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Dove Medical Press

Identification of potential drug targets by subtractive genome analysis of Escherichia coli O157:H7: an in silico approach

Overview of attention for article published in Advances and Applications in Bioinformatics and Chemistry : AABC, December 2015
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Title
Identification of potential drug targets by subtractive genome analysis of Escherichia coli O157:H7: an in silico approach
Published in
Advances and Applications in Bioinformatics and Chemistry : AABC, December 2015
DOI 10.2147/aabc.s88522
Pubmed ID
Authors

Shakhinur Islam Mondal, Sabiha Ferdous, Nurnabi Azad Jewel, Arzuba Akter, Zabed Mahmud, Muzahidul Islam, Tanzila Afrin, Nurul Karim

Abstract

Bacterial enteric infections resulting in diarrhea, dysentery, or enteric fever constitute a huge public health problem, with more than a billion episodes of disease annually in developing and developed countries. In this study, the deadly agent of hemorrhagic diarrhea and hemolytic uremic syndrome, Escherichia coli O157:H7 was investigated with extensive computational approaches aimed at identifying novel and broad-spectrum antibiotic targets. A systematic in silico workflow consisting of comparative genomics, metabolic pathways analysis, and additional drug prioritizing parameters was used to identify novel drug targets that were essential for the pathogen's survival but absent in its human host. Comparative genomic analysis of Kyoto Encyclopedia of Genes and Genomes annotated metabolic pathways identified 350 putative target proteins in E. coli O157:H7 which showed no similarity to human proteins. Further bio-informatic approaches including prediction of subcellular localization, calculation of molecular weight, and web-based investigation of 3D structural characteristics greatly aided in filtering the potential drug targets from 350 to 120. Ultimately, 44 non-homologous essential proteins of E. coli O157:H7 were prioritized and proved to have the eligibility to become novel broad-spectrum antibiotic targets and DNA polymerase III alpha (dnaE) was the top-ranked among these targets. Moreover, druggability of each of the identified drug targets was evaluated by the DrugBank database. In addition, 3D structure of the dnaE was modeled and explored further for in silico docking with ligands having potential druggability. Finally, we confirmed that the compounds N-coeleneterazine and N-(1,4-dihydro-5H-tetrazol-5-ylidene)-9-oxo-9H-xanthene-2-sulfon-amide were the most suitable ligands of dnaE and hence proposed as the potential inhibitors of this target protein. The results of this study could facilitate the discovery and release of new and effective drugs against E. coli O157:H7 and other deadly human bacterial pathogens.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 111 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 <1%
Unknown 110 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 25 23%
Student > Master 14 13%
Researcher 9 8%
Student > Ph. D. Student 9 8%
Student > Postgraduate 6 5%
Other 12 11%
Unknown 36 32%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 26 23%
Agricultural and Biological Sciences 16 14%
Immunology and Microbiology 8 7%
Unspecified 4 4%
Engineering 4 4%
Other 10 9%
Unknown 43 39%
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 December 2015.
All research outputs
#19,962,154
of 25,394,764 outputs
Outputs from Advances and Applications in Bioinformatics and Chemistry : AABC
#33
of 55 outputs
Outputs of similar age
#275,302
of 395,587 outputs
Outputs of similar age from Advances and Applications in Bioinformatics and Chemistry : AABC
#2
of 2 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 55 research outputs from this source. They receive a mean Attention Score of 2.5. This one is in the 40th percentile – i.e., 40% 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 395,587 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.