Literature DB >> 20023721

Conformational averaging in structural biology: issues, challenges and computational solutions.

Daniela Kruschel1, Bojan Zagrovic.   

Abstract

Most experimental methods in structural biology provide time- and ensemble-averaged signals and, consequently, molecular structures based on such signals often exhibit only idealized, average features. Second, most experimental signals are only indirectly related to real, molecular geometries, and solving a structure typically involves a complicated procedure, which may not always result in a unique solution. To what extent do such conformationally-averaged, non-linear experimental signals and structural models derived from them accurately represent the underlying microscopic reality? Are there some structural motifs that are actually artificially more likely to be "seen" in an experiment simply due to the averaging artifact? Finally, what are the practical consequences of ignoring the averaging effects when it comes to functional and mechanistic implications that we try to glean from experimentally-based structural models? In this review, we critically address the work that has been aimed at studying such questions. We summarize the details of experimental methods typically used in structural biology (most notably nuclear magnetic resonance, X-ray crystallography and different types of spectroscopy), discuss their individual susceptibility to conformational (motional) averaging, and review several theoretical approaches, most importantly molecular dynamics simulations that are increasingly being used to aid experimentalists in interpreting structural biology experiments.

Mesh:

Year:  2009        PMID: 20023721     DOI: 10.1039/b917186j

Source DB:  PubMed          Journal:  Mol Biosyst        ISSN: 1742-2051


  17 in total

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Journal:  Phys Chem Chem Phys       Date:  2017-12-13       Impact factor: 3.676

2.  Structural ensemble and microscopic elasticity of freely diffusing DNA by direct measurement of fluctuations.

Authors:  Xuesong Shi; Daniel Herschlag; Pehr A B Harbury
Journal:  Proc Natl Acad Sci U S A       Date:  2013-04-01       Impact factor: 11.205

3.  From a structural average to the conformational ensemble of a DNA bulge.

Authors:  Xuesong Shi; Kyle A Beauchamp; Pehr B Harbury; Daniel Herschlag
Journal:  Proc Natl Acad Sci U S A       Date:  2014-03-31       Impact factor: 11.205

4.  Using entropy maximization to understand the determinants of structural dynamics beyond native contact topology.

Authors:  Timothy R Lezon; Ivet Bahar
Journal:  PLoS Comput Biol       Date:  2010-06-17       Impact factor: 4.475

5.  The effects of rigid motions on elastic network model force constants.

Authors:  Timothy R Lezon
Journal:  Proteins       Date:  2012-01-07

6.  Peptide crystal simulations reveal hidden dynamics.

Authors:  Pawel A Janowski; David S Cerutti; James Holton; David A Case
Journal:  J Am Chem Soc       Date:  2013-05-16       Impact factor: 15.419

7.  Dynamics may significantly influence the estimation of interatomic distances in biomolecular X-ray structures.

Authors:  Antonija Kuzmanic; Daniela Kruschel; Wilfred F van Gunsteren; Navraj S Pannu; Bojan Zagrovic
Journal:  J Mol Biol       Date:  2011-05-30       Impact factor: 5.469

Review 8.  Synergistic applications of MD and NMR for the study of biological systems.

Authors:  Olivier Fisette; Patrick Lagüe; Stéphane Gagné; Sébastien Morin
Journal:  J Biomed Biotechnol       Date:  2012-01-26

9.  Vienna-PTM web server: a toolkit for MD simulations of protein post-translational modifications.

Authors:  Christian Margreitter; Drazen Petrov; Bojan Zagrovic
Journal:  Nucleic Acids Res       Date:  2013-05-22       Impact factor: 16.971

10.  A systematic framework for molecular dynamics simulations of protein post-translational modifications.

Authors:  Drazen Petrov; Christian Margreitter; Melanie Grandits; Chris Oostenbrink; Bojan Zagrovic
Journal:  PLoS Comput Biol       Date:  2013-07-18       Impact factor: 4.475

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