High-Throughput Screening of Na(V)1.7 Modulators Using a Giga-Seal Automated Patch Clamp Instrument.

Abstract

Voltage-gated sodium (Na(V)) channels have an essential role in the initiation and propagation of action potentials in excitable cells, such as neurons. Of these channels, Na(V)1.7 has been indicated as a key channel for pain sensation. While extensive efforts have gone into discovering novel Na(V)1.7 modulating compounds for the treatment of pain, none has reached the market yet. In the last two years, new compound screening technologies have been introduced, which may speed up the discovery of such compounds. The Sophion Qube(®) is a next-generation 384-well giga-seal automated patch clamp (APC) screening instrument, capable of testing thousands of compounds per day. By combining high-throughput screening and follow-up compound testing on the same APC platform, it should be possible to accelerate the hit-to-lead stage of ion channel drug discovery and help identify the most interesting compounds faster. Following a period of instrument beta-testing, a Na(V)1.7 high-throughput screen was run with two Pfizer plate-based compound subsets. In total, data were generated for 158,000 compounds at a median success rate of 83%, which can be considered high in APC screening. In parallel, IC50 assay validation and protocol optimization was completed with a set of reference compounds to understand how the IC50 potencies generated on the Qube correlate with data generated on the more established Sophion QPatch(®) APC platform. In summary, the results presented here demonstrate that the Qube provides a comparable but much faster approach to study Na(V)1.7 in a robust and reliable APC assay for compound screening.

DOI: 10.1089/adt.2016.700

Cite this paper

@article{Chambers2016HighThroughputSO, title={High-Throughput Screening of Na(V)1.7 Modulators Using a Giga-Seal Automated Patch Clamp Instrument.}, author={Chris Chambers and Ian Witton and Cathryn Adams and Luke Marrington and Juha Kammonen}, journal={Assay and drug development technologies}, year={2016}, volume={14 2}, pages={93-108} }