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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2017
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| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_19326203_v12_n10_p_Jamal http://hdl.handle.net/20.500.12110/paper_19326203_v12_n10_p_Jamal |
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paper:paper_19326203_v12_n10_p_Jamal2023-06-08T16:30:37Z An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae bacterial protein protein bioB protein DIP0983 protein DIP1084 protein glpX protein hisE protein nusB protein rpsH protein smpB unclassified drug antiinfective agent bacterial protein 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 Corynebacterium diphtheriae drug effects genetics human metabolism pathogenicity validation study Anti-Bacterial Agents Bacterial Proteins Bacterial Vaccines Computer Simulation Corynebacterium diphtheriae Genome, Bacterial Humans Ligands Models, Biological Molecular Docking Simulation 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. 2017 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_19326203_v12_n10_p_Jamal http://hdl.handle.net/20.500.12110/paper_19326203_v12_n10_p_Jamal |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
bacterial protein protein bioB protein DIP0983 protein DIP1084 protein glpX protein hisE protein nusB protein rpsH protein smpB unclassified drug antiinfective agent bacterial protein 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 Corynebacterium diphtheriae drug effects genetics human metabolism pathogenicity validation study Anti-Bacterial Agents Bacterial Proteins Bacterial Vaccines Computer Simulation Corynebacterium diphtheriae Genome, Bacterial Humans Ligands Models, Biological Molecular Docking Simulation |
| spellingShingle |
bacterial protein protein bioB protein DIP0983 protein DIP1084 protein glpX protein hisE protein nusB protein rpsH protein smpB unclassified drug antiinfective agent bacterial protein 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 Corynebacterium diphtheriae drug effects genetics human metabolism pathogenicity validation study Anti-Bacterial Agents Bacterial Proteins Bacterial Vaccines Computer Simulation Corynebacterium diphtheriae Genome, Bacterial Humans Ligands Models, Biological Molecular Docking Simulation An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae |
| topic_facet |
bacterial protein protein bioB protein DIP0983 protein DIP1084 protein glpX protein hisE protein nusB protein rpsH protein smpB unclassified drug antiinfective agent bacterial protein 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 Corynebacterium diphtheriae drug effects genetics human metabolism pathogenicity validation study Anti-Bacterial Agents Bacterial Proteins Bacterial Vaccines Computer Simulation Corynebacterium diphtheriae Genome, Bacterial Humans Ligands Models, Biological Molecular Docking Simulation |
| description |
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. |
| title |
An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae |
| title_short |
An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae |
| title_full |
An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae |
| title_fullStr |
An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae |
| title_full_unstemmed |
An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae |
| title_sort |
integrative in-silico approach for therapeutic target identification in the human pathogen corynebacterium diphtheriae |
| publishDate |
2017 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_19326203_v12_n10_p_Jamal http://hdl.handle.net/20.500.12110/paper_19326203_v12_n10_p_Jamal |
| _version_ |
1768546512462151680 |