Computational Studies on Natural Products for the Development of Multi-target Drugs

  • Veronika Temml
  • Daniela SchusterEmail author
Part of the Methods in Pharmacology and Toxicology book series (MIPT)


Secondary plant metabolites represent “privileged structures” in drug development; they frequently interact with multiple protein targets within the body. For example, the anti-inflammatory natural product resveratrol from red wine has been shown to be active on over ten targets. Computational methods allow us to tackle the complexity of plant extracts, which often contain multiple active structures, which are in turn interacting with multiple targets. Virtual screening-based target fishing with pharmacophore modeling can help to identify protein targets, and docking simulations can be employed to propose a binding mechanism. Computational methods also play an important role in the analysis of plant extracts. Dereplication databases can be used to compare mass spectra of new extracts to a database of literature data to identify already known natural products. Activity networks of plant constituents help to understand the effect of extracts on specific pathologies and help to determine the active principles. We provide an overview, over the currently used computational methods in natural product research.


Activity networks Dereplication Molecular docking Multi-target inhibitors Natural products Pharmacophore modeling Polypharmacology Virtual screening 


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute of Pharmacy/Pharmacognosy and Center for Molecular Biosciences InnsbruckUniversity of InnsbruckInnsbruckAustria
  2. 2.Institute of Pharmacy/Pharmaceutical Chemistry and Center for Molecular Biosciences InnsbruckUniversity of InnsbruckInnsbruckAustria
  3. 3.Department of Pharmaceutical and Medicinal Chemistry, Institute of PharmacyParacelsus Medical University SalzburgSalzburgAustria

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