Welcome to AutoDock

This site was built around docking engine AutoDock4.2.6 (last revision: July 2014) and the associated tools & methods. It remains open for information purposes. Most of the methods and protocols for protein-ligand docking have been re-implemented with improvements in the current docking engines:

AutoDock-GPU (2021–present): https://github.com/ccsb-scripps/AutoDock-GPU

AutoDock Vina v1.2.x (2021–present): https://github.com/ccsb-scripps/AutoDock-Vina

For the latest developments and information, please visit the linked project Github pages or our new navigation & resource site at https://rsd3.scripps.edu/.

What is AutoDock?

AutoDock is a suite of automated docking tools. It is designed to predict how small molecules, such as substrates or drug candidates, bind to a receptor of known 3D structure. Over the years, it has been modified and improved to add new functionalities, and multiple engines have been developed.

Before the official release of AutoDock-GPU and AutoDock Vina 1.2.x, the distributions of AutoDock consisted of two generations of software: AutoDock 4 and AutoDock Vina. A designated site: http://vina.scripps.edu/, was developed for the legacy version of AutoDock Vina, v1.1.2 (last revision: May 2011).

AutoDock 4 actually consists of two main programs: autodock performs the docking of the ligand to a set of grids describing the target protein; autogrid pre-calculates these grids.

In addition to using them for docking, the atomic affinity grids can be visualised. This can help, for example, to guide organic synthetic chemists design better binders.

AutoDock Vina does not require choosing atom types and pre-calculating grid maps for them. Instead, it calculates the grids internally, for the atom types that are needed, and it does this virtually instantly.

We have also developed a graphical user interface called AutoDockTools, or ADT for short, which amongst other things helps to set up which bonds will treated as rotatable in the ligand and to analyze dockings.

AutoDock has applications in:

  • X-ray crystallography;
  • structure-based drug design;
  • lead optimization;
  • virtual screening (HTS);
  • combinatorial library design;
  • protein-protein docking;
  • chemical mechanism studies

Support

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