Identification of potential drug targets in Yersinia pestis using metabolic pathway analysis: MurE ligase as a case

Aditya Sharma1, Archana Pan

  • 1Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Pondicherry 605014, India. aditya2088@gmail.com

Insights

New plague drugs are urgently needed due to resistant strains and bioterrorism threats. A computational approach identified essential Yersinia pestis drug targets, including choke point enzymes like MurE ligase, leading to a potential inhibitor discovery.

Area of Science:

  • Microbiology
  • Drug Discovery
  • Computational Biology

Background:

  • Plague outbreaks, lack of vaccines, and drug-resistant Yersinia pestis strains necessitate novel antimicrobial development.
  • The potential for Yersinia pestis to be used in bioterrorism further underscores the urgent need for new therapeutic strategies.

Purpose of the Study:

  • To identify essential drug-target candidate enzymes in Yersinia pestis CO92 using comparative metabolic pathway analysis.
  • To pinpoint potential choke point enzymes crucial for pathogen survival and non-homologous to human enzymes.
  • To demonstrate a case study for rapid drug-target identification and inhibitor discovery.

Main Methods:

  • Comparative metabolic pathway analysis of Yersinia pestis CO92.
  • Identification of non-homologous and essential enzymes.
  • Structural modeling of choke point enzymes, specifically MurE ligase.
  • Molecular docking studies against compound libraries.

Main Results:

  • Identified 245 potential drug-target candidate enzymes in Y. pestis CO92.
  • Further analysis revealed 25 potential choke point enzymes.
  • Modeled the structure of MurE ligase and performed docking studies.
  • Identified a potential inhibitor for the MurE ligase choke point enzyme.

Conclusions:

  • Comparative metabolic pathway analysis is an effective strategy for identifying essential drug targets in Yersinia pestis.
  • The identified choke point enzymes, such as MurE ligase, represent promising targets for novel antimicrobial drug development.
  • This computational approach facilitates the rapid identification of potential drug targets and inhibitors for plague treatment.

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