| Title |
Analysis of substructural variation in families of enzymatic proteins with applications to protein function prediction
|
|---|---|
| Published in |
BMC Bioinformatics, May 2010
|
| DOI | 10.1186/1471-2105-11-242 |
| Pubmed ID | |
| Authors |
Drew H Bryant, Mark Moll, Brian Y Chen, Viacheslav Y Fofanov, Lydia E Kavraki |
| Abstract |
Structural variations caused by a wide range of physico-chemical and biological sources directly influence the function of a protein. For enzymatic proteins, the structure and chemistry of the catalytic binding site residues can be loosely defined as a substructure of the protein. Comparative analysis of drug-receptor substructures across and within species has been used for lead evaluation. Substructure-level similarity between the binding sites of functionally similar proteins has also been used to identify instances of convergent evolution among proteins. In functionally homologous protein families, shared chemistry and geometry at catalytic sites provide a common, local point of comparison among proteins that may differ significantly at the sequence, fold, or domain topology levels. |
Mendeley readers
The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 9% |
| Germany | 1 | 2% |
| Turkey | 1 | 2% |
| India | 1 | 2% |
| Sweden | 1 | 2% |
| Japan | 1 | 2% |
| United Kingdom | 1 | 2% |
| Unknown | 42 | 79% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 18 | 34% |
| Student > Ph. D. Student | 15 | 28% |
| Student > Bachelor | 4 | 8% |
| Other | 4 | 8% |
| Student > Doctoral Student | 3 | 6% |
| Other | 8 | 15% |
| Unknown | 1 | 2% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 22 | 42% |
| Computer Science | 11 | 21% |
| Biochemistry, Genetics and Molecular Biology | 5 | 9% |
| Mathematics | 2 | 4% |
| Engineering | 2 | 4% |
| Other | 9 | 17% |
| Unknown | 2 | 4% |
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 24 June 2010.
All research outputs
#15,240,835
of 22,660,862 outputs
Outputs from BMC Bioinformatics
#5,353
of 7,240 outputs
Outputs of similar age
#77,182
of 94,892 outputs
Outputs of similar age from BMC Bioinformatics
#52
of 69 outputs
Altmetric has tracked 22,660,862 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,240 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 94,892 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.