Autodock tools citation

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.

For questions, support, and discussions, subscribe to the AutoDock mailing list. Ease of Use. All that is required is the structures of the molecules being docked and the specification of the search space including the binding site.

Calculating grid maps and assigning atom charges is not needed. The summary automatically remains in sync with the possible usage scenarios. Like in AutoDock 4, some receptor side chains can be chosen to be treated as flexible during docking.

AutoDock Vina tends to be faster than AutoDock 4 by orders of magnitude. Some of these projects average over 50 years worth of computation per day. Average time per receptor-ligand pair on the test set. License AutoDock Vina is released under a very permissive Apache license, with few restrictions on commercial or non-commercial use, or on the derivative works.

The docking simulation places this within the Gaussian well. One caveat is that this does not constrain the geometry of the covalent attachment to reasonable bond angles. To overcome this limitation, we tested the method using two Gaussian grids to define the bond that is formed during covalent linkage. Note, however, that the conformational freedom allowed with a single Gaussian grid may be an advantage if the method is used, for instance, to target ligands to metal coordination sites.

We also tested use of the flexible sidechain method for docking of covalent ligands. In this case, a coordinate file is created with the ligand attached to the proper sidechain in the protein, by overlapping ideal coordinates of the ligand onto the proper bond in the protein.

This sidechain-ligand structure is then treated as flexible during the docking simulation, searching torsional degrees of freedom to optimize the interaction with the rest of the protein. With the release of AutoDock3, it became apparent that the tasks of coordinate preparation, experiment design, and analysis required an effective graphical user interface to make AutoDock a widely accessible tool. AutoDockTools was created to fill this need. AutoDockTools facilitates formatting input molecule files, with a set of methods that guide the user through protonation, calculating charges, and specifying rotatable bonds in the ligand and the protein described below.

To simplify the design and preparation of docking experiments, it allows the user to identify the active site and determine visually the volume of space searched in the docking simulation. Other methods assist the user in specifying search parameters and launching docking calculations. Finally, AutoDockTools includes a variety of novel methods for clustering, displaying, and analyzing the results of docking experiments.

AutoDockTools is implemented in the object-oriented programming language Python and is build from reusable software components 15 , The easy-to-use graphical user interface has a gentle learning curve and an effective self-taught tutorial is available online.

Reusable software components are used to represent the flexible ligand, the sets of parameters and the docking calculation, enabling a range of uses from a single use to thousands of docking experiments involving many different sets of molecules, facilitating automated high-throughput applications. For example, converting the NCI diversity database of small molecules into AutoDock-formatted ligand files was possible with a short Python script of less than 20 lines by leveraging the existing software components underlying AutoDockTools.

PMV is a freely distributed Python-based molecular viewer. It is built with a component-based architecture with the following software components: ViewerFramework, a generic OpenGL-based 3-dimensional viewing component; and MolKit, a hierarchical data representation of molecules. AutoDockTools consists of a set of commands dynamically extending PMV with commands specific to the preparation, launching and analysis of AutoDock calculations. PMV also provides access to the Python-interpreter so that commands or scripts can be called interactively.

PMV commands log themselves, producing a session file that can be rerun. AutoDockTools provides an interactive method for defining the torsional tree for a given ligand and receptor.

Each step in this process has been automated to allow automatic assignment, for use in batch processes such as virtual screening. Ligand flexibility is assigned in several steps. First, a root atom is chosen, which will act as the center of rotation during coordinate transformation in the docking simulation.

To find the optimal atom, we evaluate the number of atoms in each branch, and choose the root atom that minimizes the size of the largest branch. In some cases, the user may wish to limit the flexibility of the ligand. AutoDockTools provides two choices to do this assignment automatically.

One choice selects the set of torsional degrees of freedom that will move the largest number of atoms torsions near the root , the other adds torsions progressively from the leaves, moving the fewest number of atoms and leaving the core of the molecule rigid.

Two sets of complexes were used for the validation of AutoDock4, both of which have been described previously All coordinates were checked manually for the proper biological unit and inconsistency in naming schemes.

Several misassigned charges were modified manually, as described in the previous report. The 87 HIV protease complexes were aligned to allow easy comparison of docked conformations during cross dockings. An analysis of steric clashes was performed by swapping ligands within the set of 87 aligned complexes.

Docking experiments were performed with AutoDock4 and compared with docking experiments with AutoDock3. For each complex, 50 docking experiments were performed using the Lamarckian genetic algorithm with the default parameters from AutoDock3. A maximum of 25 million energy evaluations was applied for each experiment. The results were clustered using a tolerance of 2. In the HIV cross dockings, ligand flexibility was limited to 10 torsional degrees of freedom, picking torsions that allowed the fewest number of atoms to move freezing the core of the molecule.

Flexible docking was performed allowing three torsions to rotate in residue ARG8, in both the A and B chains. The structural water water was included in complexes that included this water in the crystallographic structure, and hydrogen atoms were added in geometry that allowed hydrogen bonding to the flaps.

We have also changed the default model for the unbound system in the current version of AutoDock. Our previous method calculated internal energies for an extended form of the molecule, mimicking a conformation that might be expected when fully solvated Results from beta testers, however, showed that this protocol has severe limitations when used for virtual screening.

In cases where the ligand is sterically crowded, the artificial force field used to drive the ligand into an extended conformation tends to lead to conformations with sub-optimal energy. When the difference is calculated between this unbound conformation and the bound conformation, it leads to artificially favorable predictions of the free energy of binding. In response to this problem, we have returned to the default model of assuming that the unbound conformation of the ligand is the same as the bound conformation.

Other options in AutoDock allow the user to use an energy-minimized conformation of the ligand as the unbound model. AutoDock 4. Our first test of AutoDock4 is a redocking experiment using a set of diverse protein-ligand complexes. The results, presented in Figure 1 , are similar to the redocking study performed during the energy function calibration AutoDock4 successfully redocks most complexes with about 10 or fewer torsional degrees of freedom, but fails for most complexes with higher conformational flexibility.

In of complexes, the docked conformation with lowest energy was within 3. This is slightly better than a similar redocking experiment with AutoDock3.

AutoDock3 successfully docked complexes with about 10 or fewer torsional degrees of freedom, and in 97 of complexes, the lowest energy conformation showed RMSD less than 3. Results of redocking of diverse ligand-protein complexes. Open squares represent complexes where the docked conformation with best predicted energy was less that 3. Dots are complexes where the best docked conformation was greater than 3.

To validate the use of flexible sidechains in docking, we have used a set of 87 retroviral proteases with inhibitors. These proteins have a tunnel-shaped active site that wraps around a peptidomimetic inhibitor. An arginine-aspartate salt bridge forms at each end of the tunnel, bridging the two subunits. In complexes with large inhibitors, these arginines move to make space, whereas they adopt a more closed position in complexes with small inhibitors.

In previous work, we have demonstrated that steric clash with these arginines prevents the docking of large inhibitors to proteins in the more closed conformation.

Using a distributed computing environment, we performed a large cross docking experiment, taking inhibitors from 87 crystallographic structures and docking them to the protein conformations from these structures. We performed two parallel experiments, one with a rigid protein target, and one modeling the two ARG8 amino acids as flexible. Results are shown in Figure 2.

Parameters were chosen that correspond to a typical computational effort for an individual docking experiment, with 25,, evaluations and 50 docked conformations.

The torsional degrees of freedom in the ligand were limited to 10, with an added 6 degrees of freedom for the two arginine sidechains in the flexible sidechain tests.