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Mendeley readers
Attention Score in Context
| Title |
In silico target fishing and pharmacological profiling for the isoquinoline alkaloids of Macleayacordata (Bo Luo Hui)
|
|---|---|
| Published in |
Chinese Medicine, December 2015
|
| DOI | 10.1186/s13020-015-0067-4 |
| Pubmed ID | |
| Authors |
Qifang Lei, Haibo Liu, Yong Peng, Peigen Xiao |
| Abstract |
Some isoquinoline alkaloids from Macleaya cordata (Willd). R. Br. (Bo Luo Hui) exhibited antibacterial, antiparasitic, antitumor, and analgesic effects. The targets of these isoquinoline alkaloids are undefined. This study aims to investigate the compound-target interaction network and potential pharmacological actions of isoquinoline alkaloids of M. cordata by reverse pharmacophore database screening. The targets of 26 isoquinoline alkaloids identified from M. cordata were predicted by a pharmacophore-based target fishing approach. Discovery Studio 3.5 and two pharmacophore databases (PharmaDB and HypoDB) were employed for the target profiling. A compound-target interaction network of M. cordata was constructed and analyzed by Cytoscape 3.0. Thirteen of the 65 predicted targets identified by PharmaDB were confirmed as targets by HypoDB screening. The targets in the interaction network of M. cordata were involved in cancer (31 targets), microorganisms (12 targets), neurodegeneration (10 targets), inflammation and autoimmunity (8 targets), parasitosis (5 targets), injury (4 targets), and pain (3 targets). Dihydrochelerythrine (C6) was found to hit 23 fitting targets. Macrophage migration inhibitory factor (MIF) hits 15 alkaloids (C1-2, C11-16, C19-25) was the most promising target related to cancer. Through in silico target fishing, the anticancer, anti-inflammatory, and analgesic effects of M. cordata were the most significant among many possible activities. The possible anticancer effects were mainly contributed by the isoquinoline alkaloids as active components. |
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 % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 2% |
| Unknown | 53 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 11 | 20% |
| Student > Ph. D. Student | 8 | 15% |
| Student > Bachelor | 6 | 11% |
| Researcher | 6 | 11% |
| Student > Doctoral Student | 3 | 6% |
| Other | 4 | 7% |
| Unknown | 16 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 13% |
| Chemistry | 7 | 13% |
| Agricultural and Biological Sciences | 4 | 7% |
| Engineering | 3 | 6% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 6% |
| Other | 11 | 20% |
| Unknown | 19 | 35% |
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 23 December 2015.
All research outputs
#22,759,452
of 25,374,647 outputs
Outputs from Chinese Medicine
#517
of 660 outputs
Outputs of similar age
#324,651
of 380,106 outputs
Outputs of similar age from Chinese Medicine
#10
of 10 outputs
Altmetric has tracked 25,374,647 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 660 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. 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 380,106 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 10 others from the same source and published within six weeks on either side of this one.