Structural basis of TRPC4 regulation by calmodulin and pharmacological agents
- Max Planck Institute of Molecular Physiology, Germany
- Julius-Maximilians-Universität Würzburg, Germany
- Max Planck Institute for Molecular Physiology, Germany
- Goldfinch Bio Inc, United States
Abstract
Canonical transient receptor potential channels (TRPC) are involved in receptor-operated and/or store-operated Ca2+ signaling. Inhibition of TRPCs by small molecules was shown to be promising in treating renal diseases. In cells, the channels are regulated by calmodulin. Molecular details of both calmodulin and drug binding have remained elusive so far. Here we report structures of TRPC4 in complex with three pyridazinone-based inhibitors and calmodulin. The structures reveal that all the inhibitors bind to the same cavity of the voltage-sensing-like domain and allow us to describe how structural changes from the ligand binding site can be transmitted to the central ion-conducting pore of TRPC4. Calmodulin binds to the rib helix of TRPC4, which results in the ordering of a previously disordered region, fixing the channel in its closed conformation. This represents a novel calmodulin-induced regulatory mechanism of canonical TRP channels.
Data availability
The atomic coordinates and cryo-EM maps for TRPC4DR in complex with inhibitors, calmodulin and for TRPC4DR in LMNG are available at the Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) databases, under the accession numbers PBD 7B0S and EMD-11970 (TRPC4-GFB8438), PBD 7B16 and EMD-11979 (TRPC4-GFB9289); PBD 7B05 and EMD-11957 (TRPC4-GFB8749); PBD 7B1G and EMD-11985 (TRPC4-Calmodulin) and PBD 7B0J and EMD-11968 (TRPC4-apo in LMNG).
Article and author information
Author details
Funding
Max-Planck-Gesellschaft
- Stefan Raunser
Deutsche Forschungsgemeinschaft (TR240)
- Georg Nagel
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, Vinayagam et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Structural basis of TRPC4 regulation by calmodulin and pharmacological agents
eLife 9:e60603.
https://doi.org/10.7554/eLife.60603
Further reading
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- Structural Biology and Molecular Biophysics
In eukaryotes, RNAs transcribed by RNA Pol II are modified at the 5′ end with a 7-methylguanosine (m7G) cap, which is recognized by the nuclear cap binding complex (CBC). The CBC plays multiple important roles in mRNA metabolism, including transcription, splicing, polyadenylation, and export. It promotes mRNA export through direct interaction with a key mRNA export factor, ALYREF, which in turn links the TRanscription and EXport (TREX) complex to the 5′ end of mRNA. However, the molecular mechanism for CBC-mediated recruitment of the mRNA export machinery is not well understood. Here, we present the first structure of the CBC in complex with an mRNA export factor, ALYREF. The cryo-EM structure of CBC-ALYREF reveals that the RRM domain of ALYREF makes direct contact with both the NCBP1 and NCBP2 subunits of the CBC. Comparing CBC-ALYREF with other cellular complexes containing CBC and/or ALYREF components provides insights into the coordinated events during mRNA transcription, splicing, and export.
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Under physiological conditions, proteins continuously undergo structural fluctuations on different timescales. Some conformations are only sparsely populated, but still play a key role in protein function. Thus, meaningful structure–function frameworks must include structural ensembles rather than only the most populated protein conformations. To detail protein plasticity, modern structural biology combines complementary experimental and computational approaches. In this review, we survey available computational approaches that integrate sparse experimental data from electron paramagnetic resonance spectroscopy with molecular modeling techniques to derive all-atom structural models of rare protein conformations. We also propose strategies to increase the reliability and improve efficiency using deep learning approaches, thus advancing the field of integrative structural biology.
