List of protein-ligand docking software
The number of protein-ligand docking programs currently available is high and has been steadily increasing over the last decades. The following list presents an overview of the most common programs, listed alphabetically, with indication of the corresponding year of publication, involved organisation or institution, short description, availability of a webservice and the license. This table is comprehensive but not complete.a
| Program | Year Published | Organisation | Description | Webservice | License |
| 1-Click Docking | 2011 | Mcule | Docking predicts the binding orientation and affinity of a ligand to a target | ||
| AADS | 2011 | Indian Institute of Technology | Automated active site detection, docking, and scoring protocol for proteins with known structures based on Monte Carlo Method | ||
| ADAM | 1994 | IMMD Inc. | Prediction of stable binding mode of flexible ligand molecule to target macromolecule | ||
| AutoDock | 1990 | The Scripps Research Institute | Automated docking of ligand to macromolecule by Lamarckian Genetic Algorithm and Empirical Free Energy Scoring Function | ||
| AutoDock Vina | 2010 | The Scripps Research Institute | New generation of AutoDock | ||
| BetaDock | 2011 | Hanyang University | Based on Voroni Diagram | ||
| Blaster | 2009 | University of California San Francisco | Combines ZINC databases with DOCK to find ligand for target protein | ||
| BSP-SLIM | 2012 | University of Michigan | A new method for ligand-protein blind docking using low-resolution protein structures | ||
| CABS-dock | 2015 | University of Warsaw | A method for flexible protein-peptide docking without a priori knowledge about the binding site. Available as a standalone application and as a web server. | Freeware for academic use | |
| DARWIN | 2000 | The Wistar Institute | Prediction of the interaction between a protein and another biological molecule by genetic algorithm | ||
| DIVALI | 1995 | University of California-San Francisco | Based on AMBER-type potential function and genetic algorithm | ||
| DOCK | 1988 | University of California-San Francisco | Based on Geometric Matching Algorithm | ||
| DockingServer | 2009 | Virtua Drug Ltd | Integrates a number of computational chemistry software | ||
| Docking Study with HyperChem | 2006 | Motonori Tsuji | Biomacromolecule- and ligand-flexible docking using combination between the predicted structure-based pharmacophores and ligand-based pharmacophores | ||
| DockVision | 1992 | DockVision | Based on Monte Carlo, genetic algorithm, and database screening docking algorithms | ||
| DOLINA | 2014 | University of Basel | Pharmacophore-based alignment, local combinatorial induced-fit | ||
| EADock | 2007 | Swiss Institute of Bioinformatics | Based on evolutionary algorithms | ||
| eHiTS | 2006 | SymBioSys Inc | Exhausted search algorithm | ||
| EUDOC | 2001 | Mayo Clinic Cancer Center | Program for identification of drug interaction sites in macromolecules and drug leads from chemical databases | ||
| FDS | 2003 | University of Southampton | Flexible ligand and receptor docking with a continuum solvent model and soft-core energy function | ||
| Fitted | 2010 | Molecular Forecaster Inc. | Docking program with flexibility, covalent, metalloenzyme, displaceable water considerations | ||
| FlexX | 2001 | BioSolveIT | Incremental build based docking program | ||
| FlexAID | 2015 | University of Sherbrooke | Target side-chain flexibility and soft scoring function, based on surface complementarity | ||
| FlexPepDock | 2010 | The Hebrew University | Modeling of peptide-protein complexes, implemented within the Rosetta framework | ||
| FLIPDock | 2007 | Scripps Research Institute | Genetic algorithm based docking program using FlexTree data structures to represent a protein-ligand complex | ||
| FLOG | 1994 | Merck Research Laboratories | Rigid body docking program using databases of pregenerated conformations | ||
| FRED | 2003 | OpenEye Scientific | Systematic, exhaustive, nonstochastic examination of all possible poses within the protein active site combined with scoring Function | ||
| FTDOCK | 1997 | Biomolecular Modelling Laboratory | Based on Katchalski-Katzir algorithm. It discretises the two molecules onto orthogonal grids and performs a global scan of translational and rotational space | ||
| GalaxyPepDock | 2018 | Seoul National University | Protein-peptide docking based on interaction similarity available as a standalone application and a web server | Freeware for academic use | |
| GEMDOCK | 2004 | National Chiao Tung University | Generic Evolutionary Method for molecular docking | ||
| Glide | 2004 | Schrödinger | Exhaustive search based docking program | ||
| GOLD | 1995 | Collaboration between the University of Sheffield, GlaxoSmithKline plc and CCDC | Genetic algorithm based, flexible ligand, partial flexibility for protein | ||
| GPCRautomodel | 2012 | INRA | Automates the homology modeling of mammalian olfactory receptors based on the six three-dimensional structures of G protein-coupled receptors available so far and performs the docking of odorants on these models | ||
| HADDOCK | 2003 | Centre Bijvoet Center for Biomolecular Research | Makes use of biochemical and/or biophysical interaction data such as chemical shift perturbation data resulting from NMR titration experiments, mutagenesis data or bioinformatic predictions. Developed for protein-protein docking, but can also be applied to protein-ligand docking. | ||
| Hammerhead | 1996 | Arris Pharmaceutical Corporation | Fast, fully automated docking of flexible ligands to protein binding sites | ||
| ICM-Dock | 1997 | MolSoft | Docking program based on pseudo-Brownian sampling and local minimization | ||
| idTarget | 2012 | National Taiwan University | Predicts possible binding targets of a small chemical molecule via a divide-and-conquer docking approach | ||
| iScreen | 2011 | China Medical University | Based on a cloud-computing system for TCM intelligent screening system | ||
| Lead finder | 2008 | MolTech | Program for molecular docking, virtual screening and quantitative evaluation of ligand binding and biological activity | ||
| LeDock | 2016 | Lephar | Program for fast and accurate flexible docking of small molecules into a protein | ||
| LigandFit | 2003 | BioVia | CHARMm based docking program | ||
| LigDockCSA | 2011 | Seoul National University | Protein-ligand docking using conformational space annealing | ||
| LightDock | 2018 | Barcelona Supercomputing Center | Protein-protein, protein-DNA, protein-peptide docking using different scoring functions, backbone flexibility modeled by ANM and written in Python3 | ||
| LIGIN | 1996 | Weizmann Institute of Science | Molecular docking using surface complementarity | ||
| LPCCSU | 1999 | Weizmann Institute of Science | Based on a detailed analysis of interatomic contacts and interface complementarity | ||
| MCDOCK | 1999 | Georgetown University Medical Center | Based on a non-conventional Monte Carlo simulation technique | ||
| MEDock | 2007 | SIGMBI | Maximum-Entropy based Docking web server is aimed at providing an efficient utility for prediction of ligand binding site | ||
| Molecular Operating Environment | 2008 | Chemical Computing Group | Docking application within MOE; choice of placement methods and scoring functions | ||
| Molegro Virtual Docker | 2006 | Molexus | Based on a new heuristic search algorithm that combines differential evolution with a cavity prediction algorithm | ||
| 2016 | University of Madras | Induced-fit peptide-protein, small molecule-protein docking using mutually orthogonal Latin squares technique | |||
| MS-DOCK | 2008 | INSERM | Multi-stage docking/scoring protocol | ||
| ParaDockS | 2010 | Martin Luther University of Halle-Wittenberg and Partner Institute for Computational Biology | Molecular docking with population-based metaheuristics | ||
| ParDOCK | 2007 | Indian Institute of Technology | All-atom energy based Monte Carlo, rigid protein ligand docking | ||
| PatchDock | 2002 | Tel Aviv University | The algorithm carries out rigid docking, with surface variability/flexibility implicitly addressed through liberal intermolecular penetration | ||
| PLANTS | 2006 | University of Konstanz | Based on a class of stochastic optimization algorithms | ||
| PLATINUM | 2008 | Moscow Institute of Physics and Technology | Analysis and visualization of hydrophobic/hydrophilic properties of biomolecules supplied as 3D-structures | ||
| PRODOCK | 1999 | Cornell University | Based on Monte Carlo method plus energy minimization | ||
| PSI-DOCK | 2006 | Peking University | Pose-Sensitive Inclined -DOCK | ||
| PSO@AUTODOCK | 2007 | University of Leipzig | Particle Swarm Optimization algorithms varCPSO and varCPSO-ls are suited for rapid docking of highly flexible ligands | ||
| PythDock | 2011 | Hanyang University | Heuristic docking program that uses Python programming language with a simple scoring function and a population based search engine | ||
| Q-Dock | 2008 | Georgia Institute of Technology | Low-resolution flexible ligand docking with pocket-specific threading restraints | ||
| QXP | 1997 | Novartis Pharmaceuticals Corporation | Monte Carlo perturbation with energy minimization in Cartesian space | ||
| rDock | 1998 2006 2012 | Vernalis R&D University of York University of Barcelona | HTVS of small molecules against proteins and nucleic acids, binding mode prediction | ||
| SANDOCK | 1998 | University of Edinburgh | Guided matching algorithm | ||
| Score | 2004 | Alessandro Pedretti & Giulio Vistoli | The Score service allows to calculate some different docking scores of ligand-receptor complex | ||
| SEED | 1999 | University of Zurich | Automated docking of fragments with evaluation of free energy of binding including electrostatic solvation effects in the continuum dielectric approximation | ||
| smina | 2012 | University of Pittsburgh | A customized fork of AutoDock Vina with a better support scoring function and a high-performance energy minimization | ||
| SODOCK | 2007 | Feng Chia University | Swarm optimization for highly flexible protein-ligand docking | ||
| SOFTDocking | 1991 | University of California, Berkeley | Matching of molecular surface cubes | ||
| Surflex-Dock | 2003 | Tripos | Based on an idealized active site ligand | ||
| SwissDock | 2011 | Swiss Institute of Bioinformatics | Webservice to predict interaction between a protein and a small molecule ligand | ||
| VoteDock | 2011 | University of Warsaw | Consensus docking method for prediction of protein-ligand interactions | ||
| YUCCA | 2005 | Virginia Tech | Rigid protein-small-molecule docking |