AlphaFold2 structures guide prospective ligand discovery

Science. 2024 Jun 21;384(6702):eadn6354. doi: 10.1126/science.adn6354. Epub 2024 Jun 21.

Abstract

AlphaFold2 (AF2) models have had wide impact but mixed success in retrospective ligand recognition. We prospectively docked large libraries against unrefined AF2 models of the σ2 and serotonin 2A (5-HT2A) receptors, testing hundreds of new molecules and comparing results with those obtained from docking against the experimental structures. Hit rates were high and similar for the experimental and AF2 structures, as were affinities. Success in docking against the AF2 models was achieved despite differences between orthosteric residue conformations in the AF2 models and the experimental structures. Determination of the cryo-electron microscopy structure for one of the more potent 5-HT2A ligands from the AF2 docking revealed residue accommodations that resembled the AF2 prediction. AF2 models may sample conformations that differ from experimental structures but remain low energy and relevant for ligand discovery, extending the domain of structure-based drug design.

MeSH terms

  • Cryoelectron Microscopy
  • Deep Learning*
  • Drug Design
  • Drug Discovery* / methods
  • Humans
  • Ligands
  • Molecular Docking Simulation*
  • Protein Conformation
  • Protein Folding
  • Receptor, Serotonin, 5-HT2A* / chemistry
  • Receptor, Serotonin, 5-HT2A* / ultrastructure
  • Receptors, sigma / chemistry
  • Receptors, sigma / metabolism
  • Serotonin 5-HT2 Receptor Agonists* / chemistry
  • Serotonin 5-HT2 Receptor Agonists* / pharmacology
  • Serotonin 5-HT2 Receptor Antagonists* / chemistry
  • Serotonin 5-HT2 Receptor Antagonists* / pharmacology
  • Small Molecule Libraries / chemistry

Substances

  • Ligands
  • Receptor, Serotonin, 5-HT2A
  • Receptors, sigma
  • Small Molecule Libraries
  • Serotonin 5-HT2 Receptor Agonists
  • Serotonin 5-HT2 Receptor Antagonists