ArticleNature protocols2016
Computational protein-ligand docking and virtual drug screening with the AutoDock suite.
Article in Nature protocols, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,013 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1,013 citing papers in PubMed, 2,604 citations in OpenAlex.
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953 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.