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Article

Chemical Composition and Anti-Aging Potential of Passiflora edulis By-Product Fractions: A Comparative Study Integrating Metabolomic Profiling and Molecular Docking

by
Siripat Chaichit
1,
Nichcha Nitthikan
1,2,
Kanokwan Kiattisin
1 and
Supat Jiranusornkul
1,*
1
Department of Pharmaceutical Sciences, Faculty of Pharmacy, Chiang Mai University, Chiang Mai 50200, Thailand
2
Office of Research Administration, Chiang Mai University, Chiang Mai 50200, Thailand
*
Author to whom correspondence should be addressed.
Compounds 2026, 6(2), 32; https://doi.org/10.3390/compounds6020032
Submission received: 28 April 2026 / Revised: 26 May 2026 / Accepted: 11 June 2026 / Published: 12 June 2026
(This article belongs to the Special Issue Compounds–Derived from Nature)
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Abstract

Passion fruit (Passiflora edulis) processing generates by-products rich in bioactive secondary metabolites; however, comparative characterization across fruit fractions remains limited. This study evaluated pulp (PPE), pulp-seed (PSC), and seed (PSE) extracts for extraction yield, metabolite composition, antioxidant and anti-aging activities, and collagen-stimulatory activity in human skin fibroblasts. Extraction yields followed the order PPE > PSE > PSC. Untargeted LC–QTOF/MS profiling revealed distinct phytochemical patterns, with piceatannol enriched in PSE and trans-ferulic acid broadly abundant across all fractions. PSE showed the strongest antioxidant activity in DPPH and FRAP assays, and both PSE and PSC inhibited collagenase and hyaluronidase, while PPE showed negligible activity. All extracts were non-cytotoxic up to 0.1 mg/mL. At this concentration, PSC enhanced type I collagen production by 8.07 ± 2.24%, significantly exceeding PSE (2.26 ± 1.33%), while piceatannol stimulated collagen synthesis by 11.34 ± 1.50%, comparable to L-ascorbic acid (13.90 ± 1.16%). Molecular docking suggested that piceatannol and trans-ferulic acid may contribute to the observed anti-aging effects by interacting favorably with collagenase and hyaluronidase. These findings demonstrate that passion fruit by-product fractions exhibit complementary bioactivity profiles, with PSE favoring antioxidant and enzyme inhibitory effects and PSC enhancing collagen biosynthesis, as natural anti-aging applications.

1. Introduction

The utilization of agro-industrial by-products as valuable sources of bioactive constituents has attracted growing interest due to their relevance to sustainable development and pharmaceutical innovation. Passion fruit (Passiflora edulis) is a tropical fruit widely cultivated in Southeast Asia, South America, and other tropical regions for its distinctive aroma, flavor, and nutritional value, while its processing generates substantial amounts of by-products, particularly seeds and residual pulp. Although these materials are frequently discarded, accumulating evidence indicates that they are rich in phenolic compounds, flavonoids, stilbenes such as piceatannol and resveratrol, and other secondary metabolites with diverse pharmacological properties [1,2,3,4]. These findings highlight the potential of passion fruit by-products as alternative sources of functional bioactive agents.
Phenolic compounds and flavonoids are well-recognized for their capacity to scavenge free radicals, chelate transition metals, and modulate oxidative stress-related signaling pathways [5,6]. Oxidative stress, driven by the accumulation of reactive oxygen species (ROS), damages the collagen-rich extracellular matrix (ECM) in skin by upregulating matrix metalloproteinases (MMPs) while simultaneously inhibiting collagen production, which are major features of dermal aging [7,8,9]. Collagenase and hyaluronidase, key enzymes responsible for degrading collagen and hyaluronic acid, respectively, are implicated in accelerated skin aging and loss of tissue elasticity [10,11]. Inhibiting these enzymes, combined with stimulating collagen biosynthesis by dermal fibroblasts, therefore, represents a comprehensive anti-aging strategy [12,13]. Given the growing demand for natural bioactive compounds, plant-derived compounds with dual antioxidant and anti-aging properties are of considerable cosmeceutical interest.
Several studies have explored individual bioactivities of P. edulis by-products. Hartanto et al. [14] compared the collagenase inhibitory activity of peel and seed extracts, respectively, with peel demonstrating stronger inhibition. Gomes et al. [15] reported collagenase, elastase, and tyrosinase inhibitory activities of P. cincinnata seed extract, another Passiflora species, supported by molecular docking analysis. Chen et al. [16] evaluated the tyrosinase and hyaluronidase inhibitory activities of the acetone-extracted rind of P. edulis. Regarding collagen synthesis, Matsui et al. [17] demonstrated that piceatannol-rich seed extract promoted collagen production in dermal fibroblasts, while rind and pulp extracts did not yield this effect. Furthermore, liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (LC–QTOF/MS) has become a powerful analytical platform for untargeted metabolite profiling of complex plant matrices. High mass accuracy, resolving power, and sensitivity make it possible to detect metabolites across a wide range of chemical classes, while MS/MS fragmentation data support putative structural annotation [18]. These advantages are particularly useful for plant by-product extracts, which often contain chemically diverse secondary metabolites at different abundance levels. LC–QTOF/MS is therefore well suited for comparing phytochemical profiles among P. edulis fractions and identifying candidate metabolites associated with biological activity [19,20]. Complementing this analytical approach, molecular docking has become a widely used computational tool for predicting the binding affinities and interaction mechanisms of identified compounds with target enzymes, thereby bridging phytochemical characterization and biological activity [12].
Although several bioactivities of P. edulis by-products have been reported, a gap remains between laboratory investigations and the reality of industrial processing. During passion fruit juice production, seeds and residual pulp are commonly removed together as a combined waste stream [21], whereas previous studies have generally examined seeds, peel, or rind as separately isolated fractions [3,4,14,15,16,17]. This separation-based approach may limit translational relevance because the bioactivity of the combined pulp–seed fraction may differ from that of its individual components. Seeds are particularly rich in stilbenes such as piceatannol [4], whereas pulp contributes a distinct set of bioactive ingredients, including carotenoids, ascorbic acid, and flavonoid glycosides [22]. Comparative evaluation of isolated and combined fractions is needed to determine whether the mixed residue retains, enhances, or dilutes the functional properties of each individual fraction. In addition, integrated studies combining LC–QTOF/MS metabolite profiling, antioxidant and anti-aging activity, cellular collagen stimulation, and molecular docking within a single comparative framework are still limited. This comparison is important for assessing whether mixed passion fruit residue can be directly valorized as natural bioactive ingredients without additional fraction separation, thereby supporting a more sustainable route from juice-processing waste to the development of anti-aging agents.
Therefore, this study comparatively evaluated three passion fruit by-product fractions: pulp extract (PPE), pulp–seed extract (PSC), representing mixed residues from juice-processing waste, and seed extract (PSE). Their antioxidant and anti-aging activities, cytotoxicity, and effects on collagen production in human skin fibroblasts were investigated. Furthermore, LC–QTOF/MS-based metabolite profiling and molecular docking analyses were conducted. This integrated approach provides preliminary evidence supporting the potential of passion fruit by-product fractions as sources of natural anti-aging agents.

2. Materials and Methods

2.1. Materials

Dulbecco’s modified Eagle’s medium (DMEM), fetal bovine serum (FBS), and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) were obtained from Gibco (Thermo Fisher Scientific, Waltham, MA, USA). Penicillin–streptomycin and trypan blue were purchased from Gibco/Invitrogen (Thermo Fisher Scientific, Carlsbad, CA, USA). 2,2-Diphenyl-1-picrylhydrazyl (DPPH), ferrous chloride (FeCl2), ferric chloride (FeCl3), ferrous sulfate (FeSO4), 2,2′-azobis(2-methylpropionamidine) dihydrochloride (AAPH), aluminum chloride (AlCl3), sodium acetate (CH3COONa), N-succinyl-Ala-Ala-Ala-p-nitroanilide (AAAVPN), N-[3-(2-furyl)acryloyl]-Leu-Gly-Pro-Ala (FALGPA), hyaluronidase from bovine testis (lot no. 0000332366) and collagenase from Clostridium histolyticum, and bovine serum albumin (BSA) were supplied by Sigma–Aldrich (Steinheim, Germany). 2,4,6-Tris(2-pyridyl)-s-triazine (TPTZ) was purchased from Fluka (Buchs, Switzerland). Ethanol (95%), acetate buffer, and dimethyl sulfoxide (DMSO) were obtained from RCI Labscan (Bangkok, Thailand). Ammonium thiocyanate (NH4SCN), phosphate buffer, Folin–Ciocalteu reagent, sodium carbonate (Na2CO3), and tannic acid were purchased from Loba Chemie (Mumbai, India). Quercetin, gallic acid, L-ascorbic acid, and piceatannol were obtained from Chanjao Longevity (Bangkok, Thailand).

2.2. Passion Fruit By-Product Extracts Preparation

Passion fruits were purchased from the Royal Project Foundation, Chiang Mai, Thailand, during 2023–2024. The fruits were washed thoroughly, and fully ripe passion fruits suitable for consumption were used in this study. The edible pulp–seed portion was collected as the starting material. To comparatively evaluate the contribution of different fruit by-product fractions, the material was prepared into three sample types: pulp fraction, combined pulp–seed material, and seed fraction.
The fruits were manually separated into pulp and seed fractions using a stainless-steel knife. For the combined pulp–seed sample, both fractions were retained together at a 1:1 ratio. Samples were separately dried in a hot-air oven (UN55 Memmert, Schwabach, Germany) at 60 °C for 48 h and then coarsely ground into powder using a blender (HR2221, 700 W, Philips, Amsterdam, The Netherlands). For each fraction, 300 g of the sample was used for extraction. The solid-to-liquid ratio was maintained at 1:10 (w/v), and the samples were extracted with 70% (v/v) ethanol using an ultrasonic bath (Ultrasonic S 30H, Elma, Singen, Germany) operating at 37 kHz and 200 W at room temperature for 30 min per extraction cycle, following a method adapted from De Santana et al. [23]. After extraction, the extract solutions were collected, filtered through a 0.45 µm membrane, and concentrated under reduced pressure at 50 °C using a rotary evaporator (Eyela, Tokyo, Japan). The extraction procedure was performed in triplicate for all samples. The resulting crude extracts were designated as pulp extract (PPE), pulp–seed extract (PSC), and seed extract (PSE), respectively. All crude extracts were stored in amber glass bottles at 4 °C until further analysis. The percentage yield of extraction was obtained using the following equation:
% Yield = (E/P) × 100
where E is the weight of the obtained extract and P is the weight of the plant powder used for extraction.

2.3. Determination of Total Flavonoid Content

The total flavonoid content (TFC) of each extract was determined by an aluminum chloride colorimetric assay with some modifications [24]. Briefly, 50 µL of each sample solution (1 mg/mL) was combined with 10 µL of 10% (w/v) aluminum chloride and 10 µL of 1 M potassium acetate. The reaction mixtures were incubated at room temperature in the dark for 30 min prior to absorbance measurement at 420 nm using a microplate reader (SPECTROstar Nano, BMG Labtech, Aylesbury, UK). Piceatannol was evaluated as a test compound under the same experimental conditions. A calibration curve was constructed using quercetin standard solutions at various concentrations, where y represents the absorbance and x represents the quercetin concentration (mg). Total flavonoid content (TFC) was expressed as milligrams of quercetin equivalent per gram of extract (mg QE/g extract). The TFC was calculated using the following equation:
Total flavonoids content (mg QE/g extract) = (c × V × D)/N
where c is the concentration of quercetin (mg), V is the sample volume (mL), D is the dilution factor, and N is the weight of the sample (g).

2.4. Determination of Total Phenolic Content

The total phenolic content (TPC) of each extract was determined by a Folin–Ciocalteu assay with some modifications [24]. Briefly, 20 µL of each sample solution (1 mg/mL) was mixed with 100 µL of diluted Folin–Ciocalteu reagent (1:9, v/v; Folin–Ciocalteu reagent water) and incubated at room temperature for 5 min. Subsequently, 80 µL of 7.5% (w/v) sodium carbonate solution was added, followed by incubation in the dark for 30 min. The absorbance was measured at 765 nm using a microplate reader (SPECTROstar Nano, BMG Labtech, Aylesbury, UK). Piceatannol was evaluated as a test compound under the same experimental conditions. A calibration curve was prepared using gallic acid standard solutions at various concentrations, where y represents the absorbance and x represents the gallic acid concentration (mg). Total phenolic content (TPC) was expressed as milligrams of gallic acid equivalent per gram of extract (mg GAE/g extract). The TPC was calculated using the following equation:
Total phenolics content (mg GAE/g extract) = (c × V × D)/N
where c is the concentration of gallic acid (mg), V is the sample volume (mL), D is the dilution factor, and N is the weight of the sample (g).

2.5. Liquid Chromatography Quadrupole Time of Flight with Mass Spectroscopy (LC-QTOF/MS)

Approximately 10 mg of each passion fruit extract was weighed and dissolved in 1 mL of 70% ethanol. The samples were vortex-mixed and centrifuged at 14,000 rpm for 10 min. The supernatant was collected and filtered prior to analysis.
Metabolite profiling was conducted using liquid chromatography–quadrupole time-of-flight mass spectrometry (LC–QTOF/MS; Agilent 6545XT, Agilent Technologies, Santa Clara, CA, USA). Chromatographic separation was performed on a Poroshell 120 EC-C18 column (2.1 × 100 mm, 2.7 µm) maintained at 50 °C. The injection volume was 10 µL. The mobile phase consisted of water containing 0.1% formic acid as solvent A and acetonitrile containing 0.1% formic acid as solvent B. The flow rate was set at 0.4 mL/min. Gradient elution was carried out from 100% solvent A to 100% solvent B over 17 min, followed by column re-equilibration before the next injection. Mass spectrometric analysis was performed using an electrospray ionization source operated in both positive and negative ionization modes. The operating parameters were as follows: capillary voltage, 3500 V; nebulizer pressure, 35 psi; drying gas temperature, 325 °C; drying gas flow rate, 10 L/min; fragmentor voltage, 120 V; and mass scan range, m/z 100–1700. Data-dependent MS/MS acquisition was performed using collision energies of 10, 20, and 40 eV. Continuous mass correction was applied throughout the analysis using reference ions at m/z 121.0509 and 922.0098 in positive mode and m/z 112.9856 and 1033.9881 in negative mode.
Raw data were processed using MS-DIAL version 5.3 (RIKEN, Kanagawa, Japan) for peak detection, spectral deconvolution, and peak alignment. Putative metabolite annotation was carried out by comparing the accurate mass and MS/MS fragmentation patterns with entries in multiple spectral databases, including the MS-DIAL ESI (+/−) library, the Fiehn/Vaniya Natural Products Library, and the BMDMS-NP library. Metabolite features were retained for further analysis when the mass error was within ±5.0 ppm and the identification score exceeded 1.0.

2.6. Processing and Prioritization of Putatively Annotated Metabolites

Putatively annotated metabolites were filtered to focus on secondary metabolites relevant to the study objective, including flavonoids, phenolic acids, stilbenes, coumarins, and alkaloids. Peak intensities were log2-transformed prior to comparative analysis. Hierarchical clustering and heatmap visualization were performed in R version 4.5.1 using the ComplexHeatmap package [25], based on Euclidean distance and complete linkage. LC–QTOF/MS profiling was performed on representative pooled extracts with a single acquisition per extract; therefore, standard deviations and inferential statistics were not calculated.
To support exploratory feature prioritization, metabolites were evaluated according to log2 intensity, pairwise log2 fold-change values, and relative extract-enrichment patterns. The relative extract-enrichment score for a given extract was calculated as the difference between the log2 intensity of a metabolite in that extract and the mean log2 intensity of the same metabolite in the remaining two extracts. Positive values indicate relative enrichment in the corresponding extract fraction, and the extract showing the highest enrichment score was assigned as the dominant fraction for that metabolite. This metric was used descriptively to distinguish broadly distributed metabolites from extract-preferential metabolites and to support compound prioritization for molecular docking. Candidates for docking were selected on the basis of high mean log2 intensity (broadly distributed compounds) and high relative extract-enrichment score (extract-preferential compounds).

2.7. Antioxidation Activities of Passion Fruit Extracts

2.7.1. 2,2-Diphenyl-1-picrylhydrazyl (DPPH) Radical Scavenging Assay

The free radical scavenging activity of the extracts was estimated by the DPPH assay with some modifications [26]. Briefly, 180 µL of DPPH solution in ethanol (167 µM) was mixed with 20 µL of each sample solution. The reaction mixtures were incubated at room temperature in the dark for 30 min. Absorbance was then measured at 520 nm using a microplate reader (SPECTROstar Nano, BMG Labtech, Aylesbury, UK). Piceatannol was used as a reference antioxidant. The antioxidant activity was expressed as the IC50 value.

2.7.2. Ferric-Reducing Antioxidant Power (FRAP) Assay

The ferric-reducing antioxidant power of the extract was measured by a FRAP assay according to the method of Nitthikan [27]. The FRAP reagent was freshly prepared by mixing 300 mM acetate buffer, 10 mM TPTZ solution in 40 mM hydrochloric acid, and 20 mM ferric chloride solution at a ratio of 50:5:5. Briefly, the sample solution (1 mg/mL) was mixed with the FRAP reagent and incubated at room temperature for 5 min. The absorbance of the resulting blue-colored complex was measured at 595 nm using a microplate reader (SPECTROstar Nano, BMG Labtech, Aylesbury, UK). Piceatannol was evaluated as a test compound under the same experimental conditions. A calibration curve was constructed using ferrous sulfate at various concentrations as the standard (y = 2.6033x + 0.3179), where y represents the absorbance and x represents the ferrous sulfate content (mg). The results were expressed as milligrams of ferrous sulfate equivalent per gram of sample (mg FSE/g sample). The FRAP value was calculated using the following equation:
FRAP value (mg FeSO4/g of extract) = (c × V × D)/N
where c is the concentration of ferrous sulfate (mg), V is the sample volume (mL), D is the dilution factor, and N is the weight of the sample (g).

2.8. Anti-Aging Activities of Passion Fruit Extracts

2.8.1. Anti-Hyaluronidase Activity Assay

Samples at a concentration of 1 mg/mL were tested for the inhibition of hyaluronidase enzyme by the turbidimetric method described by Nitthikan et al. [28]. Briefly, hyaluronidase from bovine testis (EC 3.2.1.35) was incubated with the sample solution at 37.5 °C for 45 min in a water bath (Memmert Waterbath WNB, Schwabach, Germany). An acidic bovine serum albumin solution containing sodium acetate, acetic acid, and bovine serum albumin (pH 3.75) was then added to precipitate the undigested hyaluronic acid. The reaction mixture was kept at room temperature for 10 min, after which the absorbance was measured at 600 nm using a microplate reader (SPECTROstar Nano, BMG Labtech, Aylesbury, UK). Tannic acid was used as the positive control, while piceatannol was evaluated as a test compound. Anti-hyaluronidase activity was calculated using the following equation:
% Anti-hyaluronidase assay = (Asample/Acontrol) × 100
where Asample is the absorbance of the sample, hyaluronidase enzyme solution, hyaluronic acid solution, and acetic albumin acid solution. Acontrol is the absorbance of deionized water, hyaluronic acid solution, and acetic albumin acid solution.

2.8.2. Collagenase Inhibitory Assay

Collagenase inhibitory activity was assessed following a method described by Thring et al. [29]. The assay was carried out in 50 mM Tricine buffer (pH 7.5) containing 400 mM sodium chloride and 10 mM calcium chloride. Collagenase from Clostridium histolyticum (ChC; EC 3.4.24.3) was prepared in the same buffer at a concentration of 2 mg/mL. The substrate, N-[3-(2-furyl)acryloyl]-Leu-Gly-Pro-Ala (FALGPA), was freshly prepared at 1 mM in Tricine buffer. Briefly, the sample solution (1 mg/mL) was pre-incubated with collagenase for 15 min, after which FALGPA was added to initiate the reaction. Immediately after substrate addition, the absorbance was monitored at 345 nm in kinetic mode using a microplate reader (SPECTROstar Nano, BMG Labtech, Aylesbury, UK). EGCG was used as the positive control, while piceatannol was assessed as a test compound. Collagenase inhibition was calculated using the following equation:
% Collagenase inhibition = (Acontrol − Asample)/(Acontrol) × 100
where Acontrol is the absorbance of the reaction of deionized water, collagenase enzyme solution, and substrate. Asample is the absorbance of the reaction of sample solution, collagenase enzyme solution, and substrate.

2.9. In Vitro Collagen Biosynthesis Stimulation Assay

2.9.1. Cytotoxicity Test Using MTT Assay

Human dermal fibroblasts (ATCC PCS-201-012) were purchased from the American Type Culture Collection (ATCC, Manassas, VA, USA). The cytotoxicity of passion fruit extracts and chemical compounds was evaluated using the MTT assay according to the method of Chittasupho et al. [30]. The fibroblast cells were seeded in 96-well plates and cultured in DMEM supplemented with 10% fetal bovine serum, 100 U/mL penicillin, and 100 µg/mL streptomycin. The cells were treated with the extracts at final concentrations of 0.0001, 0.001, 0.01, 0.1, and 1 mg/mL and incubated at 37 °C for 24 h. After incubation, the culture medium was discarded, and the cells were gently rinsed with phosphate-buffered saline (PBS, pH 7.4). MTT solution was then added to each well, and the plates were incubated at 37 °C for 2 h. The MTT solution was subsequently discarded, and dimethyl sulfoxide (DMSO) was added to dissolve the formazan crystals. Absorbance was measured at 560 nm using a microplate reader (SPECTROstar Nano, BMG Labtech, Aylesbury, UK). Cell viability was calculated as a percentage using the following equation:
% Cell viability = (ASample/AControl) × 100
where ASample is the absorbance of test compound, and AControl is the absorbance of control group.

2.9.2. Collagen Biosynthesis of Passion Fruit Extracts by Sirius Red Assay

The Sirius Red assay was used to quantify collagen biosynthesis. This assay is based on the ability of Sirius Red, an anionic dye, to bind selectively to collagen through the interaction of the dye’s sulfonic acid groups with the basic groups of collagen [31]. Cells were seeded in 96-well plates at a density of 1 × 104 cells/well and incubated for 24 h at 37 °C in a humidified atmosphere containing 5% CO2. After incubation, the cells were treated with passion fruit extracts and further incubated under the same conditions for 24 h. Collagen production was then assessed using Sirius Red staining. Briefly, 0.1% (w/v) Sirius Red solution was added to each well and incubated for 24 h. The staining solution was subsequently removed, and the cells were washed five times with 10 mM HCl to eliminate unbound dye. The absorbance was measured at 560 nm using a microplate reader (SPECTROstar Nano, BMG Labtech, Aylesbury, UK). L-Ascorbic acid was used as the positive control. The percentage of collagen biosynthesis was calculated using the following equation:
% Collagen synthesis activity = [(ASample/AControl) × 100] − 100
where ASample is the absorbance of test compound, and AControl is the absorbance of control group.

2.10. Molecular Docking

Molecular docking was performed to evaluate the predicted binding behavior of selected putative compounds identified by LC–QTOF/MS against anti-aging-related targets, namely collagenase and hyaluronidase enzymes. Piceatannol and trans-ferulic acid were selected as representative compounds based on metabolite abundance and extract-specificity analysis. The three-dimensional structures of the selected compounds were obtained from the PubChem database and subjected to geometry optimization using Gaussian 16 at the B3LYP/6-31G(d,p) level [32,33]. The crystal structures of the target proteins were retrieved from the RCSB Protein Data Bank, including hyaluronidase (PDB ID: 2PE4) and collagenase (PDB ID: 1CGL). Protein structures were prepared by removing co-crystallized ligands and water molecules, followed by the addition of hydrogen atoms. The protonation states of amino acid residues were assigned using the PROPKA web server to reflect the pH conditions used in the in vitro anti-aging assays, pH 7.0 for collagenase and pH 3.8 for hyaluronidase. When co-crystallized ligands were available, the docking protocol was validated by redocking native ligands into their corresponding binding sites, with an RMSD value below 2.0 Å considered acceptable. The optimized compounds were subsequently docked into the binding sites of the target proteins using AutoDock Vina version 1.2 [34]. The conformations with the lowest predicted binding energies were selected for analysis of binding modes and ligand–protein interactions.

2.11. Statistical Analysis

All data are expressed as the mean ± standard deviation (SD) of three independent experiments. Statistical analysis was conducted using GraphPad Prism version 8.0. Differences among experimental groups were assessed by one-way analysis of variance (ANOVA), followed by Tukey’s multiple-comparison post hoc test. Statistical significance was defined as p < 0.05.

3. Results and Discussion

3.1. Extraction Yield, TPC, and TFC of Passion Fruit Extracts

The physical appearance of the ethanolic passion fruit extracts, PPE, PSC, and PSE, was a yellow-brown semisolid with a characteristic odor. As shown in Table 1, the highest extraction yield was obtained from PPE (71.43 ± 1.24%), followed by PSE (27.97 ± 1.03%) and PSC (21.51 ± 0.87%), respectively.
The TPC and TFC of passion fruit extracts differed among fractions. PSC showed the highest phenolic content, followed by PSE, while PPE exhibited the lowest. In contrast, TFC were predominantly enriched in the seed extract, indicating that seeds are a major source of flavonoid compounds. The higher phenolic content in PSC may result from the combined contribution of pulp and seed components, leading to a broader range of bioactive compounds. According to Sabogal-Palma et al., different maturation stages of passion fruit pulp, peel, and seed demonstrated varying amounts of phenolic compounds, with phenolic compounds being particularly abundant in the seeds and leaves, surpassing those found in the edible pulp [35]. These results indicate that different fruit fractions contribute uniquely to bioactive composition, with PSC providing broader phenolic diversity and PSE serving as a major source of flavonoids.

3.2. LC–QTOF/MS Metabolite Profiling and Feature Prioritization of Passion Fruit Extracts

Untargeted LC–QTOF/MS analysis revealed distinct metabolite profiles among the three passion fruit extracts (PPE, PSC, and PSE), in both ESI positive and negative ionization modes (Figure 1). The detected metabolites were broadly grouped into three major chemical classes, including flavonoids, phenolic compounds, and other metabolites, mainly alkaloids and coumarins. The observed sample-specific abundance patterns suggest differential distribution of secondary metabolites between pulp- and seed-derived fractions of Passiflora species [3].
PPE showed relatively high levels of hydroxycinnamic acid derivatives, including trans-ferulic acid, dicaffeoylquinic acid derivatives, 4,5-di-O-caffeoylquinic acid, and 4-methylcoumarin. This finding is consistent with previous reports describing ferulic acid, caffeic acid, chlorogenic acid, and p-coumaric acid as major phenolic acids in P. edulis pulp [36]. In addition, cyanidin-3-O-galactoside, 3-methylquercetin, and quercetin-3-O-glucosyl-6-acetate were predominantly associated with PPE, supporting the presence of anthocyanin-related and flavonol-derived compounds in passion fruit pulp and peel [3,37].
PSE was distinguished by the enrichment of stilbene derivatives and flavonoid aglycones or glycosides. Piceatannol, dihydrostilbene glycoside, and naringenin were among the most abundant metabolites in the seed fraction, supporting the role of piceatannol as a characteristic stilbenoid marker of passion fruit seeds [17]. Other PSE-associated compounds included myricetin, isorhamnetin, kaempferol, kaempferol-3-O-glucuronoside, quercitrin, syringetin-3-O-glucoside, kaempferol 3-sophoroside-7-rhamnoside, and triacetyl resveratrol. These findings are consistent with previous studies reporting high polyphenol contents and antioxidant potential in passion fruit seeds [1,17].
PSC exhibited an intermediate but distinctive metabolite profile, reflecting its mixed seed–pulp composition. This fraction contained several alkaloids and coumarins, including caffeine, trigonelline, harmane, harman, harmalol, coumarin, umbelliferone, and aloesin, together with diverse flavonoids and phenolic compounds such as naringenin-7-O-glucoside, procyanidin B1, genistein and its glycosides, rutin, vitexin, gallic acid, and p-coumaric acid. The detection of β-carboline and indole alkaloids is consistent with previous reports of harmala alkaloids in the genus Passiflora [38,39], while vitexin and rutin have been widely reported in P. edulis and related species [40,41]. This composite profile suggests complementary contributions from both pulp and seed tissues.
The present findings demonstrate distinct phytochemical patterns among the three extracts. PPE was mainly associated with phenolic acids and anthocyanin-related compounds, PSE with stilbene and flavonoid derivatives, and PSC with alkaloids, coumarins, and diverse flavonoid glycosides. These results highlight their complementary contributions to the metabolite profile of passion fruit by-products.

3.3. Comparative LC–QTOF/MS Profiling of Putatively Annotated Metabolites

To characterize the distribution of phenolic constituents across the three extracts, the top-ranked metabolites were evaluated according to normalized log2 intensity and relative extract-enrichment patterns, after excluding fatty acids, carbohydrates, and other non-phenolic metabolites from the dataset. The complete list of putatively annotated metabolites, including retention time, observed m/z, mass error, normalized log2 intensities, log2 fold-change values, relative extract-enrichment scores, dominant fraction assignment, and MSI confidence level, is provided in Supplementary Table S1.
Trans-ferulic acid and dicaffeoylquinic acid, a chlorogenic acid derivative, were consistently among the most abundant metabolites across all three extracts, displaying high log2 intensities in PPE, PSC, and PSE (Figure 2a). In contrast, piceatannol was particularly prominent in the seed-containing extracts, consistent with its established role as a seed-associated stilbene of Passiflora species [17,42].
The relative extract-enrichment analysis further distinguished broadly distributed metabolites from extract-selective compounds (Figure 2b). Both trans-ferulic acid and dicaffeoylquinic acid exhibited high mean log2 intensities but low specificity scores, indicating that these hydroxycinnamic acid derivatives represent major shared phenolic constituents across pulp- and seed-containing fractions. By contrast, piceatannol displayed both high abundance and the highest specificity score among the labeled markers, identifying it as a discriminative seed-associated metabolite. Other compounds such as naringenin and dihydrostilbene glycoside also showed moderate specificity for PSE, further supporting the enrichment of stilbene- and flavanone compounds in seed-containing fractions. Together, these profiling results indicate that the three extracts share a common phenolic backbone dominated by hydroxycinnamic acid derivatives, while the seed-containing extracts are additionally enriched in stilbenoid and flavanone constituents.

3.4. Antioxidant Activities of Passion Fruit Extracts

The antioxidant activities of the passion fruit extracts are shown in Table 2. The antioxidant activity was determined using DPPH and FRAP assays. The DPPH assay measures free radical scavenging activity, reflecting the capability of a compound to donate hydrogen atoms, while the FRAP assay quantifies antioxidant power based on the reduction in ferric (Fe3+) to ferrous (Fe2+) ions [43]. For the DPPH assay, PSE exhibited strong radical scavenging activity, as indicated by its low IC50 value; however, its activity was significantly lower than that of piceatannol (p < 0.05). PPE showed the weakest DPPH activity, consistent with its lower phenolic and flavonoid contents. In the FRAP assay, PSE exhibited the highest reducing power among the extracts, followed by PSC, whereas PPE showed no detectable activity. This may be attributed to its low phenolic content and the higher proportion of non-phenolic constituents such as sugars and polysaccharides, which contribute little to ferric ion reduction, as the FRAP assay primarily reflects the electron-donating capacity of phenolic compounds [44].
Among the samples, piceatannol exhibited the highest reducing power in the FRAP assay, highlighting its strong electron-donating capacity. Piceatannol, with its four hydroxyl groups on two aromatic rings, possesses a greater capacity for electron donation, resulting in superior reducing power. These findings suggest that piceatannol is a strong electron-donating antioxidant, which is consistent with its known mechanism of action as a potent reducing agent [4]. These results are in agreement with Morais et al. [45], who reported that passion fruit seeds exhibited the highest antioxidant capacity in the DPPH and FRAP assay compared to pulp and peel fractions. Similarly, Sabogal-Palma et al. [35] demonstrated that the seed fraction of purple passion fruit showed superior phenolic content and antioxidant activity compared to pulp and peel. The higher antioxidant activity of PSE in both assays is likely due to the abundant stilbenes, particularly piceatannol, which is a characteristic compound of P. edulis seeds with strong antioxidant properties [4]. Overall, these results demonstrate that seed-derived compounds, particularly piceatannol, play a key role in driving antioxidant activity in passion fruit fractions.

3.5. Hyaluronidase and Collagenase Inhibitory Activities of Passion Fruit Extracts

The anti-aging activities of the passion fruit extracts based on their hyaluronidase and collagenase inhibitory activities are shown in Table 3. Hyaluronidase is an enzyme that breaks down hyaluronic acid, a key component responsible for skin moisture and structural integrity. Its inhibition helps maintain skin hydration and elasticity, thereby slowing signs of aging such as wrinkles and sagging [29]. Collagenase is an enzyme that degrades collagen fibers, which are critical for skin firmness and structure. Its inhibition helps preserve skin firmness and reduce wrinkle formation [46].
In the anti-hyaluronidase activity, PSE showed the highest activity among the extracts and was comparable to piceatannol (p > 0.05), whereas PPE and PSC exhibited lower inhibition effects. For collagenase inhibition, PSE showed the highest collagenase inhibitory activity among the extracts and exhibited significantly higher activity than EGCG and piceatannol (p < 0.05), whereas PPE and PSC exhibited lower inhibitory activity. PSE demonstrated dual inhibition of collagenase and hyaluronidase, suggesting a multi-target mechanism in preserving ECM integrity responsible for maintaining skin hydration, elasticity, and firmness [47]. The stronger collagenase inhibition indicates a primary role in preventing collagen degradation, while hyaluronidase inhibition may support the maintenance of hyaluronic acid and skin hydration. Therefore, the simultaneous inhibition of these enzymes represents a multi-target strategy for preserving ECM integrity and mitigating skin aging, highlighting its potential as a natural anti-aging agent.
Based on these results, PSC and PSE were selected for subsequent cell cytotoxicity studies due to their complementary bioactive profiles. PSC exhibited strong antioxidant potential, while PSE demonstrated the strongest hyaluronidase and collagenase inhibitory activities, indicating promising anti-aging properties.

3.6. Cytotoxicity and Collagen Biosynthesis Stimulation of Passion Fruit Extracts

The MTT assay was used to evaluate the effect of passion fruit extracts on the viability of human skin fibroblasts, shown in Figure 3a. All concentrations of extracts maintained cell viability above 80%, indicating no cytotoxicity. PSC was non-toxic at all tested concentrations, with cell viability exceeding 100%, suggesting a potential cell proliferative effect. PSE showed slight cytotoxicity only at 1 mg/mL (79.66 ± 2.72%). Piceatannol promoted cell proliferation (152.89 ± 3.54%), consistent with previous reports on its ability to enhance fibroblast proliferation [4,17]. Based on these findings, 0.1 and 0.01 mg/mL were selected as the highest non-cytotoxic concentration for subsequent collagen biosynthesis assays.
As shown in Figure 3b, at 0.1 mg/mL, the Sirius Red assay revealed that PSC significantly stimulated collagen production (8.07 ± 2.24%) compared with that of PSE (2.26 ± 1.33%) (p < 0.05). Among the reference compounds, piceatannol exhibited the highest collagen-stimulating activity (11.34 ± 1.50%), comparable to that of the positive control L-ascorbic acid (13.90 ± 1.16%). At 0.01 mg/mL, only piceatannol and L-ascorbic acid retained activity, suggesting that a minimum effective concentration is required for the extracts to elicit a measurable collagen-stimulating effect.
The enhanced collagen production observed for PSC may be attributed to the combined presence of bioactive compounds from both pulp and seed fractions, which provides a broader range of phytochemicals compared to individual fractions [48]. Such complexity has been reported to contribute to enhanced biological activity in plant extracts. This suggests that anti-degradation and biosynthesis involve distinct pathways. PSE, rich in flavonoids and stilbenes, may be more effective at protecting existing collagen from enzymatic degradation, while PSC, may be more effective in promoting collagen synthesis. Previous studies have demonstrated that passion fruit seed extract rich in piceatannol suppresses UVB-induced MMP-1-mediated collagen degradation and attenuates cellular senescence [49]. Additionally, piceatannol upregulates collagen synthesis through SIRT1-mediated pathways, increasing COL1A1 and COL1A2 expression while suppressing MMP expression [50]. The collagen stimulatory effects of P. edulis extracts may be attributed to their rich polyphenolic content, as polyphenols have been shown to reduce ROS-mediated signaling and promote collagen biosynthesis in dermal fibroblasts [4,51]. Therefore, PSC and PSE may serve complementary roles, with PSC promoting collagen biosynthesis and PSE inhibiting extracellular matrix degradation, offering a dual anti-aging approach.

3.7. Molecular Docking Analysis of Putative Compounds Against Hyaluronidase and Collagenase

Based on these complementary characteristics, trans-ferulic acid and piceatannol were selected as representative compounds for molecular docking, with trans-ferulic acid representing a broadly abundant hydroxycinnamic acid derivative and piceatannol representing a seed-enriched stilbene identified by LC–QTOF/MS analysis. This selection aligns with the observed biological activity profiles, particularly the stronger antioxidant and anti-aging inhibitory effects of PSE and the collagen biosynthesis–stimulating activity of PSC, both of which contained shared phenolic acids and seed-associated stilbenes.
The binding affinities and molecular interaction patterns of piceatannol and trans-ferulic acid toward hyaluronidase and collagenase, two enzymes involved in extracellular matrix degradation and skin aging, are presented in Figure 4. In molecular docking analysis, lower predicted binding energies generally indicate more favorable ligand–receptor interactions. Among the selected putative compounds, piceatannol exhibited stronger predicted binding affinities toward both enzymes, with binding energies of −7.8 kcal/mol for hyaluronidase and −7.6 kcal/mol for collagenase, whereas trans-ferulic acid displayed comparatively weaker affinities of −6.1 and −6.7 kcal/mol, respectively.
In the hyaluronidase binding site (Figure 4a), piceatannol formed hydrogen bonds with Tyr247, Tyr261, Tyr208, and Arg265, together with hydrophobic interactions involving Tyr210 and Phe204. Trans-ferulic acid formed hydrogen bonds with Tyr75 and Tyr202, along with hydrophobic interactions involving Tyr286 and Trp321. Notably, Asp129, Tyr202, Tyr247, and Arg265 have been reported as important residues for hyaluronidase catalytic activity or substrate recognition [52,53]. The greater number of polar contacts observed for piceatannol may be related to its four hydroxyl groups, which provide more potential hydrogen-bonding sites than trans-ferulic acid [54].
In the collagenase binding site (Figure 4b), piceatannol formed hydrogen bonds with Arg214, Ser239, His218, Asn180, and Ala182, together with hydrophobic interactions involving Tyr240, Val215, and His228. These interactions positioned piceatannol near the catalytic Zn2+ ion. Trans-ferulic acid interacted with Ser239, Glu219, Tyr237, Arg214, and Ala182 through hydrogen bonding and with His222 and His228 through π-contacts. The involvement of residues such as His222 and Glu219 is relevant because these residues are associated with the catalytic region of collagenase and may influence enzyme activity [55]. The proximity of both ligands to the Zn2+ and Ca2+ ions further suggests potential interaction with the metal-containing catalytic environment [56]. Engagement of histidine residues that coordinate the catalytic zinc, particularly His218, His222, and His228, is characteristic of effective collagenase (MMP) inhibitors [57], suggesting that both compounds may interfere with enzymatic activity through partial occupancy of the zinc-binding pocket.
Taken together, the docking results suggest that piceatannol forms more extensive predicted interactions than trans-ferulic acid with both hyaluronidase and collagenase. This trend is consistent with the stronger anti-aging enzyme inhibitory activity observed for the PSE extract, in which piceatannol was identified as a major seed-associated stilbene. The enhanced predicted binding of piceatannol may be attributed to its hydroxyl-rich stilbene structure, which supports multiple hydrogen-bonding and π-interactions. In contrast, trans-ferulic acid exhibited moderate predicted binding toward both enzymes, consistent with its possible contribution as a broadly abundant phenolic acid across the extracts [58].
Nevertheless, these docking results should be interpreted as supportive mechanistic evidence rather than direct proof of enzyme inhibition, as molecular docking does not fully account for solvent effects, protein flexibility, or concentration-dependent biological responses. Further confirmation using authentic standards, enzyme kinetic assays, and binding affinity studies is therefore required to validate the contribution of piceatannol and trans-ferulic acid to the observed anti-aging activities.
The comparative analysis of the three passion fruit extracts demonstrated distinct compositional and functional profiles. PSE showed the strongest antioxidant and anti-aging inhibitory activities, possibly associated with its enrichment in piceatannol and related stilbenes, whereas PSC exhibited a broader phytochemical profile with notable collagen biosynthesis-stimulating activity, suggesting complementary contributions from seed and pulp tissues. However, the metabolites were putatively annotated by untargeted LC–QTOF/MS, and individual bioactive compounds were not quantitatively determined, limiting direct attribution of activity to specific constituents. Further studies should include targeted quantification of piceatannol and trans-ferulic acid, validation in ex vivo or in vivo skin models, and topical formulation development of PSE and PSC to evaluate stability, skin permeation, and bioavailability for cosmeceutical applications.

4. Conclusions

This study demonstrates that Passiflora edulis processing by-products exhibit fraction-dependent anti-aging potential. Although PPE gave the highest extraction yield, it showed limited functional activity compared with the seed-containing fractions. PSE showed stronger antioxidant capacity and collagenase/hyaluronidase inhibition, whereas PSC most effectively stimulated type I collagen production in human dermal fibroblasts. These findings support the working hypothesis that different passion fruit by-product fractions provide complementary, rather than identical, bioactivity profiles.
The integrated LC–QTOF/MS profiling and molecular docking results suggest that phenolic and stilbene-related metabolites, particularly piceatannol and trans-ferulic acid, may contribute to these activities. However, the metabolomic and docking results should be interpreted as supportive and hypothesis-generating, as metabolite annotations were putative and the profiling analysis was descriptive. Further validation of key metabolites, mechanisms of action, and dermal applicability will be required before practical development.
Overall, PSE and PSC represent promising sustainable sources of natural anti-aging ingredients. PSE may be more suitable for antioxidant and enzyme-inhibitory applications, whereas PSC may offer particular value for collagen-stimulatory applications, supporting the valorization of passion fruit processing by-products for future skin-aging applications.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/compounds6020032/s1, Table S1: Putatively annotated metabolites identified in PPE, PSE, and PSC by LC–QTOF/MS analysis, including retention time, observed m/z, adduct type, library matching score, normalized log2 intensities, log2 fold-change comparisons, extract-enrichment scores and MSI confidence level.

Author Contributions

Conceptualization, S.C., S.J. and N.N.; methodology, S.C., K.K. and N.N.; software, S.C. and N.N.; validation, S.C., K.K. and N.N.; formal analysis, S.C. and N.N.; investigation, S.C. and N.N.; data curation, S.C., S.J., K.K. and N.N.; writing—original draft preparation, S.C. and N.N.; writing—review and editing, S.C. and N.N.; visualization, S.C. and N.N.; supervision, S.C. and S.J.; project administration, S.C.; funding acquisition, S.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the CMU Junior Research Fellowship Program, Chiang Mai University, grant number JRCMU2566R_099.

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Materials. Further inquiries can be directed to the corresponding author.

Acknowledgments

The authors would like to thank the Faculty of Pharmacy, Chiang Mai University, for providing the necessary resources and facilities. During the preparation of this manuscript, the authors used ChatGPT (OpenAI, GPT-5.4) for the purposes of assisting with language editing and refinement of the manuscript content. The authors take full responsibility for the accuracy, integrity, and originality of the content presented in this publication.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
ANOVAAnalysis of Variance
BSABovine Serum Albumin
DIDeionized Water
DMEMDulbecco Modified Eagle Medium
DMSODimethyl Sulfoxide
DPPH2,2-Diphenyl-1-picrylhydrazyl
ECMExtracellular Matrix
FALGPAN-[3-(2-furyl)acryloyl]-Leu-Gly-Pro-Ala
FCFold Change
FRAPFerric Reducing Antioxidant Power
GAEGallic Acid Equivalent
HClHydrochloric Acid
LC-QTOF/MSLiquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry
MTT3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide
PBSPhosphate-Buffered Saline
PLS-DAPartial least squares–discriminant analysis
PPEPassion fruit pulp extract
PSCPassion fruit pulp-with-seed extract
PSEPassion fruit seed extract
QEQuercetin Equivalent
RMSDRoot Mean Square Deviation
ROSReactive Oxygen Species
SDStandard Deviation
TFCTotal Flavonoid Content
TPCTotal Phenolic Content
TPTZ2,4,6-Tripyridyl-s-triazine
UVUltraviolet
VIPVariable Importance in Projection

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Compounds 06 00032 g001
Figure 1. Hierarchical clustering heatmap of putatively identified secondary metabolites in passion fruit extracts analyzed by untargeted LC–QTOF/MS in ESI positive (left) and ESI negative (right) modes. Color intensity represents log2-transformed peak intensities (dark purple, low; yellow, high). Annotation bars indicate the dominant sample (PPE, PSC, PSE) and chemical class (flavonoids, phenolics, others) for each metabolite.
Figure 1. Hierarchical clustering heatmap of putatively identified secondary metabolites in passion fruit extracts analyzed by untargeted LC–QTOF/MS in ESI positive (left) and ESI negative (right) modes. Color intensity represents log2-transformed peak intensities (dark purple, low; yellow, high). Annotation bars indicate the dominant sample (PPE, PSC, PSE) and chemical class (flavonoids, phenolics, others) for each metabolite.
Compounds 06 00032 g001
Compounds 06 00032 g002
Figure 2. Top-ranked putative metabolites in passion fruit extracts (PPE, PSC, and PSE) identified by LC–QTOF/MS. (a) Top ten metabolites per extract ranked by log2 intensity; bar colors indicate the extract groups: PPE, orange; PSC, green; and PSE, pink. (b) Mean log2 intensity versus relative extract-enrichment scores; key discriminative markers are labeled.
Figure 2. Top-ranked putative metabolites in passion fruit extracts (PPE, PSC, and PSE) identified by LC–QTOF/MS. (a) Top ten metabolites per extract ranked by log2 intensity; bar colors indicate the extract groups: PPE, orange; PSC, green; and PSE, pink. (b) Mean log2 intensity versus relative extract-enrichment scores; key discriminative markers are labeled.
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Compounds 06 00032 g003
Figure 3. Effects of passion fruit extracts and selected compounds on human fibroblasts. (a) Cell viability after treatment with PSC, PSE, and piceatannol at 0.0001–1 mg/mL. The gray and red dashed lines indicate 100% and 80% cell viability, respectively. (b) Collagen biosynthesis stimulation after treatment with PSC, PSE, piceatannol, and L-ascorbic acid at 0.1 and 0.01 mg/mL Different letters indicate significant differences (p < 0.05): lowercase letters (a–c) for 0.1 mg/mL and uppercase letter (A) for 0.01 mg/mL. NA, not available.
Figure 3. Effects of passion fruit extracts and selected compounds on human fibroblasts. (a) Cell viability after treatment with PSC, PSE, and piceatannol at 0.0001–1 mg/mL. The gray and red dashed lines indicate 100% and 80% cell viability, respectively. (b) Collagen biosynthesis stimulation after treatment with PSC, PSE, piceatannol, and L-ascorbic acid at 0.1 and 0.01 mg/mL Different letters indicate significant differences (p < 0.05): lowercase letters (a–c) for 0.1 mg/mL and uppercase letter (A) for 0.01 mg/mL. NA, not available.
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Compounds 06 00032 g004
Figure 4. Molecular docking of piceatannol (magenta) and trans-ferulic acid (cyan) with (a) hyaluronidase and (b) collagenase. For each ligand, the 3D binding pose (left) and 2D interaction diagram (right) are shown, with key interacting residues labeled. Catalytic Zn2+ and Ca2+ ions in the collagenase active site are shown as gray and green spheres, respectively, while dashed green, pink, and orange lines indicate hydrogen-bond, hydrophobic, and π-anion interactions, respectively.
Figure 4. Molecular docking of piceatannol (magenta) and trans-ferulic acid (cyan) with (a) hyaluronidase and (b) collagenase. For each ligand, the 3D binding pose (left) and 2D interaction diagram (right) are shown, with key interacting residues labeled. Catalytic Zn2+ and Ca2+ ions in the collagenase active site are shown as gray and green spheres, respectively, while dashed green, pink, and orange lines indicate hydrogen-bond, hydrophobic, and π-anion interactions, respectively.
Compounds 06 00032 g004
Table 1. Total phenolic content (TPC) and total flavonoid content (TFC) of passion fruit extracts (PPE, PSC, and PSE).
Table 1. Total phenolic content (TPC) and total flavonoid content (TFC) of passion fruit extracts (PPE, PSC, and PSE).
Passion Fruit
Extracts		TPC
(mg GAE/g Extract)		TFC
(mg QE/g Extract)
PPE3.17 ± 0.13 c2.83 ± 0.03 b
PSC14.81 ± 3.55 a4.01 ± 0.2 b
PSE9.83 ± 0.57 b25.05 ± 0.19 a
Different letters (a–c) indicate a significant difference at p < 0.05.
Table 2. Antioxidant activities of passion fruit extracts (PPE, PSC, and PSE).
Table 2. Antioxidant activities of passion fruit extracts (PPE, PSC, and PSE).
SampleIC50 DPPH
(mg/mL)		FRAP Value
(mg FeSO4/g Sample)
PPE9.43 ± 2.66 dND #
PSC0.83 ± 0.10 c1.31 ± 0.02 c
PSE0.19 ± 0.05 b35.25 ± 3.47 b
Piceatannol0.03 ± 0.01 a179.59 ± 4.19 a
Different letters (a–d) indicate a significant difference at p < 0.05. # ND: not detected.
Table 3. Anti-hyaluronidase and collagenase inhibitory activities of passion fruit extracts (PPE, PSC, and PSE).
Table 3. Anti-hyaluronidase and collagenase inhibitory activities of passion fruit extracts (PPE, PSC, and PSE).
SamplesAnti-Hyaluronidase Activity (%)Collagenase Inhibition (%)
PPE19.91 ± 0.68 c24.58 ± 5.56 d
PSC20.13 ± 2.30 c54.24 ± 9.60 b
PSE23.75 ± 1.68 b,c79.80 ± 7.3 a
Piceatannol26.77 ± 1.43 b33.33 ± 3.07 c
Tannic acid82.13 ± 4.04 a-
(−)-EGCG-25.00 ± 12.33 d
Different letters (a–d) indicate a significant difference at p < 0.05.
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Chaichit, S.; Nitthikan, N.; Kiattisin, K.; Jiranusornkul, S. Chemical Composition and Anti-Aging Potential of Passiflora edulis By-Product Fractions: A Comparative Study Integrating Metabolomic Profiling and Molecular Docking. Compounds 2026, 6, 32. https://doi.org/10.3390/compounds6020032

AMA Style

Chaichit S, Nitthikan N, Kiattisin K, Jiranusornkul S. Chemical Composition and Anti-Aging Potential of Passiflora edulis By-Product Fractions: A Comparative Study Integrating Metabolomic Profiling and Molecular Docking. Compounds. 2026; 6(2):32. https://doi.org/10.3390/compounds6020032

Chicago/Turabian Style

Chaichit, Siripat, Nichcha Nitthikan, Kanokwan Kiattisin, and Supat Jiranusornkul. 2026. "Chemical Composition and Anti-Aging Potential of Passiflora edulis By-Product Fractions: A Comparative Study Integrating Metabolomic Profiling and Molecular Docking" Compounds 6, no. 2: 32. https://doi.org/10.3390/compounds6020032

APA Style

Chaichit, S., Nitthikan, N., Kiattisin, K., & Jiranusornkul, S. (2026). Chemical Composition and Anti-Aging Potential of Passiflora edulis By-Product Fractions: A Comparative Study Integrating Metabolomic Profiling and Molecular Docking. Compounds, 6(2), 32. https://doi.org/10.3390/compounds6020032

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