Cycloviolacins, including Cycloviolacin-O20, are synthesized through ribosomal pathways followed by post-translational modifications. Their 27–38 amino acid sequences include six cysteine residues forming the CCK motif, which provides exceptional stability . The "bracelet" or "Möbius" cyclotide subfamilies differ in loop configurations, with hydrophobic patches critical for membrane interactions .
| Feature | Value |
|---|---|
| Amino acids | 27–38 |
| CCK motif | 6 cysteine residues, 3 bonds |
| Subfamily | Likely "bracelet" (based on naming) |
| Stability | High due to cyclization |
Related cyclotides exhibit diverse bioactivities, including:
Antimicrobial: Cycloviolacin O2 targets Gram-negative bacteria via membrane disruption .
Anticancer: CyO2 enhances doxorubicin uptake in drug-resistant cancer cells .
Antiparasitic: Potency against Haemonchus contortus exceeds prototypic kalata B1 .
| Activity | Target | Cyclotide Example | Ref. |
|---|---|---|---|
| Antibacterial | Gram-negative bacteria | Cycloviolacin O2 | |
| Anticancer | Drug-resistant MCF-7/ADR cells | Cycloviolacin O2 | |
| Anthelmintic | H. contortus | Cycloviolacin O2 |
While no direct data on Cycloviolacin-O20 exists, its study could follow methodologies used for related compounds:
Structural Analysis: Use NMR or X-ray crystallography to confirm its "bracelet" or "Möbius" classification .
Mechanism of Action: Assess membrane permeabilization via SYTOX Green assays or liposome leakage .
Therapeutic Applications: Test anticancer activity in models like MCF-7/ADR or antifungal effects against Fusarium graminearum .
Cycloviolacins belong to the cyclotide family, which are small cyclic peptides containing approximately 30 amino acids with a characteristic knotted arrangement of three disulfide bonds (called a cyclic cystine knot). These peptides from Viola odorata feature a highly conserved structural motif with six cysteine residues forming three disulfide bridges, creating an exceptionally stable structure resistant to thermal, chemical, and enzymatic degradation. The cycloviolacins specifically belong to the "bracelet" subfamily of cyclotides, distinguished by their backbone topology from the "Möbius" subfamily. Their structure includes several charged residues (Glu, Lys, Arg) that are critical for their biological activity .
The PepSAVI-MS (Statistically-guided bioActive Peptides prioritized Via Mass Spectrometry) pipeline offers an adaptable method for rapid identification of bioactive peptides in complex natural product libraries. The process involves:
Fractionation of plant extracts using strong cation exchange (SCX) chromatography
Bioactivity screening of fractions against relevant targets
Mass spectrometry analysis of active fractions
Statistical correlation of mass spectral features with bioactivity data
Reduction and alkylation of disulfide bonds (creating mass shifts of 348.16 ± 0.05 Da for cyclotides)
MS/MS sequencing for peptide identification
This approach has been validated for identifying bioactive cyclotides from Viola odorata, including cycloviolacin O2 and cycloviolacin O8 .
Cyclotides from Viola odorata can undergo several post-translational modifications that affect their structure and potentially their activity. Common modifications include:
| Modification | Mass Shift | Description | Example in V. odorata |
|---|---|---|---|
| Tryptophan oxidation (single) | +16 Da | Formation of oxindolyalanine (oia) | cyO3 oia (MW 3184.39 Da) |
| Tryptophan oxidation (double) | +32 Da | Formation of N-formylkynurenine (nfk) | cyO2 nfk (MW 3170.38 Da) |
| Cyclization | -18 Da | Head-to-tail cyclization (water loss) | All mature cyclotides |
| Disulfide bond formation | -6 Da | Three disulfide bonds | All cyclotides |
These modifications can be identified through mass spectrometric analysis, with characteristic mass shifts providing clues to the specific modifications present .
The isolation of cycloviolacins from Viola odorata typically follows a multi-step process designed to maintain peptide integrity while achieving high purity:
Plant material preparation: Collection of plant parts (aerial parts typically contain different cyclotide profiles compared to underground parts)
Extraction: Maceration in organic solvents (typically methanol/dichloromethane)
Initial fractionation: Solid-phase extraction (C18) to remove large proteins and hydrophilic compounds
Chromatographic separation:
Strong cation exchange (SCX) chromatography for initial fractionation
Reversed-phase HPLC for final purification
For analytical identification, a combination of liquid chromatography with mass spectrometry (LC-MS) provides the most precise characterization. The differential expression patterns between aerial and underground parts should be considered when targeting specific cyclotides .
Recombinant production of cycloviolacins presents several challenges:
Post-translational processing: Achieving correct disulfide bond formation and head-to-tail cyclization requires specialized cellular machinery often absent in common expression systems.
Toxicity to host cells: The membrane-active properties of cyclotides can disrupt host cell membranes, limiting production yields.
Folding complexity: The knotted disulfide arrangement creates kinetic folding traps that can lead to misfolded products.
Expression construct design: Engineering efficient systems requires careful consideration of:
Fusion partners to prevent toxicity
Cleavage sites for precision excision
Cyclization domains for head-to-tail closure
Oxidative environments for disulfide formation
Purification challenges: Separating correctly folded cyclotides from misfolded species requires sophisticated analytical techniques.
Current approaches focus on using specialized strains with enhanced disulfide isomerase activity, controlled induction systems to minimize toxicity, and fusion protein strategies that can be enzymatically processed post-expression.
Cycloviolacin O2 (cyO2) demonstrates superior antimicrobial activity compared to other cyclotides from Viola odorata, particularly against Gram-negative bacteria. Comparative studies revealed:
| Cyclotide | Activity Against Gram-negative Bacteria | Activity Against Gram-positive Bacteria | Notes |
|---|---|---|---|
| Cycloviolacin O2 | Potent (μM range) | Limited | Most active against E. coli, S. Typhimurium, K. pneumoniae, P. aeruginosa |
| Kalata B1 (Möbius) | Moderate | Limited | Less effective than cyO2 |
| Other cycloviolacins | Variable | Limited | Generally less potent than cyO2 |
CyO2's selective activity against Gram-negative bacteria is attributed to its unique arrangement of charged residues. Experimental modification of these charged residues demonstrated their critical importance: masking of Glu and Lys residues caused almost complete loss of activity, while Arg modification had a less pronounced but still significant effect .
Cycloviolacins exhibit anticancer activity primarily through membrane permeabilization mechanisms, with additional chemosensitizing abilities that enhance the effectiveness of conventional chemotherapeutics. The mechanism involves:
Membrane disruption: Cycloviolacins, particularly cycloviolacin O2, directly disrupt cancer cell membranes, as demonstrated by SYTOX Green assays where cellular disruption correlates with cyclotide exposure.
Selective toxicity: Interestingly, cyO2 shows selective membrane disruption in rapidly proliferating cancer cells while causing minimal disruption in primary human brain endothelial cells, suggesting specificity toward tumor cells.
Chemosensitization: CyO2 significantly enhances the effectiveness of doxorubicin in drug-resistant breast cancer cells (MCF-7/ADR). When co-exposed to cyO2 (3 μM) and doxorubicin (5 μM), drug-resistant cells show 57-64% increased uptake of doxorubicin compared to only 19% with doxorubicin alone.
Overcoming drug resistance: Fluorescence microscopy studies demonstrate that cyO2 treatment allows increased cellular internalization of doxorubicin in drug-resistant cells, effectively circumventing resistance mechanisms related to drug efflux .
This membrane-active mechanism represents a novel approach to overcoming multidrug resistance in cancer, as it bypasses conventional resistance mechanisms like drug efflux pumps.
Cycloviolacins demonstrate multifaceted bioactivity profiles across different organisms, with notable differences in potency and specificity:
| Target Type | Key Active Cyclotides | Effective Concentration Range | Specificity |
|---|---|---|---|
| Antifungal | Cycloviolacin O8 | Micromolar | Active against agricultural pathogen Fusarium graminearum |
| Antibacterial | Cycloviolacin O2 | Low micromolar | Selective for Gram-negative bacteria |
| Anticancer | Cycloviolacin O2, O8 | 0.2-10 μM | Activity against multiple cancer types (breast, prostate, ovarian) |
The antifungal activity appears to involve multiple cyclotide species, with statistical modeling identifying both cycloviolacin O8 and potentially cycloviolacin O3/O7 (mass 3152.41 Da) as contributors to activity against F. graminearum. The mechanisms likely share commonalities with antibacterial activity, primarily involving membrane disruption, but with structural features that confer specificity toward fungal cell membranes .
For comprehensive characterization of cycloviolacin bioactivities, multiple specialized assay systems are required:
Antimicrobial activity assessment:
Radial diffusion assays (RDAs): Initial screening against bacterial strains
Minimum inhibitory concentration (MIC) assays: Quantitative measurement of inhibitory concentrations
Time-kill kinetics: Assessment of bactericidal versus bacteriostatic effects in buffer systems
SYTOX Green membrane permeabilization assays: Mechanistic evaluation of membrane disruption
Anticancer activity evaluation:
Cell proliferation assays (MTT/thiazolyl blue tetrazolium bromide): Quantification of cytotoxicity
Combination studies with conventional chemotherapeutics: Evaluation of synergistic effects
Fluorescence microscopy: Direct visualization of membrane permeabilization and drug uptake
Antifungal testing:
Growth inhibition assays against filamentous fungi
Statistical correlation of bioactivity with mass spectrometry data
The selection of appropriate positive controls, reference standards, and careful optimization of assay conditions (buffer composition, incubation time, cell density) is critical for obtaining reliable and reproducible results .
Chemical modification studies are essential for structure-activity relationship analysis of cycloviolacins. Critical parameters include:
Selective modification strategies:
Targeting specific amino acid residues (e.g., charged residues like Glu, Lys, and Arg)
Maintaining structural integrity during modification
Confirming modification specificity through mass spectrometry
Modification validation:
Mass spectrometric confirmation of expected mass shifts
Structural verification through circular dichroism or NMR to ensure global fold is maintained
Activity assays to correlate structural changes with functional impacts
Experimental controls:
Parallel processing of unmodified peptides as controls
Sequential modification of different residues to isolate individual contributions
Concentration matching between modified and unmodified peptides in activity assays
Data interpretation considerations:
Distinguishing between direct effects on target interaction versus indirect effects on structural stability
Accounting for potential aggregation behaviors in modified peptides
Correlating activity changes with 3D structural positioning of modified residues
These approaches have revealed that charged residues in cycloviolacin O2 are essential for antimicrobial activity, with Glu and Lys modifications causing near-complete activity loss, while Arg modification has lesser effects .
Optimizing high-throughput screening for novel cycloviolacins requires integration of multiple technological approaches:
Library preparation optimization:
Strategic taxonomic sampling across Violaceae family plants
Differential extraction from various plant tissues (aerial vs. underground parts)
Creation of semi-purified fraction libraries to reduce interference
Multi-dimensional screening approach:
Primary screening against diverse targets (cancer cell lines, bacterial panels, fungal pathogens)
Secondary confirmation assays with dose-response analysis
Counter-screening against non-target cells for selectivity assessment
Advanced analytical integration:
Implementation of the PepSAVI-MS pipeline for statistical correlation of bioactivity with MS features
Automation of disulfide reduction/alkylation for cyclotide identification
Machine learning algorithms to predict bioactivity from MS/MS fragmentation patterns
Validation strategy:
Isolation of hit compounds at sufficient scale for full characterization
Confirmatory bioassays with isolated material
Structure determination through combined MS/MS and NMR approaches
This integrated approach has successfully identified novel bioactive cyclotides like cycloviolacin O8, demonstrating potent anticancer and antifungal activities that were not previously characterized .
The structure-activity relationships of cycloviolacins reveal distinct structural features critical for different bioactivities:
| Structural Feature | Influence on Antimicrobial Activity | Influence on Anticancer Activity | Influence on Antifungal Activity |
|---|---|---|---|
| Charged residues | Glu and Lys essential for activity against Gram-negative bacteria | Contribute to membrane disruption | Likely important but less characterized |
| Hydrophobic residues | Create amphipathic structure necessary for membrane interaction | Critical for cancer cell membrane disruption | Facilitate interaction with fungal membranes |
| Cyclotide subfamily | Bracelet cyclotides (e.g., cyO2) more active than Möbius (e.g., kalata B1) | Bracelet cyclotides typically more cytotoxic | Varies with specific fungal target |
| Post-translational modifications | Oxidation of Trp can modify activity profile | May enhance selectivity toward cancer cells | Influence on antifungal activity not well characterized |
Addressing off-target effects in cycloviolacin research requires systematic approaches:
Comprehensive toxicity profiling:
Parallel screening against target and non-target cells
Hemolysis assays to assess red blood cell toxicity
Primary cell cultures representing different tissues (e.g., hepatocytes, endothelial cells)
In vivo models for systemic toxicity evaluation
Mechanistic clarification:
Membrane permeabilization assays with fluorescent dyes (e.g., SYTOX Green)
Investigation of potential intracellular targets through pull-down assays
Evaluation of impact on cellular signaling pathways
Structural modification strategies:
Rational design of analogs with reduced off-target activity
PEGylation or other conjugation approaches to modify biodistribution
Targeted delivery systems to limit systemic exposure
Therapeutic window assessment:
Determination of IC₅₀ values across multiple cell types
Calculation of selectivity indices to quantify therapeutic potential
Dose-limiting toxicity identification in pre-clinical models
Evidence suggests cycloviolacins may offer inherent selectivity toward certain targets. For example, cycloviolacin O2 demonstrates significant membrane disruption in cancer cells while showing minimal effects on primary human brain endothelial cells, suggesting natural selectivity that can be further optimized .
Distinguishing structurally similar cycloviolacins presents significant analytical challenges requiring advanced methodological approaches:
Enhanced chromatographic resolution:
Ultra-high performance liquid chromatography (UHPLC) with sub-2μm particles
Extended gradient profiles optimized for closely eluting species
Multi-dimensional chromatography combining orthogonal separation mechanisms (e.g., SCX followed by reversed-phase)
Advanced mass spectrometric techniques:
High-resolution accurate mass measurements (<2 ppm error)
MS/MS sequencing with electron transfer dissociation (ETD) for improved coverage
Ion mobility spectrometry for separation based on 3D structure
Chemical derivatization approaches:
Selective modification of specific residues to create diagnostic mass shifts
Differential reduction/alkylation strategies to map disulfide connectivity
Enzymatic digestions with site-specific proteases
Quantitative analysis considerations:
Internal standards for relative quantification
Isotopically labeled reference standards for absolute quantification
Statistical modeling to deconvolute co-eluting species
This comprehensive approach has enabled researchers to distinguish between cyclotides with mass differences as small as 1-2 Da, such as the identification of oxidized tryptophan modifications in cycloviolacins that result in a 16 Da mass shift per oxidation .
Enhancing the therapeutic potential of cycloviolacins involves several innovative approaches:
Targeted delivery systems:
Nanoparticle encapsulation to improve pharmacokinetics
Cancer-targeting ligand conjugation for selective delivery
Stimuli-responsive release mechanisms (pH, enzyme, redox)
Rational design strategies:
Grafting approach: Incorporation of bioactive sequences into cycloviolacin scaffolds
Charge distribution optimization for enhanced selectivity
Strategic modification of key residues to reduce off-target effects
Combination therapy development:
Building on the demonstrated chemosensitizing abilities of cycloviolacin O2
Development of optimized dosing schedules with conventional therapeutics
Identification of synergistic drug combinations for maximizing efficacy
Production optimization:
Development of efficient recombinant expression systems
Semi-synthetic approaches combining chemical synthesis with enzymatic cyclization
Sustainable plant cultivation and extraction methods
The chemosensitizing abilities of cycloviolacin O2 in drug-resistant cancer cells represent a particularly promising direction, potentially addressing one of the most significant challenges in cancer therapy .
Computational approaches offer powerful tools for advancing cycloviolacin research:
Molecular dynamics simulations:
Membrane interaction modeling at atomic resolution
Free energy calculations for membrane binding and disruption
Conformational sampling to identify bioactive states
Machine learning applications:
Prediction of bioactivity from primary sequence
Classification of cyclotides into functional subgroups
Automated annotation of MS/MS spectra for rapid identification
Quantitative structure-activity relationship (QSAR) modeling:
Development of predictive models for antimicrobial activity
Identification of key physicochemical parameters driving anticancer activity
Virtual screening of theoretical cycloviolacin variants
Systems biology integration:
Network analysis of affected pathways in target organisms
Resistance mechanism prediction through evolutionary algorithms
Multi-scale modeling linking molecular interactions to cellular responses
These computational approaches can guide experimental design, reducing the need for extensive screening and accelerating the development of optimized cycloviolacin variants with enhanced therapeutic properties.
Essential quality control parameters for recombinant or synthetic cycloviolacins include:
| Parameter | Analytical Method | Acceptance Criteria |
|---|---|---|
| Purity | RP-HPLC, capillary electrophoresis | >95% main peak |
| Identity | MS (intact mass), MS/MS sequencing | Mass error <5 ppm, sequence confirmation |
| Correct folding | Disulfide mapping, circular dichroism | Native disulfide pattern, characteristic CD spectrum |
| Cyclization confirmation | Enzymatic stability, MS/MS | Resistance to exopeptidases, absence of linear MS/MS fragments |
| Biological activity | Standardized bioassays | Activity within 20% of reference standard |
| Endotoxin content | LAL assay | <0.5 EU/mg for in vitro studies |
| Aggregation state | Size exclusion chromatography, DLS | Monodisperse population |
Each batch should be characterized using multiple orthogonal methods, with particular attention to correct disulfide bond formation and head-to-tail cyclization, as these features are critical for the stability and activity of cycloviolacins.
Effective comparative studies between natural and recombinant cycloviolacins require careful experimental design:
Sample preparation standardization:
Matched purification protocols for natural and recombinant material
Equivalent storage conditions to prevent differential degradation
Concentration determination using multiple methods (UV absorbance, amino acid analysis)
Structural equivalence assessment:
High-resolution mass spectrometry for intact mass comparison
Circular dichroism spectroscopy for secondary structure comparison
NMR analysis for tertiary structure confirmation when possible
Disulfide connectivity mapping
Functional comparison framework:
Parallel testing in multiple bioassay systems
Full dose-response curves rather than single-point comparisons
Statistical analysis of potency differences (EC50/IC50 values)
Evaluation across multiple biological targets
Reference standards and controls:
Well-characterized reference cyclotide as internal control
Inclusion of positive controls specific to each assay
Same-day testing to minimize inter-assay variability