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

Overview

Journal Bioinformatics

Publisher Oxford University Press

Specialty Biology

Date 2009 Jan 17

PMID 19147661

Citations 60

Authors

Lee-Wei Yang

Eran Eyal

Ivet Bahar

Akio Kitao

Affiliations

Soon will be listed here.

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.

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

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