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Computational protein–ligand docking and virtual drug screening with the AutoDock suite


Computational docking can be used to predict bound conformations and free energies of binding for small-molecule ligands to macromolecular targets. Docking is widely used for the study of biomolecular interactions and mechanisms, and it is applied to structure-based drug design. The methods are fast enough to allow virtual screening of ligand libraries containing tens of thousands of compounds. This protocol covers the docking and virtual screening methods provided by the AutoDock suite of programs, including a basic docking of a drug molecule with an anticancer target, a virtual screen of this target with a small ligand library, docking with selective receptor flexibility, active site prediction and docking with explicit hydration. The entire protocol will require 5 h.

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Figure 1: AutoDockTools (ADT).
Figure 2: Results of docking imatinib to its receptor in bound and apo conformations.
Figure 3: Raccoon2.
Figure 4: Raccoon result filtering.
Figure 5: AutoLigand results.
Figure 6: Docking with explicit hydration.

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This work was supported by the US National Institutes of Health (grant R01 GM069832 to A.J.O.). This is manuscript number 29118 from the Scripps Research Institute.

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Authors and Affiliations



All authors contributed equally to this work. D.S.G. and S.F. authored the protocol manuscript with extensive input from the other authors, based on tutorials developed by all authors. All authors have been instrumental in development of the AutoDock suite and training of users.

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Correspondence to Arthur J Olson.

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The authors declare no competing financial interests.

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Forli, S., Huey, R., Pique, M. et al. Computational protein–ligand docking and virtual drug screening with the AutoDock suite. Nat Protoc 11, 905–919 (2016).

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