Figure 1: Schematic showing the use of intracellular thallium-sensitive dye to measure ion conduction through potassium channels as a screening assay to measure the effects of modulator compounds.

Figure 2: Schematic illustrating an automated patch clamp ‘chip’ well where cells are flowed over holes in a borosilicate substrate to obtain whole-cell access and enable patch clamp recordings of ion channel activity, and the effects of compounds added to each well (yellow).

Compound testing

• Dose response curves were prepared using either an acoustic (ECHO, Labcyte) or a tip-based (Biomek FX, Beckman Coulter) dispenser. Compounds were run in Tl⁺ flux assays with a 30 minute pre-incubation. Rate (15-28s) denotes the rate of Tl⁺ flux. (Data represent mean ± SD, n=2).

• A subset of compounds displayed a reduction in the magnitude of the response when they were handled on the acoustic dispenser, demonstrating that the liquid handling method can influence the response in Tl⁺ flux.

Automated and Manual Patch-clamp

• Whole-cell, perforated-cell QPatch and whole-cell manual patch-clamp data for LA-05 and LA-06. (Data represent mean ± SEM, n≥1).

• Whole-cell and perforated-cell APC methods produce comparable results for both active and inactive compounds. Manual whole-cell patch-clamp (the gold standard patch-clamp technique), confirmed APC potency and efficacy data for active compounds.

Correlation Between Tl⁺ flux and APC

Figure 5: Comparison of K2P hit compound activity obtained by thallium flux HTS assay with hit validation activity from an APC (QPatch) platform.

• 173 compounds identified as ‘hits’ in a Tl⁺ flux screen of 100K compounds were screened in APC (QPatch).

• Plot shows correlation between Tl⁺ flux and APC data, coloured by activity in APC.

• Tl⁺ flux data represents fold-stimulation relative to DMSO control. APC data represents percentage of maximal channel activation.

• Compounds with the highest activity in Tl⁺ flux were the most likely to confirm in APC, but the correlation was not entirely uniform.

Figure 6: Correlation between thallium flux and APC hit compound activity is strongest for the most active compounds (bins 1-2) and for less active compounds pre-incubated in the thallium flux assay (green bars).

• Compounds were screened in Tl⁺ flux, with either a 30 minute (t=30) or no (t=0) pre-incubation.

• Compounds were then binned based on Tl⁺ flux activity; Bin 1 highest activity to Bin 5 lowest activity.

• For each bin, the percentage of compounds which were active in APC was then calculated.

• Data confirmed that compounds with the highest activity in Tl⁺ flux were the most likely to be active in APC.

• A subset of compounds showed higher activity at t=30 compared to t=0.

Compound Incubation Time

• Compounds were screened in dose response format in the Tl⁺ flux assay with either a 30 minute (t=30), a 15 minute (t=15) or no pre-incubation (t=0). Rate (15-28s) denotes the rate of Tl⁺ flux. (Data represent mean ± SD, n=2). * denotes compounds which were active in APC.

• A subset of compounds displayed a marked time dependency in the magnitude of their response. The magnitude of the response at t=0 may be indicative of the response in APC for some compounds.

Compound Properties

• Correlation between Tl⁺ flux and APC data, coloured by ACDlogP (left) or CNSMPO (right). ACDlogP is a measure of lipophilicity and CNSMPO a score for predicted CNS penetration.

• Neither metric could adequately explain the correlation between the two systems, but phys-chem properties of individual compounds may contribute to differential responses in the two systems.