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Towards comprehensive analysis of protein family quantitative stability-flexibility relationships using homology models.


ABSTRACT: The Distance Constraint Model (DCM) is a computational modeling scheme that uniquely integrates thermodynamic and mechanical descriptions of protein structure. As such, quantitative stability-flexibility relationships (QSFR) that describe the interrelationships of thermodynamics and mechanics can be quickly computed. Using comparative QSFR analyses, we have previously investigated these relationships across a small number of protein orthologs, ranging from two to a dozen [1, 2]. However, our ultimate goal is provide a comprehensive analysis of whole protein families, which requires consideration of many more structures. To that end, we have developed homology modeling and assessment protocols so that we can robustly calculate QSFR properties for proteins without experimentally derived structures. The approach, which is presented here, starts from a large ensemble of potential homology models and uses a clustering algorithm to identify the best models, thus paving the way for a comprehensive QSFR analysis across hundreds of proteins in a protein family.

SUBMITTER: Verma D 

PROVIDER: S-EPMC4676804 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Towards comprehensive analysis of protein family quantitative stability-flexibility relationships using homology models.

Verma Deeptak D   Guo Jun-Tao JT   Jacobs Donald J DJ   Livesay Dennis R DR  

Methods in molecular biology (Clifton, N.J.) 20140101


The Distance Constraint Model (DCM) is a computational modeling scheme that uniquely integrates thermodynamic and mechanical descriptions of protein structure. As such, quantitative stability-flexibility relationships (QSFR) that describe the interrelationships of thermodynamics and mechanics can be quickly computed. Using comparative QSFR analyses, we have previously investigated these relationships across a small number of protein orthologs, ranging from two to a dozen [1, 2]. However, our ult  ...[more]

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