Structural Bioinformatics Group

Welcome to AG Preissner

Our Research Activities

As an interdisciplinary research group, we focus on multiple research topics in fields of bio/cheminformatics and personalized medicine. Our primary interests are in understanding the structure, function and interaction of chemicals with therapeutic and off-targets. By applying a wide range of cheminformatics methods including chemical similarity approaches, molecular docking and simulations, we propose hypotheses to answer complex questions in drug discovery. We develop in silico models to predict the target landscape of small molecules relevant in cancer research and for other pharmaceutically relevant endpoints (cardiotoxicity, hepatotoxicity etc.). With an aim to serve the research community, we developed several bio- and cheminformatics databases and web servers (listed below). Using our knowledge base and toolchain, we analyze health care data in order to propose recommendations to improve decision making in clinical practices, and develop computational methods to contribute to the state-of-the-art in the research field.

Our group is part of the Charité Technology Transfer initiative. For more information, please check the catalogue.

List of bio/cheminformatics databases and web servers developed at our group (selected):

An extensive list of resources can be found here.

Latest News

  • 2021-04 - New Research Published: VirtualTaste: a web server for the prediction of organoleptic properties of chemical compounds, In Nucleic Acids Research
  • 2021-02 - New Research Published- Oxidative testicular injury: effect of l-leucine on redox, cholinergic and purinergic dysfunctions, and dysregulated metabolic pathways. Amino Acids-Springer Nature, Feb 2021
  • 2020-12 - Publication Promisuous 2.0 - A resource for drug repositioning; Published in NAR; doi: gkaa1061
  • 2020-12 - New Research: Computational Prediction of Potential Inhibitors of the Main Protease of SARS-CoV-2:
  • 2020-08 - Evidence for treatment with estradiol for women with SARS-CoV-2 infection - using a cohort of over 68,000 participants. Preprint of a new study with colleagues in Bethesda and Rome.
  • For older news, see News Archive