Systematic identification of anti-fungal drug targets by a metabolic network approach

Martin Kaltdorf, Mugdha Srivastava, Shishir K. Gupta, Chunguang Liang, Jasmin Binder, Anna Maria Dietl, Zohar Meir, Hubertus Haas, Nir Osherov, Sven Krappmann, Thomas Dandekar*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


New antimycotic drugs are challenging to find, as potential target proteins may have close human orthologs. We here focus on identifying metabolic targets that are critical for fungal growth and have minimal similarity to targets among human proteins. We compare and combine here: (I) direct metabolic network modeling using elementary mode analysis and flux estimates approximations using expression data, (II) targeting metabolic genes by transcriptome analysis of condition-specific highly expressed enzymes, and (III) analysis of enzyme structure, enzyme interconnectedness ("hubs"), and identification of pathogen-specific enzymes using orthology relations. We have identified 64 targets including metabolic enzymes involved in vitamin synthesis, lipid, and amino acid biosynthesis including 18 targets validated from the literature, two validated and five currently examined in own genetic experiments, and 38 further promising novel target proteins which are non-orthologous to human proteins, involved in metabolism and are highly ranked drug targets from these pipelines.

Original languageEnglish
Article number22
JournalFrontiers in Molecular Biosciences
Issue numberJUN
StatePublished - 17 Jun 2016


  • Antimycotics
  • Fungicide
  • Interaction
  • Metabolism
  • Modeling
  • Structure
  • Targets


Dive into the research topics of 'Systematic identification of anti-fungal drug targets by a metabolic network approach'. Together they form a unique fingerprint.

Cite this