:: DESCRIPTION
BSP-SLIM is a new method for ligand-protein blind docking using low-resolution protein structures.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
NO
:: MORE INFORMATION
Citation
Proteins. 2012 Jan;80(1):93-110. doi: 10.1002/prot.23165. Epub 2011 Oct 4.
BSP-SLIM: a blind low-resolution ligand-protein docking approach using predicted protein structures.
Lee HS1, Zhang Y.
:: DESCRIPTION
FRODOCK is able to generates very efficiently many potential predictions of how two proteins could interact. This approximation effectively address the complexity and sampling requirements of the initial 6D docking exhaustive search by combining the projection of the interaction terms into 3D grid-based potentials with the efficiency of spherical harmonics approximations. The binding energy upon complex formation is approximated as a correlation function composed of van der Waals, electrostatics and desolvation potential terms. This initial stage exhaustive docking obtain excellent accuracy results with standard benchmarks, thus you can use it directly as a first protein-protein rigid-body docking approach.
::DEVELOPER
The Structural Bioinformatics Group
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
J. I. Garzon, J. R. Lopéz-Blanco, C. Pons, J. Kovacs, R. Abagyan, J. Fernandez-Recio, P. Chacón (2009)
FRODOCK: a new approach for fast rotational protein-protein docking
Bioinformatics, 25, 2544-2551
:: DESCRIPTION
DockingApp is a user-friendly graphical application for carrying out molecular docking and virtual screening tasks, meant to enable non-experienced users to easily perform such activities and browse the docking results via a three-dimensional visualization.
DockingApp RF is a user-friendly graphical application for carrying out molecular docking and replicated docking, meant to enable non-experienced users to easily perform such activities and browse the docking results via a three-dimensional visualization. It implements a state-of-the-art scoring function based on a Random Forest algorithm, whose effectiveness has been proven on specific use cases of molecular docking, making DockingApp RF complementary to the classic DockingApp.
:: SCREENSHOTS
::REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Di Muzio E, Toti D, Polticelli F.
DockingApp: a user friendly interface for facilitated docking simulations with AutoDock Vina.
J Comput Aided Mol Des. 2017 Feb;31(2):213-218. doi: 10.1007/s10822-016-0006-1. Epub 2017 Jan 6. PMID: 28063067.
Macari G, Toti D, Pasquadibisceglie A, Polticelli F.
DockingApp RF: A State-of-the-Art Novel Scoring Function for Molecular Docking in a User-Friendly Interface to AutoDock Vina.
Int J Mol Sci. 2020 Dec 15;21(24):9548. doi: 10.3390/ijms21249548. PMID: 33333976; PMCID: PMC7765429.
:: DESCRIPTION
GOMoDo (GPCR Online Modeling and Docking) is a web server to seamlessly model GPCR (G-protein coupled receptors ) structures and dock ligands to the models in a single consistent pipeline.
::DEVELOPER
Department of Biotechnology, University of Verona | Institute of Computational Biomedicine (INM-9/IAS-5), Forschungszentrum Jülich.
:: SCREENSHOTS
N/A
::REQUIREMENTS
:: DOWNLOAD
NO
:: MORE INFORMATION
Citation
Sandal M, Duy TP, Cona M, Zung H, Carloni P, et al. (2013)
GOMoDo: A GPCRs Online Modeling and Docking Webserver.
PLoS ONE 8(9): e74092. doi:10.1371/journal.pone.0074092
:: DESCRIPTION
GalaxyDock is a protein-ligand docking program that allows flexibility of pre-selected side-chains of ligand using Conformational Space Annealing.
::DEVELOPER
Lab of Computational Biology and Biomolecular Engineering, Seoul National University
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
J Comput Chem. 2013 Nov 15;34(30):2647-56. doi: 10.1002/jcc.23438. Epub 2013 Sep 24.
GalaxyDock2: protein-ligand docking using beta-complex and global optimization.
Shin WH1, Kim JK, Kim DS, Seok C.
J Chem Inf Model. 2012 Dec 21;52(12):3225-32. doi: 10.1021/ci300342z. Epub 2012 Dec 12.
GalaxyDock: protein-ligand docking with flexible protein side-chains.
Shin WH, Seok C.
:: DESCRIPTION
HADDOCK (High Ambiguity Driven protein-protein DOCKing) is an information-driven flexible docking approach for the modeling of biomolecular complexes. HADDOCK distinguishes itself from ab-initio docking methods in the fact that it encodes information from identified or predicted protein interfaces in ambiguous interaction restraints (AIRs) to drive the docking process. HADDOCK can deal with a large class of modeling problems including protein-protein, protein-nucleic acids and protein-ligand complexes.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
The HADDOCK2.2 web server: User-friendly integrative modeling of biomolecular complexes.
van Zundert GC, Rodrigues JP, Trellet M, Schmitz C, Kastritis PL, Karaca E, Melquiond AS, van Dijk M, de Vries SJ, Bonvin AM.
J Mol Biol. 2015 Sep 24. pii: S0022-2836(15)00537-9. doi: 10.1016/j.jmb.2015.09.014
Cyril Dominguez, Rolf Boelens and Alexandre M.J.J. Bonvin (2003).
HADDOCK: a protein-protein docking approach based on biochemical and/or biophysical information.
J. Am. Chem. Soc. 125, 1731-1737
S.J. de Vries, A.D.J. van Dijk, M. Krzeminski, M. van Dijk, A. Thureau, V. Hsu, T. Wassenaar and A.M.J.J. Bonvin
“HADDOCK versus HADDOCK: New features and performance of HADDOCK2.0 on the CAPRI targets.”
Proteins: Struc. Funct. & Bioinformatic 69, 726-733 (2007).
:: DESCRIPTION
GPCRautomodel allows the user to upload a GPCR sequence, choose a ligand in a library and obtain the 3D structure of the free receptor and ligand-receptor complex
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
NO
:: MORE INFORMATION
Citation
Automatic modeling of mammalian olfactory receptors and docking of odorants.
Launay G, Téletchéa S, Wade F, Pajot-Augy E, Gibrat JF, Sanz G.
Protein Eng Des Sel. 2012 Aug;25(8):377-86. doi: 10.1093/protein/gzs037.
:: DESCRIPTION
Dove is a deep learning based protein docking model evluation method.It will use the atom information such as postions, types, energy scores in the interface area to judge if the docking model is reasonable.
::DEVELOPER
Kihara Bioinformatics Laboratory
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Bioinformatics. 2019 Nov 20. pii: btz870. doi: 10.1093/bioinformatics/btz870. [Epub ahead of print]
Protein Docking Model Evaluation by 3D Deep Convolutional Neural Networks.
Wang X, Terashi G, Christoffer CW, Zhu M, Kihara D.
:: DESCRIPTION
DOCK addresses the problem of “docking” molecules to each other. In general, “docking” is the identification of the low-energy binding modes of a small molecule, or ligand, within the active site of a macromolecule, or receptor, whose structure is known. A compound that interacts strongly with, or binds, a receptor associated with a disease may inhibit its function and thus act as a drug. Solving the docking problem computationally requires an accurate representation of the molecular energetics as well as an efficient algorithm to search the potential binding modes.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Lang, P.T., Brozell, S.R., Mukherjee, S., Pettersen, E.T., Meng, E.C., Thomas, V., Rizzo, R.C., Case, D.A., James, T.L., Kuntz, I.D.
DOCK 6: Combining Techniques to Model RNA-Small Molecule Complexes.
RNA 15:1219-1230, 2009.
:: DESCRIPTION
3DGarden (Global and Restrained Docking Exploration Nexus) is an integrated software suite for performing protein-protein and protein-polynucleotide docking. For any pair of biomolecules structures specified by the user, 3DGarden’s primary function is to generate an ensemble of putative complexed structures and rank them. The highest-ranking candidates constitute predictions for the structure of the complex. 3DGarden cannot be used to decide whether or not a particular pair of biomolecules interacts. Complexes of protein and nucleic acid chains can also be specified as individual interactors for docking purposes.
::DEVELOPER
Structural Bioinformatics Group, Imperial College
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
NO
:: MORE INFORMATION
Citation:
3D-Garden: a system for modelling protein-protein complexes based on conformational refinement of ensembles generated with the marching cubes algorithm.
Lesk VI, Sternberg MJ.
Bioinformatics. 2008 May 1;24(9):1137-44. doi: 10.1093/bioinformatics/btn093.
