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. 2021 Aug 23;61(8):3891-3898.
doi: 10.1021/acs.jcim.1c00203. Epub 2021 Jul 19.

AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings

Affiliations

AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings

Jerome Eberhardt et al. J Chem Inf Model. .

Abstract

AutoDock Vina is arguably one of the fastest and most widely used open-source programs for molecular docking. However, compared to other programs in the AutoDock Suite, it lacks support for modeling specific features such as macrocycles or explicit water molecules. Here, we describe the implementation of this functionality in AutoDock Vina 1.2.0. Additionally, AutoDock Vina 1.2.0 supports the AutoDock4.2 scoring function, simultaneous docking of multiple ligands, and a batch mode for docking a large number of ligands. Furthermore, we implemented Python bindings to facilitate scripting and the development of docking workflows. This work is an effort toward the unification of the features of the AutoDock4 and AutoDock Vina programs. The source code is available at https://github.com/ccsb-scripps/AutoDock-Vina.

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Figures

Fig. 1.
Fig. 1.
Example applications of AutoDockVina 1.2.0 for docking (A) multiple ligands (PDB ×ばつ72), (B) with water molecules using the hydrated docking protocol from AutoDock4 (PDB 4ykq), (C) in presence of zinc using the AutoDock4Zn forcefield (PDB 1s63), or (D) flexible macrocycles (compound 19 from the BACE dataset of the D3R Grand Challenge 4). Proteins are represented in white cartoon and crystal poses and protein residues in white thin sticks. The 2Fo-Fc electron-density map, contoured at 2.0σ, is colored grey. The docking poses are represented in sticks, and colored in green and orange when docked using the Vina or AutoDock4 scoring function, respectively. Docking with zinc was done in presence of the farnsesyl disphosphate molecule, represented in sticks and colored in white.
Fig. 2.
Fig. 2.
Docking success rate of 6 ligands redocked against HSP90, using the AutoDock4.2 scoring function, with and without the hydrated docking protocol considering the top 1, top 2 and top 3 poses. The pose prediction was considered as successful if the RMSD was inferior than 2, 1 or 0.5 Å from the crystal pose.
Fig. 3.
Fig. 3.
Early recognition of active compounds from the DUD-E dataset and crystal pose prediction. All 102 targets from the DUD-E dataset were selected and used to compare Vina and AutoDock4.2 scoring functions in AutoDock Vina. Violin plots of (A) AUC, (B) BEDROC using an α of 160.9 and (E) EF at 1%. (D) Docking success rate for Vina and AutoDock4.2 scoring functions using crystal poses considering the top 1, top 2 and top 3 poses. The pose prediction was considered as successful if the RMSD was inferior than 2, 1 or 0.5 Å from the crystal pose.

References

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