Literature DB >> 16957327

Packing regularities in biological structures relate to their dynamics.

Robert L Jernigan1, Andrzej Kloczkowski.   

Abstract

The high packing density inside proteins leads to certain geometric regularities and also is one of the most important contributors to the high extent of cooperativity manifested by proteins in their cohesive domain motions. The orientations between neighboring nonbonded residues in proteins substantially follow the similar geometric regularities, regardless of whether the residues are on the surface or buried, a direct result of hydrophobicity forces. These orientations are relatively fixed and correspond closely to small deformations from those of the face-centered cubic lattice, which is the way in which identical spheres pack at the highest density. Packing density also is related to the extent of conservation of residues, and we show this relationship for residue packing densities by averaging over a large sample or residue packings. There are three regimes: (1) over a broad range of packing densities the relationship between sequence entropy and inverse packing density is nearly linear, (2) over a limited range of low packing densities the sequence entropy is nearly constant, and (3) at extremely low packing densities the sequence entropy is highly variable. These packing results provide important justification for the simple elastic network models that have been shown for a large number of proteins to represent protein dynamics so successfully, even when the models are extremely coarse grained. Elastic network models for polymeric chains are simple and could be combined with these protein elastic networks to represent partially denatured parts of proteins. Finally, we show results of applications of the elastic network model to study the functional motions of the ribosome, based on its known structure. These results indicate expected correlations among its components for the step-wise processing steps in protein synthesis, and suggest ways to use these elastic network models to develop more detailed mechanisms, an important possibility because most experiments yield only static structures.

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Year:  2007        PMID: 16957327      PMCID: PMC2039702          DOI: 10.1385/1-59745-189-4:251

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  79 in total

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3.  Exploring global distortions of biological macromolecules and assemblies from low-resolution structural information and elastic network theory.

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4.  Flexible multi-scale fitting of atomic structures into low-resolution electron density maps with elastic network normal mode analysis.

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Journal:  J Mol Biol       Date:  2004-04-02       Impact factor: 5.469

5.  Protein sequence entropy is closely related to packing density and hydrophobicity.

Authors:  H Liao; W Yeh; D Chiang; R L Jernigan; B Lustig
Journal:  Protein Eng Des Sel       Date:  2005-03-23       Impact factor: 1.650

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Journal:  Proteins       Date:  1995-12

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Authors:  H Li; C Tang; N S Wingreen
Journal:  Proc Natl Acad Sci U S A       Date:  1998-04-28       Impact factor: 11.205

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Journal:  Proteins       Date:  2004-02-15
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  10 in total

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Authors:  Michael T Zimmermann; Sumudu P Leelananda; Pawel Gniewek; Yaping Feng; Robert L Jernigan; Andrzej Kloczkowski
Journal:  J Struct Funct Genomics       Date:  2011-06-15

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5.  MAVENs: motion analysis and visualization of elastic networks and structural ensembles.

Authors:  Michael T Zimmermann; Andrzej Kloczkowski; Robert L Jernigan
Journal:  BMC Bioinformatics       Date:  2011-06-28       Impact factor: 3.307

6.  Voronoia: analyzing packing in protein structures.

Authors:  Kristian Rother; Peter Werner Hildebrand; Andrean Goede; Bjoern Gruening; Robert Preissner
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7.  Elastic network models capture the motions apparent within ensembles of RNA structures.

Authors:  Michael T Zimmermann; Robert L Jernigan
Journal:  RNA       Date:  2014-04-23       Impact factor: 4.942

8.  A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility.

Authors:  Tsun-Tsao Huang; María Laura del Valle Marcos; Jenn-Kang Hwang; Julian Echave
Journal:  BMC Evol Biol       Date:  2014-04-09       Impact factor: 3.260

9.  The case for intrinsically disordered proteins playing contributory roles in molecular recognition without a stable 3D structure.

Authors:  Vladimir N Uversky; A Keith Dunker
Journal:  F1000 Biol Rep       Date:  2013-01-11

10.  Immunoglobulin Structure Exhibits Control over CDR Motion.

Authors:  Michael T Zimmermann; Aris Skliros; Andrzej Kloczkowski; Robert L Jernigan
Journal:  Immunome Res       Date:  2011
  10 in total

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