Predicting large-scale conformational changes in proteins using energy-weighted normal modes

D. S. Palmer, F. Jensen

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


We report the development of a method to improve the sampling of protein conformational space in molecular simulations. It is shown that a principal component analysis of energy-weighted normal modes in Cartesian coordinates can be used to extract vectors suitable for describing the dynamics of protein substructures. The method can operate with either atomistic or user-defined coarse-grained models of protein structure. An implicit reverse coarse-graining allows the dynamics of all-atoms to be recovered when a coarse-grained model is used. For an external test set of four proteins, it is shown that the new method is more successful than normal mode analysis in describing the large-scale conformational changes observed on ligand binding. The method has potential applications in protein-ligand and protein-protein docking and in biasing molecular dynamics simulations.
Original languageEnglish
Pages (from-to)2778-2793
Number of pages16
JournalProteins: Structure, Function, and Bioinformatics
Issue number10
Publication statusPublished - 1 Oct 2011


  • normal
  • mode
  • vibrational
  • analysis
  • protein
  • conformation
  • large-scale
  • frequency


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