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

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, n...

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Detalles Bibliográficos
Autores principales: Jamal, S.B., Hassan, S.S., Tiwari, S., Viana, M.V., De Jesus Benevides, L., Ullah, A., Turjanski, A.G., Barh, D., Ghosh, P., Costa, D.A., Silva, A., Röttger, R., Baumbach, J., Azevedo, V.A.C.
Formato: JOUR
Materias:
bacterial protein
protein bioB
protein DIP0983
protein DIP1084
protein glpX
protein hisE
protein nusB
protein rpsH
protein smpB
unclassified drug
antiinfective agent
bacterial vaccine
ligand
Article
bacterial genome
bacterial strain
bacterium identification
computer model
controlled study
Corynebacterium diphtheriae
gene identification
molecular docking
nonhuman
protein analysis
protein function
protein protein interaction
protein structure
proteomics
biological model
computer simulation
drug effects
genetics
human
metabolism
pathogenicity
validation study
Anti-Bacterial Agents
Bacterial Proteins
Bacterial Vaccines
Computer Simulation
Genome, Bacterial
Humans
Ligands
Models, Biological
Molecular Docking Simulation
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_19326203_v12_n10_p_Jamal
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
Descripción
Sumario: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. © 2017, Public Library of Science. All rights reserved. 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.

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