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Towards comprehensive analysis of protein family quantitative stability-flexibility relationships using homology models.
Verma, Deeptak; Guo, Jun-Tao; Jacobs, Donald J; Livesay, Dennis R.
Afiliación
  • Verma D; Department of Bioinformatics and Genomics, University of North Carolina, Charlotte, NC, USA.
Methods Mol Biol ; 1084: 239-54, 2014.
Article en En | MEDLINE | ID: mdl-24061925
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proteínas / Modelos Moleculares / Relación Estructura-Actividad Cuantitativa Límite: Animals / Humans Idioma: En Revista: Methods Mol Biol Asunto de la revista: BIOLOGIA MOLECULAR Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proteínas / Modelos Moleculares / Relación Estructura-Actividad Cuantitativa Límite: Animals / Humans Idioma: En Revista: Methods Mol Biol Asunto de la revista: BIOLOGIA MOLECULAR Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos
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