Scaffold Hunter: Facilitating Drug Discovery by Visual Analysis of Chemical Space
The search for a new drug to cure a particular disease involves to find a chemical compound that influences a corresponding biological process, e.g., by inhibiting or activating an involved biological target molecule. A potential drug candidate however does not only need to show a sufficient amount of biological activity, but also needs to adhere to additional rules that define the basic limits of druglikeness, including for example restrictions regarding solubility and molecular weight. The sheer size of the search space, i.e., the chemical space that contains the available compounds, the large number of potentially relevant data annotations per compound, the incomplete knowledge on those properties, and the complex relation between the molecular properties and the actual effects in a living organism, complicate the search and may turn the discovery process into a tedious challenge. We describe Scaffold Hunter, an interactive software tool for the exploration and analysis of chemical compound databases. Scaffold Hunter allows to explore the chemical space spanned by a compound database, fosters intuitive recognition of complex structural and bioactivity relationships, and helps to identify interesting compound classes with a desired bioactivity. Thus, the tool supports chemists during the complex and time-consuming drug discovery process to gain additional knowledge and to focus on regions of interest, facilitating the search for promising drug candidates.
KeywordsScaffold tree Chemical space Chemical compound data Integrative visualization Interactive exploration
Unable to display preview. Download preview PDF.
- 1.IMI: Innovative Medicines Initiative 2nd Call, Knowledge Management – Open Pharmacological Space (2009)Google Scholar
- 2.OpenWetWare (2012), http://www.openwetware.org
- 6.Berthold, M.R., Cebron, N., Dill, F., Gabriel, T.R., Kötter, T., Meinl, T., Ohl, P., Sieb, C., Thiel, K., Wiswedel, B.: KNIME: The Konstanz Information Miner. In: Studies in Classification, Data Analysis, and Knowledge Organization, GfKL 2007 (2007)Google Scholar
- 7.Schuffenhauer, A., Varin, T.: Rule-Based Classification of Chemical Structures by Scaffold. Molecular Informatics 30, 646–664 (2011)Google Scholar
- 12.Wetzel, S., Wilk, W., Chammaa, S., Sperl, B., Roth, A.G., Yektaoglu, A., Renner, S., Berg, T., Arenz, C., Giannis, A., Oprea, T.I., Rauh, D., Kaiser, M., Waldmann, H.: A Scaffold-Tree-Merging Strategy for Prospective Bioactivity Annotation of γ-Pyrones. Angew. Chem. Int. Ed. 49, 3666–3670 (2010)CrossRefGoogle Scholar
- 15.Downs, G.M., Barnard, J.M.: Clustering Methods and Their Uses in Computational Chemistry, pp. 1–40. John Wiley & Sons, Inc. (2003)Google Scholar
- 17.JChemPaint chemical 2D structure editor (2012), http://jchempaint.github.com
- 18.Klein, K., Kriege, N., Mutzel, P.: CT-Index: Fingerprint-based Graph Indexing Combining Cycles and Trees. In: IEEE 27th International Conference on Data Engineering (ICDE), pp. 1115–1126 (2011)Google Scholar
- 20.The Open Graph Drawing Framework (2012), http://www.ogdf.net