title: Principal component analysis of native ensembles of biomolecular structures (PCA_NEST): insights into functional dynamics.
abstract: BACKGROUND
  To efficiently analyze the 'native ensemble of conformations' accessible to proteins near their folded state and to extract essential information from observed distributions of conformations, reliable mathematical methods and computational tools are needed.
  
  
  RESULTS
  Examination of 24 pairs of structures determined by both NMR and X-ray reveals that the differences in the dynamics of the same protein resolved by the two techniques can be tracked to the most robust low frequency modes elucidated by principal component analysis (PCA) of NMR models. The active sites of enzymes are found to be highly constrained in these PCA modes. Furthermore, the residues predicted to be highly immobile are shown to be evolutionarily conserved, lending support to a PCA-based identification of potential functional sites. An online tool, PCA_NEST, is designed to derive the principal modes of conformational changes from structural ensembles resolved by experiments or generated by computations.
  
  
  BACKGROUND
  http://ignm.ccbb.pitt.edu/oPCA_Online.htm
authors.affiliation: University of Tokyo, Institute of Molecular and Cellular Bioscience, Tokyo, Japan. lwy1@iam.u-tokyo.ac.jp
authors.forename: Lee-Wei
authors.initials: LW
authors.lastname: Yang
authors.forename: Eran
authors.initials: E
authors.lastname: Eyal
authors.forename: Ivet
authors.initials: I
authors.lastname: Bahar
authors.forename: Akio
authors.initials: A
authors.lastname: Kitao
mesh_terms: D018360:Crystallography, X-Ray; D030562:Databases, Protein; D020407:Internet; D019906:Nuclear Magnetic Resonance, Biomolecular; D025341:Principal Component Analysis; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins