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The project is part of the BMBF-funded BB3R initiative. One major goal of the BB3R initiative is the establishment of alternative methods for preclinical drug development and basic research. To assess the toxicity of novel chemical entities, regulatory agencies require in-vivo testing for several toxic endpoints. In 2010, roughly 2.9 million laboratory animals have been deployed in Germany, with an increase of 6% since 2008. Thus, the establishment of alternative methods, and with it the reduction of animal testing, is of utmost importance. Determining the toxicity of compounds is vital to identify their harmful effects on humans, animals, plants and the environment.
The focus of the AG Volkamer is the development of structure-based methods to come closer to the vision of transforming toxicology into a predictive science and reducing the number of animal testing. The group strongly focuses on computer-aided prediction of off-target effects as well as the identification of novel 'toxicophores' and toxicity targets (targets associated with adverse drug reactions) using ligand- as well as protein-based structural and physicochemical information.
Structure-based (binding site assessment and comparison, pharmacophore elucidation, structure-function relationship) and ligand-based (screening, QSAR, machine learning) methods are investigated to guide the design of more selective and less toxic compounds.
The group is looking forward to new challenges and new collaborations with computational and experimental partners to jointly apply the novel methods to acute questions.
Publications / Awards
- Eid S., Turk S., Volkamer A., Rippmann F., Fulle S. (2017). KinMap: a web-based tool for interactive navigation through human kinome data. BMC Bioinformatics. 18:16.
- Volkamer A., Eid S., Turk S., Rippmann F., Fulle S. (2016). Identification and Visualization of Kinase-Specific Subpockets. Journal of Chemical Information and Modeling, 56(2):335-46
- Schneider N., Volkamer A., Nittinger E., Rarey M. (2016) Applied Biocatalysis: Supporting biocatalysis research with structural bioinformatics, book chapter, Wiley
- Volkamer A., Eid S., Turk S., Jaeger S., Rippmann F., Fulle S. (2015). Pocketome of human kinases: Prioritizing the ATP binding sites of (yet) untapped protein kinases for drug discovery. Journal of Chemical Information and Modeling, 55(3):538-49
- Volkamer A., Rarey M. (2014). Exploiting structural information for drug-target assessment. Future Medicinal Chemistry, 6(3):319-31.
- Wirth M., Volkamer A., Rippmann F., Zoete V., Michielin O., Rarey M., Sauer W. H. B. (2013) Protein pocket and ligand shape comparison and its application in virtual screening. Journal of Computer Aided Molecular Design, 27(6):511-24
- v. Behren M., Volkamer A., Henzler A. M., Schomburg K. T., Urbaczek S., Rarey M. (2013). Fast protein binding site comparison via an index-based screening technology. Journal of Chemical Information and Modeling,53(2):411-22
- Volkamer A., Kuhn D., Rippmann R., Rarey M. (2013). Predicting enzymatic function from global binding site descriptors. Proteins: Structure, Function and Bioinformatics, 81(3):479-89
- Ehrlich HC.,Volkamer A., Rarey M. (2012). Searching for substructures in fragment spaces. Journal of Chemical Information and Modeling, 52(12):3181-9
- Volkamer A., Kuhn D., Rippmann F., Rarey M. (2012). DoGSiteScorer: A web-server for automatic binding site prediction, analysis, and druggability assessment. Bioinformatics 28(15):2074-5
- Volkamer A., Kuhn D., Grombacher T., Rippmann F., Rarey M. (2012). Combining Global and Local Measures for Structure-Based Druggability Predictions. Journal of Chemical Information and Modeling, 52:360-372
- Volkamer A., Griewel A., Grombacher T., Rarey M. (2010). Analyzing the Topology of Active Sites: On the Prediction of Pockets and Sub-pockets. Journal of Chemical Information and Modeling, 50(11):2041-2052