Sebastian Raschka, last updated: 05/13/2015
#Table of Contents
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License: free, open-source (GNU GPL)
A molecular docking and scoring tool that uses a computationally (relatively) inexpensive "hybrid" force field that contains terms based on molecular mechanics as well as empirical terms. The prediction of absolute binding energies may be less accurate compared to more computationally expensive, purely force field-based methods, but this semi-empirical approach is considered as well-suited for the relative rankings.
It was succeeded by AutoDock Vina, which replaced the semi-empirical force field by an entirely knowledge-based, statistical scoring function. The authors highlight the improved speed and accuracy of AutoDock Vina, however, AutoDock 4.2 provides a more detailed output that might be useful for certain applications.
Website: http://autodock.scripps.edu/downloads/autodock-registration/autodock-4-2-download-page/
Huey, Ruth, Garrett M. Morris, Arthur J. Olson, and David S. Goodsell. 2007. “A Semiempirical Free Energy Force Field with Charge-Based Desolvation.” Journal of Computational Chemistry 28 (6): 1145–52. doi:10.1002/jcc.20634.
Usage for re-scoring:
Since the procedure involves several steps, please an usage example in this separate document.
Example output:
Total Intermolecular Interaction Energy = -3.1862 kcal/mol
Total Intermolecular vdW + Hbond + desolv Energy = -0.2499 kcal/mol
Total Intermolecular Electrostatic Energy = -2.9362 kcal/mol
Total Intermolecular + Intramolecular Energy = -5.6314 kcal/mol
epdb: USER Estimated Free Energy of Binding = -1.40 kcal/mol [=(1)+(2)+(3)-(4)]
epdb: USER Estimated Inhibition Constant, Ki = 94.72 mM (millimolar) [Temperature = 298.15 K]
epdb: USER
epdb: USER (1) Final Intermolecular Energy = -3.19 kcal/mol
epdb: USER vdW + Hbond + desolv Energy = -0.25 kcal/mol
epdb: USER Electrostatic Energy = -2.94 kcal/mol
epdb: USER (2) Final Total Internal Energy = -2.45 kcal/mol
epdb: USER (3) Torsional Free Energy = +1.79 kcal/mol
epdb: USER (4) Unbound System's Energy [=(2)] = -2.45 kcal/mol
Version:
AutoDock 4.2 Release 4.2.5.1
License: free, open-source (Apache license)
The successor of AutoDock4.2 for docking and re-scoring protein-ligand complexes with a scoring function that estimates the binding affinities, as well as individual terms, such as hydrophobic contribution and hydrogen bonding.
Website: http://vina.scripps.edu
O. Trott, A. J. Olson, AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading, Journal of Computational Chemistry 31 (2010) 455-461
Usage for re-scoring:
vina --config config.txt --score_only
Where a config.txt file has to be prepared for every protein-ligand complex, e.g.,
receptor = protein.pdbqt
ligand = ligand.pdbqt
center_x = -2.491 # Center of Grid points X
center_y = 30.038 # Center of Grid points Y
center_z = -10.765 # Center of Grid points Z
size_x = 25 # Number of Grid points in X direction
size_y = 25 # Number of Grid points in Y Direction
size_z = 25 # Number of Grid points in Z Direction
The required pdbqt files can be generated via e.g., OpenBabel or AutoDock's MGLTools.
For more details, please see the documentation for
Version:
vina --version
AutoDock Vina 1.1.2 (May 11, 2011)
License: free without any limitations (redistribution requires permission)
DrugScoreX is a new, independent DrugScore implementation with higher accuracy for scoring protein-ligand complexes. It's scoring function is based on statistical potentials.
Website: http://pc1664.pharmazie.uni-marburg.de/drugscore/
DSX: A Knowledge-Based Scoring Function for the Assessment of Protein–Ligand Complexes Gerd Neudert and Gerhard Klebe Journal of Chemical Information and Modeling 2011 51 (10), 2731-2745
Usage:
dsx_mac_64.mac -h
...
pro_file : A pdb or mol2 file of your protein.
In pdb format metals in this file will be treated as part
of the protein. => Be sure to delete metals in the pdb file
if you want to supply some metals seperately (-M met_file)!
All other HETATMs will be ignored!
In mol2 format everything will be taken as part of the
protein. => Be sure to delete molecules you want to supply
seperately (-C, -W, -M) from the protein-mol2-file!
lig_file : A mol2- or autodock dlg-file containing all molecules that
should be scored.
...
Version:
dsx_mac_64.mac -h
+---------------------------------------------------------------------------+
| 'DSX' Knowledge-based scoring function for the assessment |
| of receptor-ligand interactions |
| author : Gerd Neudert |
| supervisor : Prof. Dr. G. Klebe ___ _ _ |
| mailto : neudert@staff.uni-marburg.de ))_ )\`) |
| version : 0.88 (26.04.2011) ((_( o ((\( o |
+---------------------------------------------------------------------------+
Example:
dsx_mac_64.mac -P protein.pdb -L ligand.mol2 -D pdb_pot_0511
The directory with the PDB potentials is typically located in the main directory after downloading DrugScoreX
dsx/
ACC_DON_AnD_HYD_ARO_map.def
mac64/ # directory that contains the binaries
README.txt
pdb_pot_0511/ # potentials
License: free, open-source (GNU GPL)
Like DrugScore, a scoring function for protein-ligand complexes based on statistical potentials. It is available as standalone (IMP toolkit) and as webserver.
The two flavors are RankScore, which is recommended for scoring different ligands in a protein-binding interface (e.g., for virtual screening), and PoseScore, for finding the optimal binding pose of a set of ligand decoys (i.e., the same ligand in different orientations/conformations).
Website: http://salilab.org/imp/ (for IMP package)
Webserver: http://modbase.compbio.ucsf.edu/ligscore/
Fan H, Schneidman-Duhovny D, Irwin J, Dong GQ, Shoichet B, Sali A. Statistical Potential for Modeling and Ranking of Protein-Ligand Interactions. J Chem Inf Model. 2011, 51:3078-92.
Usage:
Requires installation of the IMP toolkit
ligand_score -h
Usage: ligand_score file.mol2 file.pdb [libfile]
Where protein_ligand_pose_score.lib is used for scoring different ligand poses (PoseScore) for the same protein-ligand complex, and protein_ligand_rank_score.lib (RankScore) is used to score different ligands for a given binding interface.
(On a Mac, the library files are typically located at: /usr/local/share/IMP/atom/protein_ligand_pose_score.lib and /usr/local/share/IMP/atom/protein_ligand_rank_score.lib)
"Two different scoring files are provided: - protein_ligand_pose_score.lib for use when one wants to find the most near-native poses of a ligand from many geometry decoys of the same ligand - protein_ligand_rank_score.lib for use when screening a compound database against a single protein to choose putative binders"
Source: http://svn.salilab.org/imp/trunk/applications/ligand_score/README.md
(On a Mac, the library files are typically located at: /usr/local/share/IMP/atom/protein_ligand_pose_score.lib and /usr/local/share/IMP/atom/protein_ligand_rank_score.lib)
Example:
ligand_score my.mol2 my.pdb /usr/local/share/IMP/atom/protein_ligand_pose_score.lib
Version:
Not individually available for ligand_score, see IMP version (IMP 2.2.0).
License: Available free of charge for academic institutions, but there is a licensing fee for industrial organizations.
DOCK 6 is a docking tool that also offers several different scoring functions that can be used for re-scoring already docked protein-ligand complexes. Below is an example for how to use Amber score (more details can be found in the DOCK6 manual at http://dock.compbio.ucsf.edu/DOCK_6/dock6_manual.htm#Scoring.
dock6 -h -------------------------------------- DOCK v6.7 Released February 2015 Copyright UCSF -------------------------------------- Usage: dock6 -i filename.in [-o filename.out] [-v]
Example:
Amber score performs minimization, a Molecular Dynamics simulation, energy minimization on protein ligand complex, and a more detailed tutorial about how the score is calculated from the different energy terms can be found at http://dock.compbio.ucsf.edu/DOCK_6/tutorials/amber_score/amber_score.htm.
For the following example, assume that we have prepared the protein and ligand accordingly, i.e., we removed ligands, metals, and water molecules from the protein PDB file and assigned the correct protonations states for histidine residues.
prepare_amber.pl lig.mol2 1a9x.pdb
(The perl script prepare_amber.pl should be located in the directory of the DOCK6 binary files, dock6/bin)
Next, we create a dock.in file that has the following contents:
ligand_atom_file lig.amber_score.mol2 limit_max_ligands no skip_molecule no read_mol_solvation no calculate_rmsd no use_database_filter no orient_ligand no use_internal_energy no flexible_ligand no bump_filter no score_molecules yes contact_score_primary no contact_score_secondary no grid_score_primary no grid_score_secondary no multigrid_score_primary no multigrid_score_secondary no dock3.5_score_primary no dock3.5_score_secondary no continuous_score_primary no continuous_score_secondary no descriptor_score_primary no descriptor_score_secondary no gbsa_zou_score_primary no gbsa_zou_score_secondary no gbsa_hawkins_score_primary no gbsa_hawkins_score_secondary no SASA_descriptor_score_primary no SASA_descriptor_score_secondary no amber_score_primary yes amber_score_secondary no amber_score_receptor_file_prefix 1a9x amber_score_movable_region ligand amber_score_minimization_rmsgrad 0.01 amber_score_before_md_minimization_cycles 100 amber_score_md_steps 3000 amber_score_after_md_minimization_cycles 100 amber_score_gb_model 5 amber_score_nonbonded_cutoff 18.0 amber_score_temperature 300.0 amber_score_abort_on_unprepped_ligand yes ligand_outfile_prefix output write_orientations no num_scored_conformers 1 rank_ligands no
In the last step, we use the dock6 executable to re-score the complex using the dock.in file.
dock6 -i dock.in > dock.out
At the bottom of the dock.out file, we find the Amber scores:
[...]
Molecule: *****
Elapsed time for docking: 34 seconds
Anchors: 1
Orientations: 1
Conformations: 1
Amber Score: -19.431744
complex: 50250.946122
receptor: -50307.949484
ligand: 37.571619
1 Molecules Processed
Total elapsed time: 41 seconds
Version:
DOCK v6.7
License: free, open-source (GNU GPL)
A conversion tool for different file formats. Comes with standalone binaries and APIs for various programming languages.
Website: http://openbabel.org
O'Boyle, Noel M., Michael Banck, Craig A. James, Chris Morley, Tim Vandermeersch, and Geoffrey R. Hutchison. “Open Babel: An Open Chemical Toolbox.” J Cheminf 3 (2011): 33.
Usage:
babel -H
Open Babel converts chemical structures from one file format to another
Usage: babel <input spec> <output spec> [Options]
Example:
babel -i mol2 my.mol2 -o pdbqt my.pdbqt
Version:
babel
No output file or format spec!
Open Babel 2.3.1 -- Oct 13 2011 -- 15:14:47
License: free, but no particular license provided
A command-line tool that adds/removes hydrogen-atoms to/from proteins and ligands in PDB format.
Website: http://kinemage.biochem.duke.edu/software/reduce.php
Word, et al.(1999) "Asparagine and glutamine: using hydrogen atom contacts in the choice of sidechain amide orientation" J. Mol. Biol. 285, 1735-1747.
Usage:
~/Desktop >./reduce -h
reduce: version 3.23 05/21/2013, Copyright 1997-2013, J. Michael Word
reduce.3.23.130521
arguments: [-flags] filename or -
Suggested usage:
reduce -FLIP myfile.pdb > myfileFH.pdb (do NQH-flips)
reduce -NOFLIP myfile.pdb > myfileH.pdb (do NOT do NQH-flips)
Flags:
-FLIP add H and rotate and flip NQH groups
-NOFLIP add H and rotate groups with no NQH flips
-Trim remove (rather than add) hydrogens
-NUClear use nuclear X-H distances rather than default
electron cloud distances
-NOOH remove hydrogens on OH and SH groups
-OH add hydrogens on OH and SH groups (default)
-HIS create NH hydrogens on HIS rings
-FLIPs allow complete ASN, GLN and HIS sidechains to flip
(usually used with -HIS)
...
Version:
reduce -v
reduce.3.23.130521
License: commercial and academic licenses
OpenEye OMEGA is a tool that uses a knowledge-based approach to generate hundreds of low-energy conformers of a ligand structure. The emphasis is on efficiency (approx. 2 sec/molecule on a machine with a 2.4 Ghz CPU, 4 GB RAM) and the quality of the generated conformers has been thoroughly validated.
The approach for low-energy conformer generation by OMEGA can be described in 3 basic steps: First, the creation of an initial 3-dimensional structure based on a fragment library, generation of a large set of conformers based on the number of rotational torsion angles, and sampling using geometric criteria and a energy scoring function based on a simplified MMFF94 force field.
Website: http://www.eyesopen.com/omega
Hawkins, Paul C. D., A. Geoffrey Skillman, Gregory L. Warren, Benjamin A. Ellingson, and Matthew T. Stahl. “Conformer Generation with OMEGA: Algorithm and Validation Using High Quality Structures from the Protein Databank and Cambridge Structural Database.” Journal of Chemical Information and Modeling 50, no. 4 (April 26, 2010): 572–84. doi:10.1021/ci100031x.
Example:
/soft/linux64/openeye/bin/omega2 \
-in ligand.mol2 \
-out confs.mol2 \
-warts true \
-fraglib /soft/linux64/openeye/data/omega2/fraglib.oeb.gz \
-commentEnergy true
-commentEnergy: writes - conformer energy in kcal/mol to be written in the comment field for each conformer.-warts true: generates unique titles for conformers (appending underscore and the integer corresponding to the rank order number of the conformer in the final ensemble).
For more info, please use
omega2 --help simple: Get a list of simple parametersomega2 --help all: Get a complete list of parameters
Version: Omega v. 3.14
License: commercial and academic licenses
OpenEye ROCS is a tool for overlaying chemical structures with a target molecule based on smilarities of shape and chemistry.
The rapid generation of overlays and its support for multiprocessing makes it a feasible tool for virtual screening - OpenEye reports that about 20-40 molecules per second can be overlayed using a single CPU of a standard computer (2.4 Ghz CPU, 4 GB RAM).
The result of a ROCS run consists of the overlayed compounds in common structure formats such as MOL2 as well as a report file with various different scores that can be used to rank the overlayed compounds based on volumetrical and chemistry matches.
Website: http://www.eyesopen.com/rocs
Hawkins, P.C.D.; Skillman, A.G. and Nicholls, A., Comparison of Shape-Matching and Docking as Virtual Screening Tools, Journal of Medicinal Chemistry, Vol. 50, pp. 74-82, 2007.
Example:
/soft/linux64/openeye/bin/rocs \
-query query.mol2 \
-dbase db.mol2 \
-randomstarts 20 -stats best -besthits 0 -maxhits 0 -maxconfs 1 \
-rankby TanimotoCombo \
-mcquery \
-prefix /home/user/my_dir/my_rocs_run \
-cutoff 0.5 \
-reportfile /home/user/my_dir/my_rocs_run.rpt -oformat mol2 -report one
Detailed documentation and more command line options can be found here.
An example for optimizing the hydrogen atoms in a protein-ligand complex. Here, only the protein hydrogen atoms in the 5-Angstrom neighborhood of the ligand (via polarH 5) are optimized as well as the ligand's hydrogen atoms (via -optGeometry Honly). Except for the hydrogen atoms, the ligand is treated as a rigid body that can undergo transitional and not conformational change during the optimization.
szybki -ligands <your_lig.mol2> \
-protein <your_prot.pdb> \
-out <out.mol2> \
-out_protein <prot.pdb> \
-optGeometry Honly \
-polarH 5
See the full documentation of OpenEye Szybki v. 1.8.
License: free, open-source (MIT license)
A PyMOL plugin with a GUI and command line interface that finds conserved water molecules in a protein X-ray crystal structure.
Documentation and code: https://github.com/hiteshpatel379/PyWATER
License: free, open-source (no particular license mentioned)
A library of GUI and command line tools for proteomics analyses
Website: http://proteowizard.sourceforge.net/index.shtml
License: free, open-source (BSD)
A C++ library for LC/MS data management and analysis.
Website: http://open-ms.sourceforge.net
Marc Sturm, Andreas Bertsch, Clemens Gröpl, Andreas Hildebrandt, Rene Hussong, Eva Lange, Nico Pfeifer, Ole Schulz-Trieglaff, Alexandra Zerck, Knut Reinert, and Oliver Kohlbacher, 2008. “OpenMS – an Open-Source Software Framework for Mass Spectrometry” BMC Bioinformatics 9: 163. doi:10.1186/1471-2105-9-163.
License: free, open-source (very permissive custom license)
A collection of different tools written in Python
Website: http://biopython.org/wiki/Main_Page
License: free, open-source (BSD)
A Python package with various functions, data structures, and algorithms for biosciences written in Python.
Website: http://scikit-bio.org
License: free, open-source (GPL)
A fast Prokaryotic Dynamic Programming Genefinding Algorithm for identifying genes in a microbial genome.
Website: http://prodigal.ornl.gov
Webserver: http://prodigal.ornl.gov/server.html
Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010 Mar 8;11(1):119.
License: free, open-source (BSD)
A library for assembling short-read DNA sequences via k-mer counting, filtering and graph traversal FTW.
Website: http://khmer.readthedocs.org
Crusoe et al., The khmer software package: enabling efficient sequence analysis. 2014.
A web-tool for visualizing and comparing high-throughput Genome sequencing data.
Website: http://epiviz.cbcb.umd.edu/
Florin Chelaru, Llewellyn Smith, Naomi Goldstein, Héctor Corrada Bravo. Epiviz: interactive visual analytics for functional genomics data. Nature Methods, 2014; DOI: 10.1038/nmeth.3038