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A New Prediction Strategy for Long Local Protein Structures Using an Original Description by Aurélie Bornot; Catherine Etchebest; Alexandre G. de Brevern is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

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## Abstract A relevant and accurate description of three‐dimensional (3D) protein structures can be achieved by characterizing recurrent local structures. In a previous study, we developed a library of 120 3D structural prototypes encompassing all known 11‐residues long local protein structures and ensuring a good quality of structural approximation. A local structure prediction method was also proposed. Here, overlapping properties of local protein structures in global ones are taken into account to characterize frequent local networks. At the same time, we propose a new long local structure prediction strategy which involves the use of evolutionary information coupled with Support Vector Machines (SVMs). Our prediction is evaluated by a stringent geometrical assessment. Every local structure prediction with a Cα RMSD less than 2.5 Å from the true local structure is considered as correct. A global prediction rate of 63.1% is then reached, corresponding to an improvement of 7.7 points compared with the previous strategy. In the same way, the prediction of 88.33% of the 120 structural classes is improved with 8.65% mean gain. 85.33% of proteins have better prediction results with a

Who reads A New Prediction Strategy for Long Local Protein Structures Using an Original Description?

Author

Aurélie Bornot; Catherine Etchebest; Alexandre G. de Brevern

Publisher

John Wiley and Sons; Wiley (John Wiley & Sons); Wiley-Liss Inc; Wiley (ISSN 0887-3585)

Published

2009

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)