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Identification of Antifungal Targets Based on Computer Modeling
Aspergillus fumigatus is a saprophytic, cosmopolitan fungus that attacks patients with a weak immune system. A rational solution against fungal infection aims to manipulate fungal metabolism or to block enzymes essential for Aspergillus survival. Here we discuss and compare different bioinformatics...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6162656/ https://www.ncbi.nlm.nih.gov/pubmed/29973534 http://dx.doi.org/10.3390/jof4030081 |
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author | Bencurova, Elena Gupta, Shishir K. Sarukhanyan, Edita Dandekar, Thomas |
author_facet | Bencurova, Elena Gupta, Shishir K. Sarukhanyan, Edita Dandekar, Thomas |
author_sort | Bencurova, Elena |
collection | PubMed |
description | Aspergillus fumigatus is a saprophytic, cosmopolitan fungus that attacks patients with a weak immune system. A rational solution against fungal infection aims to manipulate fungal metabolism or to block enzymes essential for Aspergillus survival. Here we discuss and compare different bioinformatics approaches to analyze possible targeting strategies on fungal-unique pathways. For instance, phylogenetic analysis reveals fungal targets, while domain analysis allows us to spot minor differences in protein composition between the host and fungi. Moreover, protein networks between host and fungi can be systematically compared by looking at orthologs and exploiting information from host–pathogen interaction databases. Further data—such as knowledge of a three-dimensional structure, gene expression data, or information from calculated metabolic fluxes—refine the search and rapidly put a focus on the best targets for antimycotics. We analyzed several of the best targets for application to structure-based drug design. Finally, we discuss general advantages and limitations in identification of unique fungal pathways and protein targets when applying bioinformatics tools. |
format | Online Article Text |
id | pubmed-6162656 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-61626562018-10-09 Identification of Antifungal Targets Based on Computer Modeling Bencurova, Elena Gupta, Shishir K. Sarukhanyan, Edita Dandekar, Thomas J Fungi (Basel) Review Aspergillus fumigatus is a saprophytic, cosmopolitan fungus that attacks patients with a weak immune system. A rational solution against fungal infection aims to manipulate fungal metabolism or to block enzymes essential for Aspergillus survival. Here we discuss and compare different bioinformatics approaches to analyze possible targeting strategies on fungal-unique pathways. For instance, phylogenetic analysis reveals fungal targets, while domain analysis allows us to spot minor differences in protein composition between the host and fungi. Moreover, protein networks between host and fungi can be systematically compared by looking at orthologs and exploiting information from host–pathogen interaction databases. Further data—such as knowledge of a three-dimensional structure, gene expression data, or information from calculated metabolic fluxes—refine the search and rapidly put a focus on the best targets for antimycotics. We analyzed several of the best targets for application to structure-based drug design. Finally, we discuss general advantages and limitations in identification of unique fungal pathways and protein targets when applying bioinformatics tools. MDPI 2018-07-04 /pmc/articles/PMC6162656/ /pubmed/29973534 http://dx.doi.org/10.3390/jof4030081 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Bencurova, Elena Gupta, Shishir K. Sarukhanyan, Edita Dandekar, Thomas Identification of Antifungal Targets Based on Computer Modeling |
title | Identification of Antifungal Targets Based on Computer Modeling |
title_full | Identification of Antifungal Targets Based on Computer Modeling |
title_fullStr | Identification of Antifungal Targets Based on Computer Modeling |
title_full_unstemmed | Identification of Antifungal Targets Based on Computer Modeling |
title_short | Identification of Antifungal Targets Based on Computer Modeling |
title_sort | identification of antifungal targets based on computer modeling |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6162656/ https://www.ncbi.nlm.nih.gov/pubmed/29973534 http://dx.doi.org/10.3390/jof4030081 |
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