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ZENODO
Dataset . 2021
License: CC BY NC
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2021
License: CC BY NC
Data sources: ZENODO
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Supporting data for: Low-cost drug discovery with engineered E. coli reveals an anti-mycobacterial activity of benazepril

Authors: Nadine Bongaerts; Zainab Edoo; Ayan A. Abukar; Xiaohu Song; Sebastián Sosa Carrillo; Ariel B. Lindner; Edwin H. Wintermute;

Supporting data for: Low-cost drug discovery with engineered E. coli reveals an anti-mycobacterial activity of benazepril

Abstract

Supporting data for Low-cost drug discovery with engineered E. coli reveals an anti-mycobacterial activity of benazepril The associated reference describes our work developing TESEC Mtb ALR, a genetically engineered strain of E. coli expressing the enzyme ALR derived from Mtb. We used the TESEC Mtb ALR strain in a high-throughput drug screen and identified benazepril as targeted inhibitor of the ALR enzyme. We then performed additional experiments to characterize the activity of benazepril against E. coli, Mtb and purified enzymes. These files include growth measurements, biochemical assays and other forms of biological data. They are packaged together with scripts used to analyze the data and present them in figures. Our goal in creating this archive was to present our complete analysis pipeline in the spirit of open science. It is not intended to be a stand-alone resource. Consult the associated manuscript for protocols, units of measurement and other essential technical context. Our scripts were written for Python 3.8. The raw data is presented as human-readable .csv files intended to be imported as Pandas DataFrames. Some data is also packaged as Python dictionaries saved with the Pickle package.

{"references": ["Bongaerts N et al. (2021) Low-cost drug discovery with engineered E. coli reveals an anti-mycobacterial activity of benazepril. bioRxiv 2021.03.26.437171. doi: https://doi.org/10.1101/2021.03.26.437171"]}

Keywords

Antibiotics, Drug Discovery, Escherichia coli, Tuberculosis, Synthetic Biology, Frugal Science

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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