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Attention Score in Context
| Title |
An integrated strategy for identifying new targets and inferring the mechanism of action: taking rhein as an example
|
|---|---|
| Published in |
BMC Bioinformatics, September 2018
|
| DOI | 10.1186/s12859-018-2346-4 |
| Pubmed ID | |
| Authors |
Hao Sun, Yiting Shen, Guangwen Luo, Yuepiao Cai, Zheng Xiang |
| Abstract |
Target identification is necessary for the comprehensive inference of the mechanism of action of a compound. The application of computational methods to predict the targets of bioactive compounds saves cost and time in drug research and development. Therefore, we designed an integrated strategy consisting of ligand-protein docking, network analysis, enrichment analysis, and an experimental surface plasmon resonance (SPR) method to identify and validate new targets, and then used enriched pathways to elucidate the underlying pharmacological mechanisms. Here, we used rhein, a compound with various pharmacological activities, as an example to find some of its previously unknown targets and to determine its pharmacological activity. A total of nine candidate targets were discovered, including LCK, HSP90AA1, RAB5A, EGFR, CDK2, CDK6, GSK3B, p38, and JNK. LCK was confirmed through SPR experiments, and HSP90AA1, EGFR, CDK6, p38, and JNK were validated through previous reports. Rhein network regulations are complex and interconnected. The therapeutic effect of rhein is the synergistic and comprehensive result of this vast and complex network, and the perturbation of multiple targets gives rhein its various pharmacological activities. This study provided a new integrated strategy to identify new targets of bioactive compounds and reveal their molecular mechanisms of action. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 27% |
| Student > Master | 4 | 18% |
| Other | 3 | 14% |
| Student > Bachelor | 2 | 9% |
| Lecturer | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 5 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 23% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 9% |
| Agricultural and Biological Sciences | 2 | 9% |
| Medicine and Dentistry | 2 | 9% |
| Economics, Econometrics and Finance | 1 | 5% |
| Other | 3 | 14% |
| Unknown | 7 | 32% |
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 07 September 2018.
All research outputs
#20,532,290
of 23,102,082 outputs
Outputs from BMC Bioinformatics
#6,904
of 7,329 outputs
Outputs of similar age
#292,685
of 336,142 outputs
Outputs of similar age from BMC Bioinformatics
#85
of 96 outputs
Altmetric has tracked 23,102,082 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,329 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 1st percentile – i.e., 1% 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 336,142 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 96 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.