Cone snail venom-inspired somatostatin receptor 4 (SSTR₄) agonists as new drug leads for peripheral pain

Abstract

Persistent pain affects one in five people worldwide, often with severely debilitating consequences. While current treatments can be effective for mild or acute pain, they are largely inadequate for managing moderate to severe chronic pain, underscoring the urgent need for new therapeutics. The somatostatin receptor 4 (SSTR₄), expressed in sensory neurons of the peripheral nervous system, has recently emerged as a promising target for non-opioid pain relief. However, the presence of several closely related receptors with similar ligand-binding surfaces complicates the design of receptor-specific agonists. Here, we report the discovery of consomatin Fj1, a potent and selective SSTR₄-targeting peptide derived from the venom gene repertoire of marine cone snails. Consomatin Fj1 is a mimetic of the endogenous hormone somatostatin but features a minimized receptor binding motif that provides target selectivity. Peripheral administration of synthetic consomatin Fj1 provides analgesia in mouse models of postoperative and neuropathic pain. Using structure–activity studies, we designed and functionally evaluated several Fj1 analogs, resulting in compounds with further improved potency and selectivity. These findings highlight the therapeutic potential of venom-derived peptides as a novel strategy for targeting the SSTR₄ and open new avenues for the development of effective treatments for persistent pain.

Introduction

Persistent pain, or chronic pain, poses a significant global challenge, impacting more than one in five individuals and exerting substantial personal, societal, and economic burden¹. Current treatments, including acetaminophen (paracetamol), non-steroidal anti-inflammatory drugs (NSAIDs), anticonvulsants, antidepressants, and opioids², are often effective for mild or acute pain but fall short for moderate to severe persistent pain. Moreover, many of these options carry serious side effects, including the risk of tolerance, dependence, and addiction³. The opioid crisis⁴, in particular, has highlighted the urgent need for new, non-opioid pain therapeutics.

One promising target for opioid-independent pain relief is somatostatin receptor 4 (SSTR₄), a G protein-coupled receptor (GPCR) expressed in peripheral sensory neurons and activated by the peptide hormones somatostatin (SST) and cortistatin. The human somatostatin receptor (SSTR) family includes five subtypes (SSTR_1–5), which share moderate sequence similarity and overlapping ligand-binding features⁵. Although all five receptors respond to the same endogenous ligands and signal through Gαi/o proteins, they have distinct expression patterns and physiological roles. For instance, SSTR₂ and SSTR₅ are prominently expressed in neuroendocrine tumors, where their activation inhibits cell growth⁶, and receptor-specific agonists targeting these subtypes are used clinically to treat endocrine disorders and certain cancers^7,8,9.

The first indication of the potential role of SSTR₄-selective agonists for the treatment of pain came from the SSTR_1,4-targeting peptide, TT-232, originally developed for the treatment of cancer but later found to exhibit anti-inflammatory and anti-nociceptive effects^10,11,12. These results, as well as additional studies on the small molecule agonist J-2156^13,14, established the SSTR₄ as a novel target for pain relief. Although the molecular mechanisms of SSTR₄-mediated antinociception are not fully understood, several studies have suggested that SSTR₄ activation in nociceptive neurons of the dorsal root ganglia (DRG) and trigeminal ganglia leads to downstream Gβγ-mediated activation of G protein-coupled inwardly rectifying potassium channels (GIRKs), allowing an outward flux of potassium ions, thereby hyperpolarizing cells involved in pain sensing and/or transmission¹⁵. Furthermore, SSTR₄ activation can reduce capsaicin-induced transient receptor potential cation channel subfamily V member 1 (TRPV1) currents in DRG neurons through Gα_i signaling, further hyperpolarizing the cell¹⁵. Thus, SSTR₄-selective ligands provide analgesia through the inhibition of peripheral pain signals and do not require central nervous system (CNS) administration or penetration.

Our previous discovery of a venom-derived agonist of SSTR₁ and SSTR₄, consomatin Ro1, from a marine cone snail¹⁶ provided proof of principle that cone snail venoms serve as a source of novel SSTR ligands. While consomatin Ro1 exhibited analgesic effects in vivo, its potency at the SSTR₄ was moderate, and it lacked receptor selectivity¹⁶.

Here, to investigate whether cone snails evolved additional SSTR₄-targeting toxins with improved potency and selectivity profiles, we conducted a computational search of venom gene datasets from 247 cone snail species, identifying 529 SST-like sequences. From this pool, eight candidates were selected, synthesized and profiled, leading to the discovery of consomatin Fj1, a highly potent and selective SSTR₄ agonist. In mouse models of postoperative and neuropathic pain, consomatin Fj1 produces robust analgesic effects. Structure–activity relationship studies, supported by molecular dynamics (MD) simulations, revealed further opportunities to optimize this compound for therapeutic development. Together, these findings highlight the potential of venom-derived peptides as a novel approach to treating persistent pain by targeting peripheral pathways.

Methods

Toxin sequence extraction and principal component analysis (PCA)

Consomatin sequences were extracted from the SRA datasets of cone snails from Bioproject PRNJ526781, as described previously¹⁷. Briefly, data were downloaded from NCBI and preprocessed using fastp v0.20.1. Consomatin-encoding reads were extracted using tblastn with several previously identified consomatins as queries¹⁶. These hits were assembled using Trinity v.2.13.2¹⁸ as single reads. The generated contigs with more than fivefold coverage were translated in all reading frames and putative toxins were extracted with regular expressions (“[^C]{0,2}C[^C]{0,3}WK[^C]{0,3}C[^RKC]{0,6}”) which allows the “WK” motif to appear at any position in the disulfide loop. We next extracted the length, molecular weight, isoelectric point, hydropathy, aliphaticity, aromaticity, polarity, positive and negative charge, and percentage of unique amino acids (glycine and proline), as well as the count of the 140 most common amino acid 1-to-3-mers across all sequences using an in-house script. Principal components were calculated using sklearn v.1.1.3¹⁹ in Python 3.9.16 on data scaled to remove the mean and unit variance. The first two principal components were visualized in R v.4.2.2 using ggplot v.3.4.2.

Peptide synthesis and purification

Peptides were either purchased from Genscript or synthesized in-house (to > 90% purity) as described below. Peptides were synthesized by solid-phase peptide synthesis (SPPS) at a 0.1 or 0.05 mmol scale using preloaded Fmoc-protected Tentagel R HMPA resin from Rapp Polymere (Tübingen, Germany) for C-terminal carboxylic acid sequences and TentaGel® S RAM Resins for C-terminal amide sequences. Fmoc-protected amino acids, coupling reagents, and solvents used for synthesis were purchased from Iris Biotech (Marktredwitz, Germany). Synthesis was performed using a Syro I instrument (Biotage, Uppsala, Sweden). The coupling conditions were room temperature (RT) for 2 × 120 min using 5.2 equivalents of amino acids, 4.7 equivalents of N-[(1H-benzotriazol-1-yl)(dimethylamino) methylene]-N-methylmethanaminium hexafluorophosphate N-oxide, 5.2 equivalents of 1-hydroxy-7-azabenzotriazol, and 8 equivalents of N,N-diisopropylethylamine in dimethylformamide (DMF) relative to the resin. Deprotection was performed at RT with 40% piperidine in DMF for 3 min, followed by 20% piperidine in DMF for 15 min. The washing steps were performed with 2 × N-methyl-2-pyrrolidone, 1 × dichloromethane (DCM), and 1 × DMF. After completion of peptide assembly, the peptidyl resin was washed with 3 × DCM and dried. The peptide was released from approximately 0.025 mmol of resin using a mixture (2 mL) of 95% trifluoroacetic acid (TFA), 2.5% triethylsilyl, and 2.5% water over 2.5 h. For methionine-containing sequences, the 2 mL mixture contained 87.5% TFA, 2.5% triethylsilyl, 2.5% water, 2.5% thioanisole, and 5% ethanethiol, or alternatively 87.5% TFA, 2.5% triethylsilyl, 2.5% water, 2.5% thioanisole, and 5% ethanethiol with approximately 0.4 mg sodium iodide (NaI). Cold diethyl ether (13 mL stored at − 20 °C) was added, and the mixture was further cooled to − 85 °C for 30 min before the peptide was isolated by centrifugation. The peptide was redissolved in a mixture of acetic acid, water, and acetonitrile (ACN) in a volume ratio of 1:10:4 and freeze-dried to remove unwanted carboxylation of Trp. For peptides containing methionine, acetic acid was replaced with half the volume of TFA. The freeze-dried compound was dissolved in a few drops of TFA and 5 mL of ACN, followed by the addition of 5 mL of water. Phosphate buffer (0.1 M) was added to this mixture until a total volume of 18 mL. The pH was adjusted to 6 by using 1 M hydrochloride acid. Dimethyl sulfoxide (2.0 mL) was added (10%, v/v) and the mixture was stirred for 40–72 h at RT to allow disulfide bond formation. The mixture was filtered and directly purified using one of two methods: the peptides were purified using a Luna C18(2) column from Phenomenex (Torrance, USA, 5 μm, 100 Å, 250 × 10 mm) on a Dionex Ultimate 3000 HPLC system (Thermo Fisher, Waltham, USA) or a 50 g Biotage Sfär Bio C18 D column on a Selekt System (Biotage, Sweden). For both systems, a gradient of 5–100% ACN in water/0.1% formic acid (or 0.1% TFA for methionine-containing sequences) was applied. The product was isolated and lyophilized by freeze-drying. The final product was analyzed by liquid chromatography-mass spectrometry using a Dionex Ultimate 3000 ultrahigh-performance liquid chromatography system (Thermo Fisher) connected to an Impact HD mass spectrometer (Bruker, Bremen, Germany). Information on peptide sequences, purity and integrity as determined by LC and MS is provided the supplemental information under peptide synthesis.

PRESTO-Tango beta arrestin recruitment assay

Synthetic peptides were screened at the five human SSTRs using the PRESTO-Tango β-arrestin recruitment assay as previously described²⁰. HTLA cells (a kind gift from Prof. Hans Bräuner-Osborne) maintained in DMEM (Gibco) supplemented with 10% FBS (Biowest, Nuaillé, France), 100 U/mL penicillin/100 mg/mL streptomycin (Gibco), 100 µg/mL hygromycin B (ThermoFisher Scientific), and 2 µg/mL puromycin (Gibco) (growth medium) were maintained in a water jacketed 5% CO₂ incubator and passaged every 2–3 days using trypsin/EDTA (Gibco). 1E6 cells were seeded into 6 well plates. The following day, the medium was changed, and the cells were transfected with 2 µg of DNA from the relevant receptor construct (obtained from Addgene) and 20 µL PolyFect (Qiagen) into 100 µL DMEM and incubated for 10 min. Growth medium (400 µL) was added and the mixture was added to the cells. 14–18 h later, 4E4 cells per well in 40 µL of DMEM supplemented with 1% dialyzed FBS (assay medium) were seeded into white clear bottom 386 well plates (Corning). The following day, the medium was changed to 40 µL new assay medium and peptides were reconstituted and added at 5× final concentration in HBSS supplemented with 20 mM HEPES, 1 mM CaCl₂, 1 mM MgCl₂, and 0.1% BSA (stimulation buffer). The following day, the medium was discarded, and 20 µL of a 20× dilution of BrightGlo (Promega) in stimulation buffer was added. The plate was incubated in the dark at RT for 20 min, and luminescence was read at 1000 ms integration time on a SpectraMax iD5 (Molecular Devices).

G protein dissociation assay

To determine downstream receptor signaling using native receptor sequences, we used a bioluminescence resonance energy transfer (BRET)-based assay that measures GPCR activation by monitoring the association of labeled Gβγ subunits and a G protein-coupled receptor kinase (GRK) fragment, following dissociation of Gβγ subunits from the Gα subunit as previously described²¹. HEK293 cells (ATCC) maintained in DMEM (Gibco) supplemented with 10% FBS (Biowes, Nuaillé, France) and 100 U/mL penicillin/100 mg/mL streptomycin (Gibco) (growth medium) were maintained in a water jacketed 5% CO₂ incubator and passaged every 2–3 days using trypsin/EDTA (Gibco). 1E6 cells were seeded into 6 well plates. The following day, the medium was changed, and the cells transfected by adding 0.33 µg of SSTR construct, 0.66 µg of Gα protein, 0.33 µg Venus 156–239-Gβ, 0.33 µg Venus 1–155-Gγ, and 0.33 µg masGRK3ct-Nluc DNA into 27 µL of 150 mM NaCl, and 12 µL of 100 mg/mL linear polyethyleneimine (PEI) at molecular weight 25 kDa (Polysciences, Warrington, PA, USA) into 38 µL of a 150 mM NaCl solution. The two tubes were mixed and incubated for 10–15 min before addition to the cells. The following day, 5E4 cells per well were seeded in 100 µL of growth medium into poly-d-lysine-coated white 96 well OptiPlates (PerkinElmer). The following day, the cells were washed in 80 µL of HBSS supplemented with 20 mM HEPES, 1 mM CaCl₂, and 1 mM MgCl₂ (assay buffer), and 80 µL of assay buffer supplemented with 0.1% BSA (stimulation buffer) was added. 10 µL of a 1:250 dilution of furimazine (Promega) in stimulation buffer was added, and after 120 s, 10 µL of a 10× solution of the compounds reconstituted in stimulation buffer (HBSS supplemented with 20 mM HEPES, 1 mM CaCl₂, 1 mM MgCl₂, and 0.1% BSA) was added. 180 s after furimazine addition, the plate was placed in a SpectraMax iD5 and read using a program consisting of 60 s of shaking, followed by 500 ms integration reads with a 485/20 nm filter, followed by a 535/25 nm filter.

Animal ethics

All animal studies were approved by the Institutional Animal Care and Use Committee (IACUC) at the University of Arizona and were conform to the guidelines for the use of laboratory animals of the National Institutes of Health (NIH publication no. 80–23, 1966), or in accordance with the guidelines of the Danish Animal Experimentation Inspectorate (permission number 2021-15-0201-01036) in a fully AAALAC-accredited facility, under the supervision of the local animal welfare committee at the University of Copenhagen. Experiments using animals are reported in accordance with ARRIVE (Animal Research: Reporting of In Vivo Experiments).

Paw incision model of postoperative pain

Male or female C57Bl/6j mice (6–8 weeks old, The Jackson Laboratory, Bar Harbor, ME) were housed one to six per box (single housing due to fighting) with standard bedding and ad libitum access to standard chow and tap water. Mice were kept in 12 h/12 h light/dark cycles and left to habituate for 1 week prior to testing. To analyze post-surgery acute incisional hypersensitivity, a plantar incision model was used as described by Brennan et al.²². Briefly, a 0.5 cm long incision, from the heel toward the toes, was made through the skin and fascia of the plantar aspect of the left hind paw, including the underlying muscle. The plantaris muscle was then elevated and longitudinally incised, leaving the origin and insertion intact. After hemostasis with gentle pressure, the skin was closed with two mattress sutures of 5–0 nylon on a curved needle.

Measurement of tactile sensory thresholds for postoperative pain model

Tactile sensory thresholds were assessed by measuring the withdrawal response to probing the plantar surface of the hind paw with a series of calibrated fine filaments (von Frey) following administration of peptide or vehicle (saline: 0.9% sodium chloride (NaCl) in sterile water). Each filament was applied perpendicular to the plantar surface of the paw of mice held in suspended wire mesh cages. The “up and down” method was used to identify the mechanical force required for a paw withdrawal response. The size range of stimuli was between 2.44 (0.4 mN) and 4.56 (39.2 mN). The starting filament was 3.61 (3.9 mN). The filament was placed perpendicular to the skin with a slowly increasing force until it bent; it remained bent for approximately 1 s and was then removed. Data were analyzed using the nonparametric method of Dixon, as described by Chaplan et al.²³. The results are expressed as the mean withdrawal threshold that induced a paw withdrawal response in 50% of the animals. Statistical analysis was performed as described in the “Statistical analysis” section below.

Spared nerve injury (SNI) model of neuropathic pain

C57BL/6Nrj male mice, approximately 10 weeks of age (Janvier, France), were housed 1–6 per box (single housing due to fighting) with standard bedding and ad libitum access to standard chow (Altromin 1342, Brogaarden, Denmark) and tap water. Mice were kept in 12 h/12 h light/dark cycles (experiments performed during their inactive phase) and left to habituate to the facility for 1 week prior to testing. Mice were anesthetized with 2% isoflurane gas followed by subcutaneous injection of buprenorphine (0.1 mg/kg, Department of Experimental Medicine, University of Copenhagen (UCPH)), and SNI surgery was performed on the left hind leg as follows. The skin on the lateral surface was incised for approximately 0.5 cm between the hip and knee, followed by cutaneous application of a single drop of a mixture of 10 mg/kg lidocaine and 5 mg/kg bupivacaine (Department of Experimental Medicine, UCPH) before lengthwise division of the biceps femoris muscle, leading to exposure of the three branches of the sciatic nerve. The sural branch was left intact, whereas the peroneal and tibial branches were ligated with a single surgical knot and axotomized distal to the ligation. Wounds were closed with surgical glue, and animals were monitored daily for signs of stress or discomfort, but in all cases, recovered uneventfully. Immediately post-surgery, the mice were administered carprofen (5 mg/kg, Department of Experimental Medicine, UCPH). On day 16 post-surgery, mice were injected i.p. with a volume of 10 µL/g of the indicated doses of Fj1, 30 mg/kg of gabapentin (Sigma Aldrich), or vehicle (phosphate buffered saline).

Measurement of tactile sensory thresholds for SNI model

For the SNI experiments, von Frey filaments ranging from 0.04 to 2 g (g = gram-forces) (0.04, 0.07, 0.16, 0.4, 0.6, 1.0, 1.4, 2.0) were used to determine the mechanical paw withdrawal threshold (PWT). Filaments were applied in ascending order to the frontolateral plantar surface of the hind paws innervated by the sural nerve. Mice were placed in red PVC plastic cylinders (8 (Ø) × 7.5 (h) cm) on a wire mesh and allowed to habituate for a minimum of 20 min prior to the experiment initiation. Each von Frey hair was applied five times with adequate resting periods between each application, and the number of withdrawals was recorded. The withdrawal threshold was determined as the von Frey filament eliciting at least three positive trials out of five applications in two consecutive filaments. A positive trial was defined as a sudden paw withdrawal, flinching, and/or paw licking induced by the filament. The animals were habituated to the experimental room for a minimum of 60 min before the initiation of the experiment, and the experimenter (female) was blinded to the treatment groups. Statistical analysis was performed as described in the Statistical analysis section below.

Structural preparation

Modelling of consomatin Fj1 at the SSTR₄ made use of the X-ray crystal structure of consomatin Ro1 (PDB: 7SMU)¹⁶, and the cryoEM structure of the SSTR₄ in complex with the G_i1 subunit and SST-14 ligand (PDB: 7XMS)²⁴ as modeling templates. Because of the sequence similarity of consomatin ligands and SST-14, specifically the core Trp-Lys receptor-binding motif mimicking the broader conserved Phe-Trp-Lys-Thr residues present within SST ligands, Fj1 was assumed to bind the same orthosteric binding pocket as the endogenous ligands. Modeller (v.10) utility was used to create complexes of ligands bound to the SSTR₄ binding pocket, generating 50 models with the top model assessed using the Modeller objective function to seed subsequent simulations. Due to the absence of N-terminal SSTR₄ residues present within the cryoEM structure, only residues Met47-Phe322 were included within the final complex, with the G_i1 subunit removed. Non-standard amino acids hydroxyproline (Hyp9) and D-tryptophan (D-Trp4) were included, with parameters assigned from the CHARMM36m force field. The resulting complex was inserted into a model POPC membrane using the CHARMM-GUI server and solvated in a box of CHARMM-modified TIP3P (mTIP3P) water, extending > 10 Å beyond all protein atoms. The resulting bilayer spanned an area of 100 × 100 Å², with a total of 130 lipids each in the upper and lower leaflets. Sodium and chloride ions were included to neutralize the system and attain an ionic strength of 0.1 M.

Molecular dynamics simulations

Simulations were performed using the GROMACS v2022)²⁵ package with the CHARMM36m force field^26,27. Temperature coupling was achieved using velocity rescaling applying a coupling time of 0.1 ps with the protein, membrane and water/ions coupled separately at 310 K. Semi-isotropic pressure coupling was maintained using the Parrinello–Rahman method with a coupling time of 2.0 ps. All simulations were performed with a single non-bonded cut-off of 12 Å, with van der Waals interactions switched at 1.0 Å. The Verlet neighbor searching cut-off scheme was applied with a neighbor-list update frequency of 25 steps (50 fs); the time step used in all the simulations was 2 fs. Periodic boundary conditions were applied using the particle-mesh Ewald method to account for long-range electrostatic interactions. The bond lengths were constrained using the P-LINCS algorithm²⁸. Initial minimization and equilibration of all simulations followed established procedures outlined by the CHARMM-GUI via a steepest descent protocol, followed by short positionally restrained equilibration in the NVT (canonical) and NPT ensemble. The systems were then allowed to progress for 1 μs, with each system simulated in 10 replicas, for a total simulation time of 10 μs per consomatin analog.

Statistical analysis

All statistical analyses, fittings, and plotting of curves were performed using GraphPad Prism 10.

For GPCR assays, experiments were conducted in triplicate, and EC₅₀ and pEC₅₀ ± 95% confidence intervals (CI₉₅) were calculated in Prism. When statistical analysis could not be performed (e.g., for peptides with very low activity that did not reach saturation at the highest concentration tested), assays were performed in duplicate. Some peptides, such as controls, were tested in additional independent experiments (i.e., more than three replicates); the number of replicates for these cases is indicated in parentheses in Figs. 1 and 5, as described in the figure legends.

Fig. 1

Computational selection and SSTR profiling of consomatins from a large toxin gene dataset. (A) Principal component analysis (PCA) of 529 SST-like toxin sequences was used as the basis for selecting lead compounds for SSTR screening. Percentages refer to the proportion of the total variance in the data explained by the given principal component. A subset of the PCA plot, including vertebrate SS-like sequences and selected consomatins, is shown (right box). (B) Synthesized consomatin sequences selected from the PCA plot. Cleavage sites and post-translational modifications, such as D-Trp, were predicted based on the original somatostatin-like venom peptide, consomatin Ro1. Cysteines forming intramolecular disulfide bonds are shown in yellow and the essential Trp-Lys motif is highlighted in blue and green. Post-translational modifications are indicated by γ = γ-carboxyglutamate, w = D-Trp, O = hydroxyproline, and # = C-terminal amidation. SST-14 is human somatostatin-14. Seven of the listed sequences are from snails of the Asprella clade; Ro1 and Ro2 from C. rolani, Fj1, Fj2, and Fj3 from C. fijisulcatus, and SuSa1 and SuSa2 from C. sulcatus samiae, two are from the snails of the Phasmoconus clade; Oc3 from C. ochroleucus; Pr1 from C. parius, while pG1 was predicted from the transcriptome of C. geographus from the Gastridium clade¹⁶. (C) Heatmap of activity values of selected consomatins tested at the five human SSTRs using the PRESTO-Tango β-arrestin recruitment assay. Rows correspond to the sequences shown in (B). Data are represented as EC₅₀ (top line, nanomolar, two significant digits shown) and pEC₅₀ ± 95% confidence intervals (CI95) with the number of independent repeats in parentheses (bottom line, two significant decimals shown). Approximate values (~) or “higher than” (>) and “lower than” (<) are used when we did not obtain full curves within the concentrations tested (see Fig. S1 for representative curves).

For the paw incision model, the effects at different time points were analyzed using two-way ANOVA with Geisser-Greenhouse correction and Dunnett’s post-test for multiple comparisons (all compared to vehicle), while the area under the curve plot was analyzed using one-way ANOVA with Dunnett’s post-test for multiple comparisons (all compared to vehicle). For the SNI model, the effect over time was analyzed as described for the paw incision model (all compared to the vehicle on the ipsilateral side), while the area under the curve was analyzed using a two-way ANOVA with Dunnett’s post-test for multiple comparisons (all compared to the vehicle on the ipsilateral side).

Images and visual representation

All graphs were created using either GraphPad Prism 10 or a custom Python script for heatmaps (https://github.com/Aephir/create_heatmap, v2.0.6 used). All images that are not data graphs or plots were created using Biorender, Adobe Illustrator, and/or Inkscape.

Data analysis

The BRET signals in the G protein dissociation assay were calculated by dividing the signal at 535 nm by that at 485 nm. All concentration–response curves were fitted using a variable slope (four-parameter) equation:

$$Y = \frac{{R_{min} { } + { }(R_{\max - } { }R_{min} )}}{{1 + 10^{{\left( {logEC_{50} - X} \right) \times Hill slope}} }}$$

(1)

Potency calculations were performed using log10 transformed values (pEC₅₀) before transforming the average to EC₅₀ values.

For the MD data, representative orientations of ligand complexes were determined by clustering all simulation replica trajectories (limited to 100,000 frames) using the GROMOS method with a cut-off between clusters of 0.25 nm. VMD was used along with the tachyon renderer for visualization, and the images were encoded to produce videos with ffmpeg.

Results

Identification of candidate SSTR agonists from large venom gene library

We recently discovered that cone snails have evolved a family of peptide toxins called consomatins, which resemble the hormone SST and related peptides like cortistatin and urotensin¹⁷. These toxins originated from an SST-like peptide used in the snail’s own internal signaling and later diversified after being recruited into the venom system¹⁷. To identify consomatins that might target vertebrate SSTRs, especially the SSTR₄, we analyzed genomic data from 247 cone snail species. We found 529 consomatin sequences across 169 species and used principal component analysis (PCA) to explore their evolutionary relationships. We also included three previously characterized consomatins (Ro1, Ro2, and pG1^16,29) in our analysis. Since cone snails specialize in different prey (worms, snails, or fish), we compared their toxins to natural SST-like peptides from vertebrates, annelid worms, and mollusks. As seen in our previous study¹⁷, toxins from worm-hunting snails grouped with worm hormones, while many fish-hunting snail toxins (including Ro1) clustered with vertebrate peptides (Fig. 1A). No consomatins were found in snail-hunting species. For subsequent experimental testing, we prioritized toxin sequences from fish-hunting species over those from worm hunting species, as the fish SST receptors targeted by these toxins show greater similarity to human receptors than those of worms. Furthermore, we focused on species that are closely related to the species expressing consomatin Ro1, Conus rolani from the Asprella clade. Finally, we selected those sequences that clustered closely with vertebrate hormones in the PCA, as they were more likely to activate human SSTRs. The final list of candidates is shown in Fig. 1B.

Receptor profiling identifies potent and selective agonist of the SSTR₄

The predicted mature peptide sequences selected from the PCA plot were synthesized to > 90% purity using standard solid-phase peptide synthesis and verified using reverse-phase high-performance liquid chromatography and mass spectrometry. Post-translational modifications were predicted based on modifications previously observed for the venom peptide consomatin Ro1¹⁶. Modifications included γ-carboxylation of Glu, hydroxylation of Pro (Hyp), L-to-D epimerization of a Trp positioned within the disulfide loop, and C-terminal amidation based on the presence of a Gly-Arg/Lys motif³⁰. Disulfide bonds were predicted based on the presence of two cysteine residues. We note that the predicted modifications and the proteolytic N- and C-terminal cleavage sites may differ from those found in the native toxins. Future proteomics studies on collected venom are needed to establish the exact chemical identity of the toxins studied here.

Synthetic peptides were screened at the five human SSTRs using the PRESTO-Tango β-arrestin recruitment assay²⁰ (Fig. 1C and Fig. S1). Human somatostatin-14 (SST-14) and the previously characterized peptides, consomatin Ro1 and pG1, were included for comparison. The eight new peptides that were tested showed a range of SSTR activity profiles demonstrating that cone snail venoms are a rich source for the discovery of novel ligands of the human SSTRs (Fig. 1C). For example, Fj2 activates the SSTR₂ and SSTR₄ with EC₅₀ values of 0.20 µM and 2.0 µM, respectively, Pr1 activates the SSTR₁ and SSTR₂ with EC₅₀ values of 130 nM and 41 nM, respectively, and Oc3 shows activity at SSTR₂, SSTR₃, and SSTR₄ with EC₅₀ values ranging from 5.0 nM to 4.2 µM. Interestingly, although the sequence of Ro2 is distinct from the previously characterized Ro1, the two peptides that are both derived from the same cone snail species, C. rolani, have very similar activity profiles at the human SSTR₁ and SSTR₄. Notably, none of the peptides tested showed any significant activity at SSTR₅, although it should be noted that the peptides were tested for agonism only; thus, we cannot rule out antagonist activity. Of particular interest to us was Fj1, which activated the SSTR₄ with an EC₅₀ value of 22 nM, showing 173-fold selectivity over SSTR₁ (EC₅₀ = 3.8 µM) and no measurable activity at the other three receptor subtypes when tested at concentrations up to 100 µM.

Consomatin Fj1 is a somatostatin evolog with a minimized receptor binding motif

Consomatin Fj1 is a ten amino acid long cyclic peptide from Conus fijisulcatus that contains four residues inside a disulfide loop and two residues at both its N- and C-termini (Sequence: Pro1-Val2-Cys3-D-Trp4-Lys5-Phe6-Gly7-Cys8-Hyp9-Leu10, Fig. 2A,B). The minimized disulfide loop of Fj1 closely mirrors that of several SSTR₂-selective somatostatin drug analogs, such as octreotide and lanreotide. Incorporation of a shortened disulfide loop and a D-Trp in these analogs significantly prolonged their half-lives compared to the native human hormone⁹. In contrast to these analogs, which were developed using medicinal chemistry approaches, consomatin Fj1 and other consomatins evolved from an endogenous SST-like signaling peptide following the principles of natural selection. Thus, we refer to these naturally evolved analogs as evologs¹⁶. Notably, despite these distinctively different approaches, the final products exhibit a remarkably high degree of similarity (Fig. 2B). One notable difference that distinguishes consomatin Fj1 from other SST analogs and evologs is that the characteristic D-Trp-Lys motif essential for SSTR activation⁶ resides immediately following the first cysteine residue (Fig. 2B). As discussed in more detail below, these differences partly contribute to the potency and selectivity of the peptide for the SSTR₄.

Fig. 2

Consomatin Fj1 is a naturally evolved SSTR₄-selective somatostatin evolog. (A) Chemical structure of consomatin Fj1, a ten-residue long cyclic peptide predicted from the venom gene-encoding exons of Conus fijisulcatus. Standard amino acid one or three letter abbreviations are used, extended with O/Hyp = 4-hydroxyproline, w/D-Trp = D-tryptophan, and -ol = C-terminal alcohol group in place of a carboxylic acid group. (B) Schematic comparison of the contrasting origins of consomatin Fj1 and the SST drug analog octreotide, both representing minimized SST scaffolds. Fj1 is a minimized SSTR₄-selective evolog that originated from an endogenous SS-like signaling gene, while the SSTR₂-selective drug analog octreotide was designed using medicinal chemistry approaches. (C) Representative concentration–response curves for G protein (Gα_oA) dissociation of SST-14 and Fj1 at the five human SSTRs. Fj1 shows nM potency at the human SSTR₄, with low potency at SSTR₁ and no discernable activity at the other SSTR subtypes at 1 µM. Error bars represent the standard deviation of two technical replicates.

Consomatin Fj1 induces G protein dissociation at the SSTR₄

To determine downstream receptor signaling using native receptor sequences, we assessed the activity of Fj1 at the SSTR₄ using a BRET-based assay that measures GPCR activation by monitoring the association of labeled Gβγ subunits and a G protein-coupled receptor kinase (GRK) fragment, following dissociation of Gβγ subunits from the Gα subunit²¹. We tested the activity of Fj1 at the SSTR₄ using a range of different Gα proteins in the Gα_i family, including Gα_i1, Gα_i2, Gα_i3, as well as the two dominant splice variants of Gα_o, and observed similar potencies for each Gα protein (Fig. S2). As the Gα_o type is the most highly expressed type in DRGs³¹, the proposed site for SSTR₄-mediated analgesia, we performed subsequent tests with the canonical Gα_o sequence (Gα_oA). Here, we observed similar overall receptor activation profiles as in the PRESTO-Tango screening assay: potent activation of SSTR₄ (EC₅₀ = 6.0 nM) with only limited activity at SSTR₁ (~ 30% activation at 1 µM) and no activation of the SSTR_2,3,5 when tested at up to 1 µM (Fig. 2C).

Peripheral consomatin Fj1 administration provides analgesia in a postoperative pain model

Having established that consomatin Fj1 selectively activates the SSTR₄ in the PRESTO-Tango and G protein dissociation assays, we next performed a dose response study for potential analgesic action in a model of postoperative pain, the paw incision model³². C57BL/6 J male mice injected intraperitoneally (i.p.) with 0.04–2.5 mg/kg of Fj1 and its effect on post-incision mechanical hypersensitivity was evaluated (Fig. 3A,B). Fj1 dose-dependently reduced post-incisional mechanical hypersensitivity, as measured by paw withdrawal thresholds in response to von Frey filament stimulation, with maximal effect observed at the dose of 2.5 mg/kg, and a peak effect observed at 1 h. The positive control used was morphine sulfate (5 mg/kg). While morphine exhibited higher peak efficacy than Fj1, the duration of action was shorter. Even at the 5 h time point, the mice treated with 2.5 mg/kg of Fj1 showed an increased paw withdrawal threshold of about 28% of maximum Fj1 response (P = 0.0284, as compared to vehicle). Both in the groups treated with 0.04 mg/kg and with 0.1 mg/kg of Fj1, there was a similar trend as for 2.5 mg/kg, though neither reached a statistically significant difference from the vehicle control at any time point (P = 0.2936 and P = 0.0565, respectively, at 2 h). When tested in female mice, we observed similar results with one noticeable difference (Fig. 3C,D). While the effect was statistically significant at 2.5 mg/kg of Fj1, it was not as robust as for the males with a lower effect size observed both at 0.5 h and 1 h. By administering 5 mg/kg to females, the effect more closely followed the effect of 2.5 mg/kg in males.

Fig. 3

Consomatin Fj1 provided analgesia in two mouse models of pain. Post-surgical pain model (paw incision) in either male (A,B) or female (C,D) mice. Plantar incision surgery was performed 24 h post-surgery, and mice were administered morphine sulfate (5 mg/kg), indicated doses of Fj1, or vehicle (saline) by intraperitoneal (i.p.) injections, whereafter mechanical hypersensitivity was evaluated at indicated times (A,C). Values represent mean ± CI95 from six mice. A summary of the area under the curve is shown (B,D), where each data point represents one mouse, and the error bars represent CI95. (E,F) Neuropathic pain model (spared nerve injury, SNI). The peroneal and tibial branches of the sciatic nerve of the left hindleg were ligated, 16 days post-surgery, the mice were administered gabapentin (30 mg/kg), indicated doses of Fj1, or vehicle (phosphate buffered saline) by i.p. injections, whereafter mechanical hypersensitivity was evaluated at indicated times (E). Values represent the mean ± CI95 from five (gabapentin) or six (all other conditions) mice. A summary of the area under the curve is shown (F), where each data point represents one mouse, and the error bars represent CI95. Statistical analysis was performed as described in the methods section. Asterisks indicate P values < 0.05 (*), 0.01 (**), 0.001 (***), and 0.0001 (****) as compared with the vehicle control.

Peripheral consomatin Fj1 administration provides analgesia in a neuropathic pain model

Activation of the SSTR₄ has previously been shown to provide analgesia in rodent models of neuropathic pain^14,33,34,35. Drugs that are effective in postoperative pain may not be efficacious in neuropathic pain states and vice a versa. In general, neuropathic pain is particularly difficult to treat; many current treatment options are only effective in a limited subset of patients and can elicit severe side effects^36,37,38. To assess whether Fj1 could alleviate the mechanical hypersensitivity associated with neuropathic pain, the peptide was tested in the spared nerve injury (SNI) model of peripheral neuropathic pain using male C57BL/6 mice. The sciatic nerve was injured on one side of the mouse (ipsilateral side), whereas the other side (contralateral side) served as a control. On day 16 post-injury, either 0.5 mg/kg or 5 mg/kg of Fj1, 30 mg/kg of gabapentin, or vehicle was administered by i.p. injection (Fig. 3E,F). Both doses of Fj1 reduced mechanical hypersensitivity 30 min after injection, and this effect was more pronounced after 1 h. For the 0.5 mg/kg dose, the effect persisted at 2.5 h, while for the 5 mg/kg dose, the tendency was the same, albeit not reaching statistical significance (P = 0.0548 compared to vehicle). These results demonstrate that Fj1 can provide potent and efficacious analgesia in this model, although with a slower onset and shorter duration of action than 30 mg/kg of gabapentin.

Molecular dynamics simulation reveals the binding mode of Fj1 at the SSTR₄

To investigate the binding mode of Fj1 at the SSTR₄ and better understand the molecular basis for the peptide’s selectivity and potency, we performed molecular dynamics (MD) simulations in the µs range of Fj1 to the holo-SSTR₄ embedded within a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayer. The binding mode of consomatin Fj1 was stabilized and almost exclusively characterized through the side chain interactions of D-Trp4 and Lys5 with receptor residues (Fig. 4A). D-Trp4 buried deep within the hydrophobic core cavity formed by the side chains of Leu123^3×29, Met130^3×36, Phe131^3×37, Ile181^4×61, Leu200^45×52, and Phe275^6×51 (superscripts denote the GPCRdb numbering scheme outlined by Isberg et al.³⁹). Interestingly, D-Trp4 occupied the same binding pocket as the corresponding L-Trp of SST-14 observed in the recent cryogenic electron microscopy (cryoEM) structure of SSTR₄ (PBD ID: 7XMS)²⁴ (Fig. 4B). Lys5 forms a salient salt bridge with the side chain of Asp126^3×32, also mirroring the conformation and interactions of the corresponding Lys9 in SST-14. Additionally, Lys5 in Fj1 also demonstrated transient yet notable hydrogen bonding to the side chain of Ser300^7×41 during simulation. On the opposite face of the side chain, Lys5 maintains a side-by-side stacking arrangement against the indole ring of D-Trp4, which is also present in the monomeric structure of Fj1, and is characteristic of SST receptor binding and activation⁶. Both D-Trp4 and Lys5 demonstrated limited sampling of other conformations throughout the simulation.

Fig. 4

Molecular Dynamics (MD) simulations reveal contacts between Fj1 and SSTR₄. (A) Representative orientation of Fj1 (orange stick representation) in complex with SSTR₄ (gray ribbon representation). The membrane present within the simulation was removed for clarity. The interactions made by Fj1, which facilitated binding, are labeled. The representative binding mode was obtained by clustering all replicate trajectories, with a model representing the largest cluster displayed. (B) Overlay of Fj1 (orange) and SST-14 (blue, PDB 7XMS) in complex with SSTR₄ (dark gray). (C) The orientation of Fj1 throughout a representative 1 µs simulation is shown with 10 snapshots colored from blue to white to red. (D) Representative orientation of Fj1 (orange) from the simulation when in complex with SSTR₄, overlaid with SST-14 in complex with the same receptor construct (gray, PDB 7XMS).

In contrast to the persistent orientation adopted by D-Trp4 and Lys5, residues bordering and outside the cyclic core, Pro1, Cys3, Phe6, Cys8, Hyp9, and Leu10 (i.e., with the exception of Val2) displayed considerable mobility, demonstrating limited persistent contacts describing the ligand-bound orientation (Fig. 4C,D). Likewise, residues outside of the conserved pharmacophore (Phe7-Trp8-Lys9-Thr10) in SST-14 do not form significant side chain interactions with SSTR₄, as has been observed with SSTR₂²⁴, instead forming more backbone and intramolecular interactions (most notably between Phe6-Phe11). The short cyclic core (four residues in Fj1, compared to ten residues in SST-14) does not protrude significantly beyond the binding pocket and aligns well with the smaller four-residue pseudo-core formed between Phe6 and Phe11 of the SSTR-bound structure of SST-14. Val2 presents a somewhat smaller hydrophobic interface within the helical core, packing between residues Val212^5×40 of helix 5 and Leu283^6×59 of helix 6, occupying a position similar that to of Phe7 in SST-14. These simulations showed that Fj1 binds SSTR₄ in a manner similar to SST-14, particularly in regard to the Trp-Lys motif, and that residues outside of this could be amenable to modification while retaining SSTR₄ binding.

Analog design provides improved agonists and scaffolds for future drug development

To assess the molecular determinants of SSTR₄ potency and selectivity in the G protein dissociation assay, we first performed alanine scanning of the four amino acids in the loop that were buried in the binding pocket of the receptor (Fig. 5). As expected, mutating key residues known to be important for the binding of somatostatin⁶, Trp4 (Fj1A1) and Lys5 (Fj1A2), to Ala markedly decreased potency by 5000-fold and 730-fold, respectively. The mutation of Phe6 (corresponding to Thr10 in SST-14, see Fig. 4D) to Ala (Fj1A3) also decreased the potency by 630-fold. However, mutating either Gly7 to an Ala (Fj1A4) or deleting it, thereby shortening the loop (Fj1A5), resulted in a slight increase in potency at SSTR₄ (6.2-fold and 65-fold, respectively) with no discernable increase in potency at other SSTRs. Next, we assessed the role of the predicted post-translational modifications. Changing D-Trp and L-Hyp, to their unmodified equivalents, L-Trp and L-Pro (Fj1A6 and Fj1A7, respectively), had virtually no effect on the SSTR₄ potency, although both showed an increase in SSTR₁ potency. Another epimerization, the substitution of L-Phe6 to D-Phe (Fj1A8), on the other hand decreased the potency at SSTR₄ by 42-fold. Since the MD simulations suggested that residues outside the cyclic core did not form significant and salient interactions with the receptor, we tested the “minimal core” peptide Cys3-D-Trp4-Lys5-Phe6-Gly7-Cys8 (Fj1A9). This decreased the potency by 47-fold, while deleting only the N-terminus (Fj1A10) resulted in a 13-fold decrease in potency. However, deletion of only the C-terminus (Fj1A11) resulted in an analog that was virtually equipotent at the SSTR₄.

Fig. 5

Analog design and testing identified improved ligands for SSTR₄-selective drug development. (A) Identifiers and sequences of SST-14, Fj1, and the analogs of Fj1. Sequences (left) show the Cys residues forming the intramolecular disulfide in Fj1 and its analogs highlighted in yellow. For all sequences, the Trp residue is shown in blue, the Lys residue in green, and all modifications in the analogs, as compared to Fj1, are highlighted in red. Sequences use standard amino acid one-letter abbreviations extended with O = hydroxyproline and lower-case letters denoting D-amino acids. (B) Heatmap showing the potency of Fj1 and its analogs at the five human SSTRs in the G protein dissociation assay using Gα_oA. The text in each cell represents the EC₅₀ value (first line, nanomolar, two significant digits) and the pEC₅₀ ± CI95 (two significant decimals) with the number of independent repeats for each in parentheses (second line). Approximate values (~) or “higher than” (>) and “lower than” (<) are used when we did not obtain full curves within the concentrations tested (see Fig. S3 for representative curves). The known SSTR₁ and SSTR₄ peptide agonist, TT-232 was also tested. However, we note that we could not dissolve it at sufficiently high concentrations to fully test this peptide in the assay used).

Recently, we identified consomatin pG1 as a potent and selective agonist of the SSTR₂^16,29. To investigate whether determinants from pG1 could be used to improve the potency of Fj1, we designed a hybrid analog combining the cyclic core residues of Fj1 with the amino acids flanking the pG1 core (Fj1A12). This hybrid analog showed a 92-fold increase in potency at the SSTR₄, although with a corresponding increase at the SSTR₁ and SSTR₅. Interestingly, this did not lead to increased potency at the SSTR₂. Introducing only the N-terminus of pG1 (Fj1A13) increased potency by 11-fold at the SSTR₄, with SSTR₁ activity similar to that of Fj1A12. With the suggestion from Fj1A11, that the Fj1 C-terminus was not required, we next tested the effect of adding the C-terminus from pG1, namely the single Trp residue, to Fj1. This analog (Fj1A14) showed an 85-fold increase in potency at the SSTR₄, with no enhanced activity observed at the other receptor subtypes, including the SSTR₁. Given the apparent redundancy of Gly7, we evaluated whether replacing Gly7 with hydrophilic amino acids to decrease the hydrophobicity of the peptide could be tolerated. Substituting Gly9 with Ser (Fj1A15) or Asn (Fj1A17) slightly increased the potency at SSTR₄ (14-fold and 6.8-fold, respectively), whereas a Thr at this position (Fj1A16) retained the SSTR₄ potency of Fj1, while showing a slight increase in SSTR₁ activity. Based on these observations, we next assessed whether the increased potency of Fj1A14 could be combined with the polar substitutions of Gly7. While a Ser in place of Gly7 (Fj1A18) was well tolerated at the SSTR₄, both the Thr and Asn substitutions (Fj1A19 and Fj1A20, respectively) showed a slight decrease in SSTR₄ potency compared to Fj1A14. However, all three double substitutions increased SSTR₁ activity, thereby decreasing selectivity.

These results show that while Fj1 was the most potent and selective SSTR₄ peptide agonist identified from venom-encoding genes, there are clear opportunities for further optimization of the peptide’s potency, selectivity, and physiochemical properties such as hydrophilicity.

Discussion

Cone snail venoms are a rich source of bioactive peptides, several of which have become valuable tools in biomedical research and pain drug development (reviewed in⁴⁰). One notable example is ω-MVIIA (ziconotide), a peptide from Conus magus that blocks the Cav2.2 calcium channel to inhibit pain signaling in the central nervous system (CNS)⁴¹. Ziconotide not only highlighted the role of Cav2.2 in pain but also became an FDA-approved drug for chronic, intractable pain⁴². Another analgesic peptide from Conus geographus, contulakin-G (CGX-1160), shares structural similarity with the human neuropeptide neurotensin⁴³. Although its exact mechanism is unclear, evidence suggests contulakin-G modulates the neurotensin 2 receptor (NTSR2), leading to inhibition of the R-type calcium channel (Cav2.3) in the spinal cord⁴⁴. Despite its promising pain-relieving effects, the development of contulakin-G was halted due to company closure⁴².

More recently, we identified consomatin Ro1, an analgesic peptide from C. rolani that activates the SSTR₁ and SSTR₄¹⁶. Unlike ziconotide and contulakin-G, Ro1 acts peripherally, offering potential advantages such as non-invasive administration and reduced CNS side effects like addiction or respiratory depression. Building on this, we discover consomatin Fj1, a novel and potent SSTR₄ agonist derived from C. fijisulcatus. Like Ro1, Fj1 belongs to a group of peptides called consomatins, which mimic the structure and function of somatostatin-like hormones. Fj1 demonstrates superior potency and selectivity for the SSTR4 receptor and shows therapeutic promise in preclinical pain models.

Conus rolani and C. fijisulcatus are members of the Asprella clade, deep-sea, fish-hunting cone snails^45,46. Unlike most cone snails that induce rapid prey paralysis, Asprella snails use a delayed “ambush-and-assess” strategy, in which prey becomes incapacitated over 15 min to several hours¹⁶. This suggests the presence of venom components that suppress escape responses rather than fast-acting ion channel blockers, making these snails especially promising for the discovery of novel analgesics. In this study, we focused on consomatin sequences that activate SSTR₄, however, Asprella venoms likely harbor additional analgesic compounds yet to be identified.

Consomatin Fj1 features a unique structural motif (Cys-D-Trp-Lys) that supports its high potency and SSTR₄ selectivity. MD simulations revealed a binding mode similar to that of human SST-14, the natural ligand for somatostatin receptors (see Fig. 4B,D). Notably, Fj1’s D-Trp occupies the same binding pocket as SST-14’s L-Trp^24,47, while the D-amino acid helps to stabilize the peptide and resist enzymatic degradation.

To further optimize Fj1, we performed structure–activity studies and generated analogs to explore the role of individual residues. A “core” linked by the disulfide loop and consisting of six amino acids (Fj1A9) retained activity at SSTR₄, although it was less potent. Removing residues at the N-terminus reduced potency, while trimming the C-terminus had minimal impact. One analog, Fj1A12, showed improved potency when a Trp residue from another consomatin (pG1)²⁹ was added to the C-terminus. Further analogs revealed that the Gly residue within the disulfide loop could be modified to enhance potency or solubility, though some modifications affected selectivity. Overall, our results indicate that Fj1 can be optimized further while maintaining or improving selectivity for the SSTR₄.

The small molecule SSTR₄ agonist, J-2156, which has been reported to be approximately 360-fold selective for SSTR₄ over SSTR₁ and 390-fold over SSTR₅ in binding assays⁴⁸, has been widely used in the literature^{14,15,33,35,48,49}. However, peptide agonists that can distinguish between SSTR₁ and SSTR₄, two closely related subtypes, have not been previously reported. The most widely used peptide agonist at the SSTR₄ is the heptapeptide, TT-232, which suffers from low potency and a 6.5-fold reported selectivity over SSTR₁⁵⁰. Using the venom peptide Fj1 as an inspiration, this study provides several analogs with significantly improved potency and selectivity over previously described peptide agonists and suggests additional opportunities for further optimization.

Moreover, having a potent and selective peptide agonist of the SSTR₄ expands the repertoire of existing drug leads for this target from small molecules to peptides. Peptides, especially those that have evolved by nature, often display better selectivity and fewer off-target effects or complications from hepatic metabolism⁵¹. They are also often easier to peripherally restrict, which is a strategy employed for instance in developing peripherally restricted opioid receptor agonists⁵², and was observed for Fj1 (Supplemental Tables S1–S2). One challenge with peptide drugs is their short in vivo half-life. Fj1, for example, has a half-life of 8.7 min after intraperitoneal injection (Supplemental Tables S3–S4). However, various peptide conjugation strategies can extend duration of action—many modern peptide drugs now have once-weekly dosing regimens⁵³. Given the rising success of peptide-based therapeutics^54,55, Fj1’s profile is promising for future development.

We tested Fj1 in two rodent models of pain: the incision model (for postoperative pain) and the spared nerve injury (SNI) model (for neuropathic pain). Both models showed significant reductions in mechanical hypersensitivity following a single dose of Fj1. In the incision model, injury activates both C- and Aδ-fibers and triggers a local inflammatory response⁵⁶. Fj1’s effect was more sustained than morphine’s, possibly due to its action on inflammation or a slower receptor dissociation rate. SSTR₄ expression is upregulated during inflammation⁵⁷, and activation of this receptor has been shown to reduce inflammatory pain in preclinical studies^10,58,59. The prolonged analgesic effect of Fj1 may therefore result from SSTR4-mediated inhibition of inflammation following injury, though differences in receptor binding kinetics or pharmacokinetics could also contribute. In the SNI model, both 0.5 and 5.0 mg/kg doses of Fj1 were effective at the 1-h mark, with no further benefit at the higher dose, indicating that 0.5 mg/kg may be saturating. At 2.5 h, the higher dose showed more pronounced effects, likely due to pharmacokinetic factors. These findings suggest that Fj1 effectively alleviates pain behaviors in two distinct types of pain and holds potential for treating both inflammatory and neuropathic conditions.

Our study has several limitations. Although MD simulations support Fj1’s binding mode, an experimental structure is needed for full validation. Additionally, despite promising potency and selectivity, Fj1’s pharmacokinetic properties will need optimization before clinical development and the SSTR4-mediated mechanism of action proposed here should be confirmed using SSTR4 knockout mice in the future. Additionally, although we did not observe any obvious behavioral changes in animals injected with the peptide, dedicated assays will be needed to evaluate potential motor or other side effects of Fj1, such as rotarod or open-field tests. Most importantly, clinical validation of SSTR₄ as a pain target is incomplete. While a small-molecule SSTR₄ agonist showed efficacy in a phase II trial for diabetic neuropathy, trials for osteoarthritis and chronic low back pain did not meet endpoints⁶⁰. No trials have yet investigated SSTR₄-targeting drugs for postoperative pain, the setting in which Fj1 was most effective in our models. Further studies are needed to understand which preclinical models best predict human outcomes for SSTR₄-targeted therapies. Additionally, in-depth exploration of sex differences in SSTR₄ signaling may be important, as variations in treatment responses based on sex are common in pain research.

Conclusion

Consomatin Fj1 represents a new class of venom-derived, peripherally acting peptide agonists targeting SSTR₄. Its potent analgesic effects in rodent models, coupled with its selectivity and modifiability, make it a promising drug lead for non-opioid pain treatment. As the search for effective, non-addictive pain therapies continues, venom-derived peptides like Fj1 may offer a novel path forward.