An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae

PLoS One. 2017 Oct 19;12(10):e0186401. doi: 10.1371/journal.pone.0186401. eCollection 2017.

Abstract

Corynebacterium diphtheriae (Cd) is a Gram-positive human pathogen responsible for diphtheria infection and once regarded for high mortalities worldwide. The fatality gradually decreased with improved living standards and further alleviated when many immunization programs were introduced. However, numerous drug-resistant strains emerged recently that consequently decreased the efficacy of current therapeutics and vaccines, thereby obliging the scientific community to start investigating new therapeutic targets in pathogenic microorganisms. In this study, our contributions include the prediction of modelome of 13 C. diphtheriae strains, using the MHOLline workflow. A set of 463 conserved proteins were identified by combining the results of pangenomics based core-genome and core-modelome analyses. Further, using subtractive proteomics and modelomics approaches for target identification, a set of 23 proteins was selected as essential for the bacteria. Considering human as a host, eight of these proteins (glpX, nusB, rpsH, hisE, smpB, bioB, DIP1084, and DIP0983) were considered as essential and non-host homologs, and have been subjected to virtual screening using four different compound libraries (extracted from the ZINC database, plant-derived natural compounds and Di-terpenoid Iso-steviol derivatives). The proposed ligand molecules showed favorable interactions, lowered energy values and high complementarity with the predicted targets. Our proposed approach expedites the selection of C. diphtheriae putative proteins for broad-spectrum development of novel drugs and vaccines, owing to the fact that some of these targets have already been identified and validated in other organisms.

Publication types

  • Validation Study

MeSH terms

  • Anti-Bacterial Agents / pharmacology
  • Bacterial Proteins / metabolism
  • Bacterial Vaccines / pharmacology
  • Computer Simulation
  • Corynebacterium diphtheriae / drug effects
  • Corynebacterium diphtheriae / genetics
  • Corynebacterium diphtheriae / metabolism
  • Corynebacterium diphtheriae / pathogenicity*
  • Genome, Bacterial
  • Humans
  • Ligands
  • Models, Biological
  • Molecular Docking Simulation

Substances

  • Anti-Bacterial Agents
  • Bacterial Proteins
  • Bacterial Vaccines
  • Ligands

Grant support

The study was supported by grant from the TWAS-CNPq Postgraduate Fellowship Programme (https://twas.org/opportunity/twas-cnpq-postgraduate-fellowship-programme) for granting a fellowship for doctoral studies and CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brasil: http://www.capes.gov.br/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.