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Fragment-based modeling of membrane protein loops: successes, failures, and prospects for the future.
Kelm, Sebastian; Vangone, Anna; Choi, Yoonjoo; Ebejer, Jean-Paul; Shi, Jiye; Deane, Charlotte M.
Afiliação
  • Kelm S; Department of Statistics, University of Oxford, Oxford, United Kingdom.
Proteins ; 82(2): 175-86, 2014 Feb.
Article em En | MEDLINE | ID: mdl-23589399
ABSTRACT
Membrane proteins (MPs) have become a major focus in structure prediction, due to their medical importance. There is, however, a lack of fast and reliable methods that specialize in the modeling of MP loops. Often methods designed for soluble proteins (SPs) are applied directly to MPs. In this article, we investigate the validity of such an approach in the realm of fragment-based methods. We also examined the differences in membrane and soluble protein loops that might affect accuracy. We test our ability to predict soluble and MP loops with the previously published method FREAD. We show that it is possible to predict accurately the structure of MP loops using a database of MP fragments (0.5-1 Å median root-mean-square deviation). The presence of homologous proteins in the database helps prediction accuracy. However, even when homologues are removed better results are still achieved using fragments of MPs (0.8-1.6 Å) rather than SPs (1-4 Å) to model MP loops. We find that many fragments of SPs have shapes similar to their MP counterparts but have very different sequences; however, they do not appear to differ in their substitution patterns. Our findings may allow further improvements to fragment-based loop modeling algorithms for MPs. The current version of our proof-of-concept loop modeling protocol produces high-accuracy loop models for MPs and is available as a web server at http//medeller.info/fread.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fragmentos de Peptídeos / Simulação por Computador / Modelos Moleculares / Proteínas de Membrana Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2014 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fragmentos de Peptídeos / Simulação por Computador / Modelos Moleculares / Proteínas de Membrana Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2014 Tipo de documento: Article