Evidence map›Paper›PMID 32901119›Full record

ReviewThe Journal of antibiotics2021

Novel antimicrobial development using genome-scale metabolic model of Gram-negative pathogens: a review.

Wan Yean Chung, Yan Zhu, Mohd Hafidz Mahamad Maifiah, Naveen Kumar Hawala Shivashekaregowda, Eng Hwa Wong, Nusaibah Abdul Rahim

Abstract readReview
PubMed Publisher
In one paragraph

Review in The Journal of antibiotics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. NAR genomics and bioinformatics · 2024
    Article
  2. Review
  3. Review
  4. A Systematic Strategy to Find Potential Therapeutic Targets forFrontiers in molecular biosciences · 2021
    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

6 authors.

Wan Yean ChungSchool of Pharmacy, Taylor's University, 47500, Subang Jaya, Selangor, Malaysia.
Yan ZhuBiomedicine Discovery Institute, Infection and Immunity Program and Department of Microbiology, Monash University, Melbourne, 3800, VIC, Australia.
Mohd Hafidz Mahamad MaifiahInternational Institute for Halal Research and Training (INHART), International Islamic University Malaysia (IIUM), 53100, Jalan Gombak, Selangor, Malaysia.
Naveen Kumar Hawala ShivashekaregowdaCenter for Drug Discovery and Molecular Pharmacology (CDDMP), Faculty of Health and Medical Sciences, Taylor's University, 47500, Subang Jaya, Selangor, Malaysia.
Eng Hwa WongSchool of Medicine, Taylor's University, 47500, Subang Jaya, Selangor, Malaysia. enghwa.wong@taylors.edu.my.ORCID http://orcid.org/0000-0001-9322-772X
Nusaibah Abdul RahimFaculty of Pharmacy, University of Malaya, 50603, Kuala Lumpur, Malaysia. nusaibah.abdulrahim@um.edu.my.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antimicrobial resistance (AMR) threatens the effective prevention and treatment of a wide range of infections. Governments around the world are beginning to devote effort for innovative treatment development to treat these resistant bacteria. Systems biology methods have been applied extensively to provide valuable insights into metabolic processes at system level. Genome-scale metabolic models serve as platforms for constraint-based computational techniques which aid in novel drug discovery. Tools for automated reconstruction of metabolic models have been developed to support system level metabolic analysis. We discuss features of such software platforms for potential users to best fit their purpose of research. In this work, we focus to review the development of genome-scale metabolic models of Gram-negative pathogens and also metabolic network approach for identification of antimicrobial drugs targets.

Indexed as

AnimalsAnti-Bacterial AgentsBacteriaDrug DevelopmentDrug DiscoveryGram-Negative BacteriaGram-Negative Bacterial InfectionsHumansMetabolic Networks and PathwaysAnti-Bacterial Agents

Identifiers

What OpenQuestion holds

Textmetadata
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.