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GPCRs from fusarium graminearum detection, modeling and virtual screening - the search for new routes to control head blight disease
BACKGOUND: Fusarium graminearum (FG) is one of the major cereal infecting pathogens causing high economic losses worldwide and resulting in adverse effects on human and animal health. Therefore, the development of new fungicides against FG is an important issue to reduce cereal infection and economi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5249037/ https://www.ncbi.nlm.nih.gov/pubmed/28105916 http://dx.doi.org/10.1186/s12859-016-1342-9 |
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author | Bresso, Emmanuel Togawa, Roberto Hammond-Kosack, Kim Urban, Martin Maigret, Bernard Martins, Natalia Florencio |
author_facet | Bresso, Emmanuel Togawa, Roberto Hammond-Kosack, Kim Urban, Martin Maigret, Bernard Martins, Natalia Florencio |
author_sort | Bresso, Emmanuel |
collection | PubMed |
description | BACKGOUND: Fusarium graminearum (FG) is one of the major cereal infecting pathogens causing high economic losses worldwide and resulting in adverse effects on human and animal health. Therefore, the development of new fungicides against FG is an important issue to reduce cereal infection and economic impact. In the strategy for developing new fungicides, a critical step is the identification of new targets against which innovative chemicals weapons can be designed. As several G-protein coupled receptors (GPCRs) are implicated in signaling pathways critical for the fungi development and survival, such proteins could be valuable efficient targets to reduce Fusarium growth and therefore to prevent food contamination. RESULTS: In this study, GPCRs were predicted in the FG proteome using a manually curated pipeline dedicated to the identification of GPCRs. Based on several successive filters, the most appropriate GPCR candidate target for developing new fungicides was selected. Searching for new compounds blocking this particular target requires the knowledge of its 3D-structure. As no experimental X-Ray structure of the selected protein was available, a 3D model was built by homology modeling. The model quality and stability was checked by 100 ns of molecular dynamics simulations. Two stable conformations representative of the conformational families of the protein were extracted from the 100 ns simulation and were used for an ensemble docking campaign. The model quality and stability was checked by 100 ns of molecular dynamics simulations previously to the virtual screening step. The virtual screening step comprised the exploration of a chemical library with 11,000 compounds that were docked to the GPCR model. Among these compounds, we selected the ten top-ranked nontoxic molecules proposed to be experimentally tested to validate the in silico simulation. CONCLUSIONS: This study provides an integrated process merging genomics, structural bioinformatics and drug design for proposing innovative solutions to a world wide threat to grain producers and consumers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1342-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5249037 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-52490372017-01-26 GPCRs from fusarium graminearum detection, modeling and virtual screening - the search for new routes to control head blight disease Bresso, Emmanuel Togawa, Roberto Hammond-Kosack, Kim Urban, Martin Maigret, Bernard Martins, Natalia Florencio BMC Bioinformatics Research BACKGOUND: Fusarium graminearum (FG) is one of the major cereal infecting pathogens causing high economic losses worldwide and resulting in adverse effects on human and animal health. Therefore, the development of new fungicides against FG is an important issue to reduce cereal infection and economic impact. In the strategy for developing new fungicides, a critical step is the identification of new targets against which innovative chemicals weapons can be designed. As several G-protein coupled receptors (GPCRs) are implicated in signaling pathways critical for the fungi development and survival, such proteins could be valuable efficient targets to reduce Fusarium growth and therefore to prevent food contamination. RESULTS: In this study, GPCRs were predicted in the FG proteome using a manually curated pipeline dedicated to the identification of GPCRs. Based on several successive filters, the most appropriate GPCR candidate target for developing new fungicides was selected. Searching for new compounds blocking this particular target requires the knowledge of its 3D-structure. As no experimental X-Ray structure of the selected protein was available, a 3D model was built by homology modeling. The model quality and stability was checked by 100 ns of molecular dynamics simulations. Two stable conformations representative of the conformational families of the protein were extracted from the 100 ns simulation and were used for an ensemble docking campaign. The model quality and stability was checked by 100 ns of molecular dynamics simulations previously to the virtual screening step. The virtual screening step comprised the exploration of a chemical library with 11,000 compounds that were docked to the GPCR model. Among these compounds, we selected the ten top-ranked nontoxic molecules proposed to be experimentally tested to validate the in silico simulation. CONCLUSIONS: This study provides an integrated process merging genomics, structural bioinformatics and drug design for proposing innovative solutions to a world wide threat to grain producers and consumers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1342-9) contains supplementary material, which is available to authorized users. BioMed Central 2016-12-15 /pmc/articles/PMC5249037/ /pubmed/28105916 http://dx.doi.org/10.1186/s12859-016-1342-9 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Bresso, Emmanuel Togawa, Roberto Hammond-Kosack, Kim Urban, Martin Maigret, Bernard Martins, Natalia Florencio GPCRs from fusarium graminearum detection, modeling and virtual screening - the search for new routes to control head blight disease |
title | GPCRs from fusarium graminearum detection, modeling and virtual screening - the search for new routes to control head blight disease |
title_full | GPCRs from fusarium graminearum detection, modeling and virtual screening - the search for new routes to control head blight disease |
title_fullStr | GPCRs from fusarium graminearum detection, modeling and virtual screening - the search for new routes to control head blight disease |
title_full_unstemmed | GPCRs from fusarium graminearum detection, modeling and virtual screening - the search for new routes to control head blight disease |
title_short | GPCRs from fusarium graminearum detection, modeling and virtual screening - the search for new routes to control head blight disease |
title_sort | gpcrs from fusarium graminearum detection, modeling and virtual screening - the search for new routes to control head blight disease |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5249037/ https://www.ncbi.nlm.nih.gov/pubmed/28105916 http://dx.doi.org/10.1186/s12859-016-1342-9 |
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