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

Chung WY 1 , Zhu Y 2 , Mahamad Maifiah MH 3 , Shivashekaregowda NKH 4 , Wong EH 5 , Abdul Rahim N 6

Affiliations 

  • 1 School of Pharmacy, Taylor's University, 47500, Subang Jaya, Selangor, Malaysia
  • 2 Biomedicine Discovery Institute, Infection and Immunity Program and Department of Microbiology, Monash University, Melbourne, 3800, VIC, Australia
  • 3 International Institute for Halal Research and Training (INHART), International Islamic University Malaysia (IIUM), 53100, Jalan Gombak, Selangor, Malaysia
  • 4 Center for Drug Discovery and Molecular Pharmacology (CDDMP), Faculty of Health and Medical Sciences, Taylor's University, 47500, Subang Jaya, Selangor, Malaysia
  • 5 School of Medicine, Taylor's University, 47500, Subang Jaya, Selangor, Malaysia. enghwa.wong@taylors.edu.my
  • 6 Faculty of Pharmacy, University of Malaya, 50603, Kuala Lumpur, Malaysia. nusaibah.abdulrahim@um.edu.my
J Antibiot (Tokyo), 2021 02;74(2):95-104.
PMID: 32901119 DOI: 10.1038/s41429-020-00366-2

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.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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