Synthetic cannabinoid receptor agonists inhibit the cardiac voltage-gated potassium channel hERG
Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
Chemical Biology Consortium Sweden, Science for Life Laboratories, Linköping University, Linköping, Sweden
School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore
Department of Forensic Genetics and Forensic Toxicology, National Board of Forensic Medicine, Linköping, Sweden
#Indicates corresponding authors: T.P.: tanadet.pipatpolkai@ntu.edu.sg, S.I.L.: sara.liin@liu.seAbstract
Synthetic cannabinoid receptor agonists (SCRAs) is a large group of structurally diverse designer drugs (analogues of controlled substances) associated with intense and sometimes fatal intoxication. Cardiac symptoms including tachycardia and arrhythmia are common consequences of SCRA consumption. However, little is known about the mechanisms through which SCRAs may perturb cardiac rhythm. Here we used electrophysiological techniques to screen 36 SCRAs on two ion channels responsible for cardiomyocyte repolarization, hERG (also called KV11.1) and KV7.1/KCNE1. We report that the majority of tested SCRAs inhibited hERG, primarily by reducing channel conductance, and some also inhibited KV7.1/KCNE1. In silico data suggests that SCRAs use a known drug binding site in the pore of the hERG channel, shared by established hERG blockers like astemizole, where a planar SCRA molecule lays perpendicular to the ion conducting pathway. Experimental and in silico data identify SCRA structural features associated with prominent inhibitory effects on hERG, with chemical moieties allowing bond formation and/or the ability to fit into the vestibule being important. Structure-activity-relationships for SCRA effects on hERG, KV7.1/KCNE1 and the cannabinoid receptor 1 (CB1) varied, demonstrating the importance of assessing SCRA effects on multiple potential targets. In conclusion, we found SCRAs to be inhibitors of cardiac voltage-gated potassium channels important for cardiomyocyte repolarization. These results offer mechanistic insight into potentially detrimental SCRA effects on the heart and highlight the urgency of more extensive investigation of SCRAs on cardiac function.
Article notes
Competing Interest Statement
The authors have declared no competing interest.
Introduction
Synthetic cannabinoid receptor agonists (SCRAs, exemplified by JWH-018 in Fig. 1A), commonly known as “spice” or “K2”, is a large class of new psychoactive substances (NPS) designed to mimic the effects of Δ9-tetrahydrocannabinol (Δ9-THC) (Fig. 1B), the main psychoactive component of cannabis 1. The SCRAs available on the recreational drug market is constantly changing with new compounds emerging each year to circumvent national and international legislation, posing international threats and challenges to the communities. For newly emerging SCRAs, chemical modifications may be seen at the core, tail, head (also known as linked group), or linker of the SCRA molecule (Fig. 1C). As of 2025, 277 different SCRAs have been reported to the European Union early warning system, and it is the largest group of NPS being monitored by the European Union Drug Agency (EUDA) 2.
SCRAs have been estimated to be used by 0.2-4% of the population 3 with much higher use reported in prisons 4, rough-sleeping populations 5, and populations with regular drug testing, including the military 6 and people on probation/parole 7. SCRAs are often smoked as infused herbal material or vaped as infused e-cigarette oils 8. There have also been many reports of the addition of SCRAs to cannabis products on the market 9,10 and SCRAs found in drug samples sold as opioids or benzodiazepines 11, meaning people who use SCRAs are often unaware of the actual SCRAs they are using or may not even know they are using SCRAs.
The high variability of the market and lack of pharmacological data of newly emerging drugs significantly increases the risk of harms. SCRAs are typically full agonists of the cannabinoid 1 (CB1) receptor, the receptor responsible for the psychoactivity of cannabis, whereas Δ9-THC is only a partial agonist 1. SCRAs are often significantly more potent on the CB1 receptor than Δ9-THC (exemplified by JWH-018 in Fig. 1D) and have many adverse effects reminiscent of psychostimulants rather than cannabis, including psychosis, seizures, and cardiac arrhythmia 12. Cardiovascular-related complications of SCRAs are the most common symptoms presented at accident and emergency departments 13,14 and common causes of death 15–17. For instance, 5F-MDMB-PINACA (Fig. 1E, also known as 5F-ADB), has been implicated in several fatal intoxications 18–20 and linked to cardiac symptoms 21. Thus, there is a substantial body of evidence linking SCRA intoxication to potentially fatal cardiac arrhythmias 22, with QT prolongation on the electrocardiogram (ECG) reported in several studies e.g., 23,24,25.
Despite frequent reports associating SCRA intoxication with arrhythmias, little is known about how SCRAs cause these adverse effects on a mechanistic level 22. As cardiac arrhythmias are electrophysiological disorders, cardiac ion channels may be implicated. As the first example supporting this, an electrophysiological study reported that JWH-030 (Fig. 1F) inhibits the voltage-gated potassium channel hERG (KV11.1) and prolongs the QT interval in rats 26. Moreover, a recent integrative computational and electrophysiological study show that 5F-APINACA (also called 5F-AKB48) and ADB-FUBIATA inhibit hERG and find a side pocket lateral to the central cavity for these two SCRAs 27. Another study used machine learning models to propose hERG binding of several SCRAs, though no electrophysiological experiments were conducted to confirm the predictions 28. These three studies provide the first indication on the interaction between SCRAs and hERG, highlighting the importance of more extensive studies.
The hERG channel, together with the KV7.1/KCNE1 channel, is responsible for phase 3 repolarization of the action potential in ventricular cardiomyocytes: hERG carrying the rapidly activating delayed rectifier current IKr, whereas KV7.1/KCNE1 carries the slowly activating delayed rectifier current IKs (Fig. 1G). Impaired function of hERG or KV7.1/KCNE1 can lead to a prolonged action potential duration (indicated in red in Fig. 1G), early afterdepolarizations and arrhythmic beats 29,30. This is observed in ventricular arrhythmias such as Torsades de Pointes, a life-threatening polymorphic tachycardia that is a consequence of both drug-induced Long QT Syndrome (LQTS) following hERG channel blockade and as congenital LQTS caused by deleterious mutations in the genes encoding hERG and KV7.1/KCNE1 29,30. However, whether SCRAs other than JWH-030, 5F-APINACA, and ADB-FUBIATA inhibit hERG remains unclear. In addition, the underlying mechanisms of action for most SCRAs and their putative compounding proarrhythmic effects on KV7.1/KCNE1 are unknown. This lack of understanding limits risk stratification of SCRAs, medical treatment protocols, and harm-reducing actions, such as implementing legislative controls. Thus, our study aims to address this gap in knowledge by determining the effects and mechanisms of a broad set of SCRAs on hERG and KV7.1/KCNE1 channels.
Results
SCRAs inhibit the hERG channel by reducing channel conductance
To assess the effect of a large set of SCRAs on hERG (see SI Table I and SI Figure S1 for a list of the 36 included SCRAs and corresponding structures), we used the automated planar patch-clamp (APC) technique on mammalian Chinese hamster ovary (CHO) cells stably expressing human hERG. All 36 SCRAs were evaluated in concentration-response experiments using concentrations ranging from 1.11 to 30 µM (also lower concentrations were tested for potent compounds). We employed a voltage-ladder protocol to obtain information on SCRA effects on the channel’s voltage dependence of activation (V50) and maximal conductance (Gₘₐₓ) (both determined from Boltzmann fits of the instantaneous tail currents; see Methods for details). SCRA efficacy (e.g. maximal reduction in Gₘₐₓ) and potency (SCRA concentration required to produce 50% of the compound’s maximal effect; IC50) were determined (see Methods for details). In line with previous reports, JWH-030 inhibited hERG (Fig. 1H-I), seen in our assay as a concentration-dependent decrease in Gₘₐₓ (Fig. 1J, IC50 = 23.0 ± 11.8 µM) and a small effect on V50 (Fig. 1K). Among the tested compounds, 5F-MDMB-PINACA was one of the more potent inhibitors, reducing Gₘₐx of hERG at lower concentrations than JWH-030 (Fig. 1J-M, IC50 = 9.5 ± 2.5 µM).
A more detailed electrophysiological characterization of the effects of 5F-MDMB-PINACA on hERG is provided in the Supplementary Information (SI Text, SI Fig. S2). Briefly, the compound’s inhibitory effect on hERG was not dependent on temperature or the presence of intracellular fluoride. However, 5F-MDMB-PINACA potency was enhanced in the presence of pluronic acid, likely due to improved availability of the lipophilic 5F-MDMB-PINACA compound. Furthermore, the inhibitory potency was greater in manual patch-clamp (MPC) recordings using adherent cells, whereas recordings from cells in suspension, used both in APC and MPC, yielded similar results. These data highlight the robustness of the 5F-MDMB-PINACA effect under different experimental APC conditions and indicate that our hERG APC assay, if anything, tends to underestimate the potency of SCRAs.
Most SCRAs displayed inhibitory effects on hERG, primarily in the form of decreased Gₘₐₓ (see SI Fig. S3 for concentration-response data and SI Table II for efficacy and potency). For several compounds, the concentration-response curves did not saturate at the highest concentration tested (SI Fig. S3), resulting in suboptimal curve fitting with unreliable efficacy and potency estimates. We therefore compared the effects of the 36 SCRAs at 10 µM, a concentration that provided a consistent and representative estimate of the overall inhibitory effect on hERG. At 10 µM, 24 of the SCRAs significantly reduced Gₘₐₓ (Fig. 1N). In contrast, at 10 µM only 9 of the tested SCRAs induced a significant shift in V50 (Fig. 1O). Also, the magnitude of these V50 shifts was modest, with all ΔV50 confined within a narrow range of ± 7 mV. Hence, for the rest of the study we will focus on the Gₘₐₓ response of hERG to the SCRAs.
SCRA building block chemistry impacts SCRA inhibition of hERG
We noted that chemical modifications to the building blocks (Fig. 2A) of SCRAs impacted SCRA potency and/or efficacy on hERG (SI Table II). To explore whether broader structural features contribute to these effects we conducted a structure-activity relationship (SAR) analysis both for the efficacy (maximal reduction in Gₘₐₓ) and the potency (IC50) of SCRAs on hERG. Only SAR comparisons with at least three pairs of structurally related compounds were included to allow for robust statistical assessment. That the concentration-response curves saturated before full inhibition for several SCRAs (SI Table II, SI Fig. S3) suggested variability in efficacy across SCRAs. However, no consistent SAR patterns could be identified to account for these differences in efficacy (SI Table III-IV). For potency, SCRAs with an indole core were 1.5- to 6.3-fold more potent on hERG than the corresponding SCRAs with an indazole core (Fig. 2B-C, SI Table III). This is exemplified by MDMB-CHMICA vs MDMB-CHMINACA in Figure 2D. Of the different amino acid derived head moieties (Fig. 2E), valinamide (AB) SCRAs were the least potent in all three available comparisons, where tert-leucine methyl esters (MDMB) were 2.6- to 4.1-fold more potent and tert-leucinamides (ADB) were 1.6- to 4.5-fold more potent (Fig. 2F, SI Table IV). There was no difference in potency between MDMB and ADB SCRAs (Fig. 2F, SI Table IV). For tail moieties, no SAR analysis could be performed because of too few structurally related compounds available for comparison or the lack of effect of some compounds (SI Table II).
We also noted several interesting examples of how structural motifs clearly influenced the hERG inhibitory effects of SCRAs, although with too few structurally related compounds to be included in the SAR analysis. For instance, the 5F-PINACA scaffold with either a branched MDMB or aromatic cumyl head group induced concentration-dependent inhibitory effects, whereas the bulky adamantyl in 5F-APINACA impaired the inhibitory effect (Fig. 2G). As another example, a bulky tosyl group at the tail of the Cumyl-INACA scaffold caused Cumyl-TsINACA to be a non-inhibitor (Fig. 2H). Furthermore, addition of a terminal fluorine (5F-pentyl in 5F-BZO-POXIZID) or alkene (pent-4-enyl in BZO-4en-POXIZID) on the pentyl tail of the BZO-POXIZID scaffold produced concentration-dependent inhibitory effects, whereas a simple pentyl tail (in BZO-POXIZID) rendered this SCRA a non-inhibitor (Fig. 2I). As another example of tail chemistry, terminal fluorination of the pentyl tail on the UR-144 scaffold resulted in concentration-dependent inhibitory effects, whereas its non-fluorinated counterpart was a non-inhibitor (Fig. 2J). Similarly, 5F-APINACA showed inhibitory effects, whereas APINACA was a non-inhibitor (SI Table II).
Altogether, the screening of 36 SCRAs on the hERG channel demonstrates that specific structural elements markedly influence hERG inhibition. While some of these features are also reflected in the broader SAR analyses, others are not, underscoring the complexity of SCRA interactions with the hERG channel.
SCRAs are coordinated in a promiscuous central cavity binding site in hERG
hERG has a known, promiscuous binding site in the central cavity of the pore domain that is used by many inhibitors and blockers 31,32, including the histamine receptor antagonist and hERG blocker astemizole 32–34 (see also SI Figure S4 for inhibitory effect of astemizole in our hERG assay). This central cavity binding site is just below the selectivity filter and flanked by aromatic residues, like Y652 (schematic illustration in Fig. 3A). To assess whether SCRAs may interact with hERG in this vestibule binding site and predict the mode of interaction, we developed a novel computational pipeline using accelerated weighted histogram simulations, with astemizole as a positive control (SI Fig. S5). The work from the pipeline resulted in the binding poses of astemizole matching the recently solved cryo-EM density 35 with astemizole binding perpendicular to the ion conducting pathway in the vestibule binding site, about 5 Å above Y652 (Fig. 3B-C, SI Fig. S5). From this site, astemizole blocks hERG by preventing potassium ion permeation 35. We followed the same workflow for four SCRAs, two of which were inhibitors in our hERG assay (5F-MDMB-PINACA and 5F-BZO-POXIZID) and two of which failed to inhibit the channel (BZO-POXIZID and Cumyl-TsINACA). Like astemizole, the simulations with the inhibitors 5F-MDMB-PINACA and 5F-BZO-POXIZID found an energy minimum at 5 Å above Y652 (Fig. 3D-E). Given the time constraint in the AWH simulations, we could not achieve a converged free energy landscape. However, the poses clustered from the energy minima showed the SCRAs in the vestibule in a planar orientation perpendicular to the ion conduction pathway, sandwiched between Y652 and the selectivity filter (Fig. 3F-G for 5F-MDMB-PINACA and 5F-BZO-POXIZID, respectively, and Fig. 3H for a zoomed-out representation of 5F-MDMB-PINACA). This perpendicular conformation is very similar to that of astemizole, thus we propose that this prevents potassium ion permeation. We then took 1000 snapshots from the minima of the cluster to analyse key contacting residues, leading to: i) the identification of Y652 interacting with the SCRA core by pi-pi stacking; ii) S624 and S649 interacting with either the head or the tail of the SCRA, providing hydrogen bonds; and iii) F656 interacting with the alkyl tail by hydrophobic interaction, or defining the size of the head of the SCRAs that can be accommodated in the binding pocket (Fig. 3I). All snapshots from the minima showed the distribution being mostly unimodal, suggesting a very stable binding pose (Fig. 3J-K). Also for the non-inhibitor BZO-POXIZID we found an energy minimum at 5 Å above Y652 (Fig. 3L). However, while we identified a hydrogen bond between the hydroxyl group on S624 and/or S649 and the fluorine of the 5F-pentyl tails of 5F-MDMB-PINACA and 5F-BZO-POXIZID, these are absent for BZO-POXIZID and may explain why it is a non-inhibitor. Hence, although S624 and/or S649 remain in close proximity with the tail in BZO-POXIZID (Fig. 3M), they are unable to form any H-bonding, which is expected to result in a weaker affinity to the channel. Lastly, we sought insight into the structural basis of the non-inhibitor Cumyl-TsINACA. The free energy landscape from the simulations indicates that Cumyl-TsINACA does not show a minimum at 5 Å position (Fig. 3N). This placed both S624 and S649 out of the head binding pocket, misplaced the linker region and disrupted the interaction with the tail (Fig. 3O, with main lost interactions highlighted by *). Together, this suggested how Cumyl-TsINACA fail to block potassium ion permeation.
By mutating Y652 to alanine (Y652A), the proposed pi-stacking interaction between the compound’s core and the residue is disrupted. We compared the 5F-MDMB-PINACA effect on hERG wild type and the Y652A mutant. 5F-MDMB-PINACA was less potent on the Y652 mutant (Fig. 3P-R), as if Y652 is one of the residues involved in 5F-MDMB-PINACA binding or effects. However, despite the reduced potency, the 5F-MDMB-PINACA still exerts an inhibitory effect, likely due to preserved or compensatory interactions with other residues. The reduced potency of 5F-MDMB-PINACA induced by Y652A is in the range of that previously reported for the hERG inhibitor m-hydroxymexiletine 36, but smaller than that of hERG inhibitors like amiodarone and astemizole 37.
Altogether, we conclude that for SCRAs to assume a mode of hERG interaction in the central cavity preventing potassium ion permeation, we postulate two rules: (i) The head group and the tail must be small enough to fit in the binding pocket dictated by F656. A larger head group (e.g. adamantyl) or tail group (e.g. tosyl) would prevent the SCRA from binding properly, resulting in a shift in the position of the minima in the free energy landscape. (ii) Either the head group (MDMB or Cumyl) or the fluorinated tail must be able to form hydrogen bonds with S624 or S649. SCRAs with no tail, such as MDMB-5’Br-INACA or ADB-5’Br-INACA will result in a weaker interaction with the binding pocket. Given the limitation on the convergence of the free energy in the simulations, it is challenging to determine how the small differences between the indole and indazole cores impact the pi-stacking interaction with Y652. However, indazole has been shown to be less electron-rich than indole due to the additional p-orbital on the N atom 38. This may weaken the pi-stacking interactions with Y652.
Comparing SARs for SCRA effects on hERG and the CB1 receptor reveal similarities and differences
To explore the relationship between the potential cardiotoxic effects of SCRAs via hERG and their psychoactive effects mediated by the CB1 receptor, we assessed the activity of the 36 SCRAs on CB1 stably expressed in CHO-K1 cells using an AequoScreen® intracellular calcium release assay (see Methods for details; SI Fig. S6A for exemplary example of JWH-018). The compounds showed a wide range of potencies on CB1, with EC50 values spanning from sub-nanomolar (e.g., MDMB-FUBINACA) to low micromolar levels (e.g., BZO-HEXOXIZID) (Fig. 4A).
In contrast to the results on hERG, MDMB-CHMICA and MDMB-CHMINACA showed similar potency on CB1 (Fig. 4B-C, SI Table V). Moreover, no consistent pattern in CB1 potency was observed between compounds with indole or indazole cores (Fig. 4D). For the head moiety, a similar overall SAR was seen for CB1 receptor activity as for hERG, where tert-leucine methyl esters (MDMB) and tert-leucinamides (ADB) were consistently more potent than the corresponding valinamide (AB) head moiety (Fig. 4E, SI Table VI). Moreover, an adamantyl group (5F-APINACA) instead of a MDMB or cumyl group reduced the hERG inhibitory effect and also reduced the CB1 potency (SI Fig. S6B).
Similar to the results on hERG, replacing the fluorinated pentyl tail of 5F-Cumyl-PINACA with the tosyl tail of Cumyl-TsINACA reduced the potency at the CB1 receptor, shifting the EC50 from 1.8 nM to 123 nM (Fig. 4F). For hERG, the importance of fluorination was further supported by the increased potency of 5F-BZO-POXIZID compared to BZO-POXIZID, and similarly for UR-144 versus XLR-11. At the CB1 receptor, a similar importance of tail fluorination was seen, as fluorinated SCRAs tended to show higher potency compared to their non-fluorinated counterparts (Fig. 4A, G, SI Table VII). Taken together, certain structural features, particularly in the head and tail moieties, show similarities in how they contribute to effects in hERG and CB1, whereas the core scaffold appears to contribute differently to activity on the two targets. Therefore, the potency of SCRAs on hERG and CB1 show little apparent association (SI Fig. S6C), reflecting distinct SARs.
Comparing hERG and CB1 potency ratios and effects for risk stratification
Assessing the relative risk profile of SCRAs remains complex due to the multifaceted nature of their pharmacology. Based on our data, one approach to evaluating the potential for cardiotoxicity is to consider the relative potency at the CB1 receptor compared to the hERG channel, using the ratio of hERG IC50 to CB1 EC50. Since CB1 potency reflects psychoactive strength, SCRAs with high hERG potency but low CB1 potency (i.e., a low ratio) may pose a greater cardiotoxic risk, as higher doses are likely required to achieve the desired psychoactive effects. The ratio of hERG IC50 to CB1 EC50 varied from 2.3 to over 12,000 for the 36 SCRAs we studied (Fig. 4H). All SCRAs had a ratio >1, indicating that a greater concentration of the SCRA is required to inhibit hERG than to achieve psychoactive effects (although, comparing absolute concentrations between different assays is a challenge). By this standard, BZO-4en-POXIZID (Fig. 4I) had the highest risk of cardiotoxicity, i.e., the lowest ratio. 5F-BZO-POXIZID (Fig. 4J) is also connected to a high risk of cardiotoxicity, with only a five-fold higher potency of CB1 compared to hERG (Fig. 4H). In general, the OXIZID SCRAs exhibited a high cardiotoxic risk, whereas the CHMINACA and FUBINACA SCRAs had a comparatively low cardiotoxic risk.
The pro-arrhythmic potential of other classes of compounds inhibiting hERG has been extensively studied in the past, for which compounds inducing hERG inhibition by 20% have been indicated as ‘risky’ compounds likely to induce detectable changes to action potential duration and QT interval 39,40. Given that some SCRAs showed low efficacy as hERG inhibitors (SI Table II), another way of evaluating the relative potential for the greatest cardiotoxicity of SCRAs is based on the potency at the CB1 receptor versus the SCRA concentration inducing 20% reduction in hERG conductance. In this regard, SCRAs like AM-2201 (Fig. 4K), with low CB1 receptor potency combined with relatively low concentration required to cause 20% hERG inhibition, are particularly concerning (Fig. 4L). Based on our data, it is notable that several SCRAs show similar risk profiles as two of the SCRAs with previously established clear cardiotoxic effects and/or hERG inhibition and action potential prolonging capability (5F-MDMB-PINACA and JWH-030) (Fig. 4L).
Several SCRAs show dual inhibitory effects by targeting both hERG and KV7.1/KCNE1
Both hERG and KV7.1/KCNE1 contribute to cardiomyocyte repolarization (Fig. 1G). Inhibition of KV7.1/KCNE1 alone can be proarrhythmic 41. Moreover, under conditions with impaired hERG function, upregulation of KV7.1/KCNE1 has been proposed to partially compensate for the loss of hERG 42,43. Hence, drugs that inhibit both hERG and KV7.1/KCNE1 may have compounded proarrhythmic effects 44, which is another factor to consider when evaluating potential cardiotoxic effects of SCRAs. To assess if SCRAs also affect KV7.1/KCNE1, we used mammalian CHO cells stably expressing human KV7.1/KCNE1. Several SCRAs displayed inhibitory effects on KV7.1/KCNE1, seen as reduced Gmax and/or shifted V50 (SI Fig. S7-8, SI Table II). A notable example was MDMB-5’Br-BUTINACA (Fig. 5A), which reduced Gₘₐₓ and shifted V50 towards more positive voltages (Fig. 5B-D). Both inhibitory effects on KV7.1/KCNE1 were also seen for other SCRAs, including 5F-Cumyl-PINACA, MDMB-CHMINACA, MDMB-4en-PINACA and THJ-2201 (SI Fig. S7-8). At 10 µM, 7 of the SCRAs caused a significant positive shift in V50 of activation (Fig. 5E), with the largest shift induced by MDMB-CHMINACA (ΔV50 = +10.3 ± 1.6 mV). At 10 µM, 9 of the SCRAs significantly reduced Gₘₐₓ (Fig. 5F). In contrast to hERG, 5F-MDMB-PINACA had a small effect on KV7.1/KCNE1, while JWH-030 induced the largest reduction (Fig. 5E-I, SI Table II). Hence, several SCRAs inhibited KV7.1/KCNE1, however, they were fewer and induced less prominent reduction in Gₘₐₓ compared to what was observed for hERG.
Given the limited number of SCRAs with effects on KV7.1/KCNE1 no SAR analysis could be performed. However, we note several interesting clusters of compounds, exemplified for 10 µM in Figure 5J. At 10 µM, some SCRAs had no effect on either of the two channels (e.g. Cumyl-TsINACA in black), whereas some had effects only on hERG (e.g. 5F-MDMB-PINACA, 5F-BZO-POXIZID, and AM-2201 in orange) or only on KV7.1/KCNE1 (e.g. BZO-HEXOXIZID in purple). Yet other SCRAs had inhibitory effects on both hERG and KV7.1/KCNE1 (e.g. JWH-030 in blue and MDMB-5’Br-BUTINACA, MDMB-4en-PINACA, and MDMB-CHMINACA in green), showing compounded inhibitory effects on both these repolarizing KV channels.
Discussion
We demonstrate that the majority of SCRAs included in our study inhibit hERG, primarily by reducing the channel conductance. However, the magnitude of the effects and concentrations at which they occur varies among SCRAs. Generally, we noted that SCRAs with an indole core are more potent hERG inhibitors than their indazole core counterparts. Moreover, we observed important roles for both the head and tail groups. For instance, we found that several SCRAs with fluorinated alkyl tails (mostly 5F-pentyl) are prominent hERG inhibitors. This should be a cause for concern, as 5F-pentyl is the second most common tail moiety among SCRAs 45. Moreover, bulky and inflexible groups often impaired hERG effects, showcased by Cumyl-TsINACA (with an inflexible, bulky tosyl tail) and 5F-APINACA (with a bulky and inflexible adamantyl head group). Our data suggest that SCRAs use the canonical hERG central cavity binding pocket, adopting a planar orientation perpendicular to the ion conducting pathway. Interestingly, we found only partial correlation between how SCRA structural features impact the potency to inhibit hERG compared to activating the CB1 receptor. Moreover, inhibitory SCRA effects on hERG and KV7.1/KCNE1 showed no apparent correlation, as fewer SCRAs had inhibitory effects on KV7.1/KCNE1 compared to hERG, with some compounds affecting only one of the channels. These findings indicate that different chemical properties are important for SCRA binding or effects on these different targets and demonstrate the need to experimentally test the effect of SCRAs on multiple targets.
The SCRA orientation seen in our simulations is very similar to that of cryo-EM structures of the hERG pore blockers astemizole, E-4031 and pimozide 35, and the KCa3.1 pore blocker 1,4-dihydropyridine 46, which all are shown to lie flat below the selectivity filter, form interaction with aromatic side chains, and are proposed to prevent ion permeation. Hence, although alternative binding poses and mechanisms underlying hERG inhibition by SCRAs are possible, we find it likely that SCRAs like 5F-MDMB-PINACA and 5F-BZO-POXIZID act as hERG pore blockers by obstructing and preventing currents through hERG. The susceptibility of hERG to SCRAs can be explained by the coordination geometry in the binding pocket, where Y652 provides pi-stacking, and F656 dictates the size and the shape of the head or the tail. In addition, S624 and S649 provide hydrogen bonding partners to the SCRAs, tuning the affinity to the different functional groups. In contrast, our SCRA orientation is different from that recently proposed for 5F-APINACA, which uses a side pocket lateral to the central cavity 27. One possibility is that a more lateral binding site is preferred by SCRAs that do not coordinate well in the central cavity, which would agree with our observation that a bulky adamantyl group (as in 5F-APINACA) is expected to impair SCRA interaction in the central cavity. That SCRAs can interact with lateral sites may also contribute to the lack of complete hERG inhibition at saturating concentrations for some SCRAs.
In modern structural biology, cryo-EM is a common tool for determining the drug-binding pocket and its interaction geometry. Information from the cryo-EM density map can be an excellent starting point for identifying the binding pose of related drug molecules, or even for understanding how they gain access to the binding site. To enrich detailed cryo-EM determined drug binding sites, computational approaches may reveal the dynamics of drug binding and drug pose adaptation. Well-tempered metadynamics recently identified a binding site of the NaV1.5 channel blocker flecainide in the pore just below the selectivity filter. This was very close to the site of flecainide in the cryo-EM structure, and also revealed how different compounds prefer either the central cavity or lateral fenestrations of NaV1.5 47. In our study, we used accelerated weighted histogram simulations, which is similar to metadynamics but is native to GROMACS 48, to determine the binding of astemizole to the hERG channel with a binding mode matching the electron density map. Moreover, we extended our computational approach to four SCRAs, showing that the shape of the free energy landscape can be used to determine the efficiency of the blocker. Hence, in addition to providing mechanistic insights into SCRA effects, our study highlights accelerated weighted histogram simulations, just like metadynamics, as a valuable tool in providing insights into the binding dynamics and versatility of ion channel inhibitors targeting the ion permeation pathway.
How do our findings on hERG inhibition by SCRAs compare with the current literature? Yun et al. reported JWH-030 to be an inhibitor of hERG capable of inducing QT prolongation in anesthetized rats 26; however, their paper reports an IC50 of 88.4 µM (4-fold greater than our IC50 of 21.3 ± 11.9 µM). Another study employed machine learning tools to predict hERG interaction of seven SCRAs 28. Our electrophysiology data agree with their predictions for ADB-4en-PINACA and ADB-5’Br-INACA, showing no or limited effects for these SCRAs, and for 5F-BZO-POXIZID, showing prominent inhibitory effects in our hERG assay. In a more recent study, Cheng et al. reported inhibitory hERG effects of 5F-APINACA with an IC50 of 2.2 µM 27, which is considerably lower than our IC50 (>100 µM, SI Table II). Hence, our study agrees with these reports in observing inhibitory SCRA-mediated effects on hERG, whereas experimental differences may contribute to the varying observed concentrations required to achieve effects. To our knowledge, no additional SCRA has been functionally tested on hERG, but reports on the observed side effects of the use of some SCRAs are consistent with our findings. MDMB-CHMICA has been reported in two cases of sudden cardiac death 49,50, and multiple analytically confirmed intoxications have reported tachycardia and ECG changes 51,52. Our data show that MDMB-CHMICA was one of the SCRAs requiring the lowest concentration to inhibit hERG by 20%. Moreover, 5F-MDMB-PINACA is reportedly one of the most dangerous SCRAs, linked to several fatalities 18–20,53,54 and non-fatal intoxication with symptoms suggestive of cardiac arrhythmia (palpitations, heart pain, syncope and anxiety) 21. We found this SCRA to be one of the most prominent inhibitors of hERG, with high efficacy, relatively high potency, and a low concentration needed to inhibit hERG by 20%.
Besides isolated effects on hERG, other aspects can be considered when aiming to understand links between SCRAs and adverse cardiac events. One such aspect is the relative effect on hERG compared to the CB1 receptor, where SCRAs requiring high concentrations to activate CB1 are of higher risk of inducing adverse effects via other targets. In our experiments, we note that OXIZID and tail-less SCRAs show the most unfavourable CB1 to hERG concentration relationship. It is worth noting, though, that halogenated tails might limit the penetration over the blood brain barrier and hence access to CB1 55, which would contribute to a more dangerous risk profile as higher peripheral SCRA concentrations would be required to achieve central CB1 effects. Additionally, several SCRAs also inhibited KV7.1/KCNE1 in our experiments, which is anticipated to induce dual detrimental effects on cardiac repolarization. Hence, based on our findings exploring SCRA effects on hERG, KV7.1/KCNE1 and CB1, we reason that SCRA-induced inhibition of hERG alone, or both hERG and KV7.1/KCNE1, can contribute to cardiotoxic effects, should the local SCRA concentration in the heart reach sufficiently high concentrations. Other factors, including polydrug intoxication 20,56, congenital predisposition 23,57 or electrolyte imbalance 51,52,58,59, may contribute to cardiac adverse effects following SCRA use.
Study limitations include difficulties in comparing SCRA potency across different targets, due to the use of multiple assays and SCRA delivery methods, combined with SCRAs’ high lipophilicity 55. This also contributes to challenges in relating our findings to relevant in vivo concentrations, further complicated by a lack of accurate dosing information for SCRAs (as it is only available in most cases based on self-reports by those using SCRAs). The concentration of some SCRAs have been detected in post-mortem cases. For instance, the concentration of 5F-MDMB-PINACA in post-mortem cases are reported to be about 2 ng/mL (approx. 5.3 nM) 18–20,53,54 in blood or serum samples, and 1.82 ng/mL (approx. 4.8 nM) in the heart muscle 60. However, it is not possible to interpret how well those concentrations reflect those reached in people who use SCRAs, or the original dose used. Another study limitation is that the SCRA library would need to be expanded beyond our 36 SCRAs for additional SAR analysis.
In conclusion, our extensive functional screening of SCRAs found multiple compounds with inhibitory actions on one or both repolarizing cardiac KV channels, with several of the compounds linked to cardiotoxic adverse events in literature. Our study lends support to a central cavity hERG binding site for several SCRAs, highlights chemical motifs tuning the SCRA effect on hERG, while also providing insights into similarities and differences in SCRA features impacting CB1 and KV7.1/KCNE1 effects. While this screen represents 13% of the 277 SCRAs that are monitored by the EUDA (formerly the EMCDDA) as of 2025 61, our study not only provides mechanistic insights into adverse effects of SCRAs but also motivates the evaluation of ion channel effects and cardiac effects of more SCRAs, adding another dimension to the safety and risk assessment of new drugs detected on the recreational drug market.
Methods
Chemicals
4F-MDMB-BUTICA, 5F-APINACA, ADB-4en-PINACA, ADB-5’Br-BUTINACA, ADB-CHMICA, ADB-FUBINACA, ADB-HEXINACA, Benzyl-4CN-BUTINACA, Cumyl-TsINACA, JWH-210, MDMB-CHMICA, MDMB-CHMINACA, MDMB-FUBINACA, and THJ-2201 reference standards (purity ≥ 98%) were purchased from Cayman Chemicals (Ann Arbor, USA). 5F-BZO-POXIZID, 5F-Cumyl-PINACA, 5F-MDMB-PINACA, AB-CHMICA, AB-CHMINACA, AB-FUBINACA, ADB-5’Br-INACA, ADB-CHMINACA, AM-2201, APINACA, BZO-POXIZID, BZO-4en-POXIZID, BZO-HEXOXIZID, JWH-018, JWH-030, JWH-122, MDMB-4en-PINACA, MDMB-5’Br-INACA, MDMB-5’Br-BUTINACA, MMB-CHMICA, UR-144, and XLR-11 reference standards (purity ≥ 98%) were purchased from Chiron AS (Trondheim, Norway). Astemizole was purchased from Sigma-Aldrich (Stockholm, Sweden). All compound solutions were in DMSO at a concentration of 10 mM and stored at -20 °C. Compounds were diluted in extracellular recording solution on the day of recordings. For the automated patch-clamp experiments, the compounds made no contact with plastics following dilution in extracellular solution. The final concentration of DMSO was equal in all recording solutions to control for vehicle effects. For experiments involving pluronic acid (Pluronic F-68; P5556; POLOXAMER 188 SOLUTION; Merck Life Science AB, Sweden), compound stock solutions were diluted in 2 mM pluronic acid (10% solution), warmed to approximately 60°C, and sonicated for 30 seconds. The final concentration of pluronic acid in the assay was 0.05%. DMEM/Ham’s F12, Ham’s F12, 0.25% trypsin-EDTA with phenol red, and fetal bovine serum (FBS) were purchased from Thermo Fisher (Gothenburg, Sweden). HEPES buffer, L-glutamine, protease-free bovine serum albumin (BSA), digitonin, adenosine-5’-triphosphate disodium salt hydrate (ATP), methanol, and DMSO were procured from Sigma-Aldrich (Stockholm, Sweden). The coelenterazine substrate was from Nanolight Technology (Pinetop, AZ, United States).
Cell lines
Stably expressing cell lines “CHO-hERG DUO” (here referred to as hERG; gene: KCNH2) and “CHO-KVLQT1/mink” (here referred to as KV7.1/KCNE1; gene: KCNQ1/KCNE1), (B’SYS GmBH, Witterswil, Switzerland) were used to study whole-cell K+ currents on a QPatch II 48 APC system (Sophion Bioscience A/S, Ballerup, Denmark). Cell culture and passaging was performed in accordance with standard operating procedures. Cells were harvested in serum-free medium with DetachinTM (Genlantis, CA, USA) immediately prior to experiments. For MPC on transient cell lines, CHO-K1 CCL-61 cells (ATCC, Manassas, VA, USA) were cultured in Ham’s F-12 medium supplemented with 10% fetal bovine serum (FBS) and 100 U/mL penicillin–100 µg/mL streptomycin (Gibco, Thermo Fisher Scientific, Waltham, MA, USA). Transfection was carried out using JetOPTIMUS® reagent (Polyplus, Strasbourg, France) according to the manufacturer’s protocol. Briefly, 80,000 cells were seeded per well in a 12-well plate and transfected with 300 ng of pcDNA3-GFP plasmid, 700 ng of pcDNA3-hERG plasmid with the Y652A mutation, and 1 µg of JetOPTIMUS. After 8 hours, cells were detached and reseeded at a density of 30,000 cells per well onto several poly-D-lysine-coated glass coverslips placed in a 12-well plate. For the CB1 receptor activity assay, the AequoScreen® recombinant Chinese hamster ovary (CHO) K1 cell line, stably expressing the human CB1 receptor (ES-110-A), was used (Revvity, Sollentuna, Sweden).
Automated patch-clamp experiments
Automated patch-clamp recordings were performed at 22°C, if not else indicated. Freshly harvested cell suspensions (2-3 million cells/mL) were prepared for experiments by the QPatch II 48 automated cell preparation unit. Cells were centrifuged for 150 s at 150 x g and washed twice with the extracellular recording solution. Cells were handled by the integrated pipetting robot and added to the 48 experiment sites on the planar patch-clamp consumable QPlate. Each experiment site contained an individual pair of recording electrodes and a silicon/glass biochip embedded in the flow channels. Single-cell patch recordings and population patch recordings (10 cells per well, n = 1 is defined as one population patch) were performed for hERG and for KV7.1/KCNE1, respectively. Cells were applied, positioned and sealed to the patch holes by a mild suction protocol; whole-cell access was then achieved by a stronger suction pulse.
The extracellular solution contained (in mM): 145 NaCl, 10 Glucose, 4 KCl, 2 CaCl2, 1 MgCl2, and 10 HEPES. Osmolarity was adjusted to 305-308 mOsm with sucrose and pH was adjusted to 7.4 with NaOH. The intracellular solution contained (in mM): 100 KCl, 4.3 CaCl2, 1.4 MgCl2, 25/10 KOH/EGTA, 24 KF, 10 HEPES, and 4 Mg-ATP (hERG) or 4 Na-ATP (KV7.1/KCNE1). Osmolarity was adjusted to 305-308 mOsm with sucrose, and pH was adjusted to 7.2 with KOH.
Square voltage pulses in a voltage ladder protocol were used to study current/voltage (I(V)) relationships. Each voltage protocol was first run three times in the presence of vehicle (extracellular solution supplemented with 0.3% DMSO), the 3rd serving as the baseline. Voltage protocols were repeated in the presence of 4 cumulatively rising concentrations of test compound, followed by application of vehicle for recovery. To control for assay quality, one set of vehicle-only experiments which received no test compound was included in each run. Each solution was added to the QPlate twice (5 s between applications: 10 µL per application). For the hERG voltage ladder protocol, solutions were present for 60 s before recording started. hERG cells were kept at a holding voltage of −80 mV, with brief hyperpolarizing steps to −90 mV for 50 ms (to calculate ohmic leakage) before returning to −80 mV for 200 ms. Square voltage pulses were sequentially applied in 10 mV increments (range −60 mV to +60 mV) for 5 s before stepping to −50 mV for 2 s to record tail currents. Time between start of sweeps was 10 s. The voltage pulsing protocol was executed every 150 s. In experiments using the hERG voltage pulsing protocol, the extracellular solution remained present for 7 s before recording started. hERG cells were kept at a holding voltage of −80 mV with brief hyperpolarizing steps to −90 mV for 50 ms (to calculate ohmic leakage) before returning to −80 mV. Stepping occurred in two stages, first to −50 mV for 50 ms before stepping up +40 mV for 5 s. Cells were then held −50 mV for 2 s to record tail currents and returned to −80 mV. Time between start of sweeps was 10 s, and sweeps were pulsed 20 times per protocol. The voltage pulsing protocol was executed every 201 s.
In experiments with fluoride-free intracellular solution (SI Fig S2F-G), the intracellular solution contained (in mM) 120 KCl, 5.374 CaCl2, 1.75 MgCl2, 31.25/10 KOH/EGTA, 10 HEPES, and 4 Na-ATP. Osmolarity was adjusted to 285-295 mOsm with sucrose, and pH was adjusted to 7.2 with KOH. Extracellular solution (5 µl) was added to the recording plate, and the solution remained present for 9 s before recording started. hERG cells were kept at a holding voltage of −90 mV with brief hyperpolarizing step from −100 mV for 100 ms to −110 mV for 100 ms (to calculate ohmic leakage) before a brief step to −50 mV for 100 ms (to enable automated leak subtraction) followed by an activating step to +20 mV for 4 s. Cells were then held at −50 mV for 4s to record tail currents and returned to −100 mV for 1 s. Time between start of sweeps was 15 s, and sweeps were pulsed 10 times. Following the pulsing protocol, extracellular solution (5 µl) was added to the recording plate, and the solution remained present for 5 s before voltage-ladder protocol started with a brief hyperpolarizing step from −100 mV for 100 ms to −110 mV for 100 ms (to calculate ohmic leakage) before a brief step to −50 mV for 100 ms (to enable automated leak subtraction). Square voltage pulses were sequentially applied in 10 mV increments (range −100 mV to +70 mV) for 4 s before stepping to −50 mV for 4 s to record tail currents, followed by a step to −100 mV for 1 s. Time between start of sweeps was 9.32 s, and the voltage ladder protocol was executed every 170 s. Voltage ladder protocols were repeated in the presence of 2 cumulatively rising concentrations of test compound: 2 µl was added with 5 repetitions (2 s between each application) followed by application of extracellular solution (2 µl was added with 5 repetitions (2 s between each application)) for recordings of recovery using the precedent voltage pulsing protocol. The temperature was set to 27°C.
For the KV7.1/KCNE1 voltage ladder protocol, the solutions were present for 60 s before recording started. KV7.1/KCNE1 cells were kept at a holding voltage of −90 mV, with brief hyperpolarizing steps to −100 mV for 540 ms (to calculate ohmic leakage). Square voltage pulses were sequentially applied in 10 mV increments (range −100 mV to +40 mV) for 4 s before stepping to −20 mV for 2 s to record tail currents. Time between compound application and first voltage protocol was 30 s. Time between sweeps was 15 s. The voltage ladder protocol was executed every 220 s.
Transient transfections and manual patch-clamp electrophysiology
Manual patch-clamp recordings were performed 24–48 hours post-transfection. Coverslips with CHO-K1 cells were placed in a recording chamber and continuously perfused at room temperature (22–24⁰C) with extracellular solution by a gravity-fed perfusion system.
Compounds were applied by a pressurized, automated OctaFlow perfusion system (ALA Scientific Instruments). The intracellular and extracellular solutions used MPC were identical to those used for APC electrophysiology (see above). Patch pipettes were pulled from borosilicate glass and had resistances of 3–6 MΩ when filled with intracellular solution.
Square voltage pulses were sequentially applied in 10 mV increments (range −60 mV to +50 mV from a holding potential of −80 mV) for 5 s before stepping to −50 mV for 2 s to record tail currents. Each voltage protocol was first run three times in extracellular solution, the 3rd serving as the baseline. Voltage protocols were repeated in the presence of cumulatively rising concentrations of test compound applied by continuous perfusion, each concentration was present for 30 s before the recording started. The signals were sampled at 5 kHz after low-pass filtering at 2 kHz.
Electrophysiological analysis
Data from automated and manual patch-clamp experiments were analyzed using Sophion Analyzer 10.0 software (Sophion Biosciences, Ballerup, Denmark) and Clampfit 10.7 (Molecular Devices, San Jose,CA), respectively, and GraphPad Prism 10 (version 10.0.2; GraphPad Software Inc., CA, USA). Ohmic leakage was subtracted from tail currents, and the leak-subtracted tail currents were plotted directly against the preceding test voltages to construct G(V) curves. These data were fit with a single Boltzmann curve: where Gmin is the base, Gplateau is the top, V is the voltage in mV, V50 is the voltage where half of the maximum current is reached, and slope is the slope of the curve. To set the bottom of the curve to zero, the Gmin was subtracted from the leak-subtracted tail currents, and data were again plotted directly against preceding test voltages and fit with a single Boltzmann curve: where Gmax is the top, V is the voltage in mV, V50 is the voltage where half of the maximum current is reached, and slope is the slope of the curve. The slope was set to 8 and 12 for hERG and KV7.1/KCNE1, respectively. Gmax and V50 values were exported from Sophion Analyzer (via Excel) for further analysis with GraphPad Prism.
Ratio of Gmax (G/Gmax), and ΔV50 were calculated using the “Remove Baseline and Column Math” feature in GraphPad Prism 10, using the cell-specific 3rd vehicle as the baseline, with ratio and difference calculation for G/Gmax and ΔV50, respectively, and with sub-columns defined as repeated measures. G/Gmax and ΔV50 were corrected for potential non-compound dependent effects in the recordings (i.e, run-down or run-up), again using the “Remove Baseline and Column Math” feature in GraphPad Prism 10, with ratio and difference calculation for G/Gmax and ΔV50, respectively, using the corresponding data set for the run-specific vehicle as baseline, and with sub-columns defined as replicates. These normalized data, called Gmax (rel.) and ΔV50 were then used for further analysis.
To determine concentration-dependence of responses to test compounds, Gmax (rel.) and ΔV50 values were plotted and the following 4-parameter concentration-response curve was fitted to the data: where Y is the response (Gmax (rel.) or ΔV50), IC50 is the concentration that evokes 50% of the maximum response (constrained to always be above 0), and N is the Hill slope. For Gmax (rel.), Bottom represents the maximally inhibited response and was constrained to assume a value between 0 and 1, and Top represents the baseline (no current inhibition) and was constrained to always be equal to 1. For ΔV50, Bottom represents the baseline (no shift in V50) and was constrained to always be equal to 0, while Top was the maximal V50 response and was not constrained.
In vitro biological activity at CB1 receptor
The apoaequorin system (AequoScreen® assay) is an intracellular calcium (Ca2+) release assay commonly used for measuring G-protein coupled (GPC) receptor activity. Apoaequorin is a protein that in the presence of its substrate coelenterazine converts to the aequorin photoprotein, which has three Ca2+ binding sites 62. Binding of an extracellular ligand to the GPC receptor leads to the activation of a universal G protein subunit Gα16, which in turn triggers a series of downstream events, such as the activation of the phospholipase C (PLC) enzyme, that stimulates the release of intracellular Ca2+ 62. The Ca2+ then binds to the aequorin photoprotein, which oxidizes the coelenterazine leading to the release of photons that can be measured via a luminescence reader 63.
CHO-K1 cells stably expressing CB1, the apoaequorin enzyme, and the Gα16 subunit were maintained in a humidified atmosphere at 37°C and 5% CO2 in Ham’s F12 medium supplemented with 10% heat-inactivated FBS. To perform the assays, cells were trypsinized (10 min, 37°C), centrifuged (at 200 × g, 5 min, room temperature), counted, resuspended at 3 × 105 cells/mL in DMEM/Ham’s F12 without phenol red, and supplemented with 15 mM HEPES, L-glutamine, and protease-free BSA (0.1%) (further referred to as assay medium).
The coelenterazine substrate was added to a final concentration of 2.5 μM and the suspension was incubated for 3 h (room temperature, rotating at ∼7 RPM/min, protected from light). Drug solutions were prepared as a 1:8 serial dilution in assay medium (1:4 serial dilution for Δ9-THC) with a starting concentration of 60 μM (in well after addition of cells) and then added to white, opaque-welled 96-well plates. JWH-018 (60 μM) was included as a reference on each plate, in line with earlier results generated using the AequoScreen® CB1 assay 64–66. Digitonin (67 μM) and ATP (6.7 μM) were included on each plate and served as positive controls for coelenterazine loading as both are involved in the non-CB-dependent release of calcium ions. Blank assay medium was used as a negative control. Using a TECAN Spark 10 M plate reader (Männedorf, Switzerland), 50 μL of the incubated cell suspension was dispensed into each well (15 × 103 cells/well) of the 96-well plate containing the test solutions. Luminescence was measured for 25 s (corresponding to 190 additional reading cycles).
Absolute luminescence signals were corrected for intra-plate variability in Microsoft Excel 365 using area under the curve (AUC) values of JWH-018 and were calculated for each concentration of the test compounds. Values were then blank-corrected by subtracting AUC values of the mean of the blank controls. Data were normalized to the maximum of JWH-018. The normalized values were transferred to GraphPad Prism (Version 10.0.2) to generate concentration-response curves and calculate EC50 and Emax values by curve fitting via nonlinear regression (three-parameter logistic fit). Results are represented as receptor activity of JWH-018 (%) derived from a minimum of three independent experiments (n ≥ 3), run in triplicate. There were only two independent experiments (n = 2) for JWH-030, as there was not enough of the reference standard available for a third independent experiment. As the CB1 receptor activity of the SCRAs included in this study were examined over the span of a couple years, EC50 values were normalized to the median EC50 value of JWH-018 (35.03 nM) from 139 independent experiments run over many years.
SAR-studies
Structure-activity relationship (SAR) analysis for hERG was conducted both for efficacy (maximum reduction in Gmax) and potency (IC50). Only comparisons involving at least three pairs of structurally related compounds were included. Compounds were only included if a concentration–response curve could be fitted; compounds with no measurable effect were excluded. SAR analysis for the CB1 receptor was conducted for both efficacy (Emax) and potency (EC50), where the logEC50 values were used for the statistical analysis. Only comparisons involving at least three pairs of structurally related compounds were included.
Statistical analysis
Data are reported as mean ± SEM. GraphPad Prism 10 was used for all statistical analyses. For comparisons between compound and run-specific vehicle controls in APC, a two-way ANOVA (Gaussian distribution of residuals and equal SDs assumed) followed by Dunnett’s multiple comparisons test was used. When a compound had been tested in several runs, the ANOVA (or mixed effect model when appropriate) was instead performed on the combined dataset and compared to the combined vehicle controls from corresponding runs, where all data were normalized according to their run prior to pooling. This was followed by either Dunnett’s multiple comparisons test (if more than one compound was to be compared to vehicle control) or a Šidák correction (if only one compound was to be compared to vehicle control). Correlation analysis was done with simple linear regression, accounting for n and scatter among replicates. Correlation was considered significant if the P-value of the slope significantly deviated from 0. For SAR studies on hERG, compounds were only included if a concentration–response curve could be fitted; compounds with no measurable effect were excluded. Log10IC50 values were used for statistical analysis. P values for compound-to-compound comparisons were obtained using extra-sum-of-squares F-tests and linear regression. P values for overall comparisons were calculated using two-tailed paired t-tests. A p-value < 0.05 was considered statistically significant. For SAR studies on CB1, P values for compound-to-compound comparisons were obtained using Brown-Forsythe and Welch ANOVA tests (α = 0.05) performed in GraphPad Prism, while p values for overall comparisons were calculated using two-tailed paired t-tests (α = 0.05).
Molecular docking
To determine an initial binding pose for astemizole, the hERG channel structure (PDB ID: 7CN1, 32) was obtained from the RCSB protein data bank. Autodock Tools was utilized to prepare structures of protein and ligand for docking. Autodock Tools was also used to select a grid box of 24 Å centred on residue Y652 in the vestibule of the hERG channel. Autodock Vina 67 was utilized to calculate docking of astemizole within the box. 20 independent docking runs were attempted for each ligand and 15 poses were generated for each run. Outputs were clustered according to the root mean square deviation (RMSD), and the initial binding pose was used to guide the accelerated weighted histogram simulations.
System set-up for molecular dynamics simulations
The inactivated-state hERG channel with astemizole bound (PDB entry: 7CN1, 32) from residue T399-L666 was embedded in a 100% POPC bilayer and solvated in 0.15 KCl and TIP3P water using CHARMM-GUI Membrane Builder. A single ligand (astemizole or SCRAs) was aligned with the initial binding pose of astemizole (determined by docking) using PyMOL to generate an initial configuration. Ligand parameters were generated using Ligand Reader and Modeler on CHARMM-GUI. The system was then energy-minimized and equilibrated using the standard six steps CHARMM-GUI equilibration protocol 68. This includes the following set-up: protein backbone was restrained at the force constant of 4000, 2000, 1000, 500, 200 and 50 kJmol−1 nm−2, protein side chains were restrained at the force constant of 2000, 1000, 500, 200, 50, and 0 kJmol−1 nm−2, non-H atoms of lipids were restrained at the force constant of 1000, 400, 400, 200, 40 and 0 kJmol−1 nm−2, and dihedral restraints were set at the force constant of 1000, 400, 200, 200, 100 and 0 kJmol−1 rad−2. Simulations were equilibrated with a 1 fs timestep for 125 ps for the first three steps, and then to a 2 fs timesteps for 500 ps the next two, and 5 ns for the final step. The first two steps were conducted with the NVT ensemble and the last four were conducted with the NPT ensemble. All equilibration runs were conducted at 310 K using a Berendsen thermostat 69. In all NPT ensemble equilibration, the pressure was maintained at 1 bar using a Berendsen barostat 69. All simulations were conducted using GROMACS-2023.4 70. All images from simulations were generated using PyMOL.
Accelerated weighted histogram simulations
The free energy landscape describing the path (z-axis distance) of the drug entering the binding site within the hERG channel was calculated using an accelerated weighted histogram (AWH) 71. Pressure was maintained at 1 bar and temperature was maintained at 310 K. An independent AWH bias was applied for each equilibrated structure, simulating 4 walkers for 1250 ns per walker, sharing bias data and target distribution. Bias acted on the z-axis, defined using the centre-of-mass of the drug and the Y652 residue in the vestibule of the hERG channel, aiming for a converged simulation, defined as a similar free energy landscape every 50 ns. Sampling interval was 1.0 nm above Y652 and 3.5 nm below Y652. The system initialized with an average free energy error of 20 kJ/mol, with the diffusion coefficient at 0.0002 nm2/ps at a force constant of 12800 kJ mol−1 nm−2. A harmonic potential was applied on all Cα atoms at 5.0 kJ mol−1 nm−2. Free energy landscape from 1210, 1220, 1230, 1240 and 1250 ns were averaged and used to build a final free energy landscape. The binding pose was clustered using DBSCAN with epsilon of 0.2 and minimum sample of 10. From each cluster, 1000 structures located closest to the free energy minima were extracted and used for minimum distance calculation.
Acknowledgement
We acknowledge Dr. Fredrik Elinder, Linköping University, for valuable input on the study. The hERG Y652A clone was a generous gift from Dr. Nicole Schmitt, University of Copenhagen. This study was supported by funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No. 850622), the Swedish Research Council (2021-01885), and the Strategic Research Area in Forensic Science, Linköping University. T.P. was funded by Lee Kuan Yew Postdoctoral Fellowship. C.N. was funded by a Postdoctoral Fellowship from the Swedish Society for Medical Research. Computational resources were supported by NTU-HPC center. The authors also acknowledge the support from the Chemical Biology Consortium Sweden (CBCS), node Linköping University, Electrophysiology, a national research infrastructure funded by the Swedish Research Council (2021-00179) and SciLifeLab. We acknowledge B’SYS GmbH for their collaboration and support in providing ion channel-expressing cell lines. We also thank Sophion Bioscience for their contributions to assay development, with special appreciation to Naja Møller Sørensen, Anissa Bara, and Rasmus Jacobsen for their expert assistance and valuable input throughout the project.
Declaration of interests
The authors declare no competing interests.
Supplementary Figures
Supplementary Text
Experimental characterization of 5F-MDMB-PINACA effects on hERG, to explore experimental conditions potentially impacting inhibitory effects
To more carefully assess the inhibitory effects of the SCRAs on hERG channel function, we performed additional analysis and experiments using 5F-MDMB-PINACA, which was one of the most prominent hERG inhibitors in our APC assay. For APC recordings of 5F-MDMB-PINACA, we noted a more pronounced reduction of the tail current compared to the steady-state current across voltages with a clear channel activation (SI Fig. S2A). This difference was not present in the corresponding MPC recordings (SI Fig. S2B). In both methods, the unspecific ohmic leak is compensated for using the voltage step prior to activation. In part, challenges in fully compensating for potassium ion leak in APC recordings may have contributed to the relatively larger tail current effects. However, additional factors such as the time course of the onset of 5F-MDMB-PINACA effects and possibly some degree of state dependence of 5F-MDMB-PINACA effects may contribute.
Using APC, we examined the effect of temperature on SCRA activity by performing recordings at 27°C and 35°C. While increased temperature accelerated channel kinetics (Fig. S2C), the inhibitory effect of 10 µM 5F-MDMB-PINACA was unaffected by the increased temperature (SI Fig. S2D-E) whilst the inhibitory effect of 1 µM 5F-MDMB-PINACA was slightly larger at the higher temperature (Fig. S2E). The intracellular solution used in our APC and MPC recordings contained fluoride (24 mM) to improve seal quality and recording stability 72. We observed a shift in the voltage dependence of channel activation in vehicle control experiments in the presence of fluoride by +12 mV (SI Fig. S2F, recordings were done at 27 °C). However, the inhibitory effects of 5F-MDMB-PINACA on both steady-state currents and tail currents were unaffected by the presence of fluoride (SI Fig. S2G). These data suggest that 5F-MDMB-PINACA acts independently of fluoride and its inhibitory effect is relatively temperature-independent across a range of temperatures.
Due to their high lipophilicity, SCRAs such as 5F-MDMB-PINACA may interact with hydrophobic components of the recording environment, including surfaces or materials within the APC system, even in the absence of plastic. This property could influence compound availability and apparent potency. To minimize this, pluronic acid was included as a carrier in specific experiments. Pluronic acid did not affect the voltage dependence of channel activation (SI Fig. S2H) but enhanced compound potency, as reflected by a lower IC50 for 5F-MDMB-PINACA (SI Fig. S2I). Manual patch-clamp (MPC) recordings revealed an even greater potency, with 3 µM producing a comparable effect to 10 µM in APC (SI Fig. S2J-K). A major methodological difference between MPC and APC is that the MPC recordings were performed on single, adherent cells, whereas APC recordings were performed on cells that had been enzymatically detached from the culture surface using Detachin™ and kept in suspension during measurements. To investigate if cell detachment influenced compound potency, we also performed MPC recordings on suspended cells.
Interestingly, the IC50 for 5F-MDMB-PINACA was higher for detached cells compared to adherent ones (SI Fig. S2L), approaching the IC50 for 5F-MDMB-PINACA in APC. Consequently, the potency of SCRAs on hERG may be greater than what is indicated by APC recordings using suspended cells, underscoring a role of cell state in pharmacological assessments.