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Bioinformatics Advance Access published online on January 15, 2009
Bioinformatics, doi:10.1093/bioinformatics/btp023
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© The Author (2009). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Principal Component Analysis of Native Ensembles of Biomolecular Structures (PCA_NEST): Insights into Functional Dynamics

Lee-Wei Yang 1,*, Eran Eyal 2, Ivet Bahar 2 and Akio Kitao 1,3

1Univ of Tokyo, Institute of Molecular and Cellular Bioscience, Tokyo, Japan 2Univ of Pittsburgh, School of Medicine, Dept of Computational Biology, Pittsburgh, PA, USA. and 3JST, CREST, Japan

*To whom correspondence should be addressed. Dr. Lee-Wei Yang, E-mail: lwy1{at}pitt.edu, lwy1{at}iam.u-tokyo.ac.jp


  Abstract

Motivation: 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.

Availability: http://ignm.ccbb.pitt.edu/oPCA_Online.htm

Contact: lwy1{at}iam.u-tokyo.ac.jp

Associate Editor: Prof. Burkhard Rost

Received on September 8, 2008; revised on December 11, 2008; accepted on January 8, 2009

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