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Lee-Wei Yang, Eran Eyal, Ivet Bahar and Akio Kitao. Principal Component Analysis of Native Ensembles of Biomolecular Structures (PCA_NEST): Insights into Functional Dynamics. Bioinformatics 25:606-614 (2009)
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Provide an easy-to-use application for extracting dominant motions from multiple experimental (or theoretical) structures of a given protein (or other biomolecules).


The concept of ‘native ensemble of conformations’ is such that the experimentally determined (by X-ray, NMR) protein ensembles suggest a handful of intrinsically favored conformational transition pathways that are as 'native' as can be described by first-principle-based physics models. Structural biologists and theoretical chemists are welcome to submit multiple conformers of a given protein to our online server, PCA_NEST. PCA_NEST best-aligns those iteratively until the mean structure in subsequent cycle reaches convergence. It then performs Principal Component Analysis on the best-aligned ensemble to obtain sets of dominant motions (the principal components) of the protein. We have shown previously that low modes derived from elastic network models (ENMs) coincide with PCA_NEST-derived dominant motions suggesting that once perceived structural 'errors' can be described by simple-model-inferred vibrational slow modes.

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At the moment we give the web site links to PCA_NEST. We may provide libraries, tools, codes for best-alignment, trajectory file readers and covariance matrix builder/solver in the future.

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