Accurate Structural Correlations from Maximum Likelihood Superpositions

The cores of globular proteins are densely packed, resulting in complicated networks of structural interactions. These interactions in turn give rise to dynamic structural correlations over a wide range of time scales. Accurate analysis of these complex correlations is crucial for understanding biom...

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Main Authors:	Theobald, Douglas L, Wuttke, Deborah S
Format:	Online
Language:	English
Published:	Public Library of Science 2008
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2242818/

id	pubmed-2242818
recordtype	oai_dc
spelling	pubmed-22428182008-02-15 Accurate Structural Correlations from Maximum Likelihood Superpositions Theobald, Douglas L Wuttke, Deborah S Research Article The cores of globular proteins are densely packed, resulting in complicated networks of structural interactions. These interactions in turn give rise to dynamic structural correlations over a wide range of time scales. Accurate analysis of these complex correlations is crucial for understanding biomolecular mechanisms and for relating structure to function. Here we report a highly accurate technique for inferring the major modes of structural correlation in macromolecules using likelihood-based statistical analysis of sets of structures. This method is generally applicable to any ensemble of related molecules, including families of nuclear magnetic resonance (NMR) models, different crystal forms of a protein, and structural alignments of homologous proteins, as well as molecular dynamics trajectories. Dominant modes of structural correlation are determined using principal components analysis (PCA) of the maximum likelihood estimate of the correlation matrix. The correlations we identify are inherently independent of the statistical uncertainty and dynamic heterogeneity associated with the structural coordinates. We additionally present an easily interpretable method (“PCA plots”) for displaying these positional correlations by color-coding them onto a macromolecular structure. Maximum likelihood PCA of structural superpositions, and the structural PCA plots that illustrate the results, will facilitate the accurate determination of dynamic structural correlations analyzed in diverse fields of structural biology. Public Library of Science 2008-02 2008-02-15 /pmc/articles/PMC2242818/ /pubmed/18282091 http://dx.doi.org/10.1371/journal.pcbi.0040043 Text en © 2008 Theobald and Wuttke. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Theobald, Douglas L Wuttke, Deborah S
spellingShingle	Theobald, Douglas L Wuttke, Deborah S Accurate Structural Correlations from Maximum Likelihood Superpositions
author_facet	Theobald, Douglas L Wuttke, Deborah S
author_sort	Theobald, Douglas L
title	Accurate Structural Correlations from Maximum Likelihood Superpositions
title_short	Accurate Structural Correlations from Maximum Likelihood Superpositions
title_full	Accurate Structural Correlations from Maximum Likelihood Superpositions
title_fullStr	Accurate Structural Correlations from Maximum Likelihood Superpositions
title_full_unstemmed	Accurate Structural Correlations from Maximum Likelihood Superpositions
title_sort	accurate structural correlations from maximum likelihood superpositions
description	The cores of globular proteins are densely packed, resulting in complicated networks of structural interactions. These interactions in turn give rise to dynamic structural correlations over a wide range of time scales. Accurate analysis of these complex correlations is crucial for understanding biomolecular mechanisms and for relating structure to function. Here we report a highly accurate technique for inferring the major modes of structural correlation in macromolecules using likelihood-based statistical analysis of sets of structures. This method is generally applicable to any ensemble of related molecules, including families of nuclear magnetic resonance (NMR) models, different crystal forms of a protein, and structural alignments of homologous proteins, as well as molecular dynamics trajectories. Dominant modes of structural correlation are determined using principal components analysis (PCA) of the maximum likelihood estimate of the correlation matrix. The correlations we identify are inherently independent of the statistical uncertainty and dynamic heterogeneity associated with the structural coordinates. We additionally present an easily interpretable method (“PCA plots”) for displaying these positional correlations by color-coding them onto a macromolecular structure. Maximum likelihood PCA of structural superpositions, and the structural PCA plots that illustrate the results, will facilitate the accurate determination of dynamic structural correlations analyzed in diverse fields of structural biology.
publisher	Public Library of Science
publishDate	2008
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2242818/
_version_	1611439018472374272

Accurate Structural Correlations from Maximum Likelihood Superpositions

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