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Virtual screening for oseltamivir-resistant a (H5N1) influenza neuraminidase from traditional Chinese medicine database: a combined molecular docking with molecular dynamics approach

Overview of attention for article published in SpringerPlus, March 2013
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26 Mendeley
Title
Virtual screening for oseltamivir-resistant a (H5N1) influenza neuraminidase from traditional Chinese medicine database: a combined molecular docking with molecular dynamics approach
Published in
SpringerPlus, March 2013
DOI 10.1186/2193-1801-2-115
Pubmed ID
Authors

Vasudevan Karthick, Karuppasamy Ramanathan

Abstract

The neuraminidase (NA) of the influenza virus is the target of antiviral drug, oseltamivir. Recently, cases are reported that Influenza virus becoming resistant to oseltamivir, necessitating the development of new long-acting antiviral compounds. Most importantly, H274Y mutation in neuraminidase exhibits high levels of resistance to oseltamivir. In this report, a novel class of lead molecule with potential NA inhibitory activity was found from the traditional Chinese medicine database (TCMD) using virtual screening approach. Initially ADME properties of the lead compounds were analyzed with respect to the Lipinski rule of five. Subsequently, the data reduction was carried out by employing molecular docking study. Final validation was done by means of molecular dynamic simulations. The toxicity profiles for the screened compound were also analyzed. The result indicates that neoglucobrassicin (a compound derived from TCMD) become a promising lead compound and be effective in treating oseltamivir-resistant influenza virus strains.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 4%
Unknown 25 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 19%
Student > Ph. D. Student 4 15%
Student > Bachelor 3 12%
Student > Postgraduate 3 12%
Lecturer 2 8%
Other 5 19%
Unknown 4 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 23%
Agricultural and Biological Sciences 6 23%
Medicine and Dentistry 3 12%
Pharmacology, Toxicology and Pharmaceutical Science 2 8%
Chemistry 2 8%
Other 2 8%
Unknown 5 19%
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 18 March 2013.
All research outputs
#20,185,720
of 22,701,287 outputs
Outputs from SpringerPlus
#1,461
of 1,852 outputs
Outputs of similar age
#189,209
of 215,834 outputs
Outputs of similar age from SpringerPlus
#68
of 135 outputs
Altmetric has tracked 22,701,287 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 1,852 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. 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 215,834 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 135 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.