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Assessment of template-based protein structure predictions in CASP10.
Huang, Yuanpeng J; Mao, Binchen; Aramini, James M; Montelione, Gaetano T.
Afiliación
  • Huang YJ; Center for Advanced Biotechnology and Medicine and Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, Piscataway, New Jersey, 08854; Department of Biochemistry and Molecular Biology, Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, Piscataway, New Jersey, 08854; Northeast Structural Genomics Consortium, Rutgers, The State University of New Jersey, Piscataway, New Jersey, 08854.
Proteins ; 82 Suppl 2: 43-56, 2014 Feb.
Article en En | MEDLINE | ID: mdl-24323734
Template-based modeling (TBM) is a major component of the critical assessment of protein structure prediction (CASP). In CASP10, some 41,740 predicted models submitted by 150 predictor groups were assessed as TBM predictions. The accuracy of protein structure prediction was assessed by geometric comparison with experimental X-ray crystal and NMR structures using a composite score that included both global alignment metrics and distance-matrix-based metrics. These included GDT-HA and GDC-all global alignment scores, and the superimposition-independent LDDT distance-matrix-based score. In addition, a superimposition-independent RPF metric, similar to that described previously for comparing protein models against experimental NMR data, was used for comparing predicted protein structure models against experimental protein structures. To score well on all four of these metrics, models must feature accurate predictions of both backbone and side-chain conformations. Performance rankings were determined independently for server and the combined server plus human-curated predictor groups. Final rankings were made using paired head-to-head Student's t-test analysis of raw metric scores among the top 25 performing groups in each category.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Conformación Proteica / Proteínas / Biología Computacional Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Proteins Asunto de la revista: BIOQUIMICA Año: 2014 Tipo del documento: Article Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Conformación Proteica / Proteínas / Biología Computacional Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Proteins Asunto de la revista: BIOQUIMICA Año: 2014 Tipo del documento: Article Pais de publicación: Estados Unidos