Pathway selectivity in Frizzleds is achieved by conserved micro-switches defining pathway-determining, active conformations
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The class Frizzled of G protein-coupled receptors (GPCRs), consisting of ten Frizzled (FZD1-10) paralogs and Smoothened, remains one of the most enigmatic GPCR families. This class mediates signaling predominantly through Disheveled (DVL) or heterotrimeric G proteins. However, the mechanisms underlying pathway selection are elusive. Here we employ a structure-driven mutagenesis approach in combination with an extensive panel of functional signaling readouts to investigate the importance of conserved state-stabilizing residues in FZD5 for signal specification. Similar data were obtained for FZD4 and FZD10 suggesting that our findings can be extrapolated to other members of the FZD family. Comparative molecular dynamics simulations of wild type and selected FZD5 mutants further support the concept that distinct conformational changes in FZDs specify the signal outcome. In conclusion, we find that FZD5 and FZDs in general prefer coupling to DVL rather than heterotrimeric G proteins and that distinct active state micro-switches in the receptor are essential for pathway selection arguing for conformational changes in the receptor protein defining transducer selectivity.
| Originalsprog | Engelsk |
|---|---|
| Artikelnummer | 4573 |
| Tidsskrift | Nature Communications |
| Vol/bind | 14 |
| Udgave nummer | 1 |
| Antal sider | 17 |
| ISSN | 2041-1723 |
| DOI | |
| Status | Udgivet - 2023 |
Bibliografisk note
Funding Information:
The authors thank Benoit Vanhollebeke for the ΔFZD HEK293 cells and Thomas Sakmar for the synthetic FZD. Thanks to Hannes Schihada, who was essential in the initial phase of the project conceptualization, and Ainoleena Turku for comments on the manuscript. The work was supported by grants from Karolinska Institutet, the Swedish Research Council (G.S.: 2019-01190), the Swedish Cancer Society (G.S.: 20 1102 PjF; P.K.: 20 0264P), the Novo Nordisk Foundation (G.S.: NNF20OC0063168, NNF21OC0070008, NFF22OC0078104), The Wenner-Gren Foundations (J.B.: UDP2021-0029), The German Research Foundation (L.G.: 504098926; M.K.J.: KO 5463/1-1, M.M.S.: 470002134). This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 875510. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA and Ontario Institute for Cancer Research, Royal Institution for the Advancement of Learning McGill University, Kungliga Tekniska Hőgskolan, Diamond Light Source Limited. The computations were enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS) and the Swedish National Infrastructure for Computing (SNIC) at National Supercomputer Centre (NSC) in Linköping and KTH Royal Institute of Technology (PDC) in Stockholm (G.S.: SNIC 2021/5-490, M.M.S.: SNIC 2022/22-558) partially funded by the Swedish Research Council through grant agreements no. 2022-06725 and no. 2018-05973. D.E.G. acknowledges funding from the Novo Nordisk Foundation (NNF18OC0031226) and Lundbeck Foundation (R313-2019-526). D.E.G., G.S., and M.M.S. are members of the COST Action ERNEST (CA18133), supported by COST (European Cooperation in Science and Technology, www.cost.eu ). 1-10 5
Funding Information:
The authors thank Benoit Vanhollebeke for the ΔFZD1-10 HEK293 cells and Thomas Sakmar for the synthetic FZD5. Thanks to Hannes Schihada, who was essential in the initial phase of the project conceptualization, and Ainoleena Turku for comments on the manuscript. The work was supported by grants from Karolinska Institutet, the Swedish Research Council (G.S.: 2019-01190), the Swedish Cancer Society (G.S.: 20 1102 PjF; P.K.: 20 0264P), the Novo Nordisk Foundation (G.S.: NNF20OC0063168, NNF21OC0070008, NFF22OC0078104), The Wenner-Gren Foundations (J.B.: UDP2021-0029), The German Research Foundation (L.G.: 504098926; M.K.J.: KO 5463/1-1, M.M.S.: 470002134). This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 875510. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA and Ontario Institute for Cancer Research, Royal Institution for the Advancement of Learning McGill University, Kungliga Tekniska Hőgskolan, Diamond Light Source Limited. The computations were enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS) and the Swedish National Infrastructure for Computing (SNIC) at National Supercomputer Centre (NSC) in Linköping and KTH Royal Institute of Technology (PDC) in Stockholm (G.S.: SNIC 2021/5-490, M.M.S.: SNIC 2022/22-558) partially funded by the Swedish Research Council through grant agreements no. 2022-06725 and no. 2018-05973. D.E.G. acknowledges funding from the Novo Nordisk Foundation (NNF18OC0031226) and Lundbeck Foundation (R313-2019-526). D.E.G., G.S., and M.M.S. are members of the COST Action ERNEST (CA18133), supported by COST (European Cooperation in Science and Technology, www.cost.eu).
Publisher Copyright:
© 2023, The Author(s).
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