Efficient GPCR Drug Discovery by combining Novel Cell-Based Kinetic Assays with Systems Biology

Sensor technology

InterAx created a unique, scalable and efficient drug discovery platform that enables the development of better lead molecules with significantly improved safety profiles. This allows for high quality prediction of potential therapeutic effect(s) of novel drug molecules.

The novelty of our discovery platform lies in the combination of cell-based real-time assays including patented arrestin biosensors with our proprietary computational biology approaches leading to a highly efficient and fast delivery of functionally optimized compounds.

Virtual Screening

Virtual screening focuses on the design of novel compounds with highly tailored pharmacological properties. More precisely, we employ docking studies leveraging the known structure of a GPCR target and databases of compounds to identify new compounds binding the desired receptor.

Kinetic Binding and Signaling Assays

The experimental assays in house cover the most common aspects of GPCR activation and signaling. These assays include: i) Equilibrium and kinetic ligand binding assays; ii) G protein pathway signaling assays; iii) Arrestin recruitment assays using custom-designed (patented) arrestin biosensors; iv) Receptor internalization and recycling assays. All assays are designed to deliver time-resolved kinetic data and are based on fluorescence assay principles for medium to high throughput compound screening.

Novel Arrestin Biosensors

Arrestin engineering allows to create more stable GPCR-arrestin complexes which make yet undruggable targets addressable, e.g. through stabilizing solubilized GPCRs for X ray crystallography or cryo-EM studies.

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Systems Biology

Systems Biology is a technology that allows for a holistic mathematical model describing all potential signaling pathways activated by a given GPCR independent of the cellular background it is expressed in. The signaling patterns elicited by an activated GPCR consist of a very complex system of multifactorial parameters, such as differences in time scales, enzyme kinetics and/or sub-cellular localization changes of effector proteins. Moreover, the composition and expression levels of proteins in cell lines (e.g. those used for in vitro screening assays) often differ dramatically from the target tissues in humans. This complexity makes it extremely difficult to predict the in vivo efficacies and potencies of a new compound from the parameters derived in the in vitro assays.

Systems biology addresses this complexity and closes the current gap between in vitro and in vivo correlation. It allows to determine the most important nodes in the signaling network and thereby helps to identify the most critical properties a novel drug candidate needs to possess in order to elicit the desired cellular response.
Using our proprietary network model, we will be able to mimic the composition of target tissues (e.g. by mathematically varying protein expression levels, enzyme kinetic parameters) and thereby predict responses of a novel drug candidate in vivo.

Systems Biology

Selection of Key Publications

  1. Roed, S.N., Wismann P., Underwood C.R., Kulahin N., Iversen H., Cappelen K.A., Schäffer L., Lehtonen J., Hecksher-Soerensen J., Secher A., Mathiesen J.M., Bräuner-Osborne H., Whistler J.L., Knudsen S.M., Waldhoer M. (2014). Real-time trafficking and signaling of the glucagon-like peptide-1 receptor. Mol Cell Endocrinol., 8.

  2. Heitzler, D., Durand, G., Gallay, N., Rizk, A., Ahn, S., Kim, J., et al. (2012). Competing G protein-coupled receptor kinases balance G protein and beta-arrestin signaling. Molecular Systems Biology, 8.

  3. Ostermaier, M. K., Peterhans, C., Jaussi, R., Deupi, X., & Standfuss, J. (2014). Functional map of arrestin-1 at single amino acid resolution. Proceedings of the National Academy of Sciences of the United States of America, 111(5), 1825–1830.

  4. Ostermaier, M. K., Schertler, G. F. X., & Standfuss, J. (2014). Molecular mechanism of phosphorylation-dependent arrestin activation. Current Opinion in Structural Biology, 29, 143–151.

  5. Ostermaier, M. K., Schertler, G. F. X., & Standfuss, J. Method for determining mutateable ligand-gpcr binding at single amino acid resolution and pairs of mutated ligand and GPCR. EP13171505.4, Priority date: June 2013, published Dec. 2014

  6. Rizk, A., Mansouri, M., Ballmer-Hofer, K., & Berger, P. (2015). Subcellular object quantification with Squassh3C and SquasshAnalyst. Biotechniques, 59(5), 309–312.

  7. Rizk, A., Paul, G., Incardona, P., Bugarski, M., Mansouri, M., Niemann, A., et al. (2014). Segmentation and quantification of subcellular structures in fluorescence microscopy images using Squassh. Nature Protocols, 9(3), 586–596.

  8. Singhal, A., Ostermaier, M. K., Vishnivetskiy, S. A., Panneels, V., Homan, K. T., Tesmer, J. J. G., et al. (2013). Insights into congenital stationary night blindness based on the structure of G90D rhodopsin. Embo Reports, 14(6), 520–526.

  9. Vishnivetskiy, S. A., Ostermaier, M. K., Singhal, A., Panneels, V., Homan, K. T., Glukhova, A., et al. (2013). Constitutively active rhodopsin mutants causing night blindness are effectively phosphorylated by GRKs but differ in arrestin-1 binding. Cellular Signalling, 25(11), 2155–2162.