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Evaluation of AlphaFold2 structures as docking targets

https://doi.org/10.1002/pro.4530
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility
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Predicting the accuracy of protein–ligand docking on homology models
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Evaluation of AlphaFold2 structures as docking targets
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Multi‐state modeling of G‐protein coupled receptors at experimental accuracy
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Current trends in computer aided drug design and a highlight of drugs discovered via computational techniques: A review
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inferredcites →https://doi.org/10.1021/acs.jcim.8b00545openalex-snapshot
Comparative Assessment of Scoring Functions: The CASF-2016 Update
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Accelerating A uto D ock 4 with GPUs and Gradient-Based Local Search
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Molecular Docking Screens Using Comparative Models of Proteins
inferredcites →https://doi.org/10.1021/jm0300330openalex-snapshot
Information Decay in Molecular Docking Screens against Holo, Apo, and Modeled Conformations of Enzymes
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‘The entire protein universe’: AI predicts shape of nearly every known protein
inferredcites →https://doi.org/10.1038/nprot.2016.051openalex-snapshot
Computational protein–ligand docking and virtual drug screening with the AutoDock suite
inferredcites →https://doi.org/10.1038/s41586-021-03819-2openalex-snapshot
Highly accurate protein structure prediction with AlphaFold
inferredcites →https://doi.org/10.1093/bioinformatics/btac202openalex-snapshot
Impact of protein conformational diversity on AlphaFold predictions
inferredcites →https://doi.org/10.1093/bioinformatics/btp163openalex-snapshot
Biopython: freely available Python tools for computational molecular biology and bioinformatics
inferredcites →https://doi.org/10.1093/nar/gkab1061openalex-snapshot
AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models
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Open Babel: An open chemical toolbox

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Additional file 1 of Learnt representations of proteins can be used for accurate prediction of small molecule binding sites on experimentally determined and predicted protein structures
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AlphaFold3 for Structure-guided Ligand Discovery
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ASSESSMENT OF ALPHAFOLD PROTEIN MODELS FOR SMALL-MOLECULE LIGAND DOCKING
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Large-scale prospective evaluation of co-folding across hundreds of Mac1–ligand complexes and three virtual screens
inferred← citeshttps://doi.org/10.7554/elife.110475.1openalex-snapshot
Large scale prospective evaluation of co-folding across 557 Mac1-ligand complexes and three virtual screens
inferred← citeshttps://doi.org/10.7554/elife.110475.2openalex-snapshot
Large scale prospective evaluation of co-folding across hundreds of Mac1-ligand complexes and three virtual screens
inferred← citeshttps://doi.org/10.7554/elife.110475.3openalex-snapshot
Large-scale prospective evaluation of co-folding across hundreds of Mac1–ligand complexes and three virtual screens
inferred← citeshttps://doi.org/10.7554/elife.99702openalex-snapshot
Empowering AlphaFold2 for protein conformation selective drug discovery with AlphaFold2-RAVE
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Empowering AlphaFold2 for protein conformation selective drug discovery with AlphaFold2-RAVE
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Empowering AlphaFold2 for protein conformation selective drug discovery with AlphaFold2-RAVE
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