Literature DB >> 16917941

Modeling protein conformational ensembles: from missing loops to equilibrium fluctuations.

Amarda Shehu1, Cecilia Clementi, Lydia E Kavraki.   

Abstract

Characterizing protein flexibility is an important goal for understanding the physical-chemical principles governing biological function. This paper presents a Fragment Ensemble Method to capture the mobility of a protein fragment such as a missing loop and its extension into a Protein Ensemble Method to characterize the mobility of an entire protein at equilibrium. The underlying approach in both methods is to combine a geometric exploration of conformational space with a statistical mechanics formulation to generate an ensemble of physical conformations on which thermodynamic quantities can be measured as ensemble averages. The Fragment Ensemble Method is validated by applying it to characterize loop mobility in both instances of strongly stable and disordered loop fragments. In each instance, fluctuations measured over generated ensembles are consistent with data from experiment and simulation. The Protein Ensemble Method captures the mobility of an entire protein by generating and combining ensembles of conformations for consecutive overlapping fragments defined over the protein sequence. This method is validated by applying it to characterize flexibility in ubiquitin and protein G. Thermodynamic quantities measured over the ensembles generated for both proteins are fully consistent with available experimental data. On these proteins, the method recovers nontrivial data such as order parameters, residual dipolar couplings, and scalar couplings. Results presented in this work suggest that the proposed methods can provide insight into the interplay between protein flexibility and function. Proteins 2006. (c) 2006 Wiley-Liss, Inc.

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Year:  2006        PMID: 16917941     DOI: 10.1002/prot.21060

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


  28 in total

1.  Protein loop closure using orientational restraints from NMR data.

Authors:  Chittaranjan Tripathy; Jianyang Zeng; Pei Zhou; Bruce Randall Donald
Journal:  Proteins       Date:  2011-12-13

2.  The effect of end constraints on protein loop kinematics.

Authors:  Steven Hayward; Akio Kitao
Journal:  Biophys J       Date:  2010-05-19       Impact factor: 4.033

3.  Union of geometric constraint-based simulations with molecular dynamics for protein structure prediction.

Authors:  Tyler J Glembo; S Banu Ozkan
Journal:  Biophys J       Date:  2010-03-17       Impact factor: 4.033

Review 4.  Modeling loop entropy.

Authors:  Gregory S Chirikjian
Journal:  Methods Enzymol       Date:  2011       Impact factor: 1.600

5.  On the characterization of protein native state ensembles.

Authors:  Amarda Shehu; Lydia E Kavraki; Cecilia Clementi
Journal:  Biophys J       Date:  2006-12-08       Impact factor: 4.033

6.  Unfolding the fold of cyclic cysteine-rich peptides.

Authors:  Amarda Shehu; Lydia E Kavraki; Cecilia Clementi
Journal:  Protein Sci       Date:  2008-03       Impact factor: 6.725

7.  A black-box re-weighting analysis can correct flawed simulation data.

Authors:  F Marty Ytreberg; Daniel M Zuckerman
Journal:  Proc Natl Acad Sci U S A       Date:  2008-06-10       Impact factor: 11.205

8.  A HAUSDORFF-BASED NOE ASSIGNMENT ALGORITHM USING PROTEIN BACKBONE DETERMINED FROM RESIDUAL DIPOLAR COUPLINGS AND ROTAMER PATTERNS.

Authors:  Jianyang Michael Zeng; Chittaranjan Tripathy; Pei Zhou; Bruce R Donald
Journal:  Comput Syst Bioinformatics Conf       Date:  2008

9.  Structure-based protein NMR assignments using native structural ensembles.

Authors:  Mehmet Serkan Apaydin; Vincent Conitzer; Bruce Randall Donald
Journal:  J Biomol NMR       Date:  2008-03-26       Impact factor: 2.835

10.  Efficient algorithms to explore conformation spaces of flexible protein loops.

Authors:  Peggy Yao; Ankur Dhanik; Nathan Marz; Ryan Propper; Charles Kou; Guanfeng Liu; Henry van den Bedem; Jean-Claude Latombe; Inbal Halperin-Landsberg; Russ Biagio Altman
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2008 Oct-Dec       Impact factor: 3.710

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