| Title |
Analysis of the structural quality of the CASD-NMR 2013 entries
|
|---|---|
| Published in |
Journal of Biomolecular NMR, June 2015
|
| DOI | 10.1007/s10858-015-9949-0 |
| Pubmed ID | |
| Authors |
Timothy J. Ragan, Rasmus H. Fogh, Roberto Tejero, Wim Vranken, Gaetano T. Montelione, Antonio Rosato, Geerten W. Vuister |
| Abstract |
We performed a comprehensive structure validation of both automated and manually generated structures of the 10 targets of the CASD-NMR-2013 effort. We established that automated structure determination protocols are capable of reliably producing structures of comparable accuracy and quality to those generated by a skilled researcher, at least for small, single domain proteins such as the ten targets tested. The most robust results appear to be obtained when NOESY peak lists are used either as the primary input data or to augment chemical shift data without the need to manually filter such lists. A detailed analysis of the long-range NOE restraints generated by the different programs from the same data showed a surprisingly low degree of overlap. Additionally, we found that there was no significant correlation between the extent of the NOE restraint overlap and the accuracy of the structure. This result was surprising given the importance of NOE data in producing good quality structures. We suggest that this could be explained by the information redundancy present in NOEs between atoms contained within a fixed covalent network. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 4% |
| Belgium | 1 | 4% |
| Unknown | 22 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 21% |
| Professor > Associate Professor | 4 | 17% |
| Student > Ph. D. Student | 3 | 13% |
| Student > Bachelor | 1 | 4% |
| Professor | 1 | 4% |
| Other | 5 | 21% |
| Unknown | 5 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 6 | 25% |
| Biochemistry, Genetics and Molecular Biology | 3 | 13% |
| Agricultural and Biological Sciences | 3 | 13% |
| Computer Science | 2 | 8% |
| Medicine and Dentistry | 2 | 8% |
| Other | 2 | 8% |
| Unknown | 6 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 17 June 2015.
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#18,412,793
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Outputs from Journal of Biomolecular NMR
#461
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#192,827
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Outputs of similar age from Journal of Biomolecular NMR
#3
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