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.

抗微生物药物耐药性 (AMR) 威胁着多种感染的有效预防和治疗。世界各国政府都开始致力于创新疗法的开发，以治疗这些耐药细菌。系统生物学方法已被广泛应用于提供对系统级代谢过程的宝贵见解。基因组规模的代谢模型作为基于约束的计算技术的平台，有助于新药的发现。已经开发了用于代谢模型自动重建的工具来支持系统级代谢分析。我们为潜在用户讨论此类软件平台的功能，以最适合他们的研究目的。在这项工作中，