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Proceedings of the National Academy of Sciences of the United States of America logoLink to Proceedings of the National Academy of Sciences of the United States of America
. 1993 Jan 15;90(2):644–648. doi: 10.1073/pnas.90.2.644

On the nature of the protein folding code.

S Rackovsky 1
PMCID: PMC45720  PMID: 8421700

Abstract

This paper investigates quantitatively the characteristics of the local folding code. The overlapping four-residue fragments which make up the amino acid sequences of 114 proteins are divided into classes on the basis of the physical properties of their constituent amino acids. The distribution of structural types associated with each class of sequence fragment is determined and compared with an ensemble of random structural distributions of the same size selected from the actual protein structures. A criterion is proposed, based on the relative entropies of the two types of distribution, and on a hypothesis as to the characteristics of fragments which code for local structure, that makes it possible to identify those four-residue sequence elements which encode specific time-averaged structure. It is determined that, by this criterion, only 60-70% of the four-residue fragments encode specific structures. It is suggested that the remaining sequence fragments intrinsically encode susceptibility to conformational alteration under the influence of long-range interactions and that this susceptibility is required for correct folding of the molecule. This feature introduces an inherent indeterminacy into the local folding code. The implications of this observation for the prediction of protein structure by various methods are briefly discussed.

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Selected References

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

  1. ANFINSEN C. B., HABER E., SELA M., WHITE F. H., Jr The kinetics of formation of native ribonuclease during oxidation of the reduced polypeptide chain. Proc Natl Acad Sci U S A. 1961 Sep 15;47:1309–1314. doi: 10.1073/pnas.47.9.1309. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Biou V., Gibrat J. F., Levin J. M., Robson B., Garnier J. Secondary structure prediction: combination of three different methods. Protein Eng. 1988 Sep;2(3):185–191. doi: 10.1093/protein/2.3.185. [DOI] [PubMed] [Google Scholar]
  3. 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]
  4. Chou P. Y., Fasman G. D. Prediction of the secondary structure of proteins from their amino acid sequence. Adv Enzymol Relat Areas Mol Biol. 1978;47:45–148. doi: 10.1002/9780470122921.ch2. [DOI] [PubMed] [Google Scholar]
  5. 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]
  6. 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]
  7. Kabsch W., Sander C. On the use of sequence homologies to predict protein structure: identical pentapeptides can have completely different conformations. Proc Natl Acad Sci U S A. 1984 Feb;81(4):1075–1078. doi: 10.1073/pnas.81.4.1075. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Kim P. S., Baldwin R. L. Specific intermediates in the folding reactions of small proteins and the mechanism of protein folding. Annu Rev Biochem. 1982;51:459–489. doi: 10.1146/annurev.bi.51.070182.002331. [DOI] [PubMed] [Google Scholar]
  9. Levin J. M., Robson B., Garnier J. An algorithm for secondary structure determination in proteins based on sequence similarity. FEBS Lett. 1986 Sep 15;205(2):303–308. doi: 10.1016/0014-5793(86)80917-6. [DOI] [PubMed] [Google Scholar]
  10. Nishikawa K., Ooi T. Amino acid sequence homology applied to the prediction of protein secondary structures, and joint prediction with existing methods. Biochim Biophys Acta. 1986 May 12;871(1):45–54. doi: 10.1016/0167-4838(86)90131-7. [DOI] [PubMed] [Google Scholar]
  11. Pain R. H., Robson B. Analysis of the code relating sequence to secondary structure in proteins. Nature. 1970 Jul 4;227(5253):62–63. doi: 10.1038/227062a0. [DOI] [PubMed] [Google Scholar]
  12. 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]
  13. Rackovsky S., Goldstein D. A. Protein comparison and classification: a differential geometric approach. Proc Natl Acad Sci U S A. 1988 Feb;85(3):777–781. doi: 10.1073/pnas.85.3.777. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Rackovsky S. Quantitative organization of the known protein x-ray structures. I. Methods and short-length-scale results. Proteins. 1990;7(4):378–402. doi: 10.1002/prot.340070409. [DOI] [PubMed] [Google Scholar]
  15. Rooman M. J., Wodak S. J. Identification of predictive sequence motifs limited by protein structure data base size. Nature. 1988 Sep 1;335(6185):45–49. doi: 10.1038/335045a0. [DOI] [PubMed] [Google Scholar]
  16. Rooman M. J., Wodak S. J. Weak correlation between predictive power of individual sequence patterns and overall prediction accuracy in proteins. Proteins. 1991;9(1):69–78. doi: 10.1002/prot.340090108. [DOI] [PubMed] [Google Scholar]
  17. Schiffer M., Edmundson A. B. Use of helical wheels to represent the structures of proteins and to identify segments with helical potential. Biophys J. 1967 Mar;7(2):121–135. doi: 10.1016/S0006-3495(67)86579-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Segawa S., Richards F. M. Identification of regions of potential flexibility in protein structures: folding units and correlations with intron positions. Biopolymers. 1988 Jan;27(1):23–40. doi: 10.1002/bip.360270103. [DOI] [PubMed] [Google Scholar]
  19. Shenkin P. S., Erman B., Mastrandrea L. D. Information-theoretical entropy as a measure of sequence variability. Proteins. 1991;11(4):297–313. doi: 10.1002/prot.340110408. [DOI] [PubMed] [Google Scholar]
  20. Skolnick J., Kolinski A. Simulations of the folding of a globular protein. Science. 1990 Nov 23;250(4984):1121–1125. doi: 10.1126/science.250.4984.1121. [DOI] [PubMed] [Google Scholar]
  21. Sweet R. M. Evolutionary similarity among peptide segments is a basis for prediction of protein folding. Biopolymers. 1986 Aug;25(8):1565–1577. doi: 10.1002/bip.360250813. [DOI] [PubMed] [Google Scholar]

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