↓ Skip to main content

Two Birds with One Stone? Possible Dual-Targeting H1N1 Inhibitors from Traditional Chinese Medicine

Overview of attention for article published in PLoS Computational Biology, December 2011
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
79 Dimensions

Readers on

mendeley
50 Mendeley
citeulike
3 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Two Birds with One Stone? Possible Dual-Targeting H1N1 Inhibitors from Traditional Chinese Medicine
Published in
PLoS Computational Biology, December 2011
DOI 10.1371/journal.pcbi.1002315
Pubmed ID
Authors

Su-Sen Chang, Hung-Jin Huang, Calvin Yu-Chian Chen

Abstract

The H1N1 influenza pandemic of 2009 has claimed over 18,000 lives. During this pandemic, development of drug resistance further complicated efforts to control and treat the widespread illness. This research utilizes traditional Chinese medicine Database@Taiwan (TCM Database@Taiwan) to screen for compounds that simultaneously target H1 and N1 to overcome current difficulties with virus mutations. The top three candidates were de novo derivatives of xylopine and rosmaricine. Bioactivity of the de novo derivatives against N1 were validated by multiple machine learning prediction models. Ability of the de novo compounds to maintain CoMFA/CoMSIA contour and form key interactions implied bioactivity within H1 as well. Addition of a pyridinium fragment was critical to form stable interactions in H1 and N1 as supported by molecular dynamics (MD) simulation. Results from MD, hydrophobic interactions, and torsion angles are consistent and support the findings of docking. Multiple anchors and lack of binding to residues prone to mutation suggest that the TCM de novo derivatives may be resistant to drug resistance and are advantageous over conventional H1N1 treatments such as oseltamivir. These results suggest that the TCM de novo derivatives may be suitable candidates of dual-targeting drugs for influenza.

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Denmark 1 2%
Unknown 49 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 20%
Student > Ph. D. Student 6 12%
Student > Bachelor 6 12%
Student > Postgraduate 4 8%
Professor > Associate Professor 4 8%
Other 14 28%
Unknown 6 12%
Readers by discipline Count As %
Medicine and Dentistry 14 28%
Biochemistry, Genetics and Molecular Biology 5 10%
Agricultural and Biological Sciences 5 10%
Computer Science 4 8%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Other 9 18%
Unknown 11 22%
Attention Score in Context

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 13 April 2020.
All research outputs
#20,726,842
of 25,461,852 outputs
Outputs from PLoS Computational Biology
#8,227
of 8,981 outputs
Outputs of similar age
#203,665
of 249,264 outputs
Outputs of similar age from PLoS Computational Biology
#95
of 118 outputs
Altmetric has tracked 25,461,852 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,981 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 4th percentile – i.e., 4% 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 249,264 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 118 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.