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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Modeling enzyme-ligand binding in drug discovery
|
|---|---|
| Published in |
Journal of Cheminformatics, October 2015
|
| DOI | 10.1186/s13321-015-0096-0 |
| Pubmed ID | |
| Authors |
Janez Konc, Samo Lešnik, Dušanka Janežič |
| Abstract |
Enzymes are one of the most important groups of drug targets, and identifying possible ligand-enzyme interactions is of major importance in many drug discovery processes. Novel computational methods have been developed that can apply the information from the increasing number of resolved and available ligand-enzyme complexes to model new unknown interactions and therefore contribute to answer open questions in the field of drug discovery like the identification of unknown protein functions, off-target binding, ligand 3D homology modeling and induced-fit simulations. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Germany | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 1% |
| Portugal | 1 | 1% |
| Unknown | 89 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 16 | 18% |
| Student > Ph. D. Student | 15 | 16% |
| Student > Bachelor | 14 | 15% |
| Researcher | 13 | 14% |
| Professor > Associate Professor | 8 | 9% |
| Other | 13 | 14% |
| Unknown | 12 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 20 | 22% |
| Agricultural and Biological Sciences | 15 | 16% |
| Chemistry | 14 | 15% |
| Computer Science | 8 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 5 | 5% |
| Other | 15 | 16% |
| Unknown | 14 | 15% |
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 27 October 2016.
All research outputs
#15,348,067
of 22,829,683 outputs
Outputs from Journal of Cheminformatics
#750
of 834 outputs
Outputs of similar age
#162,898
of 277,991 outputs
Outputs of similar age from Journal of Cheminformatics
#13
of 14 outputs
Altmetric has tracked 22,829,683 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 834 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one is in the 5th percentile – i.e., 5% 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 277,991 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.