Proteome mining for the identification and in-silico characterization of putative drug targets of multi-drug resistant Clostridium difficile strain 630

  • Mohtashim Lohani
  • , Anupam Dhasmana
  • , Shafiul Haque
  • , Mohd Wahid
  • , Arshad Jawed
  • , Sajad A. Dar
  • , Raju K. Mandal
  • , Mohammed Y. Areeshi
  • , Saif Khan

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Clostridium difficile is an enteric pathogen that causes approximately 20% to 30% of antibiotic-associated diarrhea. In recent years, there has been a substantial rise in the rate of C. difficile infections as well as the emergence of virulent and antibiotic resistant C. difficile strains. So, there is an urgent need for the identification of therapeutic potential targets and development of new drugs for the treatment and prevention of C. difficile infections. In the current study, we used a hybrid approach by combining sequence similarity-based approach and protein-protein interaction network topology-based approach to identify and characterize the potential drug targets of C. difficile. A total of 155 putative drug targets of C. difficile were identified and the metabolic pathway analysis of these putative drug targets using DAVID revealed that 46 of them are involved in 9 metabolic pathways. In-silico characterization of these proteins identified seven proteins involved in pathogen-specific peptidoglycan biosynthesis pathway. Three promising targets viz. homoserine dehydrogenase, aspartate-semialdehyde dehydrogenase and aspartokinase etc. were found to be involved in multiple enzymatic pathways of the pathogen. These 3 drug targets are of particular interest as they can be used for developing effective drugs against multi-drug resistant C. difficile strain 630 in the near future.

Original languageEnglish
Pages (from-to)6-10
Number of pages5
JournalJournal of Microbiological Methods
Volume136
DOIs
StatePublished - 1 May 2017
Externally publishedYes

Keywords

  • Clostridium difficile
  • Essential protein
  • Protein-protein interaction
  • Target identification

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