| Title |
A test of enhancing model accuracy in high-throughput crystallography
|
|---|---|
| Published in |
Journal of Structural and Functional Genomics, March 2005
|
| DOI | 10.1007/s10969-005-3138-4 |
| Pubmed ID | |
| Authors |
W. Bryan Arendall, Wolfram Tempel, Jane S. Richardson, Weihong Zhou, Shuren Wang, Ian W. Davis, Zhi-Jie Liu, John P. Rose, W. Michael Carson, Ming Luo, David C. Richardson, Bi-Cheng Wang |
| Abstract |
The high throughput of structure determination pipelines relies on increased automation and, consequently, a reduction of time spent on interactive quality control. In order to meet and exceed current standards in model accuracy, new approaches are needed for the facile identification and correction of model errors during refinement. One such approach is provided by the validation and structure-improvement tools of the MOL: PROBITY: web service. To test their effectiveness in high-throughput mode, a large subset of the crystal structures from the SouthEast Collaboratory for Structural Genomics (SECSG) has used protocols based on the MOL: PROBITY: tools. Comparison of 29 working-set and 19 control-set SECSG structures shows that working-set outlier scores for updated Ramachandran-plot, sidechain rotamer, and all-atom steric criteria have been improved by factors of 5- to 10-fold (relative to the control set or to a Protein Data Bank sample), while quality of covalent geometry, R(work), R(free), electron density and difference density are maintained or improved. Some parts of this correction process are already fully automated; other parts involve manual rebuilding of conformations flagged by the tests as trapped in the wrong local minimum, often altering features of functional significance. The ease and effectiveness of this technique shows that macromolecular crystal structures from either traditional or high-throughput determinations can feasibly reach a new level of excellence in conformational accuracy and reliability. |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 2 | 6% |
| North Macedonia | 1 | 3% |
| Ukraine | 1 | 3% |
| Canada | 1 | 3% |
| Denmark | 1 | 3% |
| United States | 1 | 3% |
| Unknown | 29 | 81% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 28% |
| Researcher | 6 | 17% |
| Professor | 3 | 8% |
| Student > Bachelor | 3 | 8% |
| Other | 2 | 6% |
| Other | 7 | 19% |
| Unknown | 5 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 16 | 44% |
| Biochemistry, Genetics and Molecular Biology | 7 | 19% |
| Chemistry | 3 | 8% |
| Computer Science | 2 | 6% |
| Medicine and Dentistry | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 7 | 19% |
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 17 January 2009.
All research outputs
#7,452,489
of 22,783,848 outputs
Outputs from Journal of Structural and Functional Genomics
#26
of 107 outputs
Outputs of similar age
#20,783
of 59,927 outputs
Outputs of similar age from Journal of Structural and Functional Genomics
#1
of 6 outputs
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So far Altmetric has tracked 107 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
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