Article: Development of ASIC1a ligand-gated ion channel drug screening assays across multiple automated patch clamp platforms.
Frontiers in molecular neuroscience
2022 Volume 15, Page(s) 982689
Abstract: Human acid-sensing ion channels (ASIC) are ligand-gated ionotropic receptors expressed widely in peripheral tissues as well as sensory and central neurons and implicated in detection of inflammation, tissue injury, and hypoxia-induced acidosis. This ... ...
| Abstract | Human acid-sensing ion channels (ASIC) are ligand-gated ionotropic receptors expressed widely in peripheral tissues as well as sensory and central neurons and implicated in detection of inflammation, tissue injury, and hypoxia-induced acidosis. This makes ASIC channels promising targets for drug discovery in oncology, pain and ischemia, and several modulators have progressed into clinical trials. We describe the use of hASIC1a as a case study for the development and validation of low, medium and high throughput automated patch clamp (APC) assays suitable for the screening and mechanistic profiling of new ligands for this important class of ligand-gated ion channel. Initial efforts to expand on previous manual patch work describing an endogenous hASIC1a response in HEK cells were thwarted by low current expression and unusual pharmacology, so subsequent work utilized stable hASIC1a CHO cell lines. Ligand-gated application protocols and screening assays on the Patchliner, QPatch 48, and SyncroPatch 384 were optimized and validated based on pH activation and nM-μM potency of reference antagonists (e.g., Amiloride, Benzamil, Memantine, Mambalgin-3, A-317567, PcTx1). By optimizing single and stacked pipette tip applications available on each APC platform, stable pH-evoked currents during multiple ligand applications enabled cumulative EC |
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| Language | English |
| Publishing date | 2022-10-19 |
| Publishing country | Switzerland |
| Document type | Journal Article |
| ZDB-ID | 2452967-9 |
| ISSN | 1662-5099 |
| ISSN | 1662-5099 |
| DOI | 10.3389/fnmol.2022.982689 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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