Literature DB >> 15345525

Probing protein mechanics: residue-level properties and their use in defining domains.

Isabelle Navizet1, Fabien Cailliez, Richard Lavery.   

Abstract

It is becoming clear that, in addition to structural properties, the mechanical properties of proteins can play an important role in their biological activity. It nevertheless remains difficult to probe these properties experimentally. Whereas single-molecule experiments give access to overall mechanical behavior, notably the impact of end-to-end stretching, it is currently impossible to directly obtain data on more local properties. We propose a theoretical method for probing the mechanical properties of protein structures at the single-amino acid level. This approach can be applied to both all-atom and simplified protein representations. The probing leads to force constants for local deformations and to deformation vectors indicating the paths of least mechanical resistance. It also reveals the mechanical coupling that exists between residues. Results obtained for a variety of proteins show that the calculated force constants vary over a wide range. An analysis of the induced deformations provides information that is distinct from that obtained with measures of atomic fluctuations and is more easily linked to residue-level properties than normal mode analyses or dynamic trajectories. It is also shown that the mechanical information obtained by residue-level probing opens a new route for defining so-called dynamical domains within protein structures.

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Year:  2004        PMID: 15345525      PMCID: PMC1304551          DOI: 10.1529/biophysj.104.042085

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  52 in total

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  15 in total

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6.  Tensile mechanics of alanine-based helical polypeptide: force spectroscopy versus computer simulations.

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9.  Accounting for large amplitude protein deformation during in silico macromolecular docking.

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10.  Structure-based predictive models for allosteric hot spots.

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Journal:  PLoS Comput Biol       Date:  2009-10-09       Impact factor: 4.475

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