The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Occurrence, conformational features and amino acid propensities for the π-helix
Open accessAbstract
The most abundant helix type in proteins is the alpha-helix, accounting for about 31% of amino acid secondary structure states, while the 3(10)-helix accounts for about 4%. The pi-helix appears to be extremely rare and is considered to be unstable. Existing secondary structure definition methods find very few within the Protein Data Bank. Using an improved pi-helix definition algorithm to search a non-redundant subset of high-resolution and well-refined protein structures, we found that almost every tenth protein contained a pi-helix. This enabled us to show for the first time that the pi-helix has structural parameters that are different from the hypothesized model values. It also has distinctive amino acid preferences and it is conserved within functionally related proteins. Features that may contribute to the stability of the pi-helical structure have also been identified. In addition to hydrogen bonds, several other factors contribute to the stability of pi-helices. The pi-helix may have some functional advantages over other helical structures. Thus, we describe cases where the side chains of functionally important residues at every fourth position within a pi-helix could be aligned and brought close together in a way that would not be allowed by any other helix type.
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Cites
Nonparametric Statistics for the Behavioral Sciences
Guitton, H., & Siegel, S. (1958) · Revue économique · doi:10.2307/3498751 · Cited by 35,245
Crystallography & NMR System: A New Software Suite for Macromolecular Structure Determination
Brünger, A. T., Adams, P. D., Clore, G. M., DeLano, W. L., Gros, P., Grosse-Kunstleve, R. W., Jiang, J. S., Kuszewski, J., Nilges, M., Pannu, N. S., et al. (1998) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444998003254 · Cited by 15,715
Kabsch, W., & Sander, C. (1983) · Biopolymers · doi:10.1002/bip.360221211 · Cited by 15,320
SWISS‐MODEL and the Swiss‐Pdb Viewer: An environment for comparative protein modeling
Guex, N., & Peitsch, M. C. (1997) · ELECTROPHORESIS · doi:10.1002/elps.1150181505 · Cited by 11,241
Sequence logos: a new way to display consensus sequences
Schneider, T. D., & Stephens, R. M. (1990) · Nucleic Acids Research · doi:10.1093/nar/18.20.6097 · Cited by 3,378
Prediction of protein conformation
Chou, P. Y., & Fasman, G. D. (1974) · Biochemistry · doi:10.1021/bi00699a002 · Cited by 3,309
Conformation of Polypeptides and Proteins
Ramachandran, G. N., & Sasisekharan, V. (1968) · Advances in Protein Chemistry · doi:10.1016/s0065-3233(08)60402-7 · Cited by 2,938
The structure of proteins: Two hydrogen-bonded helical configurations of the polypeptide chain
Pauling, L., Corey, R. B., & Branson, H. R. (1951) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.37.4.205 · Cited by 2,915
Proteins: Structures and Molecular Properties
Creighton, T. E. (1986) · Medical Entomology and Zoology · Cited by 2,645
Knowledge‐based protein secondary structure assignment
Frishman, D., & Argos, P. (1995) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.340230412 · Cited by 2,523
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Smith, M. E. B., Schumacher, F. F., Ryan, C. P., Tedaldi, L. M., Papaioannou, D., Waksman, G., Caddick, S., & Baker, J. R. (2010) · Journal of the American Chemical Society · doi:10.1021/ja908610s · Cited by 377
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Metadata
- Authors
- Fodje, M. N., & Al-Karadaghi, S.
- Venue
- Protein Engineering, Design and Selection
- Publisher
- Oxford University Press (OUP)
- Published
- 2002-05
- Volume
- 15
- Issue
- 5
- Pages
- 353-358
- ISSN
- 0269-2139 (ISSN-L)
- 1741-0134
- 1741-0126
- OpenAlex
- W2122468718
- Cited by
- 264
- References
- 31
- FWCI
- 3.02
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Fodje, M. N., & Al-Karadaghi, S. (2002). Occurrence, conformational features and amino acid propensities for the π-helix. Protein Engineering, Design and Selection. https://doi.org/10.1093/protein/15.5.353
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