Evidence map›Paper›PMID 27117032›Full record

ArticleJournal of microbiological methods2016

Development of a web-based tool for automated processing and cataloging of a unique combinatorial drug screen.

Alex G Dalecki, Frank Wolschendorf

Abstract read
In one paragraph

Article in Journal of microbiological methods, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Alex G DaleckiDepartment of Medicine, Division of Infectious Diseases, University of Alabama at Birmingham, 845 19th St S, Birmingham, AL 35294, United States. Electronic address: dalecki@uab.edu.
Frank WolschendorfDepartment of Medicine, Division of Infectious Diseases, University of Alabama at Birmingham, 845 19th St S, Birmingham, AL 35294, United States. Electronic address: fwolsche@uab.edu.

Funding

UAB Center for Clinical and Translational Science (CCTS)UL1TR001417 · NCATS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI KIMBERLY, ROBERT P. · 2015 to 2018
$31.4M
HTS for bactericidal inhibitors of M. tuberculosis copper resistance mechanismsR01AI104952 · NIAID · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI WOLSCHENDORF, FRANK · 2013 to 2015
$1.1M
NCATS NIH HHS UL1 TR001417NIAID NIH HHS R01 AI104952
6 · The paper itself

Abstract

Facing totally resistant bacteria, traditional drug discovery efforts have proven to be of limited use in replenishing our depleted arsenal of therapeutic antibiotics. Recently, the natural anti-bacterial properties of metal ions in synergy with metal-coordinating ligands have shown potential for generating new molecule candidates with potential therapeutic downstream applications. We recently developed a novel combinatorial screening approach to identify compounds with copper-dependent anti-bacterial properties. Through a parallel screening technique, the assay distinguishes between copper-dependent and independent activities against Mycobacterium tuberculosis with hits being defined as compounds with copper-dependent activities. These activities must then be linked to a compound master list to process and analyze the data and to identify the hit molecules, a labor intensive and mistake-prone analysis. Here, we describe a software program built to automate this analysis in order to streamline our workflow significantly. We conducted a small, 1440 compound screen against M. tuberculosis and used it as an example framework to build and optimize the software. Though specifically adapted to our own needs, it can be readily expanded for any small- to medium-throughput screening effort, parallel or conventional. Further, by virtue of the underlying Linux server, it can be easily adapted for chemoinformatic analysis of screens through packages such as OpenBabel. Overall, this setup represents an easy-to-use solution for streamlining processing and analysis of biological screening data, as well as offering a scaffold for ready functionality expansion.

Indexed as

High-Throughput Screening AssaysMicrobial Sensitivity TestsSoftwareAnti-Bacterial AgentsAutomation, LaboratoryCatalogs, Drug as TopicCopperDrug DiscoveryInternetMycobacterium tuberculosisAnti-Bacterial AgentsCopperChemoinformaticsCombinatorial screenCopperHigh throughput screenTuberculosis

Identifiers

PMID27117032
PMCPMC4921064

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.