Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.14/118243
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- Title
- Directionality in protein fold prediction
- Related
- BMC bioinformatics, Vol. 11, No. 172 (2010), p.1-17
- DOI
- 10.1186/1471-2105-11-172
- Publisher
- BioMed Central
- Date
- 2010
- FoR/RFCD Code(s)
-
080100 Artificial Intelligence and Image Processing
080200 Computation Theory and Mathematics
060100 Biochemistry and Cell Biology
- Author/Creator
- Ellis, Jonathan J
- Author/Creator
- Huard, Fabien P. E
- Author/Creator
- Deane, Charlotte M
- Author/Creator
- Srivastava, Sheenal
- Author/Creator
- Wood, Graham M
- Description
- Background: Ever since the ground-breaking work of Anfinsen et al. in which a denatured protein was found to refold to its native state, it has been frequently stated by the protein fold prediction community that all the information required for protein folding lies in the amino acid sequence. Recent in vitro experiments and in silico computational studies, however, have shown that cotranslation may affect the folding pathway of some proteins, especially those of ancient folds. In this paper aspects of cotranslational folding have been incorporated into a protein structure prediction algorithm by adapting the Rosetta program to fold proteins as the nascent chain elongates. This makes it possible to conduct a pairwise comparison of folding accuracy, by comparing folds created sequentially from each end of the protein. Results: A single main result emerged: in 94% of proteins analyzed, following the sense of translation, from N-terminus to C-terminus, produced better predictions than following the reverse sense of translation, from the C-terminus to N-terminus. Two secondary results emerged. First, this superiority of N-terminus to C-terminus folding was more marked for proteins showing stronger evidence of cotranslation and second, an algorithm following the sense of translation produced predictions comparable to, and occasionally better than, Rosetta. Conclusions: There is a directionality effect in protein fold prediction. At present, prediction methods appear to be too noisy to take advantage of this effect; as techniques refine, it may be possible to draw benefit from a sequential approach to protein fold prediction.
- Description
- 16 page(s)
- Subject Keyword
- 080100 Artificial Intelligence and Image Processing
- Subject Keyword
- 080200 Computation Theory and Mathematics
- Subject Keyword
- 060100 Biochemistry and Cell Biology
- Resource Type
- journal article
- Organisation
- Macquarie University. Dept. of Statistics
- Identifier
- http://hdl.handle.net/1959.14/118243
- Identifier
- ISSN:1471-2105
- Identifier
- mq-rm-2010003513
- Language
- eng
- Rights
- This version is archived for private and non-commercial use under the terms of this BioMed Central open access license ("license"). The work is protected by copyright and/or other applicable law. Any use of the work other than as authorized under this license is prohibited. For further rights please check the terms of the license, or contact the publisher.
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