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Identifying foldable regions in protein sequence from the hydrophobic signal

Pang, Chi N. I., Lin, Kuang, Wouters, Merridee A., Heringa, Jaap and George, Richard A. 2008, Identifying foldable regions in protein sequence from the hydrophobic signal, Nucleic acids research, vol. 36, no. 2, pp. 578-588, doi: 10.1093/nar/gkm1070.

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Title Identifying foldable regions in protein sequence from the hydrophobic signal
Author(s) Pang, Chi N. I.
Lin, Kuang
Wouters, Merridee A.
Heringa, Jaap
George, Richard A.
Journal name Nucleic acids research
Volume number 36
Issue number 2
Start page 578
End page 588
Total pages 11
Publisher Oxford University Press
Place of publication Oxford, England
Publication date 2008-02
ISSN 0305-1048
1362-4962
Keyword(s) algorithms
databases
protein
hydrophobicity
models
molecular
protein Folding
protein Structure
tertiary
proteins
sequence analysis
sequence homology
amino acid
Summary Structural genomics initiatives aim to elucidate representative 3D structures for the majority of protein families over the next decade, but many obstacles must be overcome. The correct design of constructs is extremely important since many proteins will be too large or contain unstructured regions and will not be amenable to crystallization. It is therefore essential to identify regions in protein sequences that are likely to be suitable for structural study. Scooby-Domain is a fast and simple method to identify globular domains in protein sequences. Domains are compact units of protein structure and their correct delineation will aid structural elucidation through a divide-and-conquer approach. Scooby-Domain predictions are based on the observed lengths and hydrophobicities of domains from proteins with known tertiary structure. The prediction method employs an A*-search to identify sequence regions that form a globular structure and those that are unstructured. On a test set of 173 proteins with consensus CATH and SCOP domain definitions, Scooby-Domain has a sensitivity of 50% and an accuracy of 29%, which is better than current state-of-the-art methods. The method does not rely on homology searches and, therefore, can identify previously unknown domains.
Notes Reproduced with the kind permission of the copyright owner.
Language eng
DOI 10.1093/nar/gkm1070
Field of Research 060199 Biochemistry and Cell Biology not elsewhere classified
Socio Economic Objective 970106 Expanding Knowledge in the Biological Sciences
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2007, The Authors
Free to Read? Yes
Use Rights Creative Commons Attribution non-commercial licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30040265

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.