Fragmentation-tree density representation for crystallographic modelling of bound ligands

J Mol Biol. 2012 Jun 8;419(3-4):211-22. doi: 10.1016/j.jmb.2012.03.012. Epub 2012 Mar 23.

Abstract

The identification and modelling of ligands into macromolecular models is important for understanding molecule's function and for designing inhibitors to modulate its activities. We describe new algorithms for the automated building of ligands into electron density maps in crystal structure determination. Location of the ligand-binding site is achieved by matching numerical shape features describing the ligand to those of density clusters using a "fragmentation-tree" density representation. The ligand molecule is built using two distinct algorithms exploiting free atoms with inter-atomic connectivity and Metropolis-based optimisation of the conformational state of the ligand, producing an ensemble of structures from which the final model is derived. The method was validated on several thousand entries from the Protein Data Bank. In the majority of cases, the ligand-binding site could be correctly located and the ligand model built with a coordinate accuracy of better than 1 Å. We anticipate that the method will be of routine use to anyone modelling ligands, lead compounds or even compound fragments as part of protein functional analyses or drug design efforts.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Binding Sites*
  • Crystallography, X-Ray / methods*
  • Ligands
  • Models, Molecular
  • Protein Binding*
  • Protein Conformation
  • Proteins / chemistry*
  • Proteins / metabolism
  • Structure-Activity Relationship

Substances

  • Ligands
  • Proteins