Efficient GPCR Lead Discovery by Combining Novel Biosensors with Computational Biology.

Mutated arrestins as novel biosensors

Drugs bind to biological targets, such as GPCRs, and initialize specific cellular signaling leading to beneficial effects, adverse effects or mixtures thereof, finally determining patients’ health. The cellular response is tied to the specific state that the GPCR adopts upon drug binding [1]. Current technologies allow the detection of only two GPCR states in high-throughput, one that initiates G-protein binding and one that leads to arrestin-recruitment.

However, the arrestin-bound state exists in multiple sub-states, which eventually determine receptor signaling. At present, these sub-states cannot be discriminated in high throughput drug-screening campaigns. InterAx allows to discriminate amongst these sub-states through the use of arrestin mutants binding specific arrestin-recruiting states of the receptor [2,3,4].

The pharmacological importance of the arrestin-specific sub-states has been demonstrated for various indications such as cardiovascular, ocular, oncological, immunological diseases and others [7,8].

Sensor technology

Whereas current sensors can only discriminate between inactive and active states with respect to arrestin recruitment, InterAx sensors can also differentiate among active substates.

In addition to deciphering GPCR sub-states, arrestin engineering allows to create more stable GPCR-arrestin complexes which make yet undruggable targets addressable.

The following figure shows the increase in binding strength of arrestin mutants.

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State of the art image analysis

InterAx combines its arrestin mutants with state of the art automated fluorescence microscopy analysis to provide a complete solution for microscopy based drug screening. Image analysis is performed with Squassh [5] and Squassh analyst [6], tools for the segmentation, quantification and analysis of subcellular objects.

The figure below shows the advantage of using Squassh compared to pixel based colocalization analysis (such as Pearson correlation). It displays the colocalization quantification of a subcellular marker for lysosomes with negative (RAB5, 4, 11) and positive (RAB7) controls.

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  1. 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.

  2. 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.

  3. 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.

  4. 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

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

  6. 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.

  7. 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.

  8. 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.