Conifer metabolite pisiferic acid restores activity in human Kv1.2 potassium channels carrying pathogenic sequence variants

Sequence variants in KCNA2, the gene encoding voltage-gated potassium channel Kv1.2, cause epilepsy, intellectual disability, and movement disorders. Drugs that directly correct mutant Kv1.2 function are lacking.  Kv1.2 downregulation is also implicated in pain and amyotrophic lateral sclerosis (ALS). We recently found that the abietane diterpenoid pisiferic acid (PA) from conifer Chamaecyparis pisifera beneficially restores activity in pathogenic loss-of-function (LOF)-variant Kv1.1 channels.  Here, using cellular electrophysiology, we classified 19 human Kv1.2 gene variants (pathogenic or of unknown significance) into LOF, gain of function (GOF), or mixed LOF/GOF. By hyperpolarizing their voltage dependence of activation, PA improved function in 13/13 LOF and 1/1 LOF/GOF pathogenic Kv1.2 variants tested, using cRNA ratios representative of autosomal dominant KCNA2 disorders. In silico docking, mutagenesis, and electrophysiology identified a PA binding site in the Kv1.2 voltage sensor.  Given its in vitro efficacy and low preclinical toxicity, PA is a promising lead compound for Kv1.2 LOF disorders.

Methods
Channel subunit cRNA preparation and Xenopus laevis oocyte injection

Wild-type Kv1.1 and wild-type and mutant Kv1.2 cDNAs were generated (Genscript, Piscataway, NJ) in the pMAX and pTLNx expression vectors.  As previously described, we generated cRNA transcripts encoding human Kv1.2 (wild-type and mutant) by in vitro transcription using the mMessage mMachine kit (Thermo Fisher Scientific), after vector linearization, from cDNA subcloned into plasmids (pMAX) incorporating Xenopus laevis β-globin 5’ and 3’ UTRs flanking the coding region to enhance translation and cRNA stability.  We injected defolliculated stage V and VI Xenopus laevis oocytes (Xenoocyte, Dexter, MI, US) with Kv1 cRNAs (0.1-10 ng). We incubated the oocytes at 16 oC in ND96 oocyte storage solution containing penicillin and streptomycin, with daily washing, for 1-2 days prior to two-electrode voltage-clamp (TEVC) recording.

Two-electrode voltage clamp (TEVC)

We performed TEVC at room temperature using an OC-725C amplifier (Warner Instruments, Hamden, CT) and pClamp10 software (Molecular Devices, Sunnyvale, CA) 2 days after cRNA injection as described in the section above and as before. For recording, oocytes we placed in a small-volume oocyte bath (Warner) and viewed with a dissection microscope.  We sourced chemicals from Combi Blocks. We studied the effects of pisiferic acid, which was solubilized in DMSO at a stock concentration of 250 mM before being diluted to 12 µM in bath solution (in mM): 96 NaCl, 4 KCl, 1 MgCl2, 1 CaCl2, 10 HEPES (pH 7.6).  We introduced pisiferic acid into the oocyte recording bath by gravity perfusion at a constant flow of 1 ml per minute for 3 minutes prior to recording.  Pipettes were of 1-2 MΩ resistance when filled with 3 M KCl.  We recorded currents in response to voltage pulses between -80 mV and +40 mV at 10 mV intervals from a holding potential of -80 mV, to yield current-voltage relationships and examine activation kinetics. To calculate the voltage dependence of activation (V0.5), tail currents were recorded at a voltage pulse of -40 mV immediately following prepulse voltages between -80 mV and +40 mV. We analyzed data using Clampfit (Molecular Devices) and Graphpad Prism software (GraphPad, San Diego, CA, USA), stating values as mean ± SEM. We plotted raw or normalized tail currents versus prepulse voltage and fitted them with a single Boltzmann function. To calculate the voltage dependence of inactivation, we recorded currents in response to 15-second pulses from -100 mV to + 40 mV in 10 mV increments, followed by a 100-ms pulse to +40 mV, from a holding potential of -80 mV. The current magnitude was measured from the 100-ms pulse to +40 mV, where all values were then normalized to the peak current.

In silico docking

For in silico ligand docking predictions of pisiferic acid binding to Kv1.2, we performed unguided docking to predict potential binding sites, using SwissDock with CHARMM force fields. We used AlphaFold to generate a predicted structure for Kv1.2. We prepared the channel structure for docking using DockPrep in UCSF Chimera https://www.rbvi.ucsf.edu/chimera), with which we also generated docking figures.

Statistics and Reproducibility

All values are expressed as mean ± SEM.  Multiple comparison statistics were conducted using a One-way ANOVA with a post-hoc Tukey HSD. Comparison of the two groups was conducted using a t-test; all p values were two-sided.

Schematics

The schematic in Figure 1a was generated using Biorender.com.