Bioinformatics Advance Access originally published online on January 15, 2009
Bioinformatics 2009 25(5):606-614; doi:10.1093/bioinformatics/btp023
Principal component analysis of native ensembles of biomolecular structures (PCA_NEST): insights into functional dynamics
1University of Tokyo, Institute of Molecular and Cellular Bioscience, Tokyo, Japan, 2University of Pittsburgh, School of Medicine, Department of Computational Biology, PA, USA and 3Japan Science and Technology Agency, Core Research for Evolutional Science and Technology, Japan
*To whom correspondence should be addressed.
| Abstract |
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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.
Result: 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
Supplementary information: Supplementary data are available at Bioinformatics online.
Associate Editor: Burkhard Rost
Received on September 8, 2008; revised on December 11, 2008; accepted on January 8, 2009
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