Literature DB >> 16447281

An enhanced elastic network model to represent the motions of domain-swapped proteins.

Guang Song1, Robert L Jernigan.   

Abstract

Domain swapping is a process where two (or more) protein molecules form a dimer (or higher oligomer) by exchanging an identical domain. In this article, based on the observation that domains are rigid and hinge loops are highly flexible, we propose a new Elastic Network Model, domain-ENM, for domain-swapped proteins. In this model, the rigidity of domains is taken into account by using a larger spring constant for intradomain contacts. The large-scale transition of domain swapping is then novelly decomposed into the relative motion between the rigid domains (only 6 degrees of freedom) plus the internal fluctuations of each domain. Consequently, this approach has the potential to produce much more meaningful transition pathways than other simulation approaches that try to find pathways in a search space of large numbers of dimensions. In this article, we also propose a new way to define the overlap measure. Past approaches used an inappropriate comparison of the large-scale conformation displacement against the computed infinitesimal motions of modes. Here, we propose an infinitesimal version of the large-scale conformation change and then compare it with the modes of motions. As a result, we obtain much better overlap values. Using this new overlap definition, we are also able for the first time to give a clear, intuitive explanation why "open" forms tend to produce better overlap values than "closed" forms with traditional ENMs. Finally, as an application, we present a simple approach to show how domain-ENM can be used to generated transition pathways for domain-swapped proteins. 2006 Wiley-Liss, Inc.

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Year:  2006        PMID: 16447281     DOI: 10.1002/prot.20836

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  21 in total

1.  vGNM: a better model for understanding the dynamics of proteins in crystals.

Authors:  Guang Song; Robert L Jernigan
Journal:  J Mol Biol       Date:  2007-03-28       Impact factor: 5.469

2.  Predicting the order in which contacts are broken during single molecule protein stretching experiments.

Authors:  Joanna I Sułkowska; Andrzej Kloczkowski; Taner Z Sen; Marek Cieplak; Robert L Jernigan
Journal:  Proteins       Date:  2008-04

3.  How well can we understand large-scale protein motions using normal modes of elastic network models?

Authors:  Lei Yang; Guang Song; Robert L Jernigan
Journal:  Biophys J       Date:  2007-05-04       Impact factor: 4.033

4.  A unification of the elastic network model and the Gaussian network model for optimal description of protein conformational motions and fluctuations.

Authors:  Wenjun Zheng
Journal:  Biophys J       Date:  2008-01-30       Impact factor: 4.033

5.  Coarse-grained biomolecular simulation with REACH: realistic extension algorithm via covariance Hessian.

Authors:  Kei Moritsugu; Jeremy C Smith
Journal:  Biophys J       Date:  2007-08-10       Impact factor: 4.033

Review 6.  Normal mode analysis of biomolecular structures: functional mechanisms of membrane proteins.

Authors:  Ivet Bahar; Timothy R Lezon; Ahmet Bakan; Indira H Shrivastava
Journal:  Chem Rev       Date:  2010-03-10       Impact factor: 60.622

7.  Protein elastic network models and the ranges of cooperativity.

Authors:  Lei Yang; Guang Song; Robert L Jernigan
Journal:  Proc Natl Acad Sci U S A       Date:  2009-07-14       Impact factor: 11.205

8.  Gating transition of pentameric ligand-gated ion channels.

Authors:  Fangqiang Zhu; Gerhard Hummer
Journal:  Biophys J       Date:  2009-11-04       Impact factor: 4.033

9.  Generalized spring tensor models for protein fluctuation dynamics and conformation changes.

Authors:  Tu-Liang Lin; Guang Song
Journal:  BMC Struct Biol       Date:  2010-05-17

10.  Exploring the Roles of Proline in Three-Dimensional Domain Swapping from Structure Analysis and Molecular Dynamics Simulations.

Authors:  Yongqi Huang; Meng Gao; Zhengding Su
Journal:  Protein J       Date:  2018-02       Impact factor: 2.371

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