Communications BiologyNeurosciencePeer-reviewed journal article
Identification of Druggable Binding Sites and Small Molecules as Modulators of TMC1
Pedro De‐la‐TorreiD, Claudia Martínez-GarcíaiD, Paul GratiasiD, Matthew MuniD, Paula SantanaiD, Nurunisa AkyuziD, Wendy GonzáleziD, Artur A. IndzhykulianiD, David RamíreziD
Abstract
Our ability to hear and maintain balance relies on the proper functioning of inner ear sensory hair cells, which translate mechanical stimuli into electrical signals via mechano-electrical transducer (MET) channels, composed of TMC1/2 proteins. However, the therapeutic use of ototoxic drugs, such as aminoglycosides and cisplatin, which can enter hair cells through MET channels, often leads to profound auditory and vestibular dysfunction. Despite extensive research on otoprotective compounds targeting MET channels, our understanding of how small-molecule modulators interact with these channels remains limited, hampering the discovery of novel drugs. Here, we propose a structure-based screening approach, integrating 3D-pharmacophore modeling, molecular dynamics simulations of the TMC1+CIB2+TMIE complex, and experimental validation. Our pipeline successfully identified several novel compounds and FDA-approved drugs that reduced dye uptake in cultured cochlear explants, indicating MET-modulation activity. Simulations, molecular docking and free-energy estimations allowed us to identify three potential drug-binding sites within the channel pore, phospholipids, key amino acids involved in modulator interactions, and TMIE as a flexible component of the MET complex. We also identified shared ligand-binding features between TMC and structurally related TMEM16 proteins, providing novel insights into their distinct inhibition. Our pipeline offers a broad application for discovering modulators for mechanosensitive ion channels.
- organism: human
- assay: protein structure
- research focus: drug response / drug discovery
- approach: statistical model
- approach: simulation
- Citations
- 3
- FWCI
- 1.27
- Field percentile
- top 25%
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