High quality binding modes in docking ligands to proteins

Boris Gorelik, Amiram Goldblum*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

Abstract

Multiple near-optimal conformations of protein-ligand complexes provide a better chance for accurate representation of biomolecular interactions, compared with a single structure. We present ISE-dock - a docking program which is based on the iterative stochastic elimination (ISE) algorithm. ISE eliminates values that consistently lead to the worst results, thus optimizing the search for docking poses. It constructs large sets of such poses with no additional computational cost compared with single poses. ISE-dock is validated using 81 protein-ligand complexes from the PDB and its performance was compared with those of Glide, GOLD, and AutoDock. ISE-dock has a better chance than the other three to find more than 60% top single poses under RMSD = 2.0 Å and more than 80% under RMSD = 3.0 Å from experimental. ISE alone produced at least one 3.0 Å or better solutions among the top 20 poses in the entire test set. In 98% of the examined molecules, ISE produced solutions that are closer than 2.0 Å from experimental. Paired t-tests (PTT) were used throughout to assess the significance of comparisons between the performances of the different programs. ISE-dock provides more than 100-fold docking solutions in a similar time frame as LGA in AutoDock. We demonstrate the usefulness of the large near optimal populations of ligand poses by showing a correlation between the docking results and experiments that support multiple binding modes in p38 MAP kinase (Pargellis et al., Nat Struct Biol 2002;9:268-272] and in Human Transthyretin (Hamilton, Benson, Cell Mol Life Sci 2001;58:1491-1521).

Original languageAmerican English
Pages (from-to)1373-1386
Number of pages14
JournalProteins: Structure, Function and Genetics
Volume71
Issue number3
DOIs
StatePublished - 15 May 2008

Keywords

  • AutoDock
  • Flexible docking
  • GOLD
  • Glide
  • Iterative stochastic elimination
  • Multiple binding modes
  • Populations
  • Protein-ligand docking

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