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

Autores
Jamal, Syed Babar; Hassan, Syed Shah; Tiwari, Sandeep; Viana, Marcus V.; De Jesus Benevides, Leandro; Ullah, Asad; Turjanski, Adrian; Barh, Debmalya; Ghosh, Preetam; Costa, Daniela Arruda; Silva, Artur; Röttger, Richard; Baumbach, Jan; Azevedo, Vasco A. C.
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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.
Fil: Jamal, Syed Babar. Universidade Federal de Minas Gerais; Brasil
Fil: Hassan, Syed Shah. Universidade Federal de Minas Gerais; Brasil. University Peshawar; Pakistán
Fil: Tiwari, Sandeep. Universidade Federal de Minas Gerais; Brasil
Fil: Viana, Marcus V.. Universidade Federal de Minas Gerais; Brasil
Fil: De Jesus Benevides, Leandro. Universidade Federal de Minas Gerais; Brasil
Fil: Ullah, Asad. University Peshawar; Pakistán
Fil: Turjanski, Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; Argentina
Fil: Barh, Debmalya. Institute Of Integrative Omics And Applied Biotechnology; India
Fil: Ghosh, Preetam. Virginia Commonwealth University; Estados Unidos
Fil: Costa, Daniela Arruda. Universidade Federal de Minas Gerais; Brasil
Fil: Silva, Artur. Universidade Federal do Pará; Brasil
Fil: Röttger, Richard. University of Southern Denmark; Dinamarca
Fil: Baumbach, Jan. University of Southern Denmark; Dinamarca
Fil: Azevedo, Vasco A. C.. Universidade Federal de Minas Gerais; Brasil
Materia
Bioinformatica
GEnomica
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/55100
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/55100
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriaeJamal, Syed BabarHassan, Syed ShahTiwari, SandeepViana, Marcus V.De Jesus Benevides, LeandroUllah, AsadTurjanski, AdrianBarh, DebmalyaGhosh, PreetamCosta, Daniela ArrudaSilva, ArturRöttger, RichardBaumbach, JanAzevedo, Vasco A. C.BioinformaticaGEnomicahttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Corynebacterium 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.Fil: Jamal, Syed Babar. Universidade Federal de Minas Gerais; BrasilFil: Hassan, Syed Shah. Universidade Federal de Minas Gerais; Brasil. University Peshawar; PakistánFil: Tiwari, Sandeep. Universidade Federal de Minas Gerais; BrasilFil: Viana, Marcus V.. Universidade Federal de Minas Gerais; BrasilFil: De Jesus Benevides, Leandro. Universidade Federal de Minas Gerais; BrasilFil: Ullah, Asad. University Peshawar; PakistánFil: Turjanski, Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; ArgentinaFil: Barh, Debmalya. Institute Of Integrative Omics And Applied Biotechnology; IndiaFil: Ghosh, Preetam. Virginia Commonwealth University; Estados UnidosFil: Costa, Daniela Arruda. Universidade Federal de Minas Gerais; BrasilFil: Silva, Artur. Universidade Federal do Pará; BrasilFil: Röttger, Richard. University of Southern Denmark; DinamarcaFil: Baumbach, Jan. University of Southern Denmark; DinamarcaFil: Azevedo, Vasco A. C.. Universidade Federal de Minas Gerais; BrasilPublic Library of Science2017-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/55100Jamal, Syed Babar; Hassan, Syed Shah; Tiwari, Sandeep; Viana, Marcus V.; De Jesus Benevides, Leandro; et al.; An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae; Public Library of Science; Plos One; 12; 10; 10-2017; 1-251932-6203CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0186401info:eu-repo/semantics/altIdentifier/url/http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0186401info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:37:10Zoai:ri.conicet.gov.ar:11336/55100instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:37:11.26CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae
title An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae
spellingShingle An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae
Jamal, Syed Babar
Bioinformatica
GEnomica
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 An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae
dc.creator.none.fl_str_mv Jamal, Syed Babar
Hassan, Syed Shah
Tiwari, Sandeep
Viana, Marcus V.
De Jesus Benevides, Leandro
Ullah, Asad
Turjanski, Adrian
Barh, Debmalya
Ghosh, Preetam
Costa, Daniela Arruda
Silva, Artur
Röttger, Richard
Baumbach, Jan
Azevedo, Vasco A. C.
author Jamal, Syed Babar
author_facet Jamal, Syed Babar
Hassan, Syed Shah
Tiwari, Sandeep
Viana, Marcus V.
De Jesus Benevides, Leandro
Ullah, Asad
Turjanski, Adrian
Barh, Debmalya
Ghosh, Preetam
Costa, Daniela Arruda
Silva, Artur
Röttger, Richard
Baumbach, Jan
Azevedo, Vasco A. C.
author_role author
author2 Hassan, Syed Shah
Tiwari, Sandeep
Viana, Marcus V.
De Jesus Benevides, Leandro
Ullah, Asad
Turjanski, Adrian
Barh, Debmalya
Ghosh, Preetam
Costa, Daniela Arruda
Silva, Artur
Röttger, Richard
Baumbach, Jan
Azevedo, Vasco A. C.
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Bioinformatica
GEnomica
topic Bioinformatica
GEnomica
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv 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.
Fil: Jamal, Syed Babar. Universidade Federal de Minas Gerais; Brasil
Fil: Hassan, Syed Shah. Universidade Federal de Minas Gerais; Brasil. University Peshawar; Pakistán
Fil: Tiwari, Sandeep. Universidade Federal de Minas Gerais; Brasil
Fil: Viana, Marcus V.. Universidade Federal de Minas Gerais; Brasil
Fil: De Jesus Benevides, Leandro. Universidade Federal de Minas Gerais; Brasil
Fil: Ullah, Asad. University Peshawar; Pakistán
Fil: Turjanski, Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; Argentina
Fil: Barh, Debmalya. Institute Of Integrative Omics And Applied Biotechnology; India
Fil: Ghosh, Preetam. Virginia Commonwealth University; Estados Unidos
Fil: Costa, Daniela Arruda. Universidade Federal de Minas Gerais; Brasil
Fil: Silva, Artur. Universidade Federal do Pará; Brasil
Fil: Röttger, Richard. University of Southern Denmark; Dinamarca
Fil: Baumbach, Jan. University of Southern Denmark; Dinamarca
Fil: Azevedo, Vasco A. C.. Universidade Federal de Minas Gerais; Brasil
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.
publishDate 2017
dc.date.none.fl_str_mv 2017-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/55100
Jamal, Syed Babar; Hassan, Syed Shah; Tiwari, Sandeep; Viana, Marcus V.; De Jesus Benevides, Leandro; et al.; An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae; Public Library of Science; Plos One; 12; 10; 10-2017; 1-25
1932-6203
CONICET Digital
CONICET
url http://hdl.handle.net/11336/55100
identifier_str_mv Jamal, Syed Babar; Hassan, Syed Shah; Tiwari, Sandeep; Viana, Marcus V.; De Jesus Benevides, Leandro; et al.; An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae; Public Library of Science; Plos One; 12; 10; 10-2017; 1-25
1932-6203
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0186401
info:eu-repo/semantics/altIdentifier/url/http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0186401
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Public Library of Science
publisher.none.fl_str_mv Public Library of Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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