Structure-based characterization of novel TRPV5 inhibitors
Abstract
Transient receptor potential vanilloid 5 (TRPV5) is a highly calcium selective ion channel that acts as the rate-limiting step of calcium reabsorption in the kidney. The lack of potent, specific modulators of TRPV5 has limited the ability to probe the contribution of TRPV5 in disease phenotypes such as hypercalcemia and nephrolithiasis. Here, we performed structure-based virtual screening (SBVS) at a previously identified TRPV5 inhibitor binding site coupled with electrophysiology screening and identified three novel inhibitors of TRPV5, one of which exhibits high affinity, and specificity for TRPV5 over other TRP channels, including its close homologue TRPV6. Cryo-electron microscopy of TRPV5 in the presence of the specific inhibitor and its parent compound revealed novel binding sites for this channel. Structural and functional analysis have allowed us to suggest a mechanism of action for the selective inhibition of TRPV5 and lay the groundwork for rational design of new classes of TRPV5 modulators.
Data availability
The cryo-EM density maps and atomic coordinates of all structures presented in the text will be deposited into the Electron Microscopy Data Bank and Protein Data Bank under the following access codes: ZINC9155420-bound TRPV5 (PDB: 6PBF, EMB-20292); ZINC17988990-bound TRPV5 (PDB: 6PBE, EMB-20291).
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ZINC9155420-bound TRPV5 in nanodiscsElectron Microscopy Data Bank, EMD-20292.
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ZINC17988990-bound TRPV5 in nanodiscsElectron Microscopy Data Bank, EMD-20291.
Article and author information
Author details
Funding
National Institute of General Medical Sciences (R01GM103899)
- Vera Y Moiseenkova-Bell
National Institute of General Medical Sciences (R01GM129357)
- Vera Y Moiseenkova-Bell
National Institute of General Medical Sciences (R01GM093290)
- Tibor Rohacs
National Institute of General Medical Sciences (R01GM131048)
- Tibor Rohacs
National Institute of Neurological Disorders and Stroke (R01NSNS055159)
- Tibor Rohacs
National Science Foundation (ACI-1053575)
- Marta Filizola
National Science Foundation (MCB080077)
- Marta Filizola
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Hughes 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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Further reading
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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.
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