↓ Skip to main content

Analysis of coevolution in nonstructural proteins of chikungunya virus

Overview of attention for article published in Virology Journal, June 2016
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
4 X users

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
60 Mendeley
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
Analysis of coevolution in nonstructural proteins of chikungunya virus
Published in
Virology Journal, June 2016
DOI 10.1186/s12985-016-0543-1
Pubmed ID
Authors

Jaspreet Jain, Kalika Mathur, Jatin Shrinet, Raj K. Bhatnagar, Sujatha Sunil

Abstract

RNA viruses are characterized by high rate of mutations mainly due to the lack of proofreading repair activities associated with its RNA-dependent RNA-polymerase (RdRp). In case of arboviruses, this phenomenon has lead to the existence of mixed population of genomic variants within the host called quasi-species. The stability of strains within the quasi-species lies on mutations that are positively selected which in turn depend on whether these mutations are beneficial in either or both hosts. Coevolution of amino acids (aa) is one phenomenon that leads to establishment of favorable traits in viruses and leading to their fitness. Fourteen CHIKV clinical samples collected over three years were subjected to RT-PCR, the four non-structural genes amplified and subjected to various genetic analyses. Coevolution analysis showed 30 aa pairs coevolving in nsP1, 23 aa pairs coevolving in nsP2, 239 in nsP3 and 46 aa coevolving pairs in nsP4 when each non-structural protein was considered independently. Further analysis showed that 705 amino acids pairs of the non-structural polyproteins coevolved together with a correlation coefficient of ≥0.5. Functional relevance of these coevolving amino acids in all the nonstructural proteins of CHIKV were predicted using Eukaryotic Linear Motifs (ELMs) of human. The present study was undertaken to study co-evolving amino acids in the non-structural proteins of chikungunya virus (CHIKV), an important arbovirus. It was observed that several amino acids residues were coevolving and shared common functions.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users 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 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Unknown 59 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 18%
Student > Ph. D. Student 10 17%
Student > Doctoral Student 5 8%
Student > Master 5 8%
Other 3 5%
Other 9 15%
Unknown 17 28%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 25%
Agricultural and Biological Sciences 14 23%
Immunology and Microbiology 6 10%
Computer Science 3 5%
Arts and Humanities 1 2%
Other 4 7%
Unknown 17 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 08 June 2016.
All research outputs
#13,472,400
of 22,875,477 outputs
Outputs from Virology Journal
#1,366
of 3,051 outputs
Outputs of similar age
#176,425
of 339,291 outputs
Outputs of similar age from Virology Journal
#28
of 58 outputs
Altmetric has tracked 22,875,477 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,051 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.7. This one has gotten more attention than average, scoring higher than 52% 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 339,291 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 58 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.