Sequential Ultrasound Hydrolysis and Microwave Treatment of Gluten–Starch Complexes: Functionality, Sensory Profiles, In Vitro Allergenicity and Interactions

1. Introduction

Wheat flour is a staple ingredient in wheat flour-based formulated foods such as bread, cakes, crackers, biscuits, puffed foods, fried dough products [1,2]. It consists of 70–85% starch (including damaged starch) and 10–15% protein, of which 73–82% is gluten [3,4]. The structure and function of wheat flour-based products are significantly improved through multi-step processing (e.g., mechanical mixing like malaxation, optional fermentation, molding, and baking) [5,6,7]. These popular products are attributed to properties, interactions, and Maillard reaction (MR) degree of gluten and starch [8], which dictates structural characteristics and the development of desirable odor, color, and flavor [3,4,9,10,11,12]. However, gluten composition in wheat flour-based products could induce several health risks like allergy [12,13]. The pathogenic factors of gluten would limit the use of wheat flour-based products. Nevertheless, developing high-quality gluten-containing foods requires not only optimizing both formulations and processing parameters but also maintaining a balance between sensory, quality, nutrition, and safety of foods by understanding ingredient interactions during processing.

Food processing can be classified as thermal processing and non-thermal processing. Previous research has confirmed that thermal processing method including time- and energy-efficient microwave heating, can trigger the MR to simultaneously enhance the sensory attributes, nutritional value, and functional properties of food systems [9,14,15,16,17]. Non-thermal technologies including enzymatic hydrolysis (EH) for covalent bond cleavage [18], ultrasonic treatment for structural remodeling [19], are increasingly processing methods to optimize the food physicochemical processing properties especially reducing linear allergic epitopes of food matrices. However, non-thermal pretreatment cannot drive starch gelatinization or MR, which compromises texture and results in undercooked food matrices. While thermal processing only weakly modulates gluten covalent cross-linking, it cannot achieve sufficient hypoallergenicity without impairing sensory and structural characteristics. For example, baking can increase the allergenicity or glycemic index (GI) of wheat flour [17,20,21], while microwave heating alone only moderately alters IgE reactivity and allergen-induced symptoms [21].

In contrast, multi-combined food processing techniques (integrating thermal and/or non-thermal processing methods) have attracted increasing attention due to their pronounced synergistic effects on the modification and optimization of food matrices. Previous studies have shown that food processing (e.g., hydrolysis or combined treatments) can alter gluten structure, enhancing antioxidant activity and digestibility while reducing allergenicity [22,23,24,25,26]. Similarly, incorporation of exogenous components (e.g., dietary fiber, proteins/protein hydrolysates) before starch processing (e.g., hydrothermal treatment) modulates starch intermolecular interactions and its crystalline structure, thereby enhancing the functional properties of starch (e.g., mitigate starch digestibility) [27,28,29]. Studies have also shown that combinations of heat with irradiation [30], enzymolysis with microwave/heat [31], or ultrasound with autoclaving/enzymolysis [32] can modify the immunoreactivity, digestibility, and other functional properties of food matrices. Collectively, these studies demonstrate that modification of wheat gluten, rational formulation of modified gluten-starch composites, and integration of multi-combined thermal and non-thermal processing technologies can achieve a synergistic improvement of the sensory, quality, nutritional and safety properties of cereal-based food matrices.

This study aims to integrate synergistic effects of non-thermal and thermal processing for optimizing the overall performance of gluten-containing composites. Specifically, wheat gluten was modified via ultrasonic pretreatment coupled with EH, then blended with wheat starch (WS) or rice starch (RS) at a fixed ratio, respectively. Microwave heating was applied to the prepared low-moisture composites to induce MR. By comparing different combined processing strategies, the synergistic effects were evaluated whether combined processing can simultaneously enhance the food safety (reduced gluten allergenicity) while maintaining the sensory quality, and nutritional value of the products. The intermolecular interactions between modified gluten with starch have been studied from the perspective of multi-scale effects of multi-combined processing. This work provides an innovative strategy for producing both a friendly gluten-containing food matrix with low anti-nutritional factors and a better comprehensive food complex with higher senses and nutrition.

2. Materials and Methods

2.1. Materials

Wheat gluten was purchased from Heowns Biochemical Technology Co., Ltd. (Tianjin, China). WS was purchased from Shanghai Yuanye Biotechnology Co., Ltd. (Shanghai, China). RS was purchased from Sigma Chemical Co. (St. Louis, USA). The total antioxidant capacity (T-AOC) assay kit (ABTS·⁺ method) was obtained from Beyotime Biotechnology Co., Ltd. (Shanghai, China). The free amino acid content assay kit, artificial gastric juice (SGF), and artificial intestinal juice (SIF) were all obtained from Beijing Solarbio Technology Co., Ltd. (Beijing, China). Protamex compound protease was purchased from Novozymes Inc. (Copenhagen, Denmark). RIDASCREEN® Gliadin competitive ELISA kit was purchased from R-Biopharm AG (Darmstadt, Germany), equipped with R5 monoclonal antibody targeting immunogenic proline/glutamine-rich gluten epitopes (e.g. QQPFP, QQQFP, LQPFP and QLPFP presented in α/β-, ω- and γ-gliadins) [33]. All other reagents were of analytical grade or higher.

2.2. Preparation of Gluten Hydrolysates

Wheat gluten was dissolved in 0.2 M phosphate-buffered saline (PBS, pH 6.0) to a final concentration of 5% (m/V) and split into three groups. (1) Gluten solution was stirred at 25 °C, 1200rpm, pH 6.0 for 6 h prior to protease addition with a compound protease-to-original gluten ratio of 0.81:100 (m:m). (2) Gluten solution was hydrolyzed in a water bath at 40 °C, 1200rpm, pH 6.0 for 6 h with same compound protease-to-original gluten ratio of GO. (3) Gluten solution was first subjected to ultrasonic treatment for 30 min under 360 W, 40 kHz followed by EH using the same strategy as (2) preparation. After aforementioned treatment, the enzyme in all groups was immediately inactivated by heating at 95 °C for 1 h with constant stirring. The mixtures were then centrifuged at 9500 rpm for 20 min at 25 °C, and the supernatants of (1) & (2) & (3) were denoted as original gluten (GO), enzymatically hydrolyzed gluten(GE), and coupled-treated gluten (GC) group, respectively. All groups were stored at 4 °C or lyophilized for later analysis.

2.3. Gluten Hydrolysates Analysis

2.3.1. Molecular Distribution

Amino acid profile of 1 mg/mL GO, GE, and GC in 200 mM PB (pH 6.8) was analyzed by size-exclusion high-performance liquid chromatography (SE-HPLC; Waters 600, Milford, MA, USA). The instrument was equipped with a TSK-Gel G2000SWXL or G4000SWXL column (7.8 mm i.d. × 300 mm, Tokyo, Japan), and detection was performed at 214 nm with a 20 μL injection. Elution was conducted at 1 mL/min using 200 mM PB (pH 6.8) as the mobile phase. Transferrin (80,000 Da), cytochrome C (12,384 Da), the synthetic peptide PVLGPVRGPH (1,361 Da), glutathione (307 Da), and glutamate (147 Da) were used as standards for peak time-Mw (x-y) plotting. Each sample was fractionated into different Mw ranges (> 10 kDa, 5–10 kDa, 3–5 kDa, 1–3 kDa, and < 1 kDa) based on the time ranges from the standard curve. The percentage content of each Mw fragment was calculated as follows:

C_i (%) = (A_i/∑A_total) × 100

(1)

where C_i represents relative content of the target compound (%), A_i represents integrated peak area of the target peak range, and ∑A_total represents sum of all integrated peak areas of the sample. The average molecular weight is further determined by the following equations:

M_n = (Σ_iH_i)/(Σ_i(H_i/M_i))

(2)

M_w = (Σ_i(H_i/M_i))/(Σ_iH_i)

(3)

where M_n represents average molecular weight, M_w represents weight-average molecular weight, H_i is peak height of different fractions in protein/hydrolysate sample, and M_i is molecular weight of different fractions in protein/hydrolysate sample.

2.3.2. Quantitative Analysis of Amino Acids (AAs)

GO/GE/GC were pretreated via acid hydrolysis at 110 °C for 21 h. After digestion, the digestive mixture was further processed and carried out for derivatization. During derivatization, isotope-labeled internal standards were mixed for absolute quantification. Processed samples were analyzed via an HPLC-MS/MS system (Ultimate 3000-API 3200 Q TRAP, Thermo Fisher Scientific-AB SCIEX, USA) fitted with an MSLab HP-C18 column (150 × 4.6 mm, 5 μm). Mobile phase A is water containing 0.1% formic acid and phase B was acetonitrile containing 0.1% formic acid. A 3 μL sample was injected and run under 0.8 mL/min flow rate at 50 °C column temperature. Gradient separation conditions are as following: 2% B at 0 min, 28% B at 10 min, 100% B at 10.1 min (maintained to 16 min), and 2% B at 16.1 min (maintained to 25 min). Eluents were scanned in MRM mode via an ESI source (positive ion mode) for AAs detection and quantification.

2.3.3. Zeta Potential

Zeta potential of the samples was determined using a Nanoparticle Zetasizer (Nano-ZS90, Malvern Instruments, UK).

2.4. Preparation of MR Composite Products (MRCPs)

Following optimization of reaction conditions (humidity, microwave time, microwave power, and protein-starch ratio), GO/GE/GC were thoroughly mixed with WS or RS at a 1:1 ratio. Atomized distilled water was then sprayed uniformly onto the mixed samples and mixed thoroughly to adjust the batter moisture content to ~15% (detected by laboratory moisture analyzer). The wet batter was maintained at 79% relative humidity (RH, monitored by hygrometer). The moist blended composites were preheated in a microwave oven at 600 W for 5 min. After preheating, they were further heated by microwave for 5 min at 30 s intervals for 3 repeated run in total to produce MRCPs (denoted as HGOWS, HGEWS, HGCWS, HGORS, HGERS, HGCRS). Microwave-prepared MRCPs or their water-soluble extracts (obtained with deionized water) were lyophilized for subsequent analyses.

2.5. Browning Degree & Antioxidant Ability of Scavenging ABTS·⁺

MR intermediate products (MRIPs) and MR end products (MREPs) reflect the different stages extent of the MR. The protein/hydrolysate-starch mixtures were dissolved in 10 mM PBS (pH 7.0) to a concentration of 3 mg/mL. Absorbance was measured at 294 nm (for MRIPs) and 420 nm (for MREPs), respectively. ABTS·⁺ scavenging activity was determined for all samples (GO, GE, GC, HGOWS, HGEWS, HGCWS, HGORS, HGERS, HGCRS) following the T-AOC Assay Kit instructions using a microplate reader (Infinite 200 PRO, Tecan, Switzerland). The prepared ABTS·⁺ working solution was diluted 49-fold to an absorbance of 0.7 ± 0.05 at 734 nm and allowed to stand for 12–16 h. Samples were dissolved in deionized water to 5 mg/mL. A 10 μL aliquot of each sample solution was mixed with 200 μL of the ABTS·⁺ working solution, and absorbance was measured at 734 nm. Scavenging activity was calculated using a standard curve generated with Trolox at concentrations of 0.15, 0.3, 0.6, 0.9, 1.2, and 1.5 mM. All measurements were performed in triplicate. TEAC was calculated as follows:

TEAC (mM TE/(mg/mL protein)) = [(∆A_sample − b)/a × DF]/C_prot

(4)

where ∆A_sample represents the blank-corrected absorbance of samples, a and b are the slope and intercept of the Trolox calibration curve, respectively. DF is the sample dilution factor, and C_prot indicates the protein concentration of samples (mg/mL).

2.6. In Vitro Sequential Digestion

Original composites and MRCPs (30 mg each) were digested in 15 mL SGF (37 °C, 150 rpm, 2 h). Digestive samples (1 mL) were sampled at the end of simulated gastric digestion. 15 mL SIF was added to the previous solution, and the pH was adjusted to 6.8 for simulated intestinal digestion (37 °C, 150 rpm, 4 h). Digestive samples (1 mL) were sampled at 6 h. Enzymes were inactivated (80 °C, 20 min) and the samples were centrifuged (12,000 rpm, 5 min) for free amino acid (FAA) analysis. Centrifuged samples were mixed as kit instructions and incubated in a boiling water bath for 15 min. Solutions were inverted repeatedly after cooling. After centrifugation (8,000 rpm, 5 min), absorbance of blue-purple compound formed in collected supernatant was measured at 570 nm using a microplate reader (Infinite 200 PRO, Tecan, Switzerland). All measurements were completed within 30 min of color development. The detection mechanism and calculation (5) were shown as follows:

$$\mathrm{A}\mathrm{A}\mathrm{s}+\mathrm{N}\mathrm{i}\mathrm{n}\mathrm{h}\mathrm{y}\mathrm{d}\mathrm{r}\mathrm{i}\mathrm{n}\stackrel{{\mathrm{H}}^{+}}{\to }\mathrm{R}\mathrm{u}\mathrm{h}\mathrm{e}\mathrm{m}\mathrm{a}\mathrm{n}\mathrm{n}’\mathrm{s} \mathrm{P}\mathrm{u}\mathrm{r}\mathrm{p}\mathrm{l}\mathrm{e},\mathsf{\lambda }=570 \mathrm{n}\mathrm{m}$$

C_FAA = (10 × (A_sam − A_blk))/((A_std − A_blk) × C_prot)

(5)

where C_std represents standard FAA concentration (10 μmol/mL), FAA content (μmol/mg protein) is the digestive releasing FAA measured from the supernatant, V_std or V_sam are volume of standard solution or volume of sample supernatant added to reaction system which equal to 0.05 mL, C_prot represents supernatant protein concentration (mg/mL), and A_sam, A_std, A_blk denote absorbance of sample, standard, and blank tubes, respectively. The constant value 10 is derived from C_std × V_std.

2.7. Electronic Eye Colorimetry

MRCPs were dissolved in distilled water to a concentration of 5 mg/mL and accurately pipetted into colorimetric cuvettes to ensure a consistent height. Prior to color photography, the electronic eye instrument (Digieye, VeriVide, UK) was calibrated with white tiles and swatches. A fixed diameter was set to measure color parameters, including lightness (L: 0 = black, 100 = white), red-green value (a: +a = red, -a = green), yellow-blue value (b: +b = yellow, -b = blue), whiteness (W*), chroma (C*), and color difference (∆E*). W*, C*, and ∆E* were calculated as follow [34]:

W* = 100 - [(100 - L)² + a² + b²]^1/2

(6)

C* = (a² + b²)^1/2

(7)

∆E* = [(L - L₀)²+(a - a₀)² + (b - b₀)²]^1/2

(8)

where L₀, a₀, and b₀ represent the color parameters of control samples (without microwave heating) at t = 0.

2.8. Ultra-Fast GAS Chromatography (GC-FID)-Electronic Nose Determination

An ultra-fast GC electronic nose system (Heracles II, Alpha M.O.S., France) was used to detect and analyze the fingerprint profiles of flavor volatile components and differences among various composites. The system was equipped with an autosampler (Odor Scanner HS 100, Alpha M.O.S., France) with two parallel metal columns (non-polar MXT-5-FID1 column (10 m × 180 μm × 0.4 μm) and medium polarity MXT-1701-FID2 column (10 m × 180 μm × 0.4 μm)), a cooled Tenax trap, and two ultra-sensitive FID detectors. A 1 g aliquot of the 5 mg/mL MRCP solution was weighed into a crimp-top GC vial for detection. The vials were shaken at 50 °C for 30 min at 500 r/min to generate headspace sample gas. A volume of 3,000 μL was injected with a speed of 125 μL/s and 29 s duration under 200 °C inlet temperature. Initial temperature and desorption temperature of trap was 50 °C and 240 °C with 34 s trapping duration, while the FID temperature was 260 °C. All flavor compounds of all composites with relevance index (RI) > 30 were used for qualitative screening and listed as compound name (CAS number) based on retention index and retention time from two columns (Double-column retention index qualitative method). Compound descriptors were assigned based on published literature (as Supplementary Table S1), and corresponding odor descriptions for each protein-starch composite were determined accordingly. The screened compounds data were subjected to subsequent principal component analysis (PCA) and discriminant function analysis (DFA) statistical analysis using peak area/relative content with pre-installed software (Alpha Soft V12.4 workstation with built-in AroChemBase volatile flavor substance database). All measurements were performed in quintuplicate.

2.9. Determination of Gluten Content in Composites (ELISA Assay)

MRCPs (1 g) were added to 10 mL of 60% ethanol, vortexed for ~10 min, and centrifuged at 10,000 rpm for 10 min. Supernatants were diluted 50-fold with dilution buffer. A 50 μL aliquot of diluted supernatant was dispensed into separate wells of a 96-well plate, mixed with 50 μL antibody-enzyme conjugates (stock diluted 1:11), and incubated for 30 min. The plate was inverted and blotted dry on filter paper. Each well was then washed ≥ 2 times with 250 μL of washing diluent (1:10 dilution of stock solution), with blotting dry on filter paper after each wash. A 100 μL aliquot of substrate/chromogen was added to each well and incubated for 10 min in the dark. The reaction was terminated by adding 100 μL of stop solution, and absorbance was measured at 450 nm within 10 min using a microplate reader (Infinite 200 PRO, Tecan, Switzerland). Standards at 10, 30, 90, 180, 270 ng/mL were assayed under the same conditions. Limit of detection (LOD) and limit of quantification (LOQ) of ELISA kit are 2.3 mg gliadin/kg food and 5 mg gliadin/kg food. Gluten content was calculated using RIDA®SOFT Win.NET (Z999, R-Biopharm AG, Darmstadt, Germany) based on gliadin content with the standard curve.

2.10. Molecular Docking

During food processing, starch could partially hydrolyze to produce starch dextrins/oligosaccharides or oligomeric starch with reducing end groups [35,36]. These starch fragments may interact with allergenic loci of gluten to generate masking or modifying effects [37]. Representative allergenic wheat gluten proteins, α/β-gliadin A-IV (P02863) and HMW-Dx5 subunit (P10388), were selected for docking based on their well-documented dominant immunogenicity [38,39,40,41,42]. Maltodextrin structure (CID 62698) was retrieved from PubChem. The docking was performed via AutoDock 4.2.6 with a 126 × 126 × 126 grid box. Short oligomeric starch fragments of rice and wheat (linear amylose and single-branched amylopectin) were constructed with CHARMM-GUI Glycan Reader & Modeler [43]. These computationally tractable simplified models were designed to reflect typical starch chain-length profiles: rice amylose DP24, rice amylopectin (DP18 main chain + DP6 side chain, branch point at residue 9); wheat amylose DP28, wheat amylopectin (DP20 main chain + DP8 side chain, branch point at residue 10) [44,45]. Subsequently, protein-starch pairwise docking was performed between DX5, Alpha/beta-gliadin A-IV, and the four starch fragments. HADDOCK3 performed fully blind rigid-body docking to produce 10,000 conformations, Uniform Manifold Approximation and Projection (UMAP) embedding of 10,000 rigid-body conformations was based on protein-starch contact fingerprints and colored according to clusters via Ward’s linkage hierarchical clustering [46]. After scoring-based screening of the top 500 poses and clustering, the lowest-HADDOCK-score conformation was adopted for binding characteristic analysis. The whole computational pipeline was jointly coded and realized via Python scripts and R language. Structural visualization and analysis were implemented in open-source PyMOL 3.10.

2.11. Statistic Analysis

All data were expressed as means ± standard deviations. One-way analysis of variance (ANOVA) was used to analyze differences in mean values among treatments. Significant differences (P < 0.05) were identified using Tukey’s honestly significant difference (HSD) test. All statistical analyses and calculations were performed using SPSS 19.0 (SPSS Inc., Chicago, IL, USA) and OriginPro 2017C SR2b9.4.2.380 (OriginLab Corporation, Northampton, MA, USA).

3. Results and Discussion

3.1. Physicochemical and Functional Properties of Gluten and Gluten Hydrolysates

3.1.1. Molecular Distribution

Molecular weight (Mw) distribution of intact and hydrolyzed gluten reveals hydrolysis extent and indirectly links structural alterations to functionality, particularly variations in allergenic epitopes. Figure 1(A) illustrates the relative abundance of gluten (hydrolysate) Mw fractions across different treatments. Notably, fractions of 5–10 kDa, 3–5 kDa, and 1–3 kDa that < 30% of the total fractions exhibited in an order of GO > GE > GC. Gluten subunits, which consist of five fractions (high Mw: 65–90 kDa; low Mw: 30–60 kDa), crosslink via disulfide bonds (S–S) to form protein networks ranging in Mw from 10⁵ kDa to several million Da [8]. Previous studies reported that acidic enzymolysis of gluten yielded ~70% of fragments < 15 kDa, while ultrasonic pretreatment resulted in > 90% and > 65% of fragments < 3 kDa and < 2 kDa, respectively [24,25]. These demonstrated appropriately cleavage of gluten subunits into hydrolysates through non-thermal processing rather than completely cleaving the covalent structure. However, EH remained incomplete, potentially retaining residual allergenic epitopes in fraction that > 10 kDa. The inherent resistance from gluten structure (like gliadin) stabilizing by S–S and other covalent linkages with more inaccessible sites [26] may also limited the formation of more hydrolysates. The trend of increasing small molecular peptides (SMPs) correlates positively with the higher degree of hydrolysis (DH) and reduction in S-S (increasing detection of free -SH) [47]. Compared with the GE group, the GC group contained more peptides > 10 kDa and fewer fragments < 1 kDa indicating a lower DH of GC than that of GE. It may tentatively attribute to structural rearrangement of GC triggered by S-S formation, which consistent with prior ultrasonic findings [19,25,48]. However, an appropriate DH is beneficial for maintaining the mechanical properties of gluten proteins hydrolysates to provide better ability for food applications.

3.1.2. Amino Acid Composition

The AAs composition of GO/GE/GC and the corresponding taste of each AA are detailed in Table 1. The profiles showed a high abundance of Glx (Glu+Gln) and Pro, and a lower proportion of sulfur-containing AAs (Cys and Met) as reported previously [49]. This pattern likely results from a high relative content of gliadins (especially the main allergic ω-type in gluten) [8], reflecting different patterns and degrees of protein breakdown among GO/GE/GC. Generally, during continuous hydrolysis, the levels of Glu/Pro increased initially before decreasing, whereas Cys/Met showed a opposite trend [26] However, the orders of Glx and Pro percentages were GO > GE > GC, GE > GC > GO for Cys, and GE > GO > GC for Met in this study. This indicates that the introduction of ultrasound may alter the enzymatic hydrolysis mode and further change the splicing pattern of allergenic epitopes. Less Glu and Pro of GC may suggest less allergenic possibility caused by allergic locus [25]. Essential amino acid (without Trp) ranked GC > GE > GO, revealing superior nutritional retention for GC hydrolysates. The AA categories of sample attributed to distinct taste (umami, sweet, bitter, sour, sulfurous etc.) are summarized in Table 2. Sweet, umami and sour FAAs followed GO > GC > GE, while bitter sulfur-containing FAAs ranked GE > GC > GO, mixed taste-active FAAs also displayed GO > GE > GC. These profiles indicate severe enzymatic hydrolysis (GE) accumulates bitter off-flavor FAAs, while GC yielded intermediate-MW peptides with pleasant sweet/umami FAA levels similar to GO. As reported previously [50], high-MW GO peptides fold into stable structures masking bitter hydrophobic residues, whereas low-MW GE peptides expose bitter hydrophobic terminals that activate bitter-sensing G protein-coupled receptors and weaken sweet taste. Furthermore, sweet low-calorie peptides from GO and GC support low-sugar food development. In summary, treatment-modulated peptide Mw and conformation affect gluten sensory characteristics, and GC delivers the best comprehensive performance by moderately disassembling gluten while retaining favorable taste and nutritional functions.

3.1.3. Scavenging Effect of ABTS·⁺ and Zeta Potential

As presented in Figure 1(B), GO exhibited the lowest antioxidant capacity, while GE showed marginally higher antioxidant capacity than that of GC. Ma et al. [55] demonstrated that EH and high acoustic energy disassembled β-lactoglobulin aggregates, yielding antioxidant peptides with more free radical-scavenging sites and smaller particle size. Hydrolysates with lower Mw fragments have stronger radical-scavenging capacity [24], whereas medium-Mw or hydrophobic gluten hydrolysates contribute to ABTS·⁺ scavenging via hydrophobic AAs residues [22]. These results align with higher hydrophobic AAs and lower-Mw fragments of GE/GC than counterparts of GO, which produce more functional abilities. Notably, GO had the least negative zeta potential, while GE showed more negative charge than GC. Gluten peptides exhibited negative potential at neutral pH due to carboxylic group ionization of Glu/Asp [23], and deamidation (converting Gln to Glu) enhanced this negative charge [49]. In this study, charge exposure may be caused by exposure of cleaved Glu/Asp-derived negative via EH. Nevertheless, the smaller negative charge, antioxidant activity, and low-Mw fraction in GC (vs. GE) suggest ultrasonication may induce new S–S formation or oligomerization, shielding AA side chains for EH [56]. This indicates ultrasonication mitigates excessive degradation of gluten’s higher-order structure caused by EH.

3.2. Browning Degree and Antioxidant Ability of Scavenging ABTS·⁺ for Mixtures

Figure 2(A) shows the Maillard reaction extent (MRE) and ABTS·⁺ scavenging activity of MRCPs. Notably, MRCPs followed the same ranking order yet displayed weaker ABTS·⁺ scavenging capacity relative to their protein/hydrolysate counterparts, which might attribute to more reactive FAA residues of smaller peptides before MR as molecular distribution result shown [14]. More FAA residues of GE/GC for MR during microwave heating also increased browning absorbance and reaction degree of HE(C)W(R)S [16]. It also made MRIPs absorbance were elevated in HGEW(R)S/HGCW(R)S compared to that of HGOW(R)S. Additionally, higher MRIPs absorbance than MREPs absorbance could ascribe to stable ketoamine linkages of MRIPs during Amadori rearrangement [57] and higher A420/A294 yield of microwave heating than conventional thermal treatment [58]. This also indicated moderate MR occurred in most samples. HxWS possessed greater antioxidant activity but substantially lower MRE relative to HxRS (x refers to various gluten processed products). Relative to WS, RS exhibited higher amylopectin content, alongside lower resistant starch fraction, particle size, ΔH and solubility, which impaired the thermal stability and gelatinization resistance of RS granules [59,60]. (Post-)Steaming accelerated MR progression by depleting reducing sugars and free α-amino nitrogen within gelatinized surface layer and formed melanoidins diffusing into gelatinized starch to form conjugated complexes [61,62]. Disparities between HxWS and HxRS may partially arise from stronger interactions between reducing sugars from degraded RS and low-MW gluten hydrolysate peptides, alongside greater retention of radical-scavenging moieties in WS under microwave heating. Furthermore, smaller-sized gelatinized RS rich in amylopectin may offer greater reactive surface and binding sites, boosting molecular collisions for accelerated MR. The weaker antioxidant capacity of HGCX (X = WS/RS) relative to HGEX is likely due to enhanced masking effects from high-MW peptide fractions in the GC group, implying that MRE can be modulated by tuning starch types to meet sensory requirements.

3.3. Assessment of the Digestibility of Gluten-Starch Complexes

As shown in Figure 2(B), except for HGERS (which showed markedly decreased FAAs at 6 h), FAA release increased over time for all other complexes. All samples exhibited comparable FAA release within the first 2 h while the liberation of digestible FAAs followed the ascending order HGCX > HGEX > HGOX at 6 h, which RS conjugates yielded greater FAA release. EH combined microwave heating promoted MR and gluten aggregation/cross-linking, which increased starch-protein interactions for masking modifications and reduced digestive sites thus lowered total FAAs during digestion [16,63]. Nevertheless, milk protein aggregates with elevated viscosity exhibited enhanced FAA liberation, which may be governed by protein aggregation status and enzymatic susceptibility during digestion [64]. For HGOXS, lower total FAA release compared to treated complexes may ascribe to intact gluten but not limited MRCPs formation, which mitigated digestive cleavage. Compared to HGCX, reduced AA release in HGEX may stem from increasing MRCPs formation via higher SMP content during processing, which generates more covalent complexes and impairs proteolytic cleavage by digestive enzymes. HxRS displayed greater FAA release relative to HxWS, may be owing to finer gelatinized RS rich in amylopectin, ultrasound-mediated gluten assembly and lower SMP levels. The resultant loose aggregates and limited MR allowed easier protease access and hydrolytic breakdown of the complexes. Lowest FAA release of HGERS may be caused by elevated compact, digestion-resistant aggregates formation because of more gluten SMPs coupled with higher heating-induced starch gelatinization/MRCPs formation. Additionally, encapsulation of SMPs or AAs by gelatinized starch may further hinder the detection of FAAs in supernatants. However, these findings still require further validation.

3.4. Electronic Eye Colorimetry

As shown in Supplementary Figure S1, HGEX appeared a relatively darker yellowish color than other samples. The color of HGCX was the most uniform, and HxRS composites exhibited a darker color than the corresponding HxWS composites. Color attributes of all composites were accurately quantified as shown in Figure 3 and Table 3. L* decreased in the order HGOX > HGEX > HGCX, with HxWS conjugates exhibiting higher L* values than HxRS counterparts. As reported previously [14], Maillard-derived dark compounds reduce L*, while large-size aggregates enhance L* via light reflection [65]. This suggests fewer dark compounds exist in HGOX (lower MRE), whereas moderately higher MRE in HGEX may generate high-molecular MRIPs/MREPs aggregates and elevate L* in HGEX through reflecting light. HGEX showed the highest positive a* value, while negative a* of other samples displayed as HGCWS < HGOWS < HGEWS and HGORS < HGCRS < HGERS. Most studies [5,62,66] noted no correlation between melanoidins and a*, however, the positive a* in HGEX may stem from elevated MRIPs as shown in Figure 3. All negative b* values present order as HGOWS < HGCWS < HGEWS and HGCRS < HGERS < HGORS. Increasing proportion of enzyme-resistant flour would decrease b* (yellowness) and darkened the biscuit colors [5], while MR could enhance blueness [34]. This explains the higher MRE in HGE(C)RS vs. HGE(C)WS. Additionally, elevated blueness in HGE(C)RS may relate to increased retrograded starch and MR than HGORS while HGE(C)RS may have lower retrograded starch than HGE(C)WS (P < 0.05). C* followed the same trend as b*. HGEWS had the highest C* in HxWS, while HGORS peaked in HxRS. C* of heating glucose-ammonium system has increased firstly then decreased at 100 °C and continuously reduced at 110 °C or 120 °C [34]. Study also showed C* increased in ultrasound-treated ultrafiltrated smooth hound viscera protein-sucrose conjugates [67]. For HxWS, C* variation was consistent with browning degree of MRIPs, confirming Maillard pigment formation contributed by the color of MRIPs. For HxRS, the value order of C* was contrary to the browning degree and HGORS showed highest C*. This may be ascribed to the higher gelatinization of RS vs. WS and the diffusion of melanoidins into the gelatinized RS matrix. This may drive distinct color migration: high Mw GO retains chromophores on starch granule surfaces, while lower Mw GE/GC enable more Maillard-derived chromophoric products to diffuse into granule interiors. The superimposed enhancement of light reflectance contributes more to the color increase than MREs alone. HxWS and HxRS conjugates exhibited identical trends for W* (HGEX < HGCX < HGOX) and ΔE* (HGCX < HGOX < HGEX). Reduced W* with prolonged thermal processing indicates increased MRE [67], revealing higher MRE in HGEX. Lower W* in HxRS vs. HxWS further confirms mildly higher MRE in RS conjugates, consistent with browning assays (P > 0.05). ΔE*, which correlates with heating time [67], was highest in HGEX indicating greater MRE (P > 0.05). The elevated ΔE* in HGOX may arise from Rayleigh scattering by large protein aggregates [65]. The lowest ΔE values of HGCX also demonstrate more homogeneous color distribution throughout the matrix, which suggests HGCX is suitable for subsequent food product development.

3.5. Volatile Flavor Components Determination

The profiles of volatile flavor components with RI for different composites and the corresponding descriptions are shown in Table 4. Higher RI which reflects better chromatography matching degree of detected peaks with the standard library. All composites contained a typical wheat gluten volatile (methanethiol: burnt, thiolic notes) from methionine Strecker degradation during microwave-induced MR [68]. For HxRS, higher EH correlated with enhanced MR. HGERS showed prominent creamy roasted notes while HGCRS had the most native wheat-like fresh grassy and nutty malt aroma. HGORS, with less MRE, retained minimal roasted wheat notes. For HxWS, HGOWS with less MRE was dominated by strong smoky popcorn notes, which may be caused by pyrolysis of phenolic acid retained in the wheat matrix [69]. HGEWS had the richest balanced flavor profile while HGCWS showed the strongest raw material character with pure fresh wheat and spicy notes. The difference between HxRS and HxWS may attribute to WS’s abundant endogenous flavor precursors (phenolic acids, reducing sugars) enabling synergistic pyrolysis with proteins, while RS lacks such precursors [69,70].

PCA is an unsupervised dimensionality reduction algorithm requiring no prior knowledge, whereas DFA represents a supervised approach built on training datasets; both were applied to the odorants quantified in Supplementary Table S1. Linear fitting results of PCA and DFA are presented in Figure 4, and centroid distance of identical samples are shown in Table 5. The total explained variance rates (TEV, %) of HxWS and HxRS were 95.719% and 97.742% for PCA from two PCs while those TEV for DFA from two DFs were 100%, manifesting comprehensive coverage of dataset information by these factors. Notably, PCA clusters were closely spaced or overlapped, showing more distinct clustering of HxRS than HxWS counterparts (data largely overlapped). HGOX samples have wider spacing than those of HGEX/HGCX. Sample variability, small dataset size, non-linear correlations, and instrumental/methodological deviations can induce suboptimal separation and clustering [71,72], which explains the poor clustering performance of HxWS and HGOX. Wider spacing of HGOX also indicates the significant flavor differences among parallel HGOX samples, which may be related to the unevenness of samples and the uneven heating process. Overlapping effect among HxWS reflects the higher similarity of HxWS than HxRS, potentially attributed to lower MRE and less detectable volatile aroma compounds in HxWS. HGCRS was fully isolated on the negative PC1 axis, driven by high abundance of mild Strecker degradation products (key markers: 3-methylbutanal, hexanal, methyl eugenol) that retained the native grain aroma of wheat protein. HGERS localized to the positive PC2 axis, characterized by Maillard-derived sulfur-containing heterocyclic compounds (key markers: bis(2-methyl-3-furanyl) disulfide, 2-methylthiophene), while HGORS and HGCRS fell on the negative PC2 axis with no advanced Maillard products. HGCWS isolated on the negative PC1 axis, with the same native cereal aldehyde markers as the HGCRS. HGEWS localized to the positive PC2 axis with Maillard-derived markers, while HGOWS fell on the negative axis with smoky phenolic acid pyrolysis products (key markers: guaiacol, 2-acetylthiazoline, dimethyl trisulfide).

In contrast, DFA successfully discriminated all clusters with wider spacing particularly for HxRS. It is attributed to DFA’s ability to maximize inter-cluster differences and perform cross-validation using prior sample information [71,72]. Relative aroma index (RAI, %) in Table 5 revealed more precise inter-cluster differences, with a order as: HGEX vs HGCX > HGOX vs HGCX > HGOX vs HGEX. HxWS inter-group comparison exhibited significantly higher RAI than those of HxRS. AAs generating sulfurous/sweet/mixed flavor have large content gap between GC and GE hydrolysates may contribute to the savory/umami taste of protein hydrolysates [6], potentially explaining the discrepancy and palatable flavor between HGEX and HGCX. For HxRS, DF1 explained 84.16% of inter-group variance, representing the core discriminant dimension between HGCRS and HGORS/HGERS, with the same key markers driving separation as PC1. DF2 accounted for 15.54% of variance, serving as the discriminant dimension to distinguish HGORS, with hexyl heptanoate and trans-4,5-epoxy-(E)-2-decenal as core negative markers. For HxWS, DF1 (67.14% variance) as the core dimension could distinguish HGEWS/HGCWS, and DF2 (32.86% variance) as the dimension could separate HGCWS. The lower DF1 and PC1 variance in WS may be attributed to endogenous phenolic and lipid flavor precursors in WS, which introduced additional flavor variation and reduced separation between hydrolysis degrees. Consistent clustering patterns across both matrices confirmed that HGCX retained native cereal aroma via mild Strecker degradation, while HGOX/HGEX formed distinct profiles via intense thermal reactions. Starch matrix was the key modulator of chemometric discrimination power, composites with RS enable clearer separation of samples. The flavor profiles indicate combined treatment, especially HGCRS, have balanced MR-derived roasted wheat aroma while maximally retaining the fresh, pure original flavor of wheat gluten and starch.

3.6. ELISA Assays for Gluten Allergens

Gluten allergen detection results (Table 6) showed that HGCX matrices exhibited gluten levels < 10.00 ppm, far below the 10–20 ppm threshold for gluten-free (GF) foods specified by the International Codex Alimentarius Commission (CAC), the USA, EU, Australia, New Zealand, Argentina, and other regions [73,74,75,76]. HGEX had gluten contents around 15 ppm, while untreated groups exceeded 20 ppm. The R5 antibody strongly bound to the QQPFP, QQQFP, LQPFP and QLPFP sequences in α/β-, ω- and γ-gliadins, however, enzymolysis and deamidation (Gln to Glu) during fermentation and hydrolysis processes could destroyed toxic epitopes of gluten [33]. Relative to GO, GE/GC containing higher SMPs exhibited a reduced Glx + Pro ratio (56.16% to 55.31%/54.35%), potentially disturbing epitope conformation. MRCPs may generate through reactions between epitope-related AAs and reducing termini of starch/pyrolyzed dextrins while ultrasound and enzymatic treatments attenuated protein allergenicity, thereby reducing gluten detectability [19,32]. HGOX/HGEX retain allergenicity whereas combined treatment delivers strong synergies to lower gluten allergenicity. This suggests the promising potential of HGCX for gluten-free functional foods.

3.7. Interaction Between Wheat Gluten Subunit and Starch Fragments

Figure 5 illustrates the interaction of glutenin/gliadin with maltodextrin. Binding energies (BEs) were -0.96 and -0.92 kcal/mol, with inhibition constants (Ki) of 196.29 and 211.84 mM for glutenin and gliadin, respectively. Total interaction energy was -4.39 and -4.34 kcal/mol for glutenin and gliadin. Maltodextrin fragments spontaneously bind to both glutenin and gliadin mainly through hydrogen bonds with Gln/Glu residues and hydrophobic forces. This indicates gluten allergenicity may be mitigated by achieving epitope shielding effect.

Average contact frequencies for each residue between protein subunits and starch fragments were compared to identify different binding patterns and the best binding modes as shown in Figure 6 (individual dots stand for unique docking poses) and Table 7. Rigid-body docking revealed richer binding modes for RS fragments interacting with gluten subunits, while wheat amylopectin exhibited only two binding patterns toward glutenin. The abundant interaction sites of RS fragments increase reactive group contact probability, potentially enhancing the MRE of modified gluten-RS systems. Studies reported Gln would deamidate to Glu by transglutaminase 2 (TG2) in vivo, which further activates epitopes and stimulates T cells [38,39,40,77]. Major glutenin allergenic epitopes are QQPGQ, QQPGQGQQ, QQSGQGQ, and QGYYPTSPQQS from HMW glutenins, which could trigger a cascade of allergic and immunoreactive symptoms [40,41,78,79]. While α/β-, ω5-, and γ-gliadins possess highly homologous IgE-binding epitopes, with the consensus sequence being QQX₁PX₂QQ (where X₁ represents L, F, S or I; X₂ represents Q, E or G) and other epitopes (e.g. ¹VRVPVPQLQP¹⁰, ²⁵VQQQQFPG³², ⁵³QPYLQQFPQQPFPPQLP⁷², and ⁷⁷QSFPPQQPYPQQ⁸⁸, ¹²⁹QQQPSSQVSFQQ²³⁰), which would increase risks of urticaria, allergic reactions and WDEIA and AEDS [38,39,79,80,81]. Optimal binding conformations showed that RS fragments preferentially targets the 60–115 residue region of gliadin, precisely covering the immunodominant linear epitopes ⁶¹QQPYP⁶⁴/⁹⁷QQPYP¹⁰¹ and the R5-targeted epitope ⁷⁸LQPFP⁸², whereas WS fragments conservatively binds the non-epitopic 826–848 region of glutenin. Thermodynamically, rice amylopectin forms more stable complexes with both gliadin and glutenin than wheat amylopectin, while amylose exhibits the opposite trend, demonstrating that branched structural characteristics primarily determine starch–gluten binding stability.

Figure 7 illustrates the structural landscapes, quality assessments and molecular conformations, following flexible refinement and energy minimization of screened rigid-body. Binding energies and intermolecular forces for the various protein-starch fragment complexes were detailed in Table 7 and Table S2. Further flexref, emref and mdref refinements and conformational energy landscape analysis confirmed that starch fragments exhibit broad-spectrum, multi-pocket and multi-stable binding toward gliadin. Starch-gliadin complexes occupied more low-energy conformationas with higher thermodynamic probability, enabling comprehensive surface shielding of gliadin rather than single-point epitope blocking. This structurally explains the significantly reduced allergenicity of modified gluten through multi-modal processing. Rice amylopectin complexes yielded lower HADDOCK scores and more hydrogen bonds than wheat amylopectin counterparts. Starch–gliadin interactions were mainly governed by van der Waals hydrophobic stacking and Gln/Glu/Pro-mediated hydrogen-bond networks (correspond to core allergenic motifs of gluten immunodominant epitopes), consistent with AutoDock results. In contrast, starch–glutenin binding relied more on electrostatic forces with limited dominant stable conformations, indicating prevalent transient and low-probability binding. Combined with ELISA results, RS reduces gluten allergenicity via dual mechanisms of specific linear epitope masking and universal steric shielding, while WS mainly interferes with conformational epitopes. Both starches primarily exert shielding effects on gliadin. These molecular-level findings clarify the improved comprehensive quality of modified gluten–RS complexes and validate the synergistic modification performance of combined non-thermal enzymatic-ultrasonic treatment and microwave heating in starch-gluten food systems.

4. Conclusions

Wheat-derived baked products carry potential health hazards for gluten-sensitive populations, as gluten triggers immunoreactive and allergic responses. This study prepared modified gluten hydrolysates via ultrasonic-enzymatic combined processing. The processing gluten was then mixed with WS or RS and subjected to microwave heating to generate MRCPs as a simplified gluten-based baked model. The resulting model exhibited desirable sensory properties with natural wheat-based & mild MR flavor and acceptable color. Ultrasound–enzymatically treated HGCX samples exhibited comprehensively improved functional performance, including elevated ABTS·⁺ radical scavenging activity, superior digestibility with abundant nutritional AAs liberation, and markedly reduced allergenic hazards, with gluten levels falling below 10 ppm. In terms of the experimental and molecular mechanism, the improvements were attributed to the enrichment of beneficial AAs with suitable AA profile, moderate MRCPs formation, and altered starch-gluten interaction pattern (masking effect driven by higher binding affinity with stronger hydrophobic interactions and hydrogen bonds between Glu/Gln and glucose). These effects may collectively disrupt allergenic epitope spatial/linear structures, mask epitopes of gluten (e.g. ⁶¹QQPYP⁶⁴, ⁹⁷QQPYP¹⁰¹, and ⁷⁸LQPFP⁸²) via coupling food processing and starch-gluten binding. This work demonstrates that multi-technique combined processing effectively optimizes the comprehensive quality of gluten-starch systems. It offers critical technical guidance for developing high-quality gluten-based foods with satisfactory color, flavor, functionality, and safety (low allergens). Moreover, the established cereal-based food model provides a valuable reference for industrial production of healthy baked foods for gluten-susceptible population.