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Molecular modeling and lead design of substituted zanamivir derivatives as potent anti-influenza drugs

Overview of attention for article published in BMC Bioinformatics, December 2016
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  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

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1 patent

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Title
Molecular modeling and lead design of substituted zanamivir derivatives as potent anti-influenza drugs
Published in
BMC Bioinformatics, December 2016
DOI 10.1186/s12859-016-1374-1
Pubmed ID
Authors

Dhwani Dholakia, Sukriti Goyal, Salma Jamal, Aditi Singh, Asmita Das, Abhinav Grover

Abstract

Influenza virus spreads infection by two main surface glycoproteins, namely hemagglutinin (HA) and neuraminidase (NA). NA cleaves the sialic acid receptors eventually releasing newly formed virus particles which then invade new cells. Inhibition of NA could limit the replication of virus to one round which is insufficient to cause the disease. An experimentally reported series of acylguanidine zanamivir derivatives was used to develop GQSAR model targeting NA in different strains of influenza virus, H1N1 and H3N2. A combinatorial library was developed and their inhibitory activities were predicted using the GQSAR model. The top leads were analyzed by docking which revealed the binding modes of these inhibitors in the active site of NA (150-loop). The top compound (AMA) was selected for carrying out molecular dynamics simulations for 15 ns which provided insights into the time dependent dynamics of the designed leads. AMA possessed a docking score of -8.26 Kcal/mol with H1N1 strain and -7.00 Kcal/mol with H3N2 strain. Ligand-bound complexes of both H1N1 and H3N2 were observed to be stable for 11 ns and 7 ns respectively. ADME descriptors were also calculated to study the pharmacokinetic properties of AMA which revealed its drug-like properties.

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 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 19%
Researcher 3 19%
Student > Master 2 13%
Student > Ph. D. Student 2 13%
Other 1 6%
Other 2 13%
Unknown 3 19%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 4 25%
Biochemistry, Genetics and Molecular Biology 2 13%
Arts and Humanities 1 6%
Veterinary Science and Veterinary Medicine 1 6%
Agricultural and Biological Sciences 1 6%
Other 4 25%
Unknown 3 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 26 September 2019.
All research outputs
#7,290,657
of 22,997,544 outputs
Outputs from BMC Bioinformatics
#2,877
of 7,312 outputs
Outputs of similar age
#135,657
of 421,290 outputs
Outputs of similar age from BMC Bioinformatics
#49
of 133 outputs
Altmetric has tracked 22,997,544 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 7,312 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 59% of its peers.
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 421,290 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 133 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.