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

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...

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Main Authors: Wan, Yean Chung, Yan, Zhu, Mahamad Maifiah, Mohd Hafidz, Hawala Shivashekaregowda, Naveen Kumar, Eng, Hwa Wong, Abdul Rahim, Nusaibah
Format: Article
Language:English
English
English
Published: Springer Nature 2021
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Online Access:http://irep.iium.edu.my/84284/1/84284_Novel%20antimicrobial%20development%20using%20genome-scale.pdf
http://irep.iium.edu.my/84284/2/84284_Novel%20antimicrobial%20development%20using%20genome-scale_WoS.pdf
http://irep.iium.edu.my/84284/3/84284_Novel%20antimicrobial%20development%20using%20genome-scale_SCOPUS.pdf
http://irep.iium.edu.my/84284/
https://www.nature.com/articles/s41429-020-00366-2#citeas
https://doi.org/10.1038/s41429-020-00366-2
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Summary: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.