py
write_clustering_histogram_postscript.py
write_component_energies.py
write_largest_cluster_ligand.py
write_lowest_energy_ligand.py
write_random_state_ligand.py

Note that the scripts that end in "4.py" are for AutoDock 4.  See the "How to" section to learn more about these scripts.

---

Where do I download the Python scripts from?

All the AutoDock Python scripts are distributed as part of AutoDockTools, which is distributed as part of the MGLTools bundle.

---

Where are these Python scripts installed?

They can be found at the following locations, depending on your platform (Linux, Mac OS X or Windows) and on the version of MGLTools you installed (1.5.0):
 

Linux

    <InstallationDirectory>/MGLToolsPckgs/AutoDockTools/Utilities24

    If you install as root, <InstallationDirectory> is:

    /usr/local/MGLTools-1.5.0

    If you install as a regular user, <InstallationDirectory> is:

    $HOME/MGLTools-1.5.0

Mac OS X

    /Library/MGLTools/1.5.0/MGLToolsPckgs/AutoDockTools/Utilities24

Windows

    <InstallationDirectory>\MGLToolsPckgs\AutoDockTools\Utilities24

    Note that by default,  <InstallationDirectory> is:

    C:\Program Files\MGLTools 1.5.0

Steps to Generate a Ligand Input File for AutoDock

1. Convert a 1D description (SMILES string, e.g.) or 2D description (from a molecule sketching program such as ChemDraw, Ghemical or PRODRG) of the ligand into 3D coordinates.  Pay attention to the stereoisomeric form, especially chirality.
2. Alternatively, obtain the structure of the ligand from a database.
3. Generate the correct tautomeric form.  If this is not known, all tautomers should be generated and docked independently.
4. Add all the hydrogen atoms, to make sure all the valencies of the heavy atoms are satisfied.
5. Compute partial charges for the ligand using your preferred method and level of theory.
6. AutoDock 3 and AutoDock 4 use the United Atom model.  This means only polar hydrogens are included in the coordinates file. A molecule with all hydrogens can be converted into a United Atom model using AutoDockTools (ADT)'s "Edit > Hydrogens > Merge Non-Polar" menu option.
7. The ligand needs torsion information to be added depending on which torsions are to be treated as rotatable during the docking.  Then it needs to be saved in PDBQ format for AutoDock 3, and PDBQT format for AutoDock 4. There are more details on how to do this using ADT in the tutorials, "Using AutoDock 3.0.5 with AutoDockTools", "Using AutoDock 4 with AutoDockTools" and  "Using AutoDock for Virtual Screening".

Obtaining 3D Coordinates for a Ligand

There are a variety of ways of obtaining coordinates for a small organic molecule ('ligand')—this list is by no means exhaustive:

• Databases
• CSD (Commercial, Cambridge Structural Database) — this is the "world repository of small molecule crystal structures".
• PDB — (Free) — RCSB Protein Data Bank — great if you are looking for a structure of a small molecule in complex with a protein or other macromolecule.
• ZINC (Free) — ZINC Is Not Commercial! — "a free database of commercially-available compounds for virtual screening. ZINC contains over 4.6 million compounds in ready-to-dock, 3D formats".
  
• Chemical Drawing Software
• ChemDraw (Commercial, available from CambridgeSoft)
• Corina (Commercial, available from Molecular Networks GmbH) — note there is an Online Demo available, too.
• Discovery Studio (Commercial, available from Accelrys)
• Ghemical (Free software) — runs in X11 on Linux and Mac OS X; great for sketching and energy minimisation.
  
• Ghemical-GMS (Free software) — can also be used to generate input for GAMESS.
• PRODRG (Free web service) — produces AutoDock 3 PDBQ files, which can be converted into PDBQT files for AutoDock 4.
  

Requirements for AutoDock

• AutoDock 3 requires 3D coordinates and partial charges for all the heavy atoms and polar hydrogens in the ligand; these must be given in PDBQ format.
• AutoDock 4 requires 3D coordinates, partial charges and AutoDock 4 atom types for all the heavy atoms and polar hydrogens in the ligand; these must be given in PDBQT format.

Yes, AutoDock can be used when the location of the binding site is unknown. This is often referred to as "blind docking", when all that is known is the structure of the ligand and the macromolecule.

It will be necessary to set up the dockings to search the entire surface of the protein (or other macromolecule) of interest. This can be achieved using AutoGrid to create very large grid maps, with the maximum number of points in each dimension, and if necessary, creating sets of adjacent grid map volumes that cover the macromolecule. The third-party tool BDT can be used to set up such sets of grid maps.

Several authors have used AutoDock to perform blind docking (see 1.-6.); for instance, Hetenyi et al. published two papers showing that AutoDock can be used to perform blind docking of peptides to proteins, and drug-sized molecules to proteins.

1. Hetenyi, C. and van der Spoel, D. (2002) Efficient docking of peptides to proteins without prior knowledge of the binding site. Protein Science, 11(7): 1729-1737.
2. Kovacs, M., Toth, J., Hetenyi, C., Malnasi-Csizmadia, A., and Sellers, J.R. (2004) Mechanism of blebbistatin inhibition of myosin II. Journal of Biological Chemistry, 279(34): 35557-35563.
3. Bikadi, Z., Hazai, E., Zsila, F., and Lockwood, S.F. (2006) Molecular modeling of non-covalent binding of homochiral (3S,3 ' S)-astaxanthin to matrix metalloproteinase-13 (MMP-13). Bioorganic & Medicinal Chemistry, 14(16): 5451-5458.
4. Hazai, E., Bikadi, Z., Zsila, F., and Lockwood, S.F. (2006) Molecular modeling of the non-covalent binding of the dietary tomato carotenoids lycopene and lycophyll, and selected oxidative metabolites with 5-lipoxygenase. Bioorganic & Medicinal Chemistry, 14(20): 6859-6867.
5. Hetenyi, C. and van der Spoel, D. (2006) Blind docking of drug-sized compounds to proteins with up to a thousand residues. FEBS Letters, 580(5): 1447-1450.
6. Iorga, B., Herlem, D., Barre, E., and Guillou, C. (2006) Acetylcholine nicotinic receptors: finding the putative binding site of allosteric modulators using the "blind docking" approach. Journal of Molecular Modeling, 12(3): 366-372.

In AutoDock 4, we have introduced a new command "parameter_file" that takes a new parameter library file that contains the various force field parameters.  In most cases, you will not need to modify these values, but it is important to know where they are and how to change them if necessary.

The standard AutoDock 4 parameters are in the file "AD4_parameters.dat" which can be found in the "autodocksuite-4.n.m/src/autodock-4.x.y" directory of the AutoDock 4 distribution, where n and m are the major and minor version numbers of the AutoDock Suite, and x and y are the major and minor version numbers of AutoDock.  Here is an example:

# $Id: AD4_parameters.dat,v 1.14 2007/04/27 06:01:47 garrett Exp $
# 
# AutoDock 
# 
# Copyright (C) 1989-2007,  Garrett M. Morris, David S. Goodsell, Ruth Huey, Arthur J. Olson, 
# All Rights Reserved.
# 
# AutoDock is a Trade Mark of The Scripps Research Institute.
# 
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
# 
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
# 
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.

# AutoDock Linear Free Energy Model Coefficients and Energetic Parameters
#                        Version 1.0
#                     $Revision: 1.14 $

# AutoDock 4 free energy coefficients with respect to original (AD2) energetic parameters
#
#               Free Energy Coefficient
#               ------
FE_coeff_vdW    0.1560
FE_coeff_hbond  0.0974
FE_coeff_estat  0.1465
FE_coeff_desolv 0.1159
FE_coeff_tors   0.2744

# AutoDock 4 Energy Parameters

# - Atomic solvation volumes and parameters
# - Unweighted vdW and Unweighted H-bond Well Depths
#
# - Atom Types
# - Rii = sum of vdW radii of two like atoms (in Angstrom)
# - epsii = vdW well depth (in Kcal/mol)
# - vol = atomic solvation volume (in Angstrom^3)
# - solpar = atomic solvation parameter
# - Rij_hb = H-bond radius of the heteroatom in contact with a hydrogen (in Angstrom)
# - epsij_hb = well depth of H-bond (in Kcal/mol)
# - hbond = integer indicating type of H-bonding atom (0=no H-bond)
# - rec_index = initialised to -1, but later on holds count of how many of this atom type are in receptor
# - map_index = initialised to -1, but later on holds the index of the AutoGrid map
# - bond_index = used in AutoDock to detect bonds; see "mdist.h", enum {C,N,O,H,XX,P,S}
#
# - To obtain the Rij value for non H-bonding atoms, calculate the 
#        arithmetic mean of the Rii values for the two atom types.
#        Rij = (Rii + Rjj) / 2
#
# - To obtain the epsij value for non H-bonding atoms, calculate the 
#        geometric mean of the epsii values for the two atom types.
#        epsij = sqrt( epsii * epsjj )
#
# - Note that the Rij_hb value is non-zero for heteroatoms only, and zero for H atoms;
#        to obtain the length of an H-bond, look up Rij_hb for the heteroatom only;
#        this is combined with the Rii value for H in the receptor, in AutoGrid.
#        For example, the Rij_hb for OA-HD H-bonds will be (1.9 + 1.0) Angstrom, 
#        and the weighted epsij_hb will be 5.0 kcal/mol * FE_coeff_hbond.
#
#        Atom   Rii                             Rij_hb       rec_index
#        Type         epsii           solpar         epsij_hb    map_index
#                            vol                          hbond     bond_index
#        --     ----  -----  -------  --------  ---  ---  -  --  -- --
atom_par H      2.00  0.020   0.0000   0.00051  0.0  0.0  0  -1  -1  3    # Non H-bonding Hydrogen
atom_par HD     2.00  0.020   0.0000   0.00051  0.0  0.0  2  -1  -1  3    # Donor 1 H-bond Hydrogen
atom_par HS     2.00  0.020   0.0000   0.00051  0.0  0.0  1  -1  -1  3    # Donor S Spherical Hydrogen
atom_par C      4.00  0.150  33.5103  -0.00143  0.0  0.0  0  -1  -1  0    # Non H-bonding Aliphatic Carbon
atom_par A      4.00  0.150  33.5103  -0.00052  0.0  0.0  0  -1  -1  0    # Non H-bonding Aromatic Carbon
atom_par N      3.50  0.160  22.4493  -0.00162  0.0  0.0  0  -1  -1  1    # Non H-bonding Nitrogen
atom_par NA     3.50  0.160  22.4493  -0.00162  1.9  5.0  4  -1  -1  1    # Acceptor 1 H-bond Nitrogen
atom_par NS     3.50  0.160  22.4493  -0.00162  1.9  5.0  3  -1  -1  1    # Acceptor S Spherical Nitrogen
atom_par OA     3.20  0.200  17.1573  -0.00251  1.9  5.0  5  -1  -1  2    # Acceptor 2 H-bonds Oxygen
atom_par OS     3.20  0.200  17.1573  -0.00251  1.9  5.0  3  -1  -1  2    # Acceptor S Spherical Oxygen
atom_par F      3.09  0.080  15.4480  -0.00110  0.0  0.0  0  -1  -1  4    # Non H-bonding Fluorine
atom_par Mg     1.30  0.875   1.5600  -0.00110  0.0  0.0  0  -1  -1  4    # Non H-bonding Magnesium
atom_par MG     1.30  0.875   1.5600  -0.00110  0.0  0.0  0  -1  -1  4    # Non H-bonding Magnesium
atom_par P      4.20  0.200  38.7924  -0.00110  0.0  0.0  0  -1  -1  5    # Non H-bonding Phosphorus
atom_par SA     4.00  0.200  33.5103  -0.00214  2.5  1.0  5  -1  -1  6    # Acceptor 2 H-bonds Sulphur
atom_par S      4.00  0.200  33.5103  -0.00214  0.0  0.0  0  -1  -1  6    # Non H-bonding Sulphur
atom_par Cl     4.09  0.276  35.8235  -0.00110  0.0  0.0  0  -1  -1  4    # Non H-bonding Chlorine
atom_par CL     4.09  0.276  35.8235  -0.00110  0.0  0.0  0  -1  -1  4    # Non H-bonding Chlorine
atom_par Ca     1.98  0.550   2.7700  -0.00110  0.0  0.0  0  -1  -1  4    # Non H-bonding Calcium
atom_par CA     1.98  0.550   2.7700  -0.00110  0.0  0.0  0  -1  -1  4    # Non H-bonding Calcium
atom_par Mn     1.30  0.875   2.1400  -0.00110  0.0  0.0  0  -1  -1  4    # Non H-bonding Manganese
atom_par MN     1.30  0.875   2.1400  -0.00110  0.0  0.0  0  -1  -1  4    # Non H-bonding Manganese
atom_par Fe     1.30  0.010   1.8400  -0.00110  0.0  0.0  0  -1  -1  4    # Non H-bonding Iron
atom_par FE     1.30  0.010   1.8400  -0.00110  0.0  0.0  0  -1  -1  4    # Non H-bonding Iron
atom_par Zn     1.48  0.550   1.7000  -0.00110  0.0  0.0  0  -1  -1  4    # Non H-bonding Zinc
atom_par ZN     1.48  0.550   1.7000  -0.00110  0.0  0.0  0  -1  -1  4    # Non H-bonding Zinc
atom_par Br     4.33  0.389  42.5661  -0.00110  0.0  0.0  0  -1  -1  4    # Non H-bonding Bromine
atom_par BR     4.33  0.389  42.5661  -0.00110  0.0  0.0  0  -1  -1  4    # Non H-bonding Bromine
atom_par I      4.72  0.550  55.0585  -0.00110  0.0  0.0  0  -1  -1  4    # Non H-bonding Iodine

These are the default values that are "baked in" to AutoGrid 4 and AutoDock 4, and are the values that will be used if you do not specify your own parameter file explicitly in your GPF or DPF with the "parameter_file" command.

You can add new atom types and parameters to this file, or modify the existing ones.  If you come up with new or modified parameters, we would like to know about them, so we can incorporate them in future releases.  Thanks!

Yes, for both the macromolecule and the ligand, if you want to use the AutoDock 4 force field properly, you should always add all hydrogens, compute Gasteiger charges and then  merge the non-polar hydrogens.  This is because AutoDock 4 uses the united atom model to represent molecules, and the AD4 scoring function was calibrated using Gasteiger partial charges on both the ligand and the macromolecule.

Polar hydrogens are hydrogen atoms that are bonded to electronegative atoms like oxygen and nitrogen.  (ADT assumes that non-polar hydrogens are hydrogens bonded to carbon atoms.)

Using ADT

There is a command in ADT to help you decide on the protonation of the Histidines, but you have to load the commands before you can use it: go to "File > Load Module" and then scroll down, click on "repairCommands", and then click "Load Module" followed by "Dismiss". Now, go to "Edit > Hydrogens > Edit Histidine Hydrogens".

If there are any histidines in your molecule, a panel will open up listing each histidine residue along with a row of radio buttons. You can use these to choose whether each histidine should be neutral, HD1; neutral, HE2; or protonated.

Using Reduce/Molprobity

There is a very nice tool called Reduce (with a web-accessible front end called Molprobity) that can be used for adding hydrogens and optimising the hydrogen-bond network by flipping amido groups in Asn and Gln sidechains, and His imidazole rings by 180º. It can also be used for evaluating the quality of your protein structure. See:

Word, et al. (1999) "Asparagine and glutamine: using hydrogen atom contacts in the choice of sidechain amide orientation" J. Mol. Biol. 285, 1733-1745.

The various parameters in the AutoDock 4 scoring function are described in another FAQ, Where do I set the AutoDock 4 force field parameters?. The atom types' names and parameters are specified in a file that can be called anything, but by default is called "AD4_parameters.dat". You can find a copy of this default file in the source code of AutoGrid and AutoDock. This parameter file can be specified by the "parameter_file" keyword in the GPF and DPF, but if this keyword is not given, then AutoGrid and AutoDock use the default values. So the only time you need to use the "parameter_file" keyword is when you want to change the default values, or to add new atom types.

How do I add new atom types?

Important: Bear in mind that the AutoDock 4 scoring function was calibrated for the current set of atom types, and that if you add new ones, strictly speaking you should perform a re-calibration of the force field to determine the correct coefficients for the molecular mechanics terms and the empirical term of the linear free energy model.

You will need to find, compute or set the following values for each new atom type, which you specify after the "atom_par" keyword. Note that the values on each "atom_par" line are space delimited, not fixed width. You will need to add one "atom_par" line for every new atom type. It is possible to define 'synonyms' for atom types, by repeating the numerical atom parameter lines for every variant of the atom type's one- or two-character name.

• name of the atom type; this can be one or two characters long, and should correspond to the atom type at the end of ATOM or HETATM lines in PDBQT files; specify this in the "Atom Type" field
• van der Waals radius of the atom/ion (in Angstrom); specify twice this value in the "Rii" field
• epsilon or energy well depth for two like interacting atoms/ions (in Kcal/mol); specify in the "epsii" field
• volume of the atom/ion (in Angstrom^3); compute this from 4/3 * PI * (Rii/2)^3; specify in the "vol" field
• atomic solvation parameter of the atom/ion; the a_i or "ASP" values in the equation for S_i in the description of the Desolvation Free Energy Term in AutoDock 4; specify this in the "solpar" field
• hydrogen bonding radius (in Angstrom); for non-hydrogen-bonding atom types this is 0.0; specify this in the "Rij_hb" field
• hydrogen bonding energy well depth (in Kcal/mol); for non-hydrogen-bonding atom types this is 0.0; specify this in the "epsij_hb" field
• hydrogen bonding type; an integer; for non-hydrogen-bonding atom types this is 0; specify this in the "hbond" field
• receptor type index; an integer; default value is -1; specify this in the "rec_index" field
• grid map index; an integer; default value is -1; specify this in the "map_index" field
• bond type index; an integer; default value is 4; specify this in the "bond_index" field

The last six values (0.0 0.0 0 -1 -1 4) will be the same if the atom type is not involved in hydrogen bonding.

Note that a comment can be specified after a number sign symbol, #

Remember to use the "parameter_file AD4_parameters.dat" command in both the GPF and DPF, so that the new parameters are used in both the AutoGrid pre-calculation of the grid maps, and in the AutoDock dockings. Specify this command on the first line of the GPF and DPF files.

• If you want to download AutoDock 3 please take a look at the page on "Obtaining AutoDock 3" for more information.
• If you want to download AutoDock 4 please follow this link: Download AutoDock 4.

ADT (AutoDockTools) is distributed as part of MGLTools. It is free of charge. Click on the platform you need to download: either Unix/Linux, Windows or Mac OS X (both PowerPC and Intel versions are available). Make sure you read the "Instructions" page for the platform you decide to download. You can also download the source code.

To run AutoDock on Windows, you must first download and install Cygwin, a Linux-like environment for Windows. Cygwin is available from http://www.cygwin.com. Follow the instructions for installing and setting up Cygwin from the Cygwin web site. There is also plenty of documentation about Cygwin.

ADT runs on Windows, out of the box.

Download the AutoGrid and AutoDock binaries for Cygwin: they are called autogrid4.exe and autodock4.exe (or autogrid3.exe and autodock3.exe, depending on which version you downloaded). For AutoDock 4, you will download a file called 'autodocksuite-4.2.1-i86Cygwin.tar.gz'; choose to "Save to Disk" if asked, and save it to your Desktop. Open a Cygwin terminal and type this:

      whoami

This will tell you what your username is. In the next command change YOUR_USERNAME to whatever whoami says your username is:

      cd /cygdrive/c/Documents\ and\ Settings/YOUR_USERNAME/Desktop

Now extract the files from the .tar.gz file:

      tar xvzf autodocksuite-4.0.1-i86Cygwin.tar.gz

These are in the directory bin/i86Cygwin. Copy the AutoGrid 4 and AutoDock 4 .exe files to the /usr/local/bin directory, by typing the following at the Cygwin terminal:

     cd i86Cygwin
     cp autodock4.exe /usr/local/bin
     cp autogrid4.exe /usr/local/bin

or for AutoGrid 3 and AutoDock 3:

     cp autodock3.exe /usr/local/bin
     cp autogrid3.exe /usr/local/bin

Now open a new Cygwin terminal, and type:

      which autodock4

or for AutoDock 3:

      which autodock3

This should find /usr/local/bin/autodock4 or /usr/local/bin/autodock3. You can now tell ADT to use AutoDock from /usr/local/bin/autodock3, and AutoGrid from /usr/local/bin/autogrid3.

You should have downloaded a file with a name such as "autodocksuite-4.2.1-i86Linux2.tar.gz" for Linux, and "autodocksuite-4.2.1-i86Darwin8" or "autodocksuite-4.2.1-ppcDarwin8" for Mac OS X.

At the command line, change directory to the directory where you downloaded the file, <download-directory> (Note: you should substitute <download-directory> with the full path to where the downloaded file is):

cd <download-directory>

Now let's extract the contents from the GNU-zipped tar file; in this example, we assume you have downloaded the Linux binaries:

tar xvzf autodocksuite-4.2.1-i86Linux2.tar.gz

This will create a new directory called "i86Linux2". In it, you will find two executables, called "autodock4" and "autogrid4". Let's change directory there first:

cd i86Linux2

Now move the executables to the directory where you normally keep your binaries. On Linux and Mac OS X, this is often /usr/local/bin. The main thing is that this directory is in your path.

mv autogrid4 /usr/local/bin
mv autodock4 /usr/local/bin

Now every time you open a new shell or Terminal, you should now be able to run AutoGrid 4 and AutoDock 4.

You'll need either to build autodock from source or install the missing library. Since libstdc++.so.6 comes preinstalled with the latest Linux systems, in this case, it would be better to build autodock from source.

See also: http://mgldev.scripps.edu/pipermail/autodock/2009-June/005997.html

PDBQT Files

AutoGrid 3 uses a PDBQS file for the receptor, which stores the atomic coordinates, partial charges and solvation parameters for all the atoms in the macromolecule. AutoDock 3 uses a PDBQ file for the ligand, which stores the atomic coordinates, partial charges and a description of the rigid and rotatable parts of the molecule.

In AutoDock 4, however, we have moved to one format, PDBQT, which stores the atomic coordinates, partial charges and AutoDock atom types, for both the receptor and the ligand. This is a big improvement on AutoDock 3 when it comes to atom types: AutoDock 3 determines the atom's type by looking at the first character of the atom name; AutoDock 4 now uses one or two-character names that do not interfere or depend on the atom names. It has also meant we can increase the number of atom types, allowing us to distinguish, for example, between nitrogens that do and do not accept hydrogen bonds, for example.

Format Definition

A complete PDBQT file must have:

• partial charges.
• AutoDock 4 atom-types.

Both ligand and receptor PDBQT files used for the standard AutoDock 4 force field have additional requirements:

• Gasteiger PEOE partial charges.
• A united-atom representation (i.e. only polar hydrogens). A united atom representation can be obtained by first computing the partial charges for an all-hydrogen model of the molecule. Then, for each non-polar heavy atom that has any hydrogens bonded to it, the partial charge of the hydrogen should be added to that of the bonded heavy atom, then this hydrogen atom can be deleted.

Ligands can be treated as flexible in AutoDock, and we use the idea of a "torsion tree" to represent the rigid and rotatable pieces. There is always one "root", and zero or more "branches". Branches can be nested. Every branch defines one rotatable bond. The torsion tree is represented in the PDBQT with the following records, and the placement of these records is important, and usually means reordering the ATOM/HETATM records:

1. A ROOT record precedes the rigid part of the molecule, from which zero or more rotatable bonds may emanate.
2. The rigid root contains one or more PDBQT-style ATOM or HETATM records. These records resemble their traditional PDB counterparts, but diverge in columns 71-79 inclusive (where the first character in the line corresponds to column 1). The partial charge is stored in columns 71-76 inclusive (in %6.3f format, i.e. right-justified, 6 characters wide, with 3 decimal places). The AutoDock atom-type is stored in columns 78-79 inclusive (in %-2.2s format, i.e. left-justified and 2 characters wide..
3. An ENDROOT record follows the last atom in the rigid "root". The ROOT/ENDROOT block of atoms should be given first in the PDBQT file. The simplest way to treat a ligand is rigidly, and this would mean putting a ROOT record before the first ATOM/HETATM and an ENDROOT record after the last ATOM/HETATM.
4. Sets of atoms that are moved by rotatable bonds are enclosed by BRANCH and ENDBRANCH records. These BRANCH/ENDBRANCH blocks follow the ROOT/ENDROOT block. Both BRANCH records and ENDBRANCH records should give two integers separated by spaces, which are the serial numbers of the first and second atoms involved in the rotatable bond. The BRANCH record should be followed by the ATOM/HETATM record of the second atom in the rotatable bond. It is possible to nest BRANCH/ENDBRANCH blocks; see the example below.
5. The last atom in a branch should be followed by an ENDBRANCH record, whose serial numbers of the two atoms in the rotatable bond should match those in the corresponding BRANCH record.
6. The last line of the PDBQT file contains a TORSDOF record, which is followed by an integer. This is the number of torsional degrees of freedom in the ligand, and is independent of the number of rotatable bonds, if any, defined by the preceding records.

NOTE: the serial number is the integer in columns 7-11 inclusive of the ATOM or HETATM record; the first character in the line corresponds to column 1.

For example, in this PDBQT file, branch 15-21 is nested within branch 9-11, and means there are rotatable bonds between A9 and A11, and also A17 and C21; there is also branch 7-24, with a rotatable bond between A7 and C22:

         COMPND    NSC7810
         REMARK  3 active torsions:
         REMARK  status: ('A' for Active; 'I' for Inactive)
         REMARK    1  A    between atoms: A7_7  and  C22_23 
         REMARK    2  A    between atoms: A9_9  and  A11_11 
         REMARK    3  A    between atoms: A17_17  and  C21_21 
         ROOT
         ATOM      1  A1  INH I           1.054   3.021   1.101  0.00  0.00     0.002 A
         ATOM      2  A2  INH I           1.150   1.704   0.764  0.00  0.00     0.012 A
         ATOM      3  A3  INH I          -0.006   0.975   0.431  0.00  0.00    -0.024 A
         ATOM      4  A4  INH I           0.070  -0.385   0.081  0.00  0.00     0.012 A
         ATOM      5  A5  INH I          -1.062  -1.073  -0.238  0.00  0.00     0.002 A
         ATOM      6  A6  INH I          -2.306  -0.456  -0.226  0.00  0.00     0.019 A
         ATOM      7  A7  INH I          -2.426   0.885   0.114  0.00  0.00     0.052 A
         ATOM      8  A8  INH I          -1.265   1.621   0.449  0.00  0.00     0.002 A
         ATOM      9  A9  INH I          -1.339   2.986   0.801  0.00  0.00    -0.013 A
         ATOM     10  A10 INH I          -0.176   3.667   1.128  0.00  0.00     0.013 A
         ENDROOT
         BRANCH   9  11  
         ATOM     11  A11 INH I          -2.644   3.682   0.827  0.00  0.00    -0.013 A
         ATOM     12  A16 INH I          -3.007   4.557  -0.220  0.00  0.00     0.002 A
         ATOM     13  A12 INH I          -3.522   3.485   1.882  0.00  0.00     0.013 A
         ATOM     14  A15 INH I          -4.262   5.209  -0.177  0.00  0.00    -0.024 A
         ATOM     15  A17 INH I          -2.144   4.784  -1.319  0.00  0.00     0.052 A
         ATOM     16  A14 INH I          -5.122   4.981   0.910  0.00  0.00     0.012 A
         ATOM     17  A20 INH I          -4.627   6.077  -1.222  0.00  0.00     0.012 A
         ATOM     18  A13 INH I          -4.749   4.135   1.912  0.00  0.00     0.002 A
         ATOM     19  A19 INH I          -3.777   6.285  -2.267  0.00  0.00     0.002 A
         ATOM     20  A18 INH I          -2.543   5.650  -2.328  0.00  0.00     0.019 A
         BRANCH  15  21 
         ATOM     21  C21 INH I          -0.834   4.113  -1.388  0.00  0.00     0.210 C
         ATOM     22  O1  INH I          -0.774   2.915  -1.581  0.00  0.00    -0.644 OA
         ATOM     23  O3  INH I           0.298   4.828  -1.237  0.00  0.00    -0.644 OA
         ENDBRANCH  15  21 
         ENDBRANCH   9  11  
         BRANCH   7  24  
         ATOM     24  C22 INH I          -3.749   1.535   0.125  0.00  0.00     0.210 C
         ATOM     25  O2  INH I          -4.019   2.378  -0.708  0.00  0.00    -0.644 OA
         ATOM     26  O4  INH I          -4.659   1.196   1.059  0.00  0.00    -0.644 OA
         ENDBRANCH   7  24  
         TORSDOF 3

Yes, there is a limit on the number of atoms in the ligand.  By default, the maximum number of atoms is 2048.

This limit is specified in the source code in the file 'constants.h', by the 'MAX_ATOMS' definition:

#define MAX_ATOMS    2048     /* Maximum number of atoms in Small Molecule. */

The path to the constants file is 'autodocksuite-4.0.1/src/autodock-4.0.1/constants.h'.  If you change this line, make sure to change the 'MAX_RECORDS' definition to match the same value as MAX_ATOMS.

The overall flexibility pattern encoded in a ligand pdbq(t) file can visualized using ADT.

• To do so:

1. Read the previously-formatted-ligand molecule into ADT using File->Read Molecule
2. Choose it to be ligand using Ligand->Choose
3. You will then be given the choice of whether or not to  'Use Previous Torsion Tree'

=> choose Yes
    4.  You can then see which torsions are active using Ligand->Torsion Tree->Choose Torsions....

• Another  way to determine whether a bond is treated as rotatable in ligand pdbq(t) file is to edit the file and look at the BRANCH statements, searching for the numbers of the two atoms in that specific bond.  Each BRANCH statement corresponds to one rotatable bond.  The  BRANCH statement includes the numbers of the corresponding atoms.  For example,  a bond between atoms numbered 12 and 27 is rotatable if the statement BRANCH 12 27 appears in the pdbq(t) file.

The host (moses=>mgl) and the path (/export/cvs=>/opt/cvs) have been changed. If you are using "bash", please use:

export CVSROOT=:pserver:anonymous@mgl1.scripps.edu:/opt/cvs

If you are using "csh" or "tcsh", use:

setenv CVSROOT :pserver:anonymous@mgl1.scripps.edu:/opt/cvs

http://mgltools.scripps.edu/documentation/how-to/access-to-cvs

You can also download VSTutorial.tar.gz (13 MB) - snapshot from CVS created on Jan 25 2008.

The default size for something called the "stack" on Linux and Mac OS X is too small for AutoDock to run. You need to tell the system to remove this limit, and this depends on which shell you are using. You can find out what shell you are running by typing:

  echo $SHELL

in a terminal.

If you are using "csh" or "tcsh", you should put this command:

  limit stacksize unlimited

in your "~/.cshrc" or "~/.tschrc", whichever one you have.

If you are using "sh" or "bash" (the default shell on many Linuxes and now on the latest version of Mac OS X, 10.3, aka Panther), then put this command:

  ulimit -s unlimited

in your "~/.bashrc" or "~/.bash_profile". (Note: Some people running Mandrake 9.1 have reported ulimit -s 131072 works better than ulimit -s unlimited .)

Either way, remember you will need to source your ".cshrc" or ".bash_profile" before this will take effect. Type source .cshrc or source .bash_profile at the prompt in the terminal. Now try running AutoDock again, everything should work properly now. (For the curious, you can type limit (csh & tcsh) or ulimit -a (sh & bash) and you will see what the value of the stack size is.)

Before You Start AutoDock 3

You need AutoGrid 3 grid maps that have been computed for the receptor you want to dock to.

AutoGrid 3

To run AutoGrid 3, you need:

• a grid parameter file, or GPF; let's say it is called my_receptor.gpf
• a receptor file in PDBQS format--the receptor can be a protein, DNA, RNA or other macromolecule.

Once you have these files, you can type the following at the command line:

     autogrid3 -p my_receptor.gpf -l my_receptor.glg &

AutoGrid 3 uses the following flags:

• -p specifies the name of the GPF (grid parameter file) that will be read in by AutoGrid 3
• -l specifies the name of the GLG (grid log file) that will be created by AutoGrid 3

AutoDock 3

Before you can start AutoDock 3, you need:

• a docking parameter file, or DPF; let's say it is called my_docking.dpf
• a ligand saved as a PDBQ file
• a set of grid maps calculated by AutoGrid 3; this includes:
  • the map files (extension ".map")
  • the grid size file (extension ".xyz")
  • the grid field file (extension ".fld")

Once you have these files, you can type the following at the command line:

     autodock3 -p my_docking.dpf -l my_docking.dlg &

Take a look at the AutoDock 3 User's Guide for more details.

Before You Start AutoDock 4

You need AutoGrid 4 grid maps that have been computed for the receptor you want to dock to.

AutoGrid 4

To run AutoGrid 4, you need:

• a grid parameter file, or GPF; let's say it is called my_receptor.gpf
• a receptor file in PDBQT format--the receptor can be a protein, DNA, RNA or other macromolecule.

Once you have these files, type the following at the command line:

     autogrid4 -p my_receptor.gpf -l my_receptor.glg &

AutoGrid 4 uses the following flags:

• -p specifies the name of the GPF (grid parameter file) that will be read in by AutoGrid 4
• -l specifies the name of the GLG (grid log file) that will be created by AutoGrid 4

AutoDock 4

Before you can start AutoDock 4, you need:

• a docking parameter file, or DPF; let's say it is called my_docking.dpf
• a ligand saved as a PDBQT file
• optionally, a flexible residues file saved in PDBQT format, holding the atoms in the receptor that will be treated as moving
• a set of grid maps calculated by AutoGrid 4; this includes:
  • the map files (extension ".map")
  • the grid size file (extension ".xyz")
  • the grid field file (extension ".fld")

Once you have these files, you can type the following at the command line:

     autodock4 -p my_docking.dpf -l my_docking.dlg &

Here is part of a typical DPF (docking parameter file) for AutoDock:

ga_pop_size 150                      # number of individuals in population
ga_num_evals 25000000                # maximum number of energy evaluations
ga_num_generations 27000             # maximum number of generations
ga_elitism 1                         # number of top individuals to survive to next generation
ga_mutation_rate 0.02                # rate of gene mutation
ga_crossover_rate 0.8                # rate of crossover
ga_window_size 10                    #
ga_cauchy_alpha 0.0                  # Alpha parameter of Cauchy distribution
ga_cauchy_beta 1.0                   # Beta parameter Cauchy distribution
set_ga                               # set the above parameters for GA or LGA
sw_max_its 300                       # iterations of Solis & Wets local search
sw_max_succ 4                        # consecutive successes before changing rho
sw_max_fail 4                        # consecutive failures before changing rho
sw_rho 1.0                           # size of local search space to sample
sw_lb_rho 0.01                       # lower bound on rho
ls_search_freq 0.06                  # probability of performing local search on individual
set_sw1                              # set the above Solis & Wets parameters

The parameters that begin with 'ga_' control the genetic algorithm, while the parameters that begin with 'sw_' control the Solis and Wets local search method.  This block of parameters, along with the "set_ga" and "set_sw1" commands, tells AutoDock to run a hybrid global-local search, i.e. Lamarckian GA.

Which parameters are the most important?

The  parameters that control how long the GA and LGA runs are 'ga_num_evals' and 'ga_num_generations'.  AutoDock stops a docking if either the maximum number of evaluations or the maximum number of generations is reached, whichever comes first.  In this case, the docking would terminate based on reaching the maximum number of energy evaluations, namely 25 million evals, since there are fewer than 27000 generations in these runs.  An energy evaluation is performed every time the GA or the local search computes the fitness of a candidate docking.  If there is a population of 150, as specified by the 'ga_pop_size' parameter, then every generation, there will be 150 energy evaluations to compute the fitness of all the members of the population; if there is any local search, then the proportion of the population set by the 'ls_search_freq' parameter will undergo local searches.  Here, the local search frequency is set to 0.06, so 6% of 150 individuals, or 9 individuals, will undergo local search.  In this example the number of local search iterations is set to 300, using the 'sw_max_its' parameter, so each of these 9 local searches could consume up to 300 energy evaluations each.  Note that the Solis and Wets local search method changes the step size during the search, and it will terminate if the current step size becomes smaller than 'sw_lb_rho', which here is set to 0.01; it will also terminate if the maximum number of iterations, 'sw_max_its', is exceeded, whichever condition is reached first.

The number of energy evaluations needed for a docking will depend on the number of torsions in the ligand (and receptor, if it is flexible).  For rigid ligands and rigid receptors, here are some general guidelines:

Number of Torsions	ga_num_evals	ga_num_generations
0	25 000  to  250 000	27 000
1-10	250 000  to  25 000 000	27 000
>10	>25 000 000	27 000

There are some AutoDock users who prefer to set 'ga_num_evals' to a very large number and then set the 'ga_num_generations' parameter to a number in the range of 500 to 1000.  There are no hard-and-fast rules here, and it is well worth trying a few variations of parameters on your own docking problem before settling on your best values.

It is worth noting that Hetenyi et al. showed that for the same docking, keeping everything else constant, increasing  'ga_pop_size' from 50 to 300 in steps of 50, that they got the most robust docking results with a population size of 300.  You may want to increase the default from 150 to 300, and see if you get better docking results.

How many dockings should I run?

The more dockings you do, the better your statistics and clustering are likely to be.  We recommend you run at least 50 dockings, specified by the  'ga_run' parameter. Make sure that each AutoDock process starts with different random number generator (RNG) seeds.  If you use the default 'seed pid time', the RNG will be seeded with the current AutoDock process ID and the number of seconds since 0 hours, 0 minutes, 0 seconds, January 1, 1970, Coordinated Universal Time, without including leap seconds.

References

Hetenyi, C. and van der Spoel, D. (2002) Efficient docking of peptides to proteins without prior knowledge of the binding site. Protein Science, 11(7): 1729-1737.

Whatever you have specified as flexible will be energy minimised: at least the ligand, and if you have any, the flexible sidechains you have specified with the "flexres" keyword in the DPF. The energy minimisation will be performed in the context of the grid maps you have calculated for the receptor. So you could use this command to optimise the position, orientation and conformation of a ligand in an active site, to remove any bad contacts that may be present in an x-ray crystal structure.

The ligand's position, orientation and torsion angles (if flexible) will be optimised, in addition to any flexible sidechains' torsion angles if specified.

The starting point of the ligand can be controlled by the "tran0", "quaternion0" and "dihe0" keywords in the AutoDock 4 DPF. (Note that in AutoDock 3, the orientation is specified using the "quat0" keyword.)

• To keep the ligand's input position the same as in the ligand PDBQT, use the same "tran0" x,y,z values as those specified in the "about" line of the DPF.
• To keep the ligand's input orientation, use "quaternion0 1. 0. 0. 0.".
• To keep the input conformation, use "dihe0" with a "0." value for every torsion in the ligand.

The easiest way is to edit the file adthosts.py from the AutoDockTools folder and replace autogrid3/autodock3.

#AutoDockTools/adthosts.py
hostMacros = {
    'localhost': { 'host' : 'localhost',
		   'autogrid' : 'autogrid3', # replace autogrid3 with autogrid4 path
                   'autodock' : 'autodock3', # replace autodock3 with autodock4 path
                   'queuetype' : 'int',
                   'userSpecific' : 0 },
    }

The problem with this approach is that when you update ADT using Help->Update menu, you need to redo this for the updated adthosts.py as well. The other way to make ADT remember the path is to create a file called _adtrc in the current working directory and paste the following code in there:

import socket
localhost = socket.gethostbyname_ex(socket.gethostname())[0] 
self.ADstart_editHostMacros.addItem_cb(macro=localhost, host=localhost,autogrid='autogrid4',autodock='autodock4',queuetype='int',userSpecific=0)

Since ADT runs _adtrc when it starts up, this approach should survive across updates.

You should always start ADT in the same directory as the macromolecule and ligand files you want to dock. You can start ADT from the command line in a Terminal by typing “adt” and pressing <Return> or <Enter>.

If you want to try and find novel compounds, you probably want to use a library designed for diversity, one which probes a large chemical space. If there are small molecules which are known to bind to your macromolecule, you may want to construct a tailored library of related compounds.

This will depend on your receptor and the computational resources available to you. One recent successful AutoDock virtual screening used 100 dockings per compound with 5,000,000 energy evaluations per docking. (Chenglong Li, Lan Xu, Dennis W. Wolan, Ian A. Wilson, and Arthur J. Olson (2004) "Virtual Screening of Human 5-Aminoimidazole-4-carboxamide Ribonucleotide Transformylase against the NCI Diversity Set by Use of AutoDock to Identify Novel Nonfolate Inhibitors" J. Med. Chem., 47: 6681-6690)

When the results are sorted by lowest energy found for each compound, the compounds that bind as well as your positive control or better can be considered as potential hits. Remember to allow for the roughly 2.5 Kcal/mol standard error in the AutoDock scoring function. If you do not have a positive control, consider the compounds with the lowest energies as potential hits.

Note: You may also want to consider the lowest energy in the most populated cluster in your docking results, instead of the lowest energy found for all the dockings of a given compound.

One way is to sort the compounds by lowest energy first. An alternative is to sort the compounds by the lowest energy in the largest cluster (typically clustering using an RMSD tolerance of 2 Angstroms).

Follow up the sorting by using ADT to inspect visually the chemical complementarity of the binding modes.

Generally, it is wise to inspect the top 30 to 50 results. Some practitioners advocate visually inspecting the top 100-150 hits.

ADT

• We recommend you download ADT (short for "AutoDockTools") which we have developed just for this purpose. ADT is part of the MGLTools and it runs on Windows, Linux and Mac OS X. (You need X11 on Mac OS X). Use the menu option "Analyze > Dockings > Open..." for one DLG, or "Analyze > Dockings > Open All..." for many DLGs containing docking results of the same ligand and target, as you might obtain from running a docking in parallel on a cluster.

Open a DLG (docking log) in a text editor and search for the word "HISTOGRAM", and if you used the "analysis" keyword in your DPF (docking parameter file), then you will find AutoDock's conformational clustering histogram. This sorts the docking results into conformationally similar bins, according to the RMSD tolerance you set using the rmstol keyword, and according to whether you used the rmsnosym command. (By default, AutoDock tries to compute the minimum RMSD by taking into consideration the symmetry in the molecule, and works well if the two conformations are very similar; using the rmsnosym command guarantees that a 1-to-1 correspondence of atoms is considered in computing the RMSD. ADT does not consider symmetry in the RMSD calculations in clustering, and uses the same algorithm as the rmsnosym command.)

NOTE: by default, AutoDock 4 uses only the ligand atoms for the cluster analysis, if you have sidechains that are flexible in the receptor . You can use the new command rmsatoms all to include all the moving atoms in the RMSD calculation; the alternative form of the command, rmsatoms ligand_only computes the RMSD for only the atoms in the ligand, although this command is not necessary since this is the default.

If you find more than one cluster, which one should you choose?

The answer depends on a number of factors: first of all, it's best to have done at least 50 runs, to get a good sampling of results to cluster (I prefer to do at least 100 dockings). Also, use an RMSD tolerance that is appropriate for the size of your ligand: larger ligands need larger rmstol values, typically at least 2 Angstroms.

The next question is, did each docking search for long enough? In other words, did the number of energy evaluations (ga_num_evals in GA and LGA dockings; cycles, accs and rejs in SA dockings) match the dimensionality of the search problem? This depends on the number of torsions in the ligand (and protein, if flexible), and how these torsions are arranged in the molecule (are they arranged linearly, or are they nested?). Ideally, if you run a docking for long enough, you should always converge on the lowest energy solution, and obtain just one cluster.

However, if you obtain two or more clusters, and the lowest-energy cluster is less populated than another cluster with higher energy, which one is the "right" answer? What happens to the clustering results if you increase the number energy evaluations? Does the size of the lowest energy cluster increase to exceed the number in the other cluster?

Which cluster you choose should also depend on a visual inspection of the binding modes, comparing how the ligand interacts with the receptor. Does one binding mode look more chemically-reasonable than the other(s)?

Also bear in mind that the if the difference in the energies between the mean energies of the two clusters is less than about 2.5 kcal/mol, this is within the standard deviation of the AutoDock force field, and it is difficult to say which one is the "correct" one.

If you have two ligands, and they bind to the same receptor, but one forms just one cluster, while the other forms more than one cluster, yet they both bind with about the same estimated binding free energy, which one will be better? This is a key question that we are currently investigating ways to quantify: stay tuned!

After you extract the docked conformations from the AutoDock log file using get-dockings, you obtain a PDB formatted file that contains the docked conformations of the ligand. These are sorted in order of increasing energy, and in accordance with the conformational clustering. This PDB file puts each docked conformation in between MODEL and ENDMDL records. This file does not contain the macromolecule coordinates which you docked to. Don't Panic! These are still in the original PDBQS file you used to generate the AutoGrid maps. In other words, the output docked coordinates of the ligand are written in the same reference frame as the original macromolecule PDBQS.

To view the dockings in relation to the macromolecule, in InsightII 2000, for example, read in the PDB file of MODELs first (with "Keep all frames" turned on). Then read in the macromolecule PDBQS file using the first docked conformation as the "Reference" structure. You can read in the PDBQS file as a PDB formatted file (it works in InsightII, except you do not see PDBQS files in the file browser: you must type in the PDBQS file name yourself.) You should now see the macromolecule and the docked conformations together.

Alternatively, you can add the macromolecule and the docked conformations together into one PDB file that contains everything. At the UNIX prompt, type this:

  % get-dockings mydocking.dlg 
  % pdbqtopdb mymacromolecule.pdbqs >> mydocking.dlg.pdb

This will append the macromolecule (in PDB format) to the stacked MODELs in the "mydocking.dlg.pdb" file, so you can now read in this file and you should see everything together.

The "Reference RMSD" values that are printed in the "RMSD TABLE" in the DLG are computed from the coordinates of

• either the input ligand (PDBQ or PDBQT) file specified by the "move" command in the DPF, if you did not include the "rmsref" command in your DPF;
• or the ligand (PDBQ or PDBQT) file you specified in the "rmsref" command in the DPF.

If you do not specify the "rmsref" command, and the ligand input coordinates happen to be translated far from the receptor, you will appear to get high Reference RMSD values. _Don't Panic!_ This is normal, and you don't need to worry about these high values.

You may want to check that the input ligand coordinates are far from the crystallographically observed binding position in active site, by reading in the input ligand and the receptor in ADT.

We usually use the "rmsref" DPF-command to specify the x-ray crystallographic coordinates of a known binding mode taken from a complex PDB structure. This can be a useful way of checking if your redocking is successful, if the Reference RMSD values are less than 2-3 Å from the crystal structure position of the ligand.

Extracting Dockings from DLG Files

AutoDock 4 writes out the coordinates of the atoms in the ligand (and any moving parts of the receptor, if you are doing a flexible sidechain docking). It does not write out the coordinates of the fixed part of the receptor. Each docked conformation is written in PDBQT format in the DLG (docking log file). (Note that AutoDock 3 writes in PDBQ format). So if you did 10 dockings, there should be 10 different docked conformations in the DLG.

Each line of the PDBQT-formatted docked conformation is prefixed by the string "DOCKED: ", so it is possible to extract these lines from the DLG using a couple of simple UNIX commands. You need to go to the UNIX/Linux/Cygwin/Mac OS X Terminal and change directory (cd) to the directory that contains your DLG, then type the following line at the command line and press < Return > (substitute my_docking.dlg with the name of your DLG):

    grep '^DOCKED' my_docking.dlg | cut -c9- > my_docking.pdbqt

The grep command is a UNIX command that prints lines that match a pattern. Here, the pattern is ^DOCKED, and the ^ or caret symbol (Shift-6 on most keyboards) means "at the start of the line", so this pattern matches all lines that begin with the prefix "DOCKED". The | character (Shift-\ or Shift-backslash) is called a pipe, and it takes the output of the command on its left and feeds it into the input of the command on the right. The cut command selects portions of each line, and the flag -c9- means "cut out all the characters after column 9', which has the effect of removing the "DOCKED: " prefix from the line. The last part of the command, > my_docking.pdbqt, uses the > redirect command (Shift-. = greater-than symbol) to save the output into a new file called my_docking.pdbqt.

Converting from PDBQT to PDB

To convert from PDBQT format to PDB format, the simplest thing to do is to remove the charge (Q) and atom type (T) columns; this can be achieved using a simple UNIX command. Make sure you are in the same directory where you created my_docking.pdbqt, and type:

    cut -c-66 my_docking.pdbqt > my_docking.pdb

This will create a PDB file, containing all of the docking results. Each docking will appear as a single "MODEL", which is the PDB record usually used to denote an NMR model. Each "MODEL" will contain the ligand and any moving parts of the receptor. If you would like to view the models in this PDB file, you can go load the multi-model PDB file in a program like "PyMol"http://pymol.sourceforge.net/ and then click on the "Play" button to play through all the docked conformations. Click the "Stop" button to halt the play-back, and click on the ">" and "<" buttons to step through the conformations one-at-a-time. It is possible to load the PDB file of the receptor, too, to see how the ligand interacts.

Splitting a Multi-Model PDB File into Separate PDB Files

If you want to split the PDB file that contains all the docked conformations, my_docking.pdb, into separate PDB files each containing just one docking, then use these commands:

    set a=`grep ENDMDL my_docking.pdb | wc -l`
    set b=`expr $a - 2`
    csplit -k -s -n 3 -f my_docking. mydocking.pdb '/^ENDMDL/+1' '{'$b'}'
    foreach f ( mydocking.[0-9][0-9][0-9] )
      mv $f $f.pdb
    end

For example, if there were 50 ENDMDL records in the file my_docking.pdb, these commands would create 50 separate PDB files numbered from 000 to 049, and they would be named my_docking.000.pdb, my_docking.001.pdb, my_docking.002.pdb and so on, all the way up to my_docking.049.pdb.

Creating a PDB File of the Complex

To create a single PDB file that contains a complex of both the the receptor and all the models of the docked ligand, you can use the following command to combine the PDB file of the receptor (receptor.pdb) and all the docked conformations of the ligand stored in 'my_docking.pdb':

    cat receptor.pdb my_docking.pdb | grep -v '^END   ' | grep -v '^END$' > complex.pdb

This uses the UNIX cat command which concatenates files together. This command will create a new PDB file called complex.pdb.

To create a PDB file that contains a complex of both the receptor and a single ligand, then use the commands for splitting the multi-model docked PDB file, select the docked conformation of the ligand, and then use the following command to combine the PDB file of the receptor (receptor.pdb) and the docked conformation of the ligand; say we chose the ligand conformation in 'my_docking.042.pdb':

    cat receptor.pdb my_docking.042.pdb | grep -v '^END   ' | grep -v '^END$' > complex.pdb

This uses the UNIX cat command which concatenates files together, and the grep command with the -v flag which extracts all the lines except lines containing the END record. This command then creates a new PDB file called complex.pdb, that contains the coordinates of the receptor, followed by all the models of the docked ligand stored in the PDB file my_docking.pdb.

The first thing to check is that the ligand fits into some kind of pocket on the receptor. The second is that there is a chemical match between the atoms in the ligand and those in the receptor. For example, check that carbon atoms in the ligand are near hydrophobic atoms in the receptor, while nitrogens and oxygens in the ligand are near complementary hydrogen bonding atoms. Check for charge complementarity. Also consider whatever else you may know about your particular system: for instance, if you know the mechanism of action of the enzyme and which residues are involved, examine how the ligand binds to these residues. In the case of HIV-1 Protease, good inhibitors bind in a mode that mimics the transition state, placing a hydroxyl group near the two catalytic aspartic acid sidechains.

In AutoDock 4, conformational clustering is performed after all the dockings have finished if the keyword analysis is given in the docking parameter file (DPF).

By default, only the atoms in the moving ligand (defined by the move keyword in the DPF) are used in the RMSD clustering calculations. There is a DPF keyword, rmsatoms that can take the argument all, that tells AutoDock 4 to include the atoms in the flexible residues in the receptor in the RMSD calculations for the clustering.

1. AutoDock uses a random number generator to create new poses for the ligand
during its search. 

2. The random number generator used by AutoDock produces a sequence of random
numbers based on two initial seeds. The new conformations for the search are
created using this sequence of random numbers to set location, orientation and
torsion values.

3. The default values for these two seeds are 'pid' and 'time'. Process id
and time vary between AutoDock calculations.

4. Therefore, the sequence of random numbers is different between different
AutoDock calculations. As a result, the 'search' is encountering a different
set of random conformations. Thus the results differ.

Please note, it is possible to specify the seeds explicitly. In this case,
multiple AutoDock calculations should give the same, albeit restricted, results.

A separate consideration is that convergence of the docked results is an
indication of the thoroughness of the search.  If the dockings in a single
AutoDock calculation vary greatly, possibly the the search hasn't been
thorough enough to find the minima in the energy landscape for a particular
docking problem.  In this case, the search may need to be extended by
increasing the number of energy evaluations or the number of generations.