Identifying Artifacts from Large Library Docking

J Med Chem. 2024 Sep 26;67(18):16796-16806. doi: 10.1021/acs.jmedchem.4c01632. Epub 2024 Sep 10.

Abstract

While large library docking has discovered potent ligands for multiple targets, as the libraries have grown the hit lists can become dominated by rare artifacts that cheat our scoring functions. Here, we investigate rescoring top-ranked docked molecules with orthogonal methods to identify these artifacts, exploring implicit solvent models and absolute binding free energy perturbation as cross-filters. In retrospective studies, this approach deprioritized high-ranking nonbinders for nine targets while leaving true ligands relatively unaffected. We tested the method prospectively against hits from docking against AmpC β-lactamase. We prioritized 128 high-ranking molecules for synthesis and testing, a mixture of 39 molecules flagged as likely cheaters and 89 that were plausible inhibitors. None of the predicted cheating compounds inhibited AmpC detectably, while 57% of the 89 plausible compounds did so. As our libraries continue to grow, deprioritizing docking artifacts by rescoring with orthogonal methods may find wide use.

MeSH terms

  • Artifacts
  • Bacterial Proteins / chemistry
  • Bacterial Proteins / metabolism
  • Ligands
  • Molecular Docking Simulation*
  • Small Molecule Libraries* / chemistry
  • Small Molecule Libraries* / metabolism
  • Small Molecule Libraries* / pharmacology
  • beta-Lactamase Inhibitors / chemical synthesis
  • beta-Lactamase Inhibitors / chemistry
  • beta-Lactamase Inhibitors / pharmacology
  • beta-Lactamases* / chemistry
  • beta-Lactamases* / metabolism

Substances

  • beta-Lactamases
  • Small Molecule Libraries
  • AmpC beta-lactamases
  • Ligands
  • Bacterial Proteins
  • beta-Lactamase Inhibitors