Unveiling the patterns and mechanisms of time-specific release of multifunctional peptides from cricket protein

Abstract

Endpoint-based studies failed to clarify time-resolved hydrolysis properties, bioactivities, peptide profiles, and structural characteristics. Current study aimed to explore the correlations of these characteristics during Alcalase hydrolysis of cricket protein (CP) for 30–300 min. Prolonged hydrolysis increased degree of hydrolysis (DH) to 20.3%, with low-molecular-weight peptides (< 2 kDa) accounting for 88.0%–94.0%. Cricket protein hydrolysates (CPHs) showed strongest antioxidant and angiotensin I-converting enzyme (ACE) inhibitory activities at 30 and 300 min, respectively, whereas dipeptidyl peptidase-IV (DPP-IV) inhibition exhibited a bimodal pattern. Structural analyses demonstrated hydrolysis disrupted ordered CP structure, with α-helix+β-sheet decreasing by 17.4%–26.5%, alongside lowered surface hydrophobicity and increased sulfhydryl exposure. Antioxidant and ACE inhibition were positively associated with structural unfolding and hydrolysis property promotion, whereas DPP-IV inhibition appeared to relate more to peptide-release characteristics. Activity-guided peptidomics and multivariate analyses prioritized LYPL/VYGPL, SGLFDK/PAALGL, and SGPRLH/FAGPS as candidate peptides potentially associated with antioxidant, ACE inhibitory, and DPP-IV inhibitory activities, respectively.

Graphical abstract

Highlights

• •Alcalase time-specifically dictated hydrolysis property, peptide profiles and multifunction.
• •Antioxidant and ACE inhibition positively correlated with structural unfolding related hydrolysis efficacy promotion.
• •DPP-IV inhibition relied more on characteristics of specific peptide motifs.
• •Activity-guided multivariate and differential peptide profile analysis revealed candidate peptides.

1. Introduction

Protein is one of the essential sources of energy and nutrition for the body. Dietary proteins are degraded into low-molecular-weight peptides by gastrointestinal proteases and peptidases after ingestion, and some of the released peptides possess biological activities. The health-promoting properties of bioactive peptides have attracted widespread attention because of their antioxidant, antihypertensive, and antidiabetic potential (Teixeira et al., 2023). Recent studies have identified peptides with ACE inhibitory, DPP-IV inhibitory, antioxidant, anti-inflammatory, and antidiabetic potential from red seaweed and casein proteins, further highlighting the functional diversity and health-promoting potential of food-derived bioactive peptides (Aziz et al., 2025; Basri et al., 2025). Meanwhile, the continuous growth of the global population has increased the demand for sustainable proteins and stimulated interest in edible insects as alternatives to conventional animal-derived proteins. The Food and Agriculture Organization (FAO) of the United Nations has also recognized insect proteins as promising alternatives because of their high feed-conversion efficiency and low carbon emissions (Ma et al., 2023). Cricket has emerged as a particularly favorable option, characterized by a protein content of more than 70% and a well-balanced amino acid profile (Udomsil et al., 2019). These characteristics make cricket protein (CP) a promising precursor for the development of bioactive peptides and sustainable multifunctional ingredients. Previous studies have demonstrated the potential of cricket proteins as promising precursors for the generation of bioactive peptides with diverse biological functions (Teixeira et al., 2023). Nevertheless, the time-dependent evolution of peptide profiles and multiple bioactivities during enzymatic hydrolysis of cricket protein remains insufficiently characterized. However, its application in food products remains limited by neophobia-induced low consumer acceptance and insufficient exploration of its multifunctional potentials (Kröger et al., 2022).

Enzymatic hydrolysis can process whole insects into less recognizable ingredients while releasing peptides with potential biological activities. Previous studies have indicated that the bioactivities of protein hydrolysates are associated with their hydrolysis properties and peptide profiles, both of which are influenced by structural changes during protein hydrolysis (Dong et al., 2024). Normally, enzymatic hydrolysis unfolds protein structures, thereby exposing cleavage sites and facilitating the efficient release of peptides with specific bioactivities (Losasso et al., 2022). This phenomenon has been verified in various plant/animal proteins, and is also applicable to insect proteins (Tian et al., 2020). For example, structural unfolding of silkworm pupa protein before hydrolysis significantly enhanced the ACE and DPP-IV inhibitory activities of its hydrolysate (Thongrattanatrai et al., 2023). These findings collectively support close associations among structural characteristics, hydrolysis properties, peptide profiles, and bioactivities. However, previous research has primarily relied on endpoint analyses of protein hydrolysates, ignoring the time-dependent characterization in protein structure, hydrolysis properties, and peptide profiles during hydrolysis. Correspondingly, the dynamic changes of bioactivities were also ignored. Structural analyses can elucidate the unfolding behavior of proteins throughout hydrolysis. Meanwhile, the integration of peptidomics, bioinformatics, and activity evaluation also offers a powerful approach to track the release, features and bioactivities of peptides throughout hydrolysis. Additionally, bioactive sequences encrypted within parent proteins may exert diverse functions, indicating the potential of food proteins as precursors of multifunctional peptides. Nevertheless, previous studies mainly linked specific bioactivity with a single protein resource, and failed to capture the time-specific hydrolysis property and peptide release driven by structural changes during hydrolysis.

Therefore, this study aimed to characterize the time-resolved changes and interrelationships among hydrolysis properties, bioactivities changes, peptide profiles, and structural characteristics during CP hydrolysis, and further to clarify candidate peptides associated with antioxidant, ACE inhibitory and DPP-IV inhibitory capacities. Specifically, hydrolysis properties and bioactivities of cricket protein hydrolysates (CPHs) prepared at 30–300 min were initially detected, and then their peptide sequences were identified and quantified by UPLC-Q-Orbitrap-MS² and the PepOS workflow. Subsequently, bioactivity-guided multivariate analyses were applied to reveal the quantitative relationships between peptide abundance patterns at different hydrolysis time and related bioactivities by combinations of peptidomics and bioinformatics. The promising peptide candidates were further assessed for their potential target interactions by molecular docking. Furthermore, a multi-approach using Fourier transform infrared spectroscopy (FTIR), surface hydrophobicity, sulfhydryl content and transmission electron microscopy (TEM) was implemented to monitor the dynamic changes in CP structure during hydrolysis. Correlations among hydrolysis property, bioactivities and structural characteristics were conducted as well.

2. Materials and methods

2.1. Materials and reagents

Cricket was provided by Ming Sheng Agricultural Science and Technology Development Co., Ltd. (Yunnan, China). Alcalase® 2.4 L FG (2.4 AU/g) was obtained from Novozymes (Tianjin, China). 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) were purchased were purchased from Aladdin Biochemical Technology Co. (Shanghai, China). ACE inhibitory activity assay kit was obtained from Dojindo Molecular Technologies Inc. (Cat. No. A502, Kumamoto, Japan). DPP-IV inhibitory activity assay kit was obtained from Cayman Chemical Company (Item No. 700210, Ann Arbor, MI, USA). 5,5′-Dithiobis (2-nitrobenzoic acid) (DTNB), cytochrome c, Gly-Gly-Tyr-Arg, Gly-Gly-Gly, bacitracin and aprotinin were purchased from Yuanye Bio-Technology Co., Ltd. (Shanghai, China). Reagents for UPLC-Q-Orbitrap-MS² were of chromatographic grade, while other reagents and chemicals were of analytical grade.

2.2. Preparation of cricket protein hydrolysates (CPHs)

CPHs were prepared according to our previously reported method (Wu et al., 2026), with slight modifications. Cricket was washed, blanched in boiling water for 2 min, dried at 55 °C for 6 h, defatted, ground into powder and then sieved through a 100-mesh sieve. Cricket powder was evenly mixed with deionized water at a ratio of 1:12 (w/v). Subsequently, the pH of cricket slurry was adjusted to 8.0, and 5% (w/w) Alcalase was added based on the protein content of the cricket powder. Hydrolysis was conducted in a water bath (SHA-C, Changzhou Yineng Experimental Instrument Factory, Changzhou, China) at 55 °C for 30, 60, 120, 180, 240 and 300 min. Enzymatic reaction was terminated by heating at 100 °C for 10 min, after which the pH was adjusted to 7.0. The resulting mixture without centrifugation was lyophilized using a vacuum freeze dryer (LGJ-12, Songyuan Huaxing Technology Development (Beijing) Co., Ltd., Beijing, China) and stored at −20 °C for structural characterization, including FTIR, free and total sulfhydryl, surface hydrophobicity and TEM. Concurrently, CPHs were collected by centrifuging the mixture at 8000 rpm for 15 min in a refrigerated centrifuge (GL-20G-C, Shanghai Anting Scientific Instrument Co., Ltd., Shanghai, China), and the supernatant was used for measuring enzymolysis properties, biological activities and peptide profiles.

2.3. Degree of hydrolysis (DH) and amino acid composition

DH was calculated by the ratio of amino nitrogen to total nitrogen, and the contents of amino nitrogen and total nitrogen in CPHs were determined by formaldehyde titration and the Kjeldahl method, respectively, with the latter performed using a Kjeldahl distillation apparatus (LC-KNA-B3, Shanghai Lichen Bangxi Instrument Technology Co., Ltd., Shanghai, China). Amino acid composition was determined according to Liu, Zhao, et al. (2024) with slight modifications, in brief, CPH was initially hydrolyzed with 6.0 M HCl at 110 °C for 22 h, and then adjusted to pH 2.5 and centrifuged at 10,000 rpm for 10 min. Amino acid composition were quantified based on the standard amino acid retention time and peak area using an amino acid analyzer (L-8900, Hitachi, Tokyo, Japan).

2.4. Molecular weight (MW) distribution

MW distribution was performed by Agilent 1260 Infinity II high-performance liquid chromatography system (CA, USA) connecting with a variable wavelength detector (VWD; Agilent Technologies, Santa Clara, CA, USA) and a TSKgel G2000 SWXL column (7.8 mm × 300.0 mm, Tosoh Bioscience, Honshu, Japan). The mobile phase was acetonitrile and water (2:8, v/v) containing 0.1% trifluoroacetic acid. CPH (1 mg/mL, 10 μL) was isocratic eluted at a flow rate of 0.5 mL/min for 40 min, and detection was conducted at 220 nm. MW distribution was determined via a calibration curve constructed with standards (cytochrome c, Gly-Gly-Tyr-Arg, Gly-Gly-Gly, bacitracin and aprotinin).

2.5. Biological activity assay

2.5.1. Antioxidant activity

The antioxidant activity of CPHs was evaluated using DPPH and ABTS radical-scavenging assays according to Thongrattanatrai et al. (2023), respectively, with slight modifications. For the DPPH assay, equal volumes of CPH solution and 0.1 mM DPPH solution were incubated in the dark for 30 min. For the ABTS assay, 38.4 mg ABTS and 33.1 mg K₂S₂O₈ were dissolved in 100 mL deionized water and reacted in the dark at 4 °C for 16 h. CPH solution was then mixed with the ABTS stock solution at 1:2 (v/v) and incubated for 6 min. Absorbance was measured at 517 nm (DPPH) or 734 nm (ABTS) using a multimode microplate reader (SpectraMax M5, Molecular Devices, San Jose, CA, USA). IC₅₀ values were calculated from the corresponding dose–response curves.

2.5.2. ACE/DPP-IV inhibitory activity

ACE and DPP-IV inhibitory activities were determined using the ACE Kit-WST enzymatic assay kit and DPP-IV inhibitor screening assay kit, respectively, in strict accordance with the manufacturers' protocols. For the ACE assay, the protein concentration of CPH was 0.2 mg/mL, and absorbance was recorded at 450 nm using a multimode microplate reader (ELx800, BioTek Instruments, Inc., Winooski, VT, USA). Captopril was used as the positive control, and the corresponding blank correction and inhibition calculation were performed according to the kit instructions. For the DPP-IV assay, the protein concentration of CPH was 1.0 mg/mL. Fluorescence intensity was measured using a SpectraMax M5 multi-mode microplate reader (Molecular Devices, LLC, San Jose, CA, USA) at excitation and emission wavelengths of 350–360 and 450–465 nm, respectively. Sitagliptin was used as the positive control, and background correction and inhibition calculation were performed according to the manufacturer's protocol.

2.6. Identification and characterization of cricket peptides

For LC-MS/MS analysis, equal aliquots from the three independently prepared hydrolysis batches at each hydrolysis time were pooled to generate one composite sample. The pooled CPH sample was then reconstituted in ultrapure water to a final concentration of 1.0 mg/mL and filtered through a 0.22 μm membrane. Peptide profiles were analyzed using an UltiMate 3000 UPLC system coupled to a Q Exactive Focus Orbitrap mass spectrometer (Thermo Fisher Scientific, Germany). Chromatographic separation was performed on a Hypersil GOLD C18 column (1.9 μm, 2.1 mm × 100 mm; Thermo Fisher Scientific) maintaining at 30 °C. The mobile phases consisted of (A) acetonitrile and (B) ultrapure water containing 0.1% formic acid. Gradient elution was carried out at a flow rate of 0.20 mL/min with an injection of 2 μL as follows: 0–1 min, 5% A; 1–2.5 min, 5–10% A; 2.5–12.5 min, 10–25% A; 12.5–20 min, 25–52.5% A; 20–22 min, 52.5–95% A. Mass spectra were acquired in positive electrospray ionization (ESI⁺) mode with a spray voltage of 3.2 kV and a capillary temperature of 350 °C, employing a full-scan data-dependent MS² acquisition method (m/z 200–2000) with resolutions of 70,000 (MS¹) and 35,000 (MS²). Peptide identification and bioactivity prediction were conducted using PepOS 3.2 proteomics analysis platform (Liu, Yang, et al., 2024). Subsequently, peptidomics and bioinformatics were performed to characterize the dynamic peptide profiles of CPHs. All identified peptides were initially evaluated using PeptideRanker (http://distilldeep.ucd.ie/PeptideRanker/), and peptides with scores >0.5 were retained for further UpSet visualization via Hiplot Pro (https://hiplot.com.cn/) and Chiplot (https://www.chiplot.online/) platforms. In silico toxicity was predicted using ToxinPred, and peptides classified as non-toxic were retained as potentially non-toxic candidates (Gupta et al., 2013).

2.7. Partial least squares-discriminant analysis (PLS-DA)

Two-level PLS-DA strategy was used to distinguish peptide profile evolution in this study. PLS-DA was performed using MetaboAnalyst 6.0 (Pang et al., 2024) with the complete LC-MS/MS dataset without PeptideRanker pre-screening. Peptide ion intensity as predictor matrix and hydrolysis time as response variable. This analysis aimed to characterize the overall temporal evolution of peptide composition. On the other hand, activity-oriented PLS-DA was conducted using selected peptides with PeptideRanker scores >0.5 and their relative peak areas. After auto-scaling, CPHs showing relatively high activities were selected as high-activity profiles, including 30 min for antioxidant activity, 300 min for ACE inhibition, and 60, 120, and 240 min for DPP-IV inhibition. Given the limited number of hydrolysis-time profiles, the activity-oriented PLS-DA was used as an exploratory approach for peptide prioritization rather than as a confirmatory classification model. Peptides were prioritized based on score/loading patterns, VIP values, and abundance trends to identify candidates associated with each bioactivity.

2.8. Molecular docking

Molecular docking was performed using SYBYL-X 2.1.1 software to investigate the interactions between cricket peptides and target proteins. Three-dimensional structures of target proteins were retrieved from the Protein Data Bank (PDB; https://www.rcsb.org/), including Keap1 complex (PDB ID: 2FLU), human ACE (PDB ID: 1O8A), and human DPP-IV/CD26 in complex with omarigliptin (PDB ID: 4PNZ). Prior to docking, water and co-crystallized ligands were removed, and polar hydrogens were added to prepare the receptors. Three-dimensional structures of the screened peptides were constructed using SYBYL-X 2.1.1 and energy-minimized with the Tripos force field and Gasteiger-Hückel charges. Docking simulations were performed using Surflex-Dock GeomX module with default parameters, and the protocol threshold was set to 0.5. Docking results were evaluated based on T-score and C-score, and peptides with T-score > 5 and C-score ≥ 4 were considered to have favorable binding potential.

2.9. Fourier transform infrared spectroscopy (FTIR)

FTIR spectra were acquired using a Thermo Nicolet iS5 spectrometer (Thermo Fisher Scientific, Waltham, MA, USA). Samples were prepared using the potassium bromide (KBr) pellet method. CP and uncentrifuged CPH samples (2.0 mg each) were thoroughly mixed with dry KBr, finely ground, and compressed into transparent pellets. Spectra were recorded over 4000–400 cm⁻¹ at a resolution of 4 cm⁻¹, with 32 scans averaged for each spectrum to improve the signal-to-noise ratio.

2.10. Free and total sulfhydryl (F-SH and T-SH)

F-SH and T-SH contents of CPHs were quantified according to a reported procedure with slight adjustments (Liu, Zhao, et al., 2024). Ellman's reagent was prepared by dissolving 4 mg DTNB in 1 mL Tris-Glycine buffer (containing 0.086 M Tris, 0.09 M glycine, 4.00 mM EDTA, pH 8.0). For T-SH determination, 8 M urea was added to the Tris-Glycine buffer to expose buried sulfhydryl groups, whereas no urea was added for F-SH determination. Protein suspension (0.3%, w/v) of 5 mL was combined with 50 μL of Ellman's reagent and incubated with shaking at 25 °C for 1 h. After incubation, mixture was centrifuged at 10,000 ×g for 20 min at room temperature to collect supernatant, and absorbance of supernatant was measured at 412 nm against a buffer blank. Sulfhydryl content was calculated based on the molar extinction coefficient of DTNB (13,600 M⁻¹ cm⁻¹), and expressed as μM/g protein.

2.11. Surface hydrophobicity

CPH was dissolved in 10 mM phosphate buffer (pH 7.0), followed by serial dilution to protein concentrations of 0.05, 0.1, 0.2, 0.3, and 0.4 mg/mL. For measurement, CPH (2 mL) was mixed with 8 mM ANS (40 μL), vortexed, and incubated for 10 min. Fluorescence intensity was measured at excitation/emission wavelengths of 390/470 nm with a 5 nm slit width. Surface hydrophobicity was determined by the initial slope of fluorescence intensity versus concentration plot.

2.12. Transmission electron microscope (TEM)

Morphological observation of CPH was performed using a TEM (HT7800, Hitachi, Japan). CPH dispersion of 0.1 mg/mL was deposited onto a carbon-coated copper grid and allowed to adsorb at room temperature for 5 min. Subsequently, excess liquid was removed by blotting with filter paper. CPH was then air-dried under ambient conditions and negatively stained with 2% phosphotungstic acid for 2 min. Residual stain was carefully blotted away after staining, and conducted to image once air-drying. Micrographs were acquired at an accelerating voltage of 80 kV to characterize the morphological features.

2.13. Data analysis

Experimental data are expressed as mean ± standard deviation from three independently prepared hydrolysis batches (n = 3). Statistical analysis was conducted using SPSS 24.0 software, and significant differences (p < 0.05) among groups were assessed using Duncan's multiple range test. FTIR analysis was performed with OMNIC software (Thermo Fisher Scientific, Waltham, MA, USA), while fluorescence spectroscopy data were analyzed using Peak Fit 4.12 software (Systat Software, San Jose, CA, USA).

3. Results and discussion

3.1. Changes in hydrolysis property, MW distribution and amino acid compositions of CPH

As an efficient broad-spectrum alkaline protease, Alcalase has been documented for its suitability in producing bioactive peptides, and its ability to cut protein groups and generate low molecular weight peptides well consistence with the structural characteristics of bioactive peptides. Alcalase have been reported to be capable of releasing peptides with multifunction (Ozón et al., 2022). Therefore, it was selected in this study to prepare CPH, and enzymatic hydrolysis process was dynamically monitored from 30 to 300 min to investigate the release pattern of peptides. As shown in Fig. 1A, DH of CPHs exhibited a general upward trend over time, reaching maximum at 300 min (20.3%). A distinct plateau phase was observed between 60 and 240 min, at which DH was approximately 18.7%. It might be due to the fact that the abundant cleavage sites available in cricket protein led to a rapid increase in DH at the early stage. As the hydrolysis progressed, the growth rate of DH gradually declined, which could be attributed to the reduced substrate concentration and possible inhibitory effect of products (Singh et al., 2022). Meanwhile, accumulations of hydrophobic groups during hydrolysis further led to the formation of compact aggregates, which might in turn restrict enzymatic accessibility. Aligns with the trends of DH, protein recovery increased progressively from 37.9% at 30 min to 49.9% at 300 min (Fig. 1B). This phenomenon was primarily caused by the enzymatic breakdown of cricket protein into smaller and more soluble fragments (proteins, peptides, and amino acids). Furthermore, enzymatic hydrolysis also enhanced solubility by unfolding the protein structure of cricket. Similarly, Chen et al. (2011) observed a reduction in β-sheet content and an increase in random coils during hydrolysis, which contributed to solubility increase of soy protein.

Fig. 1.

Hydrolysis property and characteristics of CPHs. (A) DH, (B) Recovery, (C) Molecular weight distribution, (D) amino acids composition. Different letters (a–e) indicate significant differences (p < 0.05).

MW distribution and amino acid compositions are important factors influencing the biological activities of peptides (Mirzaee et al., 2023). MW distribution of CPHs was in agreement with DH results. In Fig. 1C, peptides with MW < 2 kDa were dominant in all CPHs ranged from 88.0%–94.0%, and this proportion gradually increased with prolonged hydrolysis time. Notably, low-MW peptides (< 0.5 kDa) accounted for over 60.0% in CPHs after 120 min hydrolysis. SDS-PAGE also supported this situation that Alcalase treatments caused a substantial disappearance in large-molecular-weight protein bands, which is due to the degradation of proteins into small fragments (Fig. S1). Current results indicated that Alcalase could effectively degrade cricket protein into small peptide fragments. Additionally, amino acid compositions diversified among CPHs obtained at different hydrolysis time with 528.2–669.9 mg/g (Fig. 1D). CPHs were characterized by the high levels of Glu, Pro and Ala, followed by Asp and Leu. Notably, CPHs contained appreciable levels of hydrophobic amino acids (259.7–332.1 mg/g), including Gly, Ala, Val, Met, Ile, Leu, Phe and Pro. Contents of aromatic amino acids Phe and Tyr ranged from 35.7 to 46.6 mg/g, while sulfur-containing amino acids, including Cys and Met, ranged from 10.2 to 13.6 mg/g. CPHs prepared at 240 and 300 min displayed the highest contents of hydrophobic, aromatic and sulfur-containing amino acids, whereas significantly lower contents of these amino acids were found in CPHs at 120- and 180-min hydrolysis. Hydrophobic, aromatic and sulfur-containing amino acid residues are widely recognized as pivotal contributors for peptides to exert biological activities, since these residues are often involved in interactions with radicals, enzymes, or other molecular targets (Sun & Udenigwe, 2020). On the basis of the amino acid profiles, CPHs were expected to possess promising nutritional and functional properties.

3.2. Peptide population characterization and bioactivity prediction of CPH

In this study, UPLC-Q-Orbitrap-MS/MS was applied to identify the time-evolution peptide profiles of CPHs, with aim of following the characterization of peptide population during hydrolysis and their relationship with bioactivities via peptidomic and bioinformatic approaches. The number of identified peptides increased progressively across hydrolysis time (30, 60, 120, 180, 240, and 300 min), reaching 1072, 1301, 1333, 1399, 1408, and 1439, respectively. This finding aligned with the observed increases in DH and low-MW fractions in CPHs, thereby further confirming the time-dependent efficacy of Alcalase in cricket peptides' release. As shown in Fig. 2A, the hierarchical clustering heatmap revealed marked differences in peptide composition among hydrolysis time points and reflected dynamic changes occurring throughout hydrolysis. Specifically, the gradient from red to blue indicated a decrease in peptide abundance, and the distinct distribution of red/blue regions suggested that peptide generation and degradation proceeded continuously during enzymatic hydrolysis. To further visualize the overall variation in peptide population of CPHs, PCA was performed (Fig. 2B). The first two principal components explained 46.5% of the total variance, with PC1 and PC2 accounting for 25.8% and 20.7%, respectively. Along PC1, CPHs prepared at 120- and 240 min were distributed at opposite ends, indicating the greatest separation in peptide composition along this axis. Along PC2, 60- and 240 min hydrolysis showed the largest separation. Notably, compared with CPHs prepared at 120- and 240 min, the remaining time points clustered relatively closer, suggesting a higher similarity in peptide composition among these hydrolysates.

Fig. 2.

Peptide profile characterization and bioactivity prediction of CPHs under different enzymatic hydrolysis time. (A) Hierarchical cluster heatmaps of peptide profile dynamics, (B) PCA plot of dynamic changes of peptides, (C) PeptideRanker scores, and values at the top represent the number of peptides with scores >0.5, (D) Biological function of potentially bioactive peptides from CPHs.

Subsequently, to predict the likelihood of biological activities, the identified peptides were further analyzed using a neural network-based algorithm PeptideRanker (Mooney et al., 2012). Peptides with PeptideRanker scores above 0.5 are generally considered to exhibit potential biological activities (Zenezini Chiozzi et al., 2016). Therefore, using this threshold as a selective criterion, peptide scoring above 0.5 was selected for further functional analysis. As shown in Fig. 2C, the number of peptides with scores >0.5 at the six-hydrolysis time were 241, 279, 317, 309, 300, and 343, respectively, indicating prolonged hydrolysis facilitated the release of potentially bioactive peptides. This trend might be attributed to the prolonged hydrolysis increased DH and enriched low-MW peptides in CPH, which have been reported to be associated with higher potential bioactivity (Marcet et al., 2023). To further predict the potential bioactivities of CPHs, screened cricket peptides with active probability were matched to the reported active sequences in database annotations (Fig. 2D). Cricket peptides sharing identical sequences or sequence fragments with reported bioactive peptides were annotated as potential candidates for the corresponding bioactivities. Peptide sequences containing in CPHs (30–300 min) were predicted to exert a range of regulatory functions, such as amelioration of cardiovascular diseases (diabetes, hypertension, and obesity), antioxidation, immune-stimulation, and anti-amnesia. Among these biological activities, antidiabetic (DPP-IV inhibitor), antihypertensive, and antioxidant activities were the most prominent, as indicated by the significantly higher number of associated peptide sequences compared to other function (Gabrilyants et al., 2025; Lee et al., 2021). DPP-IV and ACE are targets of antidiabetics and antihypertension, and antioxidant is regarded as preventive strategies defense various chronic diseases. Taken together, current results displayed that cricket was promising precursor of bioactive peptides with multifunction.

3.3. Peptidomics analysis of CPH as a source of bioactive peptides with multifunction

3.3.1. DPP-IV inhibitory activity of CPH

DPP-IV is widely considered as a key regulator of glucose metabolism due to its critical role in inactivation of incretin hormones including glucagon-like peptide-1 and glucose-dependent insulinotropic polypeptide. DPP-IV reduces insulin secretion and elevates blood glucose through cleaving these peptides, which contributes to type 2 diabetes mellitus (Wang et al., 2024). DPP-IV inhibition exhibited a distinct bimodal pattern throughout hydrolysis (Fig. 3A). Inhibitory activity increased from 21.6% at 30 min to 35.2% at 60 min, decreasing to 23.2% at 180 min, rebounding to 33.6% at 240 min, and then declining to 26.6% at 300 min. In the early stage, rapid enzymatic cleavage generated a large number of short peptides, leading to a sharp rise in DPP-IV inhibition. Continuous hydrolysis might degrade peptide fragments into amino acids, causing a temporary decline. Subsequently, the increasing activity of CPH at 240 min likely reflected the further release of original peptides aligning with increased DH. A similar pattern was reported in whey protein hydrolysates (Lacroix & Li-Chan, 2012). DPP-IV inhibitory activity of whey protein hydrolysates increased at the first 30 min, plateaued at 30–60 min, decreased at 60–180 min, and increased again in the final 30 min. It suggested that original inhibitors were released to compensate for the peptide loss by degradation.

Fig. 3.

Analysis of DPP-IV inhibition and peptide characteristics of CPHs. (A) DPP-IV inhibition, (B) Distribution of putative DPP-IV inhibitory peptide candidates, (C) Sequence logo analysis, (D) Upset diagram of putative DPP-IV inhibitory peptide candidates, (E) Exploratory activity-oriented PLS-DA biplot for prioritizing time-specific peptides. Visualization results of peptides SGPRLH (F) and FAGPS (G) in molecular docking. Different letters denote significant differences (p < 0.05).

DPP-IV inhibitory discrepancy necessitated interpretation from the perspective of peptide population. Therefore, putative DPP-IV inhibitory peptide candidates in CPHs with PeptideRanker >0.5 were analyzed using peptidomics and bioinformatics study. As shown in Fig. 3B, heatmap of DPP-IV inhibitory peptides in CPHs further confirmed the peptide profiles' differences among CPHs. Red box revealed the dynamic changes of cricket peptides over hydrolysis time aside from time-specific or shared peptides, and blue box represented the peptides emerged only at the late stage of hydrolysis. The intermittent presence of peptides at non-consecutive time points reflected a dynamic cycle of generation, cleavage, and re-release, explaining the fluctuation phenomenon of inhibitory activity observed between 30 and 300 min. Known structural information was subsequently applied to explain the DPP-IV inhibitory differences and explore potential peptides, particularly focusing on the highly active CPHs to understand their source of activity. Amino acids composition of the putative DPP-IV inhibitory peptide candidates evolved over time (Fig. 3C). Hydrophobic amino acids (Leu, Ile, Ala and Val), Gly and Pro in peptide sequence contributed to potent DPP-IV inhibition (Fang et al., 2026), and dynamic occurrence of these amino acid residues at both N- and C-terminus of peptides slightly supported the DPP-IV inhibition and related differences of CPHs. Additionally, Pro residues at C2 position flanked by hydrophobic residues were also beneficial for DPP-IV inhibition, which partially explained the potent activity of CPHs at 60–300 min (Fang et al., 2026). Notably, CPHs at 180 and 300 min possessed similar structural properties with that of 240 min but displaying obvious weaker activity, highlighting the possibility of other amino acids.

Differences in time-specific peptide profiles may contribute to the variation in DPP-IV inhibitory activity among CPHs. Upset method could elucidate the intersection relationships among sets, and offer an intuitive visualization of complex set overlaps compared to traditional Venn diagram (Chen & Boutros, 2011). In this study, upset diagram further revealed that these CPHs contained numerous unique peptides (Fig. 3D), which may be associated with differences in DPP-IV inhibitory activity among CPHs. As shown in Fig. 3E, exploratory activity-oriented PLS-DA was used to prioritize peptides associated with the relatively high DPP-IV inhibitory activities observed at 60, 120, and 240 min. The loading patterns suggested preferential associations of AGDDAPRAVFPS and AFN with CPH at 60 min, AAPAL and MY with CPH at 120 min, and SGPRLH and FAGPS with CPH at 240 min. To further evaluate peptide-receptor interactions, these representative peptides were docked onto the DPP-IV crystal structure (Table 1). Except AGDDAPRAVFPS, all selected peptides showed favorable docking capacity, suggesting their potential binding affinity toward DPP-IV. In addition, DPP-IV inhibitory peptides previously featured Pro residue at the second position of C-/N-terminals. The key role of Pro lied in occupying the S1 subsite of DPP-IV, thereby achieving competitive inhibition (Yan et al., 2026). N-terminal Gly-Pro-type peptides were potent inhibitors (Li, Yang, et al., 2025). Based on these structural characteristics, SGPRLH and FAGPS with the highest docking scores were selected for visualization. SGPRLH and FAGPS shared interactions with the auxiliary binding region of DPP-IV involving Glu 361, Ile 407, and Glu 408. SGPRLH formed hydrogen bonds with Glu 361 and Glu 408 at distances of 1.9–2.2 Å, and also established hydrophobic contact with Ile 407 (Fig. 3F). FAGPS interacted with Glu 361, Glu 408, Tyr 585 and Ile 407 region through hydrogen bonds of 2.0–3.2 Å, and further formed a salt bridge with Glu 408 (Fig. 3G). Consistent with our findings, Gao et al. (2020) reported that bovine α-lactalbumin-derived DPP-IV inhibitory peptides ELKDLKGY and ILDKVGINY also interacted with Glu 361 and/or Glu 408 in molecular docking. Overall, exploratory activity-oriented PLS-DA, sequence profiling, and molecular docking collectively prioritized peptide candidates associated with the relatively high DPP-IV inhibitory activity of CPHs at different hydrolysis times. Among them, SGPRLH and FAGPS were prioritized as promising candidate peptides potentially associated with the DPP-IV inhibitory activity of CPH.

Table 1.

Peptide Ranker score, toxicity, and docking results of promising peptide candidates.

	Sequence	PeptideRanker	Toxicity	T-Score	C-Score
DPP-IV inhibition	SGPRLH	0.6676	Non-toxin	9.7164	4
	MY	0.8421	Non-toxin	7.4443	4
	FAGPS	0.7116	Non-toxin	7.4389	4
	AAPAL	0.5869	Non-toxin	6.9506	4
	AFN	0.7733	Non-toxin	5.5362	4
	AGDDAPRAVFPS	0.5376	Non-toxin	–	–
ACE inhibition	SGLFDK	0.6209	Non-toxin	9.8447	4
	PAALGL	0.5782	Non-toxin	8.6943	4
	FAWQ	0.9129	Non-toxin	8.2330	5
	AEAFL	0.5023	Non-toxin	7.7145	4
	LSLM	0.5414	Non-toxin	7.2328	4
	HGL	0.5468	Non-toxin	6.0200	4
Antioxidant	VYGPL	0.6613	Non-toxin	5.7045	4
	LYPL	0.7522	Non-toxin	5.1000	4
	NGAGGF	0.8092	Non-toxin	4.3893	5
	NFAY	0.6841	Non-toxin	4.1661	4
	YLL	0.6000	Non-toxin	3.7808	4
	LYYL	0.5939	Non-toxin	3.4107	4

3.3.2. ACE inhibitory activity of CPH

Inhibiting ACE lowers blood pressure by reducing angiotensin II formation and preserving bradykinin-mediated vasodilation (Dong et al., 2024). As shown in Fig. 4A, ACE inhibitory potential of CPHs obtained at various hydrolysis time was assessed. The inhibitory rate of CPH increased rapidly at the early stage, reaching approximately 63.0% within 30 min, followed by a plateau period within 30–120 min. it continuously rose after 120 min, reaching its peak at 300 min with 78.0%. Overall trend of ACE inhibitory activity observed was highly consistent with the DH results in CPHs, and a previous study reported that protein hydrolysate with a higher DH was tend to be strong ACE inhibitor. For instance, Das et al. (2024) found that Channa punctata protein pancreatin hydrolysate with 26% DH showed greater ACE inhibitory activity than that of pepsin hydrolysate with 9% DH. It might partially attribute to the low-MW peptide generation causing by increased hydrolysis, which was regarded as a key factor for ACE inhibition. Our results also confirmed that high DH increased the low-MW fractions of CPHs, especially for <2 kDa.

Fig. 4.

Analysis of ACE inhibition and peptide characteristics of CPHs. (A) ACE inhibition, (B) Distribution of peptide lengths, (C) Peptide characteristics, and (D) Upset diagram of putative ACE inhibitory peptide candidates. (E) Exploratory activity-oriented PLS-DA biplot for prioritizing time-specific peptides. Visualization results of peptides SGLFDK (F) and PAALGL (G) in molecular docking. Different letters denote significant differences (p < 0.05).

Most reported ACE inhibitory peptides were short peptides consisting of 2–12 amino acids, and larger ones bind poorly to the active site of ACE with reducing efficacy (Darewicz et al., 2014). Therefore, the length distribution of putative ACE inhibitory peptide candidates in CPHs with PeptideRanker scores >0.5 was initially analyzed (Fig. 4B). Results indicated that CPHs were mainly composed of short peptides consisting of 2–6 amino acids, and their quantities increased along with prolonged hydrolysis time. The predominance of short peptides (2–6 amino acids) was consistent with structural characteristics previously associated with ACE inhibitory peptides. ACE inhibition is closely associated with specific structural features of peptides. C-terminal aromatic and/or N-terminal branched-chain amino acids contributed to the ACE inhibition of peptides (Qiu et al., 2024), and some scholars also believed that positively charged amino acids at the last three positions of C-terminus enhanced ACE inhibition (Zhang et al., 2022). Additionally, the strong ACE inhibition of Pro-rich peptide was attributed to its aromatic pyrrole ring, which enabled peptide to engage in π-π stacking with aromatic residues within the ACE active site (Zhang et al., 2019). We conducted targeted analysis of peptide profiles in CPHs based on these structural characteristics (Fig. 4C). Results exhibited that peptides in CPHs basically suitable for the properties of positively charged amino acids at the last three positions and Pro containing, which mirrored the changes of ACE inhibitory activity observed. It revealed that they might be the predominant contributors of CPHs to inhibit ACE.

Unique peptides held a significant role in the interpretation of bioactivities. Fig. 4D illustrates the dynamic evolution of ACE inhibitory peptide profiles in CPHs, which was dominated by time-specific sequences, particularly at 300 min (107 unique sequences). These time-specific peptides may contribute to, or be associated with, the differences in ACE inhibitory activity among CPHs. As shown in Fig. 4E, exploratory activity-oriented PLS-DA was used to prioritize peptides associated with the 300 min CPH, which exhibited the highest ACE inhibitory activity. The loading vectors of SGLFDK, PAALGL, HGL, LSLM, FAWQ, and AEAFL were preferentially oriented toward the 300 min profile, suggesting their association with this high-activity hydrolysate. Molecular docking of these peptides against ACE was then performed using SYBYL, and T-Score ≥ 5 and C-Score ≥ 4 were chosen as criteria (Table 1). All these peptide candidates exhibited favorable docking scores toward ACE. Among them, SGLFDK and PAALGL were further chosen for docking visualization due to their matchiness with the sequence features discussed above. For example, both of them are short peptides within the favorable size range for ACE inhibition. SGLFDK contains hydrophobic and aromatic residues together with a C-terminal Lys, whereas PAALGL is a Pro-containing peptide enriched in hydrophobic residues. Docking visualization further supported this interpretation (Fig. 4F and G). SGLFDK formed multiple interactions with Arg 124, Glu 123, Arg 522 and Arg 402 residues through van der Waals contacts, attractive charge interactions, carbon‑hydrogen bonds and hydrogen bonds, with hydrogen bond distances ranging from 2.0 to 2.8 Å. Similarly, PAALGL also formed stable interactions with Asn 66, Asp 121, Glu 123, and Glu 403 residues, with hydrogen bond distances of 1.7–2.3 Å. Fortunately, Previous studies identified Glu 123, Arg 124, Glu 403 and Arg 522 as important combination sites for active ACE-inhibitory peptides (Guo et al., 2023). Taken together, exploratory activity-oriented PLS-DA and molecular docking prioritized specific peptides associated with the high ACE inhibitory activity of the 300 min CPH, among which SGLFDK and PAALGL were prioritized as promising candidates.

3.3.3. Antioxidant activity of CPH

Sustained and dysregulated oxidative stress can disrupt cellular function, and further to promote vascular dysfunction, which contributes to the development of chronic diseases such as diabetes, hypertension, and atherosclerosis (Wang et al., 2023). Therefore, antioxidant activity of CPHs was studied as well. Enzymatic hydrolysis significantly enhanced the antioxidant capacity of CP, as evidenced by the sharp reduction of IC₅₀ values in ABTS and DPPH assays (Fig. 5A and B), consistent with previous observations that proteolytic processing can be accompanied by changes in the antioxidant activity of protein-rich foods (Iqbal et al., 2025). IC₅₀ values of CPH reached the lowest levels within the first 30 min hydrolysis (ABTS: 0.180 mg/mL; DPPH: 0.950 mg/mL). This pattern suggested that Alcalase rapidly released antioxidant peptides at the initial stage. Extended hydrolysis contributed less to activity enhancement and might even cleave released sequences, thereby reducing the overall radical scavenging capacity of CPHs. Interestingly, an opposite trend was observed between DH and antioxidant of CPHs in this study. Consistently, previous research also revealed that a high DH aligning with prolonged hydrolysis was unnecessary condition for achieving maximum biological activity (Di Filippo et al., 2025). Hydrophobic and aromatic amino acid residues are widely recognized as key contributors to antioxidant capacity of peptides (Kalita et al., 2024). Hydrophobic amino acids improve peptide solubility in lipid systems to promote interactions with lipids and delay oxidation, whereas aromatic amino acids such as Phe and Tyr donate protons to neutralize free radicals (Power et al., 2013). Therefore, amino acid features of putative antioxidant peptide candidates in CPHs with Peptide Ranker >0.5 were analyzed in this study. A high proportion of these peptide candidates consisted of hydrophobic (Ala, Leu, Pro, Phe) and aromatic (Phe, Tyr) amino acid residues, supporting the conclusion in previous research (Fig. 5C). Similarly, Cavaliere et al. (2021) demonstrated <2 kDa fraction of soy-corn protein hydrolysate with high contents of hydrophobic amino acids exhibited potent DPPH and ABTS radical scavenging activities of 81.54% and 98.02%, respectively. Beermann et al. (2009) reported that aromatic amino acid residues accounted for 38% in antioxidant peptides prepared from beta-conglycinin and glycinin. Notably, aromatic amino acid residues showed the highest proportion in antioxidant peptides from CPH at 30 min (24.0%), while that of other CPHs retained below 20.0% (Fig. 5D). In contrast, antioxidant of CPHs at 60 and 120 min might be attributed to their high proportion of hydrophobic amino acid residues.

Fig. 5.

Analysis of antioxidant and peptide characteristics of CPHs. IC₅₀ values in radical scavenging activities of (A) DPPH, and (B) ABTS. (C) Amino acid compositions, (D) Aromatic and hydrophobic amino acid compositions, and (E) Upset diagram of putative antioxidant peptide candidates. Different letters denote significant differences (p < 0.05). (F) Exploratory activity-oriented PLS-DA biplot for prioritizing time-specific peptides. Visualization results of peptides LYPL (G) and VYGPL (H) in molecular docking. Different letters denote significant differences (p < 0.05).

As shown in Fig. 5E, upset analysis revealed distinct peptide profile at each hydrolysis time, the quantities of unique antioxidant peptides from 30 to 300 min were 36, 77, 71, 66, 0 and 107, respectively. These time-specific peptides might contribute to the observed differences of antioxidant across CPHs. To further prioritize peptide candidates associated with the superior antioxidant activity observed at 30 min, exploratory activity-oriented PLS-DA was conducted (Fig. 5F). CPH prepared at 30 min hydrolysis showed a distinct score pattern, consistent with its lowest IC₅₀ values in both ABTS and DPPH assays. Moreover, loading vectors of peptides YLL, NGAGGF, NFAY, VYGPL, LYYL and LYPL were preferentially oriented toward the CPH at 30 min, indicating their preferential association with antioxidant. Table 1 presents the PeptideRanker score, toxicity predictions, and molecular docking results of these peptides. No toxicity was predicted. Top two peptides LYPL and VYGPL were selected for visualization based on their priority in docking scores (Fig. 5G and H). Both of them adopted favorable conformations within the binding pocket and formed multiple non-covalent interactions (van der Waals contacts, carbon‑hydrogen bonds and conventional hydrogen bonds) with Keap1 receptor. Docking results further supported the potential interactions of LYPL and VYGPL with Keap1, which may provide complementary evidence for their antioxidant potential. Specifically, LYPL interacted with Asn 387 and Ala 72 residues, and VYGPL interacted with Asn 387 and Leu 84, with hydrogen bond distances mainly ranging from 1.9 to 2.3 Å. Collectively, exploratory activity-oriented PLS-DA and molecular docking prioritized specific peptides associated with the high antioxidant activity of the 30 min CPH, among which LYPL and VYGPL were promising candidates.

3.4. Structural characteristics of CP after enzymatic hydrolysis

3.4.1. FTIR analysis

Enzymatic hydrolysis was reported to be capable of altering the molecular structure of proteins, which might directly determine the peptide release in protein hydrolysates (Habinshuti et al., 2023). Therefore, FTIR, F-SH/T-SH contents, surface hydrophobicity, and TEM were used to explore the structural changes of CP before and after hydrolysis in this study. As shown in Fig. 6A, all samples exhibited similar major absorption bands, and no obvious new absorption bands appeared after hydrolysis. The amide I band, arising primarily from C O stretching vibration, shifted from 1657 cm⁻¹ to 1655 cm⁻¹, indicating changes in the local chemical environment and conformation of the peptide backbone after hydrolysis (Kong & Yu, 2007). Normally, the ordered structure of protein is primarily stabilized by non-covalent interactions (hydrogen bonds and hydrophobic forces). The Amide II band (1580–1510 cm⁻¹), attributed to N—H bending and C—N stretching vibrations, also shifted from approximately 1536 cm⁻¹ to 1547 cm⁻¹, further suggesting changes in the peptide-backbone environment. These results were consistent with previous research showing that enzymatic hydrolysis not only cleaves peptide bonds but also can alter these interactions, thereby leading to unfolding and rearrangement of secondary structure (Mohamed et al., 2025). Furthermore, quantitative secondary-structure analysis based on the amide I band in the range of 1700–1600 cm⁻¹ further supported this interpretation. The amide I region is comprised of β-sheet (1640–1610 cm⁻¹), random coil (1650–1640 cm⁻¹), α-helix (1658–1650 cm⁻¹), and β-turn (1700–1660 cm⁻¹). The α-helix and β-sheet are generally regarded as more ordered structures, whereas the β-turn and random coil are associated with greater conformational flexibility (Xu et al., 2016). Enzymatic hydrolysis significantly decreased the combined content of α-helix and β-sheet and increased that of β-turn and random coil, reflecting a transition of CP from compact conformation to flexible structure (Fig. 6B). Specifically, compared with the unhydrolyzed CP, α-helix + β-sheet proportion in CPHs decreased from 59.3% to 43.6–49.0%, while β-turn + random coil increased from 40.7% to 51.1–56.5%. These changes suggested that hydrolysis altered the secondary structure of CP, resulting in a more flexible conformation. A similar increase in secondary-structure flexibility was also reported for sunflower seed protein upon Alcalase hydrolysis (Dabbour et al., 2020). Additionally, the β-turn + random coil content did not increase continuously with prolonged hydrolysis, suggesting that the major redistribution of secondary structures occurred during the early stage of hydrolysis, whereas further hydrolysis did not produce a continuous directional change in secondary-structure composition.

Fig. 6.

Effects of enzymatic hydrolysis on the structural characterization of CP and CPHs. (A) FTIR spectra, (B) Secondary structure content, (C) T-SH and F-SH contents, (D) Surface hydrophobicity. Different letters denote significant differences (p < 0.05).

3.4.2. F-SH and T-SH analysis

F-SH and T-SH are crucial functional groups within proteins, and changes in sulfhydryl contents can serve as an indicator of protein denaturation (Yang et al., 2023). The contents of F-SH and T-SH in CPHs initially increased and then stabilized over time, with a rapid rising observed at the early stage of hydrolysis (0–120 min) (Fig. 6C). FTIR results revealed that the secondary structure of CP rapidly transitioned from ordered to unfolded conformations at the early stage, providing favorable conditions for sulfhydryl group exposure. Sadeghian-Motahar et al. (2025) reported that enzymatic hydrolysis of gluten led to the unfolding of protein structure, as evidenced by decreases in α-helix and β-sheet in FTIR, thereby resulting in an increase in F-SH content. The increase of F-SH content in CPHs might be attributed to two mechanisms: firstly, continuous enzymatic hydrolysis disrupted CP structure, exposing cysteine residues originally buried within protein core (He et al., 2014); Secondly, hydrolysis cleaved some disulfide bonds (S–S) within CP, leading to the formation and release of new F-SH groups (Yang et al., 2023). Interestingly, the apparent increase of T-SH content in CPHs couldn't represent an actual gain in SH groups but instead reflect an enhanced detectability. Enzymatic hydrolysis induced structural unfolding exposed inaccessible cysteine residues and increased the accessibility of previously buried sulfhydryl groups to Ellman's reagent, thereby raising the measured T-SH content (Udenigwe et al., 2016). Additionally, prolonged hydrolysis failed to elevate T-SH contents continuously, it might be due to the insufficient unfolding effect, and prolonged hydrolysis might also accelerate the oxidation of F-SH groups in presence of oxygen, thereby limiting the continuous increase of T-SH (Di Filippo et al., 2024).

3.4.3. Surface hydrophobicity (H₀) analysis

Surface hydrophobicity serves as a critical physicochemical parameter reflecting the extent of exposed hydrophobic region accessible to the solvent. A higher H₀ presents greater exposure of hydrophobic groups. As shown in Fig. 6D, enzymatic hydrolysis decreased the H₀ of CPHs compared to unhydrolyzed CP group (199.3 μmol g-1), and a general downward trend in H₀ of CPHs were observed with prolonged hydrolysis time except for 120 min. The relatively compact conformations of hydrolysate at 120 min (high proportion of α-helix + β-sheet in FTIR) might cause insufficient residue exposure, thereby showing low H₀. Similarly, hydrophobicity of mung bean protein also decreased after hydrolysis (Liu et al., 2022). In this study, decrease in H₀ values of CPHs with decreasing MW was consistent with the pattern previously reported for rice protein hydrolysates (Yang, Li, et al., 2022), demonstrating a positive correlation between H₀ and MW. This phenomenon indicated that large number of non-polar side group exposure in high-MW peptide chains enhanced the binding possibility with hydrophobic probes, showing a high H₀ values, while this is not the case for low-MW ones (Avramenko et al., 2013). Another possible explanation is that enzymatic cleavage of peptide bonds leads to the numerous formations of ionizable amino groups (–NH₃⁺) and carboxyl groups (–COO⁻) (Islam et al., 2025). This chemical modification increased the overall polarity and hydrophilicity of CPHs, thereby counteracting the contribution of exposed hydrophobic residues via compromising the non-polar binding sites essential for ANS probe interaction. Overall, the general decrease of H₀ with extensive hydrolysis time might be attributed to the reduction of hydrophobic residue exposure and enhancement of molecular polarity.

3.4.4. TEM analysis

Fig. 7 illustrates the morphological transformation of CPHs throughout Alcalase hydrolysis. Distinct time-dependent differences in TEM were evident, suggesting enzymatic hydrolysis significantly altered the nanoscale aggregation behavior of CP. Native CP appeared as compactly, large and irregularly shaped blocks or clumps (0 min), and these dense structures represented insoluble protein aggregates with partially retained native conformations. As hydrolysis progressed, massive blocks disintegrated into fine and uniform particles until 120 min. It revealed that accumulated intermediate peptides accompanying with prolonged hydrolysis underwent thermodynamic rearrangement, leading to the self-assembly of amphiphilic peptides into micelle-like nanostructures with hydrophilic exteriors and buried hydrophobic cores (Wang et al., 2022). Such configuration effectively reduced the surface exposure of hydrophobic groups by sequestering them within the core, which was consistent with the surface hydrophobicity analysis. At 300 min, CP formed a relatively distinct interconnected structure along with stable aggregation network, which partially explained the plateau of β-turn + random coil proportion, F-SH/T-SH content and surface hydrophobicity with prolonged hydrolysis. One interpretation of this phenomenon was that a higher DH promoted the release of peptide fragments in CPH, which further assembled into macromolecular peptides or amorphous aggregates via non-covalent interactions (including hydrophobic interactions and hydrogen bonds) (Zhang et al., 2023). Overall, with increasing hydrolysis time and DH, morphology gradually evolved from compact and coarse aggregates to more homogeneous and interconnected structures, indicating enzymatic hydrolysis not only altered the spatial structural characteristics of CP but also affected its molecular aggregation mode.

Fig. 7.

TEM images of CP and CPHs with scale bars. A represents CP, and B-G represent CPHs at 30, 60, 120, 180, 240, and 300 min, respectively.

3.5. Correlations between functional properties and structural characteristics of CPH

Enzymatic hydrolysis alters the ordered structural characteristics of proteins and may consequently influence enzyme accessibility and peptide-release patterns (de Carvalho Oliveira et al., 2024). Therefore, time-specific correlations among hydrolysis property, bioactivities (anti-diabetes, antihypertension and antioxidant), and structural characteristics were further conduct in this study (Fig. 8). DH positively correlated with antioxidant (ABTS and DPPH radical-scavenging activities) and ACE inhibition. A higher DH is generally accompanied by increased protein cleavage and a greater proportion of low-MW peptide fragments. Growing evidence supported the positive correlations between low-MW fractions causing by high DH and bioactivity. Small molecular size and flexible spatial structures of low-MW oligopeptides made it easy to precisely combine with targets, thereby facilitating the efficient exertion (Li, Du, et al., 2025). For instance, low-MW fraction (< 1 kDa) of mussel protein hydrolysate exhibited superior ACE inhibitory activity (Heo et al., 2023). Secondary structure changes further elucidated the structure-activity relationship. Contents of α-helix and β-sheet were negatively correlated with antioxidant capacity and ACE inhibition, whereas β-turn content was positively related. These correlations indicated that the transition from relatively ordered to more flexible structures was associated with antioxidant capacity and ACE inhibitory activity. Consistently, Wei et al. (2024) found that ACE inhibitory peptides FDRPFL and KWEKPF were enriched in β-turn structure. Simultaneously, T-SH content showed stronger positive correlations with antioxidant capacity and ACE inhibition than F-SH, suggesting a closer association of T-SH with these activity patterns. It aligned with a previous study that a strong correlation between increased T-SH and antioxidant activity (Di Filippo et al., 2024). Hydrophobicity negatively correlated with multiple activities, seemingly contradicting the known positive contribution of hydrophobic amino acid residues to bioactivities. This discrepancy might be attributed to the reduction of hydrophobic residue exposure and enhancement of molecular polarity in CPHs rather than a diminished contribution of hydrophobic residues. Interestingly, DPP-IV inhibitory activity showed no strong correlations with these global hydrolysate parameters, suggesting that its variation may be less closely associated with overall structural or hydrolysis characteristics. Instead, DPP-IV inhibitory activity may be more strongly influenced by sequence-specific factors, together with the abundance and accessibility of individual peptides. For instance, it was reported that peptides rich in basic amino acid residues might exhibit strong DPP-IV inhibitory activity by forming hydrogen bonds, salt bridges, and hydrophobic interactions with the enzyme (Kong et al., 2021). In addition, EP-, IPH-, -NHM and PF- motifs were crucial for DPP-IV inhibitory peptides (Yang, Dai, et al., 2022).

Fig. 8.

Correlations among hydrolysis property, structural characteristics, and biological activities of CPHs.

4. Conclusion

Alcalase hydrolysis time-critically affected the hydrolysis property, peptide profiles, structural characteristics, and multiple bioactivities of CPHs with various periods favoring specific bioactivities. Antioxidant activity peaked at the early stage, while ACE inhibition reached maximum at the later stage. In contrast, DPP-IV inhibition followed a bimodal pattern， it reflected the time-specific differences in hydrolysis property and peptide release. Structural transition of CP from a relatively ordered to a more flexible conformation, together with the enrichment of low-MW peptides, was positively correlated with antioxidant and ACE inhibition, whereas DPP-IV inhibition appeared to be more closely related to the release of specific peptide motifs at different hydrolysis time. Activity-guided peptidomics and multivariate analyses prioritized LYPL and VYGPL, SGLFDK and PAALGL, and SGPRLH and FAGPS as candidate peptides potentially associated with antioxidant, ACE inhibitory, and DPP-IV inhibitory activities, respectively. Molecular docking further suggested favorable interactions between these peptides and corresponding target receptors. This study provided a time-resolved framework for the rational design of CPHs with multifunctionality, and also supported the sustainable application of edible insect proteins as promising precursors for developing multifunctional peptides in functional foods and nutraceuticals. Future work could experimentally verify the activities of these candidate peptides and further evaluate their gastrointestinal stability, in vivo efficacy, and stability and functionality in food matrices.

CRediT authorship contribution statement

Guangbin Wu: Writing – original draft, Investigation, Data curation, Conceptualization. Hanzhu Tan: Writing – original draft, Software, Investigation. Xiaonan Sui: Validation, Supervision, Conceptualization. Dongrui Zhao: Supervision, Methodology, Data curation. Jihong Wu: Visualization, Validation, Conceptualization. Shuguang Wang: Writing – review & editing, Validation, Project administration, Methodology, Funding acquisition, Conceptualization. Bifen Chen: Writing – review & editing, Validation, Software, Methodology, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary data

Supplementary material

Data availability

Data will be made available on request.