Correspondences between low-energy modes in enzymes: Dynamics-based alignment of enzymatic functional families

Andrea Zen, Vincenzo Carnevale, Arthur M. Lesk, Cristian Micheletti

Research output: Contribution to journalArticlepeer-review

54 Scopus citations

Abstract

Proteins that show similarity in their equilibrium dynamics can be aligned by identifying regions that undergo similar concerted movements. These movements are computed from protein native structures using coarse-grained elastic network models. We show the existence of common large-scale movements in enzymes selected from the main functional and structural classes. Alignment via dynamics does not require prior detection of sequence or structural correspondence. Indeed, a third of the statistically significant dynamics-based alignments involve enzymes that lack substantial global or local structural similarities. The analysis of specific residue-residue correspondences of these structurally dissimilar enzymes in some cases suggests a functional relationship of the detected common dynamic features. Including dynamics-based criteria in protein alignment thus provides a promising avenue for relating and grouping enzymes in terms of dynamic aspects that often, though not always, assist or accompany biological function.

Original languageEnglish (US)
Pages (from-to)918-929
Number of pages12
JournalProtein Science
Volume17
Issue number5
DOIs
StatePublished - May 2008

All Science Journal Classification (ASJC) codes

  • Biochemistry
  • Molecular Biology

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