In silico Identification of Putative Drug Targets in Pseudomonas aeruginosa Through Metabolic Pathway Analysis

  • Deepak Perumal
  • Chu Sing Lim
  • Meena K. Sakharkar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4774)

Abstract

Comparative genomic analysis between pathogens and the host Homo sapiens has led to identification of novel drug targets. Microbial drug target identification and validation has been the latest trend in pharmacoinformatics. In order to identify a suitable drug target for the pathogen Pseudomonas aeruginosa an in silico comparative analysis of the metabolic pathways between the pathogen and the host Homo sapiens was performed. Detection of bacterial genes that are non-homologous to human genes, and are essential for the survival of the pathogen represents a promising means of identifying novel drug targets. Metabolic pathways for the pathogen and H.sapiens were obtained from the metabolic pathway database KEGG and were compared to identify unique pathways present only in the pathogen and absent in the host. We identified 361 enzymes from both unique and common pathways between the pathogen and the host of which 50 belong to the 12 unique pathways. Enzymes from both genomes were subject to a BLASTp search and sequences homologous to human were removed as non essential. P.aeruginosa targets without human homologs were identified when the e-value threshold was set as 10− 2. Of the 214 targets that had no hits only 30 targets belong to unique pathways. These 30 targets were then compared with the list of candidate essential genes identified by mutagenesis. Only 8 targets matched with the essential genes list and these were considered as potential drug targets. We have built homology model for the four target genes lpxC, kdsA, kdsB and waaG using MODELLER software. This approach enables rapid potential drug target identification, thereby greatly facilitating the search for new antibiotics.

Keywords

Pseudomonas aeruginosa Homo sapiens Comparative microbial genomics KEGG Homology MODELLER kdsA kdsB waaG lpxC Potential drug targets 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Deepak Perumal
    • 1
    • 2
  • Chu Sing Lim
    • 2
  • Meena K. Sakharkar
    • 1
  1. 1.School of Mechanical and Aerospace Engineering, Nanyang Technological UniversitySingapore
  2. 2.BioMedical Engineering Research Centre, Nanyang Technological UniversitySingapore

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