Journal Article

Principal component analysis of native ensembles of biomolecular structures (PCA_NEST): insights into functional dynamics

Lee-Wei Yang, Eran Eyal, Ivet Bahar and Akio Kitao

in Bioinformatics

Volume 25, issue 5, pages 606-614
Published in print March 2009 | ISSN: 1367-4803
Published online January 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp023
Principal component analysis of native ensembles of biomolecular structures (PCA_NEST): insights into functional dynamics

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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@iam.u-tokyo.ac.jp

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  5623 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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