Cov_DOX: A Method for Structure Prediction of Covalent Protein-Ligand Bindings

J Med Chem. 2022 Apr 14;65(7):5528-5538. doi: 10.1021/acs.jmedchem.1c02007. Epub 2022 Mar 30.

Abstract

A handful of molecular docking tools have been extended to enable a covalent docking. However, all of them face the challenge brought by the covalent bond between proteins and ligands. Many covalent drug design scenarios still heavily rely on demanding crystallographic experiments for accurate binding structures. Aiming at filling the gap between covalent dockings and crystallographic experiments, we develop and validate a hybrid method, dubbed as Cov_DOX, in this work. Cov_DOX achieves an overall success rate of 81% with RMSD < 2 Å for the Top 1 pose prediction in the validation against a test set including 405 crystal structures for covalent protein-ligand complexes, covering various types of the warhead chemistry and receptors. Such accuracy is not far from the much more demanding crystallographic experiments, in sharp contrast to the performance of the covalent docking front runners (success rate: 40-60%).

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Binding Sites
  • Drug Design*
  • Ligands
  • Molecular Docking Simulation
  • Protein Binding
  • Proteins* / chemistry

Substances

  • Ligands
  • Proteins