Recombinant Conus radiatus Iota-conotoxin-like R11.17

What is the molecular structure of Recombinant Conus radiatus Iota-conotoxin-like R11.17 and how does it compare to native ι-RXIA?

Recombinant Conus radiatus Iota-conotoxin-like R11.17 is likely structurally similar to ι-RXIA, which contains an unconventional D-phenylalanine residue near its C-terminus. This unusual structural feature plays a significant role in the peptide's function. The solution structure of ι-RXIA reveals a compact, disulfide-rich conformation that is stabilized by multiple disulfide bonds. Compared to the native peptide, the recombinant version should maintain the same amino acid sequence and disulfide bonding pattern, although ensuring proper D-amino acid incorporation presents a significant challenge in recombinant production systems. Structural studies using NMR spectroscopy would be necessary to confirm identical folding between recombinant R11.17 and native ι-RXIA.

What is known about the iota-conotoxin family from Conus radiatus to which R11.17 belongs?

The iota-conotoxin family from Conus radiatus represents an excitatory group of conotoxins that includes at least 16 homologous peptides identified from this single species. Unlike other conotoxin families like μ-conotoxins (which block the sodium channel pore) or δ-conotoxins (which inhibit channel inactivation), iota-conotoxins shift the voltage-dependence of sodium channel activation to more hyperpolarized potentials. This unique mechanism makes them valuable research tools. This peptide family contains members like ι-RXIA that induce seizures when injected intracranially into mice and produce repetitive action potentials in motor axons. The extensive molecular diversity within this single family highlights the evolutionary strategy of cone snails to develop highly specialized venom components with precise physiological effects.

How does the selectivity of R11.17 compare to other conotoxins from the same species?

Conus radiatus produces multiple toxin families with distinct target selectivity. While iota-conotoxins like R11.17 primarily target voltage-gated sodium channels (with preference for Nav1.6 > Nav1.2 > Nav1.7), other peptides from the same species target completely different ion channels. For example, κM-RIIIK and κM-RIIIJ from Conus radiatus target potassium channels, specifically Kv1-family channels. κM-RIIIK blocks Shaker K channels with an IC50 of ~1 μM and has even higher affinity for TSha1, a Shaker homolog from trout (IC50 ~20 nM). κM-RIIIJ has ~10-fold higher potency (~30 nM) for blocking homomeric Kv1.2-mediated currents compared to RIIIK. This diversity of targets from the same species demonstrates the remarkable molecular complexity of cone snail venoms and their evolutionary specialization.

What expression systems are most suitable for producing functional Recombinant R11.17?

The optimal expression system for R11.17 depends on whether it contains the D-phenylalanine residue found in ι-RXIA. Standard prokaryotic and eukaryotic expression systems cannot directly incorporate D-amino acids. For R11.17 variants lacking D-amino acids, E. coli expression systems using periplasmic targeting (which provides an oxidizing environment for disulfide formation) or fusion with thioredoxin/other solubility tags can be effective. For peptides containing D-amino acids, solid-phase peptide synthesis followed by oxidative folding is the recommended approach. Alternatively, a semi-synthetic approach can be used where the peptide is recombinantly produced with an L-amino acid, then enzymatically converted post-purification using an isomerase. Each method requires optimization of folding conditions to ensure proper disulfide bond formation essential for biological activity.

What are the critical quality control parameters for ensuring proper folding of recombinant R11.17?

Multiple complementary analytical techniques should be employed to verify proper folding:

The gold standard remains functional validation through electrophysiological recordings, as proper folding is essential for the peptide to exert its characteristic effect of shifting the voltage-dependence of sodium channel activation.

How can the D-phenylalanine residue be incorporated into recombinant R11.17 production?

Incorporating the D-phenylalanine residue into recombinant R11.17 presents a significant challenge since standard recombinant expression systems cannot directly incorporate D-amino acids. Several methodological approaches can address this:

• Chemical synthesis: Solid-phase peptide synthesis allows direct incorporation of D-phenylalanine during synthesis.

• Enzymatic conversion: Produce the peptide recombinantly with L-phenylalanine, then employ phenylalanine isomerase enzymes to convert specific residues post-purification.

• Semi-synthetic approaches: Produce peptide fragments recombinantly, with chemical synthesis of the D-Phe-containing segment, followed by native chemical ligation.

• Genetic code expansion: Emerging technologies for incorporating non-canonical amino acids, though currently limited for D-amino acids.

The importance of this modification is highlighted by studies showing that the analog with L-Phe instead (ι-RXIA[L-Phe44]) had two-fold lower affinity and faster off-rate than ι-RXIA on Nav1.6 and was completely inactive on Nav1.2, demonstrating the critical role of this D-amino acid in determining both potency and selectivity.

How does R11.17 modulate sodium channel function compared to other sodium channel-targeting toxins?

R11.17, like other iota-conotoxins, employs a unique mechanism of action among sodium channel toxins. Unlike μ-conotoxins (which block the channel pore) or δ-conotoxins (which inhibit inactivation), iota-conotoxins shift the voltage-dependence of activation to more hyperpolarized potentials. This means the channels open at more negative membrane potentials than they normally would, leading to neuronal hyperexcitability. This mechanism can be quantified through voltage-clamp protocols that determine the half-maximal activation voltage (V1/2) before and after toxin application. For ι-RXIA acting on Nav1.6, this shift is significant and concentration-dependent. This distinct mechanism makes iota-conotoxins valuable for investigating how altered gating properties contribute to neuronal excitability and potentially for studying channelopathies characterized by shifts in activation parameters.

What electrophysiological protocols are most appropriate for characterizing R11.17 activity?

To properly characterize R11.17's effects on sodium channels, the following electrophysiological protocols are recommended:

• Activation protocols: Incrementally depolarizing voltage steps from a hyperpolarized holding potential to generate conductance-voltage (G-V) relationships before and after toxin application. Data should be fit to Boltzmann equations: G/Gmax = 1/(1+exp[(V-V1/2)/k]), where V1/2 is the half-maximal activation voltage and k is the slope factor.

• Steady-state inactivation protocols: Conditioning prepulses followed by a test pulse to determine availability-voltage relationships.

• Concentration-response measurements: Determine EC50 values for the shift in V1/2 by applying increasing toxin concentrations.

• Kinetic protocols: Measure time course of toxin effects to determine kon and koff rates.

• Subtype selectivity testing: Apply protocols to cells expressing different sodium channel subtypes to establish selectivity profile.

For ι-RXIA, two-electrode voltage clamp in Xenopus oocytes and patch-clamp recordings in mammalian expression systems have successfully characterized its effects, with the linear relationship between kobs and toxin concentration indicating a bimolecular reaction mechanism with a Kd of approximately 3 μM for Nav1.6.

What is the sodium channel subtype selectivity profile of R11.17 and how should it be experimentally determined?

Based on data from related iota-conotoxins like ι-RXIA, R11.17 likely exhibits selectivity among sodium channel subtypes. For ι-RXIA, the order of sensitivity was Nav1.6 > Nav1.2 > Nav1.7, with other subtypes (Nav1.1, Nav1.3, Nav1.4, Nav1.5, and Nav1.8) being insensitive. To comprehensively determine the selectivity profile of R11.17, the following experimental approach is recommended:

• Expression of individual sodium channel α-subunits (Nav1.1-Nav1.9) with the β1 subunit in a controlled expression system (e.g., Xenopus oocytes or HEK293 cells).

• Application of standardized voltage protocols to assess shifts in activation parameters across all subtypes.

• Construction of complete concentration-response curves for each channel subtype.

• Determination of EC50 values and maximal efficacy for each subtype.

• Confirmation in native neurons expressing identified channel subtypes (e.g., DRG neurons for Nav1.8/1.9).

This systematic approach allows for quantitative comparison of potency and efficacy across channel subtypes, establishing a comprehensive selectivity profile essential for using R11.17 as a research tool.

How do mutations in R11.17 affect its binding affinity and sodium channel subtype selectivity?

Structure-function studies of iota-conotoxins provide insight into how specific residues contribute to function. For ι-RXIA, the D-phenylalanine near the C-terminus is critical, as replacing it with L-phenylalanine (ι-RXIA[L-Phe44]) resulted in two-fold lower affinity and faster off-rate on Nav1.6, and complete loss of activity on Nav1.2. This demonstrates that even subtle stereochemical changes can significantly impact both potency and selectivity. To systematically investigate structure-function relationships, alanine scanning mutagenesis (replacing individual residues with alanine) can identify critical binding determinants. Additionally, charge reversals of basic residues often found in conotoxins can reveal electrostatic interactions important for channel binding. Cross-referencing mutation effects with the three-dimensional structure can create a functional map of the toxin surface, identifying the active binding face that interacts with the channel.

What structural features determine R11.17's preference for specific sodium channel subtypes?

The molecular basis for sodium channel subtype selectivity of iota-conotoxins likely involves interactions with non-conserved residues in the voltage-sensing domains of different channel subtypes. While specific structural features determining R11.17's selectivity are not directly addressed in the available data, research on related toxins suggests several approaches to identify these determinants:

• Chimeric approach: Creating chimeric constructs between Nav1.6 (sensitive) and Nav1.1 (insensitive) can identify domains responsible for toxin sensitivity.

• Point mutations in the S3-S4 linker regions of voltage-sensing domains: These regions often interact with gating modifier toxins.

• Comparative analysis of homologous peptides with different selectivity profiles: Correlation of sequence differences with functional properties.

• Co-crystal structures or cross-linking studies: Direct identification of binding interface residues.

The preference of ι-RXIA for Nav1.6 > Nav1.2 > Nav1.7 suggests interaction with regions that differ between these channel subtypes, potentially in the voltage-sensing domain of domain II, which is critical for channel activation.

How does R11.17 interact with the voltage-sensing domains of sodium channels at the molecular level?

While detailed molecular interaction data specific to R11.17 is not available in the search results, the mechanism of iota-conotoxins suggests binding to one or more voltage-sensing domains (VSDs) of sodium channels, likely the domain II VSD critical for activation. This interaction stabilizes the activated (outward) conformation of the voltage sensor, facilitating channel opening at more negative potentials. The interaction likely involves:

• Electrostatic interactions between positively charged residues on the toxin and negatively charged residues in the S1-S2 loop or S3-S4 linker of the VSD.

• Hydrophobic interactions involving aromatic residues (including the critical D-phenylalanine) with hydrophobic pockets in the VSD.

• Specific hydrogen bonding networks that determine subtype selectivity.

These molecular interactions can be investigated using site-directed mutagenesis of both toxin and channel, paired with electrophysiological recording and computational modeling (molecular dynamics simulations). Unlike pore blockers, which physically occlude the ion conduction pathway, gating modifiers like R11.17 alter the energetics of conformational changes associated with channel opening.

How can R11.17 be used to investigate the role of Nav1.6 in neuronal excitability and action potential generation?

R11.17's preferential activity on Nav1.6 makes it a valuable tool for investigating this channel's contribution to neuronal excitability. Nav1.6 is the predominant sodium channel at nodes of Ranvier and is also expressed in the axon initial segment of many neurons. Specific research applications include:

• Dissecting the contribution of Nav1.6 to action potential initiation and propagation by applying R11.17 at concentrations selective for Nav1.6 over other subtypes.

• Investigating the role of Nav1.6 in repetitive firing behaviors by examining how R11.17 affects firing frequency and patterns in different neuronal populations.

• Studying the impact of hyperpolarized activation of Nav1.6 on synaptic integration and network activity.

• Examining how modulation of Nav1.6 activation impacts pathological hyperexcitability in models of epilepsy, neuropathic pain, or other disorders involving Nav1.6 dysfunction.

ι-RXIA has been shown to induce repetitive action potentials in both myelinated (A-fiber) and unmyelinated (C-fiber) axons in mouse sciatic nerve, consistent with Nav1.6 expression in both fiber types. This makes R11.17 particularly valuable for studying how Nav1.6 contributes to different aspects of peripheral nerve function.

What experimental approaches can utilize R11.17 to study sodium channel localization and mobility in neurons?

R11.17 can be adapted for studying sodium channel localization and mobility through several innovative approaches:

• Development of fluorescently labeled R11.17 derivatives: By conjugating fluorophores to R11.17 while preserving its binding properties, researchers can visualize Nav1.6 distribution in live neurons. This requires careful selection of conjugation sites that don't interfere with the binding interface.

• Biotinylated R11.17 for electron microscopy: Using R11.17 as a specific probe for Nav1.6 in immunogold electron microscopy to determine precise subcellular localization at ultrastructural resolution.

• R11.17 tethered to quantum dots: For single-particle tracking to study the dynamics and mobility of Nav1.6 channels in the plasma membrane.

• Activity-dependent labeling: Using R11.17 derivatives that preferentially bind to specific conformational states to investigate the distribution of functionally active channels.

• Competition assays with R11.17: To quantify the proportion of Nav1.6 versus other subtypes in specific neuronal compartments by comparing the effects of R11.17 to pan-specific sodium channel probes.

These approaches leverage R11.17's selectivity for Nav1.6 to provide insights into the spatial organization and dynamics of these channels in different neuronal compartments.

How can R11.17 be employed to investigate the role of sodium channels in neurological disorders?

R11.17's ability to selectively modulate Nav1.6 channels makes it valuable for investigating their role in neurological disorders:

• Epilepsy research: ι-RXIA induces seizures upon intracranial injection, modeling hyperexcitability. R11.17 can be used to determine if selective Nav1.6 modulation is sufficient to induce epileptiform activity in brain slice preparations or in vivo models.

• Multiple sclerosis and demyelinating disorders: Nav1.6 redistribution along demyelinated axons contributes to axonal injury. R11.17 can help determine how altered Nav1.6 function affects vulnerability to excitotoxicity in demyelinated axons.

• Neuropathic pain: By applying R11.17 to specific sensory neuron populations, researchers can assess Nav1.6's contribution to hyperexcitability in pain models.

• Neurodevelopmental disorders: Several Nav1.6 mutations are associated with developmental disorders. R11.17 can be used to determine how altered gating properties contribute to neuronal dysfunction.

• Neurodegeneration: Nav1.6-mediated persistent sodium currents can drive excitotoxicity. R11.17 can help determine if targeting Nav1.6 specifically can be neuroprotective.

The advantage of using R11.17 over genetic approaches is that it allows acute, reversible modulation of channel function with temporal precision, enabling researchers to determine the immediate consequences of altered Nav1.6 function.

What controls should be included in electrophysiological experiments using R11.17?

Rigorous electrophysiological experiments with R11.17 should include the following controls:

• Vehicle control: Application of the buffer in which R11.17 is dissolved to ensure observed effects are toxin-specific.

• Inactive analog control: If available, an analog with reduced activity (similar to ι-RXIA[L-Phe44]) to confirm specificity.

• Positive control: Application of a well-characterized sodium channel modulator (e.g., TTX for block, veratridine for activation) to confirm preparation viability.

• Channel subtype controls: Testing on cells expressing only Nav1.1 or other insensitive subtypes to confirm selectivity.

• Concentration-response relationship: Testing multiple concentrations to establish a full concentration-response curve, not just a single dose.

• Washout experiments: Demonstrating reversibility (or irreversibility) of effects to understand binding kinetics.

• Time control: Recording without toxin application for an equivalent period to account for potential time-dependent changes in channel properties.

• Heterologous expression system controls: Testing with and without β-subunits to understand their influence on toxin binding and efficacy.

These controls ensure that experimental results can be confidently attributed to R11.17's specific pharmacological properties.

What are the optimal storage and handling conditions for maintaining R11.17 stability?

To maintain the stability and activity of R11.17, the following storage and handling protocols are recommended:

Additionally, batch-to-batch consistency should be verified using analytical methods (HPLC, mass spectrometry) and functional assays before use in critical experiments. Activity assays using a consistent electrophysiological protocol on a stable cell line expressing Nav1.6 can serve as quality control for each batch.

What are the potential pitfalls and artifacts in interpreting R11.17 experimental data?

When interpreting experimental results with R11.17, researchers should be aware of several potential pitfalls:

• Concentration uncertainty: Peptide quantification methods (absorbance, BCA, etc.) can give different values. Functional titration against a standard may be more reliable.

• Disulfide bond heterogeneity: Multiple disulfide isomers may exist in preparations, with different activities.

• Partial effects: At subsaturating concentrations, effects may appear as a mixture of affected and unaffected channels rather than uniform partial modulation.

• Use-dependence artifacts: Changes in effect during repetitive stimulation may be misinterpreted as use-dependence rather than slow binding kinetics.

• State-dependent binding: Effects may vary depending on holding potential and pulse protocols.

• Off-target effects: At high concentrations, selectivity may be lost, leading to effects on other channel subtypes.

• Cell-type specific effects: Auxiliary subunits or post-translational modifications in different expression systems may alter apparent potency or efficacy.

• Series resistance errors: In voltage-clamp recordings, uncorrected series resistance can distort measurements of voltage-dependent parameters.

To mitigate these issues, use multiple concentrations, compare results across different preparation types, and employ complementary experimental approaches.

How does R11.17 compare to genetic approaches for studying Nav1.6 function?

R11.17 offers distinct advantages and limitations compared to genetic approaches for studying Nav1.6:

The complementary strengths make combining both approaches particularly powerful: genetic models can validate R11.17's specificity, while R11.17 can distinguish acute effects from developmental compensation in genetic models.

What advantages and limitations does R11.17 have compared to other sodium channel-targeting conotoxins?

R11.17, as an iota-conotoxin, offers unique advantages and limitations compared to other sodium channel-targeting conotoxins:

The unique mechanism of iota-conotoxins like R11.17 makes them particularly valuable for studying how subtle changes in channel gating parameters affect neuronal excitability - a distinction not possible with simple channel blockers. Additionally, while μ-conotoxins typically target multiple sodium channel subtypes, iota-conotoxins show higher subtype selectivity (with preference for Nav1.6 > Nav1.2 > Nav1.7), making them more precise tools for dissecting the contributions of specific subtypes to neuronal function.

How does R11.17 complement other voltage-sensing domain-targeting toxins in ion channel research?

R11.17 belongs to a broader class of gating modifier toxins that target voltage-sensing domains of ion channels. Its value in a comprehensive toxin toolkit includes:

• Complementary targeting: While many spider and scorpion toxins target the voltage sensors of domains II and IV to inhibit activation or inactivation respectively, iota-conotoxins like R11.17 facilitate activation by stabilizing the activated state of voltage sensors, providing a tool for bidirectional modulation of channel function.

• Different channel state preferences: Various toxins preferentially bind to and stabilize different conformational states (resting, activated, inactivated), allowing researchers to probe the entire conformational landscape of the channel.

• Subtype selectivity patterns: Each toxin family exhibits unique selectivity profiles across channel subtypes, enabling researchers to create "fingerprints" of channel composition in complex tissues.

• Combined application: Sequential or simultaneous application of R11.17 with toxins targeting different domains can provide insights into coupling between voltage sensors and cooperative interactions during gating.

• Comparative structure-function studies: Comparing binding determinants of different toxin families illuminates the structural conservation and divergence of voltage-sensing domains across channel types.

When used as part of a comprehensive toxin toolkit, R11.17 enables detailed investigation of voltage-sensor movements and their coupling to channel gating, complementing rather than duplicating the information provided by other gating modifiers.

How might R11.17 be engineered to enhance its potential as a research tool?

Several engineering approaches could enhance R11.17's utility as a research tool:

• Increasing subtype selectivity: Structure-guided mutations could enhance selectivity for Nav1.6 over Nav1.2 and Nav1.7, creating a more precise tool for isolating Nav1.6-specific functions.

• Affinity optimization: Modifications to increase binding affinity would allow use at lower concentrations, reducing potential off-target effects.

• Creating labeled derivatives: Strategic conjugation of fluorophores, biotin, or photoaffinity labels would enable visualization, pull-down assays, or covalent capture of the toxin-channel complex.

• Membrane-tethered variants: Developing membrane-delimited constructs that can be genetically encoded would allow cell-type specific targeting in complex tissues.

• Creating chimeric toxins: Combining domains from R11.17 with other conotoxins could create novel probes with unique pharmacological profiles.

• Developing PEGylated or Fc-fused variants: These modifications would extend the in vivo half-life for chronic studies.

• Creating conditional activatable variants: Engineering photoswitchable or chemically-triggered variants would enable precise temporal control of toxin activity.

These engineering approaches would need to be guided by detailed structure-function studies to ensure that modifications do not compromise the core pharmacological properties.

What research questions about voltage-gated sodium channels could be uniquely addressed using R11.17?

R11.17's unique mechanism of shifting voltage-dependent activation enables several investigations that would be difficult with other tools:

The ability to shift activation without affecting other gating parameters makes R11.17 particularly valuable for these investigations.

What potential exists for developing R11.17 derivatives as research tools for human channelopathies?

R11.17 derivatives hold significant potential for studying human channelopathies:

• Models of epilepsy: Many SCN8A (Nav1.6) mutations associated with epileptic encephalopathies cause hyperpolarized shifts in activation similar to R11.17's effect. R11.17 could be used to model these functional changes in animal models or neuronal cultures.

• Probing gain-of-function vs. loss-of-function: By comparing the effects of R11.17 (activation enhancer) with blockers like TTX, researchers can determine whether therapeutic strategies should target enhanced function or compensate for lost function.

• State-dependent therapeutics: Understanding how R11.17 binds to different channel states could guide development of drugs that selectively target pathological channel conformations while sparing normal function.

• Precision medicine approaches: R11.17 variants with tailored selectivity for specific mutant channels could help predict patient-specific responses to sodium channel modulators.

• Biomarker development: R11.17 derivatives could be used to quantify functional expression of specific sodium channel subtypes in accessible patient samples (e.g., sensory neurons derived from iPSCs).

As our understanding of channelopathies grows increasingly sophisticated, tools like R11.17 that can selectively modulate specific functional parameters of individual channel subtypes will become increasingly valuable for both basic research and translational applications.