| Title |
The 13C Chemical-Shift Index: A simple method for the identification of protein secondary structure using 13C chemical-shift data
|
|---|---|
| Published in |
Journal of Biomolecular NMR, March 1994
|
| DOI | 10.1007/bf00175245 |
| Pubmed ID | |
| Authors |
David S. Wishart, Brian D. Sykes |
| Abstract |
A simple technique for identifying protein secondary structures through the analysis of backbone 13C chemical shifts is described. It is based on the Chemical-Shift Index [Wishart et al. (1992) Biochemistry, 31, 1647-1651] which was originally developed for the analysis of 1H(alpha) chemical shifts. By extending the Chemical-Shift Index to include 13C(alpha), 13C(beta) and carbonyl 13C chemical shifts, it is now possible to use four independent chemical-shift measurements to identify and locate protein secondary structures. It is shown that by combining both 1H and 13C chemical-shift indices to produce a 'consensus' estimate of secondary structure, it is possible to achieve a predictive accuracy in excess of 92%. This suggests that the secondary structure of peptides and proteins can be accurately obtained from 1H and 13C chemical shifts, without recourse to NOE measurements. |
Mendeley readers
The data shown below were compiled from readership statistics for 550 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 1% |
| India | 4 | <1% |
| Germany | 2 | <1% |
| Belgium | 2 | <1% |
| United Kingdom | 2 | <1% |
| Hong Kong | 1 | <1% |
| Australia | 1 | <1% |
| Portugal | 1 | <1% |
| Sweden | 1 | <1% |
| Other | 6 | 1% |
| Unknown | 522 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 171 | 31% |
| Researcher | 113 | 21% |
| Student > Master | 44 | 8% |
| Student > Bachelor | 43 | 8% |
| Professor > Associate Professor | 24 | 4% |
| Other | 77 | 14% |
| Unknown | 78 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 138 | 25% |
| Biochemistry, Genetics and Molecular Biology | 132 | 24% |
| Chemistry | 122 | 22% |
| Physics and Astronomy | 12 | 2% |
| Engineering | 8 | 1% |
| Other | 41 | 7% |
| Unknown | 97 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 April 2022.
All research outputs
#7,729,343
of 23,506,079 outputs
Outputs from Journal of Biomolecular NMR
#138
of 619 outputs
Outputs of similar age
#6,617
of 22,828 outputs
Outputs of similar age from Journal of Biomolecular NMR
#1
of 4 outputs
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So far Altmetric has tracked 619 research outputs from this source. They receive a mean Attention Score of 2.9. This one is in the 47th percentile – i.e., 47% of its peers scored the same or lower than it.
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