Skip to main content
Protein Science : A Publication of the Protein Society logoLink to Protein Science : A Publication of the Protein Society
. 1995 Dec;4(12):2517–2525. doi: 10.1002/pro.5560041208

A simple and fast approach to prediction of protein secondary structure from multiply aligned sequences with accuracy above 70%.

P K Mehta 1, J Heringa 1, P Argos 1
PMCID: PMC2143048  PMID: 8580842

Abstract

To improve secondary structure predictions in protein sequences, the information residing in multiple sequence alignments of substituted but structurally related proteins is exploited. A database comprised of 70 protein families and a total of 2,500 sequences, some of which were aligned by tertiary structural superpositions, was used to calculate residue exchange weight matrices within alpha-helical, beta-strand, and coil substructures, respectively. Secondary structure predictions were made based on the observed residue substitutions in local regions of the multiple alignments and the largest possible associated exchange weights in each of the three matrix types. Comparison of the observed and predicted secondary structure on a per-residue basis yielded a mean accuracy of 72.2%. Individual alpha-helix, beta-strand, and coil states were respectively predicted at 66.7, and 75.8% correctness, representing a well-balanced three-state prediction. The accuracy level, verified by cross-validation through jack-knife tests on all protein families, dropped, on average, to only 70.9%, indicating the rigor of the prediction procedure. On the basis of robustness, conceptual clarity, accuracy, and executable efficiency, the method has considerable advantage, especially with its sole reliance on amino acid substitutions within structurally related proteins.

Full Text

The Full Text of this article is available as a PDF (905.9 KB).

Selected References

These references are in PubMed. This may not be the complete list of references from this article.

  1. Barton G. J., Newman R. H., Freemont P. S., Crumpton M. J. Amino acid sequence analysis of the annexin super-gene family of proteins. Eur J Biochem. 1991 Jun 15;198(3):749–760. doi: 10.1111/j.1432-1033.1991.tb16076.x. [DOI] [PubMed] [Google Scholar]
  2. Bazan J. F. Structural design and molecular evolution of a cytokine receptor superfamily. Proc Natl Acad Sci U S A. 1990 Sep;87(18):6934–6938. doi: 10.1073/pnas.87.18.6934. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Benner S. A., Gerloff D. Patterns of divergence in homologous proteins as indicators of secondary and tertiary structure: a prediction of the structure of the catalytic domain of protein kinases. Adv Enzyme Regul. 1991;31:121–181. doi: 10.1016/0065-2571(91)90012-b. [DOI] [PubMed] [Google Scholar]
  4. Bowie J. U., Lüthy R., Eisenberg D. A method to identify protein sequences that fold into a known three-dimensional structure. Science. 1991 Jul 12;253(5016):164–170. doi: 10.1126/science.1853201. [DOI] [PubMed] [Google Scholar]
  5. Chou P. Y., Fasman G. D. Conformational parameters for amino acids in helical, beta-sheet, and random coil regions calculated from proteins. Biochemistry. 1974 Jan 15;13(2):211–222. doi: 10.1021/bi00699a001. [DOI] [PubMed] [Google Scholar]
  6. Colloc'h N., Etchebest C., Thoreau E., Henrissat B., Mornon J. P. Comparison of three algorithms for the assignment of secondary structure in proteins: the advantages of a consensus assignment. Protein Eng. 1993 Jun;6(4):377–382. doi: 10.1093/protein/6.4.377. [DOI] [PubMed] [Google Scholar]
  7. Crawford I. P., Niermann T., Kirschner K. Prediction of secondary structure by evolutionary comparison: application to the alpha subunit of tryptophan synthase. Proteins. 1987;2(2):118–129. doi: 10.1002/prot.340020206. [DOI] [PubMed] [Google Scholar]
  8. Devereux J., Haeberli P., Smithies O. A comprehensive set of sequence analysis programs for the VAX. Nucleic Acids Res. 1984 Jan 11;12(1 Pt 1):387–395. doi: 10.1093/nar/12.1part1.387. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Donnelly D., Overington J. P., Blundell T. L. The prediction and orientation of alpha-helices from sequence alignments: the combined use of environment-dependent substitution tables, Fourier transform methods and helix capping rules. Protein Eng. 1994 May;7(5):645–653. doi: 10.1093/protein/7.5.645. [DOI] [PubMed] [Google Scholar]
  10. Garnier J., Levin J. M. The protein structure code: what is its present status? Comput Appl Biosci. 1991 Apr;7(2):133–142. doi: 10.1093/bioinformatics/7.2.133. [DOI] [PubMed] [Google Scholar]
  11. Garnier J., Osguthorpe D. J., Robson B. Analysis of the accuracy and implications of simple methods for predicting the secondary structure of globular proteins. J Mol Biol. 1978 Mar 25;120(1):97–120. doi: 10.1016/0022-2836(78)90297-8. [DOI] [PubMed] [Google Scholar]
  12. Gibrat J. F., Garnier J., Robson B. Further developments of protein secondary structure prediction using information theory. New parameters and consideration of residue pairs. J Mol Biol. 1987 Dec 5;198(3):425–443. doi: 10.1016/0022-2836(87)90292-0. [DOI] [PubMed] [Google Scholar]
  13. Hirst J. D., Sternberg M. J. Prediction of structural and functional features of protein and nucleic acid sequences by artificial neural networks. Biochemistry. 1992 Aug 18;31(32):7211–7218. doi: 10.1021/bi00147a001. [DOI] [PubMed] [Google Scholar]
  14. 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]
  15. Kneller D. G., Cohen F. E., Langridge R. Improvements in protein secondary structure prediction by an enhanced neural network. J Mol Biol. 1990 Jul 5;214(1):171–182. doi: 10.1016/0022-2836(90)90154-E. [DOI] [PubMed] [Google Scholar]
  16. Levin J. M., Pascarella S., Argos P., Garnier J. Quantification of secondary structure prediction improvement using multiple alignments. Protein Eng. 1993 Nov;6(8):849–854. doi: 10.1093/protein/6.8.849. [DOI] [PubMed] [Google Scholar]
  17. Lim V. I. Structural principles of the globular organization of protein chains. A stereochemical theory of globular protein secondary structure. J Mol Biol. 1974 Oct 5;88(4):857–872. doi: 10.1016/0022-2836(74)90404-5. [DOI] [PubMed] [Google Scholar]
  18. Lüthy R., McLachlan A. D., Eisenberg D. Secondary structure-based profiles: use of structure-conserving scoring tables in searching protein sequence databases for structural similarities. Proteins. 1991;10(3):229–239. doi: 10.1002/prot.340100307. [DOI] [PubMed] [Google Scholar]
  19. Muggleton S., King R. D., Sternberg M. J. Protein secondary structure prediction using logic-based machine learning. Protein Eng. 1992 Oct;5(7):647–657. doi: 10.1093/protein/5.7.647. [DOI] [PubMed] [Google Scholar]
  20. Overington J., Donnelly D., Johnson M. S., Sali A., Blundell T. L. Environment-specific amino acid substitution tables: tertiary templates and prediction of protein folds. Protein Sci. 1992 Feb;1(2):216–226. doi: 10.1002/pro.5560010203. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. 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]
  22. 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]
  23. Rost B., Sander C. Prediction of protein secondary structure at better than 70% accuracy. J Mol Biol. 1993 Jul 20;232(2):584–599. doi: 10.1006/jmbi.1993.1413. [DOI] [PubMed] [Google Scholar]
  24. Russell R. B., Barton G. J. The limits of protein secondary structure prediction accuracy from multiple sequence alignment. J Mol Biol. 1993 Dec 20;234(4):951–957. doi: 10.1006/jmbi.1993.1649. [DOI] [PubMed] [Google Scholar]
  25. Russell R. B., Breed J., Barton G. J. Conservation analysis and structure prediction of the SH2 family of phosphotyrosine binding domains. FEBS Lett. 1992 Jun 8;304(1):15–20. doi: 10.1016/0014-5793(92)80579-6. [DOI] [PubMed] [Google Scholar]
  26. Salamov A. A., Solovyev V. V. Prediction of protein secondary structure by combining nearest-neighbor algorithms and multiple sequence alignments. J Mol Biol. 1995 Mar 17;247(1):11–15. doi: 10.1006/jmbi.1994.0116. [DOI] [PubMed] [Google Scholar]
  27. Zhang X., Mesirov J. P., Waltz D. L. Hybrid system for protein secondary structure prediction. J Mol Biol. 1992 Jun 20;225(4):1049–1063. doi: 10.1016/0022-2836(92)90104-r. [DOI] [PubMed] [Google Scholar]
  28. Zvelebil M. J., Barton G. J., Taylor W. R., Sternberg M. J. Prediction of protein secondary structure and active sites using the alignment of homologous sequences. J Mol Biol. 1987 Jun 20;195(4):957–961. doi: 10.1016/0022-2836(87)90501-8. [DOI] [PubMed] [Google Scholar]

Articles from Protein Science : A Publication of the Protein Society are provided here courtesy of The Protein Society

RESOURCES