Small molecule peptide with sour taste activity and use thereof
By using virtual screening and machine learning models, small molecule peptides DSEPV and EPVLL were screened from a dairy peptide library. Their acidity activity was verified by an electronic tongue, which solved the problems of single flavor and low screening efficiency of traditional acidulants, and achieved efficient and diversified food flavor control.
Patent Information
- Application Number
- CN202511408238.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-29
- Publication Date
- 2026-02-03
- Estimated Expiration
- 2045-09-29
AI Technical Summary
Traditional acidulants in the food industry have limited flavor, strong irritation, or unpleasant aftertaste. Furthermore, existing peptide screening methods are time-consuming and inefficient, making it difficult to meet the demand for rapid development of novel flavor peptides.
We used virtual screening technology combined with machine learning models (such as XGBoost, random forest and multilayer perceptron) to screen small molecule peptides DSEPV and EPVLL from dairy peptide libraries, verified their acidity activity using electronic tongue technology, and ensured their purity and stability using high performance liquid chromatography.
The rapid screening of small molecule peptides DSEPV and EPVLL with acidity activity significantly improves the efficiency of discovering acidity-active lead molecules, providing new choices for healthy and diverse food flavors and meeting consumer needs.
Smart Images

Figure CN120887952B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of food flavor science and technology, specifically to a small molecule peptide with acidity activity and its applications. Background Technology
[0002] Traditional acidulants, such as citric acid and malic acid, are widely used in the food industry to impart a sour flavor to food. However, these traditional acidulants often suffer from problems such as limited flavor profiles, strong irritation, or unpleasant aftertastes, restricting their application in complex flavor systems. With increasing consumer demand for healthy, safe, and diverse food flavors, the development of novel acidulants has become a research hotspot in food science. Peptides, due to their biological origin, high safety, and potential for diverse flavor characteristics, are considered ideal alternatives to traditional acidulants. However, traditional peptide screening methods mainly rely on in vitro experiments or empirical design, which are time-consuming and inefficient, making it difficult to meet the need for rapid development of novel flavor peptides.
[0003] In recent years, the application of machine learning technology in the field of biomolecular screening has significantly improved screening efficiency. By integrating multi-dimensional features (such as amino acid composition, physicochemical properties, and molecular fingerprints), machine learning models can rapidly identify candidate molecules with specific functions from a vast peptide library. Furthermore, electronic tongue technology, as an objective flavor assessment tool, can efficiently verify the flavor characteristics of candidate peptides, providing reliable technical support for the development of functional peptides. However, systematic screening and verification studies of acid-active peptides are still relatively limited. Therefore, developing small molecule peptides with acid-like activity and well-defined sequences is of great significance for improving the diversity and precision of food flavor regulation. Summary of the Invention
[0004] The purpose of this invention is to provide a small molecule peptide with acidic activity and its application, in order to solve the problems mentioned in the background art.
[0005] To achieve the above objectives, the present invention provides the following technical solution:
[0006] A small molecule peptide with acidic activity, wherein the amino acid sequence of the small molecule peptide is shown in SEQ ID NO:1 or SEQ ID NO:2.
[0007] The application of the above-mentioned small molecule peptides in the preparation of acidic flavoring agents.
[0008] Compared with the prior art, the beneficial effects of the present invention are:
[0009] 1. This invention employs virtual screening technology combined with machine learning models (such as XGBoost, random forest, and multilayer perceptron) to rapidly screen small molecule peptides DSEPV and EPVLL with sour taste activity from dairy peptide libraries by integrating multi-dimensional features such as amino acid composition, physicochemical properties, and molecular fingerprints. Compared with traditional in vitro experiments or empirical screening methods, this method can achieve efficient screening without a large amount of actual synthesis and testing, significantly reducing the number of candidate peptides and improving the efficiency of discovering sour taste active lead molecules, providing a simple and feasible technical solution for food flavor regulation.
[0010] 2. This invention uses electronic tongue technology (SA402B electronic tongue system) to verify the flavor characteristics of the screened DSEPV and EPVLL small molecule peptides, and combines high performance liquid chromatography (HPLC) to ensure the purity and stability of the peptide samples. The experimental results show that DSEPV and EPVLL have significant response values in the acidity dimension (8.4 and 5.2, respectively), confirming that they have excellent acidity activity, providing a reliable basis for the development of biological acidulants.
[0011] 3. The DSEPV and EPVLL small molecule peptides obtained by screening in this invention are derived from dairy products and have biological origin characteristics. They can be used as ideal substitutes for traditional acidulants (such as citric acid and malic acid), meet consumers' demand for healthy and high-quality food flavors, provide new options for the design of complex flavor systems, and have important significance for flavor control in the food industry. Attached Figure Description
[0012] Figure 1 AUC curves for all features of the MLP of this invention;
[0013] Figure 2 The AUC curves for all features RF of this invention are shown.
[0014] Figure 3 The AUC curves for all features of XGBoost in this invention are shown.
[0015] Figure 4 This is the AUC curve of the MLP descriptor of this invention;
[0016] Figure 5 This is the AUC curve of the descriptor RF of this invention;
[0017] Figure 6 This is the AUC curve of the XGBoost descriptor of this invention;
[0018] Figure 7 This is the AUC curve of the fingerprint MLP of the present invention;
[0019] Figure 8 This is the AUC curve of the fingerprint RF of the present invention;
[0020] Figure 9 This is the AUC curve of the fingerprint XGBoost of the present invention;
[0021] Figure 10 The AUC curve of the protein characteristic MLP of this invention;
[0022] Figure 11 The AUC curve of the protein characteristic RF of this invention;
[0023] Figure 12 The AUC curve of the XGBoost protein characteristic of this invention is shown.
[0024] Figure 13 This is an AUC curve of the first 200 features of the MLP of this invention;
[0025] Figure 14 This is an AUC curve of the first 200 features of the present invention.
[0026] Figure 15 The AUC curves for the first 200 features of XGBoost in this invention are shown.
[0027] Figure 16 This is a schematic diagram showing the docking results of the small molecule peptide DSEPV and the acid taste receptor OTOP1 in this invention.
[0028] Figure 17 This is a schematic diagram showing the docking results of the small molecule peptide EPVLL with the acid taste receptor OTOP1 in this invention.
[0029] Figure 18 This is the high-performance liquid chromatography total chromatogram of the small molecule peptides DSEPV and EPVLL of the present invention;
[0030] Figure 19 This is a high-performance liquid chromatogram of the small molecule peptide DSEPV of the present invention;
[0031] Figure 20 This is a high-performance liquid chromatogram of the small molecule peptide EPVLL of the present invention;
[0032] Figure 21 This is an electronic tongue radar image of the small molecule peptide DSEPV of this invention;
[0033] Figure 22 This is an electronic tongue radar image of the small molecule peptide EPVLL of the present invention. Detailed Implementation
[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0035] Please see Figures 1 to 22 The present invention provides:
[0036] Example 1: Screening of small molecule peptides and prediction of sour taste activity
[0037] The small molecule peptides involved in this study utilize computer virtual screening technology to screen two small molecule peptides with sour taste activity, DSEPV (SEQ ID NO:1) and EPVLL (SEQ ID NO:2), from a dairy peptide library.
[0038] The specific method involves extracting multi-dimensional features from a dataset containing peptide sequences, SMILES strings, and binary labels representing sour taste activity. This includes using Biopython's ProtParam to calculate physicochemical descriptors (such as molecular weight, isoelectric point, and hydrophobicity), generating a 1024-bit Morgan fingerprint and a 167-bit MACCS bond using RDKit, and calculating topological, geometric, and electronic descriptors from the SMILES strings. Features were standardized and dimensionality reduced using the SelectKBest method, retaining the top 200 features with the highest ANOVAF scores. Three machine learning models—XGBoost, Random Forest, and Multilayer Perceptron (MLP)—were used for binary classification. Model parameters were optimized using 5-fold hierarchical cross-validation and GridSearchCV, with the area under the ROC curve (AUC-ROC) as the evaluation metric. Finally, the peptide sequences DSEPV and EPVLL were selected as candidate peptides with sour taste activity.
[0039] The full name of DSEPV is Asp-Ser-Glu-Pro-Val; the full name of EPVLL is Glu-Pro-Val-Leu-Leu.
[0040] like Figure 1-15 As shown, in the dataset, all machine learning models achieved an AUC value exceeding 0.85, indicating excellent discriminative ability. Furthermore, the small molecule peptides DSEPV and EPVLL were identified as having sour taste activity by multiple machine learning models.
[0041] Next, AutoDock Vina 1.2.0 was used to perform molecular docking analysis on the screened small peptides DSEPV and EPVLL to predict their binding sites with the sour taste perception-related receptor OTOP1. Figure 16 and Figure 17 As shown, DSEPV mainly forms stable hydrogen bonds and hydrophobic contact networks with residues such as ARG-232, GLU-228, and TYR-269. EPVLL also forms a similar stable interaction with the binding site of OTOP1. Molecular dynamics simulations (Amber 22, 100 ns) further verified the stability of the DSEPV-OTOP1 and EPVLL-OTOP1 complexes, with total binding free energies of -14.12 kcal / mol and -28.58 kcal / mol, respectively, indicating strong binding affinity.
[0042] Example 2: Synthesis and purification of small molecule peptides
[0043] The synthesis and purification methods of the small molecule peptides DSEPV and EPVLL in this invention are as follows:
[0044] The sour peptides involved in this invention were synthesized and provided by Liaoning Newgene Biochemical Technology Co., Ltd. The peptide samples included DSEPV and EPVLL, both prepared using the Fmoc solid-phase peptide synthesis method. During the synthesis process, Wang resin was used as the solid-phase support. Each Fmoc amino acid monomer was sequentially coupled under the action of HBTU or HATU and DIEA, and Fmoc deprotection was performed after each reaction step. After peptide chain assembly, the target peptide was cleaved from the resin using a trifluoroacetic acid mixed lysis buffer, and the side chain protecting groups were removed. The crude peptide was collected after precipitation with cold anhydrous diethyl ether, further purified by reversed-phase high-performance liquid chromatography, and the molecular weight was confirmed by mass spectrometry, finally obtaining the desired sour peptide sample.
[0045] Accurately weigh 0.8 mg of each peptide sample and dissolve it separately in 1 mL of methanol-water solution containing 0.1% phosphoric acid. Sonicate for 3 minutes to ensure complete dissolution. Filter the solution through a 0.22 μm membrane and transfer to sample vials. High-performance liquid chromatography (HPLC) analysis was performed using an HPLC system (4.6 mm × 250 mm, 5 μm particle-packed column) to analyze the purity and stability of DSEPV and EPVLL. The mobile phases were methanol and acetonitrile aqueous solution containing 0.1% phosphoric acid (phase A) and acetonitrile (phase B), the column temperature was 40°C, and the detection wavelength was 220 nm. The results showed that the retention times of DSEPV and EPVLL were 8.600 min and 12.119 min, respectively. Figure 19 and Figure 20 The purity of all samples reached over 98%, indicating that the samples have good stability.
[0046] Chromatogram of total mixture ( Figure 18 The results showed multiple clear chromatographic peaks within the 8–13 minute range. By comparing the retention times of the single peptide with those of the mixture, the identity of the corresponding peaks in the mixture could be confirmed. Therefore, these chromatograms collectively demonstrate that the synthesized peptide has the correct structure, reliable purity, and can be effectively separated and identified.
[0047] Example 3: Sensory evaluation of small molecule peptides
[0048] Sensory evaluation of the electronic tongue was conducted using the SA402B electronic tongue system (Insent, Japan) to assess the taste characteristics of DSEPV and EPVLL. Sensors included CO0, AE1, CA0, CTO, and AAE. The sour taste threshold was set to -13 mV, and the measurement time was 30 seconds, with three parallel measurements. Each peptide solution (normalized concentration) was equilibrated to room temperature before testing. The corrected sour taste response values were 8.4 for DSEPV and 5.2 for EPVLL, indicating significant sour taste activity. (Radar chart) Figure 21 and Figure 22 The results showed that DSEPV and EPVLL performed exceptionally well in the sourness dimension, validating their potential as active peptides for sourness.
[0049] This invention utilizes virtual screening technology combined with a machine learning model to efficiently screen small molecule peptides DSEPV and EPVLL with sour taste activity from a dairy peptide library. Molecular docking and molecular dynamics simulations verified the stable binding of DSEPV and EPVLL to OTOP1, and electronic tongue experiments further confirmed their significant sour taste activity (response values of 8.4 and 5.2, respectively). As bio-derived sour taste active peptides, DSEPV and EPVLL can be used in the preparation of sour flavoring agents, providing a new option for food flavor regulation and possessing significant application value.
[0050] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.
Claims
1. A small molecule peptide with acidic activity, characterized in that, The amino acid sequence of the small molecule peptide is shown in SEQ ID NO:1 or SEQ ID NO:
2.
2. The application of the small molecule peptide with acidic activity as described in claim 1 in the preparation of acidic flavoring agents.
Citation Information
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