Your browser doesn't support javascript.
loading
Modeling and fitting protein-protein complexes to predict change of binding energy.
Dourado, Daniel F A R; Flores, Samuel Coulbourn.
Afiliación
  • Dourado DF; Department of Cell and Molecular Biology, Computational and Systems Biology, Uppsala University, Biomedical Center Box 596, 751 24, Uppsala, Sweden.
  • Flores SC; Department of Cell and Molecular Biology, Computational and Systems Biology, Uppsala University, Biomedical Center Box 596, 751 24, Uppsala, Sweden.
Sci Rep ; 6: 25406, 2016 05 13.
Article en En | MEDLINE | ID: mdl-27173910
It is possible to accurately and economically predict change in protein-protein interaction energy upon mutation (ΔΔG), when a high-resolution structure of the complex is available. This is of growing usefulness for design of high-affinity or otherwise modified binding proteins for therapeutic, diagnostic, industrial, and basic science applications. Recently the field has begun to pursue ΔΔG prediction for homology modeled complexes, but so far this has worked mostly for cases of high sequence identity. If the interacting proteins have been crystallized in free (uncomplexed) form, in a majority of cases it is possible to find a structurally similar complex which can be used as the basis for template-based modeling. We describe how to use MMB to create such models, and then use them to predict ΔΔG, using a dataset consisting of free target structures, co-crystallized template complexes with sequence identify with respect to the targets as low as 44%, and experimental ΔΔG measurements. We obtain similar results by fitting to a low-resolution Cryo-EM density map. Results suggest that other structural constraints may lead to a similar outcome, making the method even more broadly applicable.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proteínas / Modelos Moleculares / Complejos Multiproteicos Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sci Rep Año: 2016 Tipo del documento: Article País de afiliación: Suecia

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proteínas / Modelos Moleculares / Complejos Multiproteicos Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sci Rep Año: 2016 Tipo del documento: Article País de afiliación: Suecia
...