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

Research output: Contribution to journalReview ArticleResearchpeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Pages (from-to)95-104
Number of pages10
JournalJournal of Antibiotics
Volume74
Issue number2
DOIs
Publication statusPublished - Feb 2021

Keywords

  • biochemical reaction networks
  • medical research

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