Abstract
A new method for predicting protein fold-classes and protein domains from sequence data is constructed and used for generating a data base of protein fold-class assignments. Any given sequence of amino acids is assigned a specific prediction of one out of 45 typical protein fold-classes, a prediction of one out of 4 super fold-classes for the content of secondary structures and a profile of fold-class predictions along the sequence. The prediction accuracy for the super fold-classes is around 91% correct and 82% correct for the specific fold-classes. This accuracy is maintained down to a few percent of sequence identity.
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- Bohr H., Bohr J., Brunak S., Cotterill R. M., Lautrup B., Nørskov L., Olsen O. H., Petersen S. B. Protein secondary structure and homology by neural networks. The alpha-helices in rhodopsin. FEBS Lett. 1988 Dec 5;241(1-2):223–228. doi: 10.1016/0014-5793(88)81066-4. [DOI] [PubMed] [Google Scholar]
- Bohr J., Bohr H., Brunak S., Cotterill R. M., Fredholm H., Lautrup B., Petersen S. B. Protein structures from distance inequalities. J Mol Biol. 1993 Jun 5;231(3):861–869. doi: 10.1006/jmbi.1993.1332. [DOI] [PubMed] [Google Scholar]
- Brunak S., Engelbrecht J., Knudsen S. Cleaning up gene databases. Nature. 1990 Jan 11;343(6254):123–123. doi: 10.1038/343123a0. [DOI] [PubMed] [Google Scholar]
- Dubchak I., Holbrook S. R., Kim S. H. Prediction of protein folding class from amino acid composition. Proteins. 1993 May;16(1):79–91. doi: 10.1002/prot.340160109. [DOI] [PubMed] [Google Scholar]
- Goldstein R. A., Luthey-Schulten Z. A., Wolynes P. G. Protein tertiary structure recognition using optimized Hamiltonians with local interactions. Proc Natl Acad Sci U S A. 1992 Oct 1;89(19):9029–9033. doi: 10.1073/pnas.89.19.9029. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Holley L. H., Karplus M. Protein secondary structure prediction with a neural network. Proc Natl Acad Sci U S A. 1989 Jan;86(1):152–156. doi: 10.1073/pnas.86.1.152. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Holm L., Sander C. Protein structure comparison by alignment of distance matrices. J Mol Biol. 1993 Sep 5;233(1):123–138. doi: 10.1006/jmbi.1993.1489. [DOI] [PubMed] [Google Scholar]
- Jones D. T., Taylor W. R., Thornton J. M. A new approach to protein fold recognition. Nature. 1992 Jul 2;358(6381):86–89. doi: 10.1038/358086a0. [DOI] [PubMed] [Google Scholar]
- Jones D., Thornton J. Protein fold recognition. J Comput Aided Mol Des. 1993 Aug;7(4):439–456. doi: 10.1007/BF02337560. [DOI] [PubMed] [Google Scholar]
- Matthews B. W. Comparison of the predicted and observed secondary structure of T4 phage lysozyme. Biochim Biophys Acta. 1975 Oct 20;405(2):442–451. doi: 10.1016/0005-2795(75)90109-9. [DOI] [PubMed] [Google Scholar]
- Pascarella S., Argos P. A data bank merging related protein structures and sequences. Protein Eng. 1992 Mar;5(2):121–137. doi: 10.1093/protein/5.2.121. [DOI] [PubMed] [Google Scholar]
- Qian N., Sejnowski T. J. Predicting the secondary structure of globular proteins using neural network models. J Mol Biol. 1988 Aug 20;202(4):865–884. doi: 10.1016/0022-2836(88)90564-5. [DOI] [PubMed] [Google Scholar]