The use of soluble protein structures in modeling helical proteins in a layered membrane.
J Biomol Struct Dyn
; 32(2): 308-18, 2014.
Article
em En
| MEDLINE
| ID: mdl-23527746
ABSTRACT
Major advances have been made in the prediction of soluble protein structures, led by the knowledge-based modeling methods that extract useful structural trends from known protein structures and incorporate them into scoring functions. The same cannot be reported for the class of transmembrane proteins, primarily due to the lack of high-resolution structural data for transmembrane proteins, which render many of the knowledge-based method unreliable or invalid. We have developed a method that harnesses the vast structural knowledge available in soluble protein data for use in the modeling of transmembrane proteins. At the core of the method, a set of transmembrane protein decoy sets that allow us to filter and train features recognized from soluble proteins for transmembrane protein modeling into a set of scoring functions. We have demonstrated that structures of soluble proteins can provide significant insight into transmembrane protein structures. A complementary novel two-stage modeling/selection process that mimics the two-stage helical membrane protein folding was developed. Combined with the scoring function, the method was successfully applied to model 5 transmembrane proteins. The root mean square deviations of the predicted models ranged from 5.0 to 8.8 Å to the native structures.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Membrana Celular
/
Proteínas de Membrana
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
J Biomol Struct Dyn
Ano de publicação:
2014
Tipo de documento:
Article
País de afiliação:
Austrália