HADDOCK 2.2 – Docking approach for the Modeling of Biomolecular Complexes

HADDOCK 2.2

:: 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.

Haddock Server

::DEVELOPER

BONVIN LAB

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ MacOsX
  • Python

:: DOWNLOAD

  HADDOCK 

:: 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).

GPCRautomodel – Automatic Modeling of Mammalian Olfactory Receptors and Docking of Odorants

GPCRautomodel

:: 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

GPCRautomodel team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: 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.

Dove – A Deep-learning based dOcking decoy eValuation mEthod

Dove

:: 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

  • Linux
  • Python

:: DOWNLOAD

Dove

:: 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.

DOCK 6.9 – Docking Molecules to each other

DOCK 6.9

:: 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

DOCK Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

DOCK

:: 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.

3D-Garden 1.4 – Protein-protein and Protein-polynucleotide Docking

3D-Garden 1.4

:: 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

  • Web Browser

:: 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.

FRODOCK 3.0 – Fast Rotational DOCKing tool

FRODOCK 3.0

:: 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

  • Windows / Linux

:: DOWNLOAD

  FRODOCK

:: 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

MGA-Glide 1.0 – Grid-based Protein-ligand Docking software

MGA-Glide 1.0

:: DESCRIPTION

MGA-Glide is a novel deep conformational search method for grid-based protein-ligand docking software.

::DEVELOPER

Akiyama Laboratory , Tokyo Institute of Technology

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

MGA-Glide

:: MORE INFORMATION

Citation

Multiple grid arrangement improves ligand docking with unknown binding sites: Application to the inverse docking problem.
Ban T, Ohue M, Akiyama Y.
Comput Biol Chem. 2018 Apr;73:139-146. doi: 10.1016/j.compbiolchem.2018.02.008.

PPDbench – Benchmarking of Docking software on Protein-peptide Complexes

PPDbench

:: DESCRIPTION

PPDbench server is made in order to provide an easy webserver to calculate FNAT, L-RMSD and I-RMSD values of docked and original poses of protein-peptide complexe’s.

::DEVELOPER

PPDbench team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

Benchmarking of different molecular docking methods for protein-peptide docking.
Agrawal P, Singh H, Srivastava HK, Singh S, Kishore G, Raghava GPS.
BMC Bioinformatics. 2019 Feb 4;19(Suppl 13):426. doi: 10.1186/s12859-018-2449-y.

KiDoQ – Prediction of Dihydrodipicolinate synthase inhibtors using Docking and QSAR

KiDoQ

:: DESCRIPTION

KiDoQ, a web server has been developed to serve scientific community working in the field of designing inhibitors against Dihydrodipicolinate synthase (DHDPS), a potential drug target enzyme of a unique bacterial DAP/Lysine pathway.

::DEVELOPER

KiDoQ team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2010 Mar 11;11:125. doi: 10.1186/1471-2105-11-125.
KiDoQ: using docking based energy scores to develop ligand based model for predicting antibacterials.
Garg A1, Tewari R, Raghava GP.

MM-ISMSA – Scoring Function for Protein-Protein and Protein-Ligand Docking and Molecular Dynamics

MM-ISMSA

:: DESCRIPTION

MM-ISMSA is an ultrafast and accurate scoring function for protein-protein and protein-ligand docking

::DEVELOPER

Unidad de Bioinformatica CBMSO

:: SCREENSHOTS

MM-ISMSA

:: REQUIREMENTS

  • Windows / Linux
  • Python
  • PyMOL

:: DOWNLOAD

  MM-ISMSA

:: MORE INFORMATION

Citation

Javier Klett, Alfonso Núñez-Salgado, Helena G. Dos Santos, Álvaro Cortés-Cabrera, Almudena Perona, Rubén Gil-Redondo, David Abia, Federico Gago, and Antonio Morreale
MM-ISMSA: an ultra-fast and accurate scoring function for protein-protein docking.
J Chem Theory Comput. 2012 Sep 11;8(9):3395-3408