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

Authors

Syed Babar Jamal, Federal University of Minas Gerais
Syed Shah Hassan, Federal University of Minas Gerais, Islamia College University Peshawar
Sandeep Tiwari, Federal University of Minas Gerais
Marcus V. Viana, Federal University of Minas Gerais
Leandro de Jesus Benevides, Federal University of Minas Gerais
Asad Ullah, Islamia College University Peshawar
Adrián G. Turjanski, Universidad de Buenos Aires (UBA)
Debmalya Barh, Institute of Integrative Omics and Applied Biotechnology
Preetam Ghosh, Virginia Commonwealth University
Daniela Arruda Costa, Federal University of Minas Gerais
Artur Silva, Federal University of Para
Richard Röttger, University of Southern Denmark
Jan Baumbach, University of Southern Denmark
Vasco A.C. Azevedo, Federal University of Minas Gerais

Document Type

Article

Original Publication Date

2017

Journal/Book/Conference Title

PLOS One

DOI of Original Publication

10.1371/journal.pone.0186401

Comments

Originally published at https://doi.org/10.1371/journal.pone.0186401

Date of Submission

February 2018

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. diphtheriaeputative 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.

Rights

This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Is Part Of

VCU Computer Science Publications