@article{BencurovaGuptaSarukhanyanetal.2018,
  author    = {Bencurova, Elena and Gupta, Shishir K. and Sarukhanyan, Edita and Dandekar, Thomas},
  title     = {Identification of antifungal targets based on computer modeling},
  series = {Journal of Fungi},
  volume    = {4},
  journal   = {Journal of Fungi},
  number    = {3},
  issn      = {2309-608X},
  doi       = {10.3390/jof4030081},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-197670},
  pages     = {81},
  year      = {2018},
  abstract  = {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.},
  language  = {en}
}