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Hic Sunt Dracones: Molecular Docking in Uncharted Territories with Structures from AlphaFold2 and RoseTTAfold

  • Christian Kersten*
    Christian Kersten
    Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Mainz, Staudingerweg 5, 55128 Mainz, Germany
    *Email: [email protected]
  • Steven Clower
    Steven Clower
    Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Mainz, Staudingerweg 5, 55128 Mainz, Germany
  • , and 
  • Fabian Barthels
    Fabian Barthels
    Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg-University Mainz, Staudingerweg 5, 55128 Mainz, Germany
Cite this: J. Chem. Inf. Model. 2023, 63, 7, 2218–2225
Publication Date (Web):March 8, 2023
https://doi.org/10.1021/acs.jcim.2c01400
Copyright © 2023 The Authors. Published by American Chemical Society

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    Abstract

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    AlphaFold2 and RoseTTAfold impress with their high accuracy in protein structure prediction. However, for structure-based virtual screenings, not only the overall structure but especially the binding sites need to be accurately predicted. In this work, the docking performance for 66 targets with known ligands but without experimental structures available in the protein data bank was elucidated. The results suggest that using an experimental surrogate–ligand complex is often superior over homology models, and only at low sequence identity to the closest homologue AlphaFold2 structures show an equal performance. The generally high fluctuation of receiver operating characteristic area under the curve values obtained for different homology models suggests that multiple combinations of docking programs and homology models should be tested prior to prospective virtual screenings, and in some cases post-processing of crude models might be necessary.

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    Supporting Information

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    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.2c01400.

    • Detailed results of binder–decoy docking with FlexX, results of FlexX docking-setup pretesting with the DUD-E diversity subset, statistical evaluation of binder–decoy discrimination dockings with FlexX, detailed results of binder–decoy docking with FRED, statistical evaluation of binder–decoy discrimination dockings with FRED, excerpt of ROC AUC values for structures discussed, statistical evaluation of binder–decoy discrimination dockings with FlexX and FRED selecting homology model dockings with highest values in ROC AUC and logAUC, and violin-plot and box-plot representation of FlexX and FRED docking results (XLSX)

    • Ligands and decoys used for docking (ZIP)

    • Python script used for Uniprot–PDB comparison and BLAST sequence analysis and ChEMBL “single protein” target list as the starting point for test set generation (ZIP)

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    Cited By

    This article is cited by 1 publications.

    1. Ariane Nunes-Alves, Kenneth Merz. AlphaFold2 in Molecular Discovery. Journal of Chemical Information and Modeling 2023, 63 (19) , 5947-5949. https://doi.org/10.1021/acs.jcim.3c01459

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