Protein flexibility in ligand docking and virtual screening to protein kinases

J Mol Biol. 2004 Mar 12;337(1):209-25. doi: 10.1016/j.jmb.2004.01.003.

Abstract

The main complicating factor in structure-based drug design is receptor rearrangement upon ligand binding (induced fit). It is the induced fit that complicates cross-docking of ligands from different ligand-receptor complexes. Previous studies have shown the necessity to include protein flexibility in ligand docking and virtual screening. Very few docking methods have been developed to predict the induced fit reliably and, at the same time, to improve on discriminating between binders and non-binders in the virtual screening process. We present an algorithm called the ICM-flexible receptor docking algorithm (IFREDA) to account for protein flexibility in virtual screening. By docking flexible ligands to a flexible receptor, IFREDA generates a discrete set of receptor conformations, which are then used to perform flexible ligand-rigid receptor docking and scoring. This is followed by a merging and shrinking step, where the results of the multiple virtual screenings are condensed to improve the enrichment factor. In the IFREDA approach, both side-chain rearrangements and essential backbone movements are taken into consideration, thus sampling adequately the conformational space of the receptor, even in cases of large loop movements. As a preliminary step, to show the importance of incorporating protein flexibility in ligand docking and virtual screening, and to validate the merging and shrinking procedure, we compiled an extensive small-scale virtual screening benchmark of 33 crystal structures of four different protein kinases sub-families (cAPK, CDK-2, P38 and LCK), where we obtained an enrichment factor fold-increase of 1.85+/-0.65 using two or three multiple experimental conformations. IFREDA was used in eight protein kinase complexes and was able to find the correct ligand conformation and discriminate the correct conformations from the "misdocked" conformations solely on the basis of energy calculation. Five of the generated structures were used in the small-scale virtual screening stage and, by merging and shrinking the results with those of the original structure, we show an enrichment factor fold increase of 1.89+/-0.60, comparable to that obtained using multiple experimental conformations. Our cross-docking tests on the protein kinase benchmark underscore the necessity of incorporating protein flexibility in both ligand docking and virtual screening. The methodology presented here will be extremely useful in cases where few or no experimental structures of complexes are available, while some binders are known.

MeSH terms

  • Algorithms
  • Azepines / chemistry
  • Azepines / metabolism
  • Drug Design
  • Enzyme Inhibitors / chemistry
  • Enzyme Inhibitors / metabolism
  • Hydroxybenzoates / chemistry
  • Hydroxybenzoates / metabolism
  • Ligands*
  • Models, Molecular
  • Molecular Sequence Data
  • Molecular Structure
  • Protein Binding
  • Protein Conformation*
  • Protein Kinase Inhibitors
  • Protein Kinases / chemistry*
  • Protein Kinases / metabolism*
  • Receptors, Cell Surface / chemistry
  • Receptors, Cell Surface / metabolism
  • Staurosporine / chemistry
  • Staurosporine / metabolism

Substances

  • Azepines
  • Enzyme Inhibitors
  • Hydroxybenzoates
  • Ligands
  • Protein Kinase Inhibitors
  • Receptors, Cell Surface
  • ophiocordin
  • Protein Kinases
  • Staurosporine