Constructing ensembles for intrinsically disordered proteins

The relatively flat energy landscapes associated with intrinsically disordered proteins makes modeling these systems especially problematic. A comprehensive model for these proteins requires one to build an ensemble consisting of a finite collection of structures, and their corresponding relative st...

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Bibliographic Details
Main Authors: Stultz, Collin M. (Contributor), Fisher, Charles K. (Author)
Other Authors: Harvard University- (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Research Laboratory of Electronics (Contributor)
Format: Article
Language:English
Published: Elsevier, 2015-10-02T17:41:59Z.
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Online Access:Get fulltext
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100 1 0 |a Stultz, Collin M.  |e author 
100 1 0 |a Harvard University-  |e contributor 
100 1 0 |a Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science  |e contributor 
100 1 0 |a Massachusetts Institute of Technology. Research Laboratory of Electronics  |e contributor 
100 1 0 |a Stultz, Collin M.  |e contributor 
700 1 0 |a Fisher, Charles K.  |e author 
245 0 0 |a Constructing ensembles for intrinsically disordered proteins 
260 |b Elsevier,   |c 2015-10-02T17:41:59Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/99137 
520 |a The relatively flat energy landscapes associated with intrinsically disordered proteins makes modeling these systems especially problematic. A comprehensive model for these proteins requires one to build an ensemble consisting of a finite collection of structures, and their corresponding relative stabilities, which adequately capture the range of accessible states of the protein. In this regard, methods that use computational techniques to interpret experimental data in terms of such ensembles are an essential part of the modeling process. In this review, we critically assess the advantages and limitations of current techniques and discuss new methods for the validation of these ensembles. 
546 |a en_US 
655 7 |a Article 
773 |t Current Opinion in Structural Biology