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The GD box: A widespread non-contiguous supersecondary structural element

MPG-Autoren

Alva,  V
Max Planck Institute for Developmental Biology, Max Planck Society;

Dunin-Horkawicz,  S
Max Planck Institute for Developmental Biology, Max Planck Society;

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Habeck,  M
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Developmental Biology, Max Planck Society;

Coles,  M
Max Planck Institute for Developmental Biology, Max Planck Society;

Lupas,  AN
Max Planck Institute for Developmental Biology, Max Planck Society;

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Zitation

Alva, V., Dunin-Horkawicz, S., Habeck, M., Coles, M., & Lupas, A. (2009). The GD box: A widespread non-contiguous supersecondary structural element. Protein Science, 18(9), 1961-1966. doi:10.1002/pro.207.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0013-C3F7-3
Zusammenfassung
Identification and characterization of recurrent supersecondary structural elements is central to understanding the rules governing protein tertiary structure. Here we describe the GD box, a widespread non-contiguous supersecondary element, which we initially found in a group of topologically distinct but homologous beta-barrels - the cradle-loop barrels. The GD box is similar both in sequence and structure and comprises two short unpaired beta-strands connected by an orthogonal type-II beta-turn and a non-contiguous beta-strand forming hydrogen bonds with the beta-turn. Using structure-based analysis, we have detected 518 instances of the GD box in a non-redundant subset of the SCOP database comprising 3771 domains. Apart from the cradle-loop barrels, this motif is also found in a diverse set of non-homologous folds including other topologically related beta-barrels. Since non-local interactions are fundamental in the formation of protein structure, systematic identification and characterization of other non
-contiguous supersecondary structural elements is likely to prove valuable to protein structure modeling, validation, and prediction.