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. 2025 Jul 4;29:102734. doi: 10.1016/j.fochx.2025.102734

Characterization of key aroma components of jasmine tea with diverse aroma types: Focus on jasmine tea scented with multipetal jasmine

Yuan Chen a,b, Huimin An a,b,1, Yiwen Huang a,b, Youcang Jiang a,b, Jiaqi Ying a,b, Sirui Wang a,b, Chunniu Li f, Zhaoyang Bu f, Xianmin Li f, Yuelan Pang g, Zhusheng Liu g, Shi Li a,b,c,d,e,⁎, Zhonghua Liu a,b,c,d,e,⁎, Jianan Huang a,b,c,d,e,⁎
PMCID: PMC12275125  PMID: 40686887

Abstract

In this study, the aroma characteristics of jasmine tea (JT) scented by three kinds of multipetal jasmine, Xiangfei 2, 4 and 11 were investigated with common double-petal jasmine as control. Compared with the strong floral aroma of double-petal jasmine tea (TS), the JT scented with Xiangfei 2 (TC) showed fresher aroma, the JT scented with Xiangfei 11 (TB) exhibited sweeter aroma, while the overall aroma of JT scented by Xiangfei 4 (TA) was overall lower. Among them, Benzoic acid, 2-hydroxyl-, ethyl ester contributed to TB's sweet note, 3-Hexen-1-ol, benzoate, (Z) - and Methyl salicylate were related to the fresh aroma of TC, Linalool, Methyl anthranilate, 4-Hexen-1-ol, acetate and Benzyl alcohol were linked to TS's floral aroma. Molecular docking identified hydrogen bonding and hydrophobic interactions as key drivers for aroma compounds binding to olfactory receptors, and molecular dynamics simulations (MDs) validated the stability of these interactions. This study provides a theoretical basis for the application of multipetal jasmine in JT processing.

Keywords: Jasmine tea, Multipetal jasmine, Characteristic volatiles, Molecular docking, Molecular dynamics simulation

Highlights

  • •

    JT was scented by multipetal jasmine for the first time.

  • •

    Different jasmine varieties endowed JT with different flavor types.

  • •

    13 compounds are the volatiles that lead to the characteristic aroma of JT.

  • •

    Molecular docking and molecular dynamics revealed the mechanism of flavor perception of JT.

1. Introduction

Jasmine tea (JT in short), one of the most consumed and produced types of scented tea, is processed by mixing fresh jasmine flowers with finished tea (Chen et al., 2025). The unique fragrance and refreshing flavor of JT have made it the most commonly used base tea in in novel-tea beverage (Xiao et al., 2024). Simultaneously, the health benefits of JT, including anti-oxidation, anti-depression, and sedative effects, have enhanced its competitiveness in the health beverage market (Tang et al., 2021; Zhang et al., 2024; Zhang et al., 2021). In recent years, scholars have improved the aroma concentration and taste quality of JT by changing the scenting method, flower amount and scenting time (An et al., 2024; Chen et al., 2024). However, there is limited research on the development and innovation of JT aroma type, which is mainly due to the relatively single variety of jasmine planting.

Jasminum sambac, an upright or climbing shrub of Jasminum, Oleaceae, is mainly planted in humid and sunny areas with double-petal varieties (Fang et al., 2024). The various floral structures of jasmine are generally classified based on the number of corolla layers, which include single-petal, double-petal, and multi-petal varieties. Double-petaled jasmine has long dominated JT production. However, rising demand from novel-tea beverage and functional beverage markets has strained its supply. Consequently, developing widely adaptable jasmine varieties with diverse flowering periods is urgent to enable year-round tea scenting and boost yields. A recent study showed that JT scented with single-petal jasmine “Bijian” had a fresher aroma than the traditional double-petal jasmine “Shuangban” (Zhang et al., 2025). However, the low yield, weak resistance and standard aberration of single-petal jasmine “Bijian” make it difficult to be widely planted and applied (Hong, 2023). Multi-petal jasmine possesses multiple layers and may contain richer aromatic substances compared with single and double-petaled varieties (Li, 2012). Therefore, we speculate that using multipetal jasmine to scent tea could endow jasmine tea with novel fragrance, which is helpful to meet the diversified needs of consumers and alleviate the shortage of jasmine raw material supply.

Molecular docking is a computational technology that elucidates the mechanism of intermolecular interactions by predicting the binding modes and affinities of ligands and receptors (Jiang et al., 2025). Molecular dynamics simulation can not only explore the static structure of molecules, but also simulate the dynamic changes under different conditions, and reveal the characteristics of molecular interactions. (Lu et al., 2023). Nowadays, this technologies have become an important tool to analyze the interaction mechanism between tea characteristic aroma components and olfactory receptors (Huang, Deng, et al., 2025; Huang, Wang, et al., 2025; Zhu et al., 2025). Many studies have identified the characteristic aroma components of jasmine tea, but the specific mechanism of these compounds on the flavor perception of jasmine tea is still unknown (An et al., 2020). Aroma can affect mood through a variety of physiological mechanisms (Wu et al., 2025). In-depth study of the docking mechanism between aroma compounds and olfactory receptors may provide new insights into elucidating the antidepressant mechanism of jasmine tea.

In this study, three kinds of multi-petal jasmine (Xiangfei 2, 4, 11) and common double-petal jasmine were used as flower raw materials, and green tea was used as base tea to develop JT with different aroma types. Solid-phase micro-extraction (SPME) combined with gas chromatography–mass spectrometry (GC–MS) technology was used to measure volatile compounds. Multivariate statistical methods combined with odor activity value calculation was used to explore the characteristic aromatic components of JT. Additionally, the interactions between the characteristic aroma components of JT and olfactory receptors was elucidated by molecular docking and molecular dynamics simulation technology. This study enriched the types of JT products and provided a theoretical basis for the application of multi-petal varieties in JT processing.

2. Materials and methods

2.1. Materials

The pan-fired green tea provided by Hunan Weishan Tea Co., Ltd. was used as the base tea. Double-petal jasmine, Xiangfei 4, Xiangfei 11 and Xiangfei 2 were all picked from Heng County, Nanning city, China on a sunny afternoon. When the flowers opened to the claw shape, they were mixed with the base tea for scenting to obtain jasmine tea TS, TA, TB and TC respectively. The tea samples were enclosed in sterile polyethylene bags, subsequently transported to the laboratory, and stored at 4 °C until analysis.

2.2. Sensory evaluation of jasmine tea

To initially evaluation the aroma quality of tea samples, five professional reviewers (comprising three females and two males, aged between 25 and 45) holding National Senior Tea Evaluator Qualification Certificate performed sensory evaluation and quantitative descriptive analysis (QDA). In briefly, each tea sample was brewed with 100 °C water using a leaf/water ratio of 1:50 (W/W) for 3 min the first time and 5 min the second time. The tea infusion was then immediately poured into a tea bowl for the panel's evaluation. Then the intensity of aroma attributes, including freshness, persistence, sweetness, flowery and grassy, was then scored on a scale of 0 (indicating no presence) to 10 (indicating extreme concentration). All tea assessors granted written consent to partake in the study and were assigned a distinct code to maintain their anonymity. Each sample was assessed three times.

2.3. Volatile compounds identification methods

2.3.1. SPME collects aroma compounds

Volatile compounds from jasmine tea samples were extracted using automated solid phase microextraction (SPME) as reported by An et al. (An et al., 2024). An automatic sampler (CTC Analytics, Guangzhou, China) was used. Briefly, 1.0 g (accurate to 0.0001 g) of tea powder (crushed by a mixed grinder (SMF 2002, Subol, China) at 50 Hz) and 10 μL ethyl decanoate (50 ppm, St. Louis, Missouri, USA) were transferred into a 15 mL headspace sample bottle, and shaken at 80 °C for 10 min. Subsequently, the 30/50 DVB/CAR/PDMS extraction head (Supelco, Bellefonte, PA, USA) was positioned 1 cm above the liquid surface and allowed to adsorb at a temperature of 80 °C for a duration of 30 min.

2.3.2. GC–MS condition

Volatile compounds in all samples were analyzed utilizing the Agilent 7890B-7000C system (Agilent, Santa Clara, CA, USA). The analysis employed an Agilent HP-5MS ultra-inert capillary column with dimensions of 30 m × 0.25 mm × 0.25 μm, operated in splitless injection mode. The flow rate of high-purity helium (99.999 %) was set at 1.0 mL/min, with a split ratio of 20:1. The temperature of the gas chromatographic sampler was maintained at 250 °C, and the following temperature program was implemented for the column: an initial temperature of 40 °C; a ramp to 180 °C at a rate of 5 °C/min; followed by an increase to 250 °C at a rate of 20 °C/min, held for 1 min.

The conditions for the mass spectrometer were as follows: electron ionization energy was set at 70 eV, the interface temperature was maintained at 230 °C, the ion source temperature was also set at 230 °C, the mass scan range was from 50 to 550 amu, and the solvent delay time was established at 3 min.

2.3.3. Qualitative and qualitive analysis of volatile compounds

The results were qualitatively analyzed by the retention index (RI) counting function of Canvas browser software equipped with NIST 20 (version 1.0, J & X Technologies, Shanghai, China) and n-alkanes (C5-C25) (Anpel, Shanghai, China).

The volatile compounds were quantitatively analyzed according to the method of Chen et al. (2023). The concentrations of the volatile compounds were determined in micrograms per liter (μg/L) utilizing the internal standard solution, as described by the following equation:

Ci=Cis×Ai/Ais

Ci represents the mass concentration of a specific component measured in micrograms per liter (μg/L), while Cis denotes the mass concentration of the internal standard, also expressed in micrograms per liter (μg/L). Additionally, Ai refers to the chromatographic peak area corresponding to the component of interest, and Ais indicates the chromatographic peak area associated with the internal standard.

2.3.4. Calculation of OAV

The odor activity value (OAV) of volatile compounds was calculated using the following equation.

OAVi=Ci/OTi

where Ci (μg/g) represents the relative content of volatile compounds. OTi (μg/g) represents the odor threshold of volatile compounds in water. OT values were taken from the compilations of flavor thresholds values in water and other media (L. J. van Gemert, 2015).

2.4. Molecular docking

Two olfactory receptors (ORs) widely used in the research of tea aromatic molecular docking were selected for analysis: OR1A1 (UniProt ID: Q9P1Q5) and OR1D2 (UniProt ID: P34982). The three-dimensional (3D) structure of the receptor was downloaded from the UniProt website (https://www.uniprot.org/) and saved in PDB format. The sfd files for the aromatic compounds were obtained from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/) and then converted to pdb file format using OpenBabel.

Molecular docking was performed using AutoDockTools 1.5.7 (Scripps Research, USA). Receptor proteins were treated by removing water molecules and adding hydrogen atoms, and they were selected as receptors and exported to PDBQT format. The aroma compounds were hydrogenated and the torsion bond were defined, and they were selected as the ligand to be exported to the PDBQT format. The pdbqt files of receptors and ligands were imported into AutoDockTools 1.5.7. When constructing the docking box, the receptor protein is centered, the docking box completely covers the receptor protein, and the ligand is located outside the docking box. The parameters of the docking frame are collected (Table S1). For each ligand-receptor pair, 20 docking simulations were performed, and the conformation with the highest binding score was selected as the best binding conformation. PyMol 2.5.5 (DeLano Scientific LLC, USA) was used to visualize the docking results.

2.5. Molecular dynamics simulation

MDs of the complex were performed using GROMACS 2020.6 with the AMBER99SB force field and SPC water model at a 2 fs time step. Long-range electrostatic interactions were addressed through the particle mesh Ewald technique. The system was equilibrated for 100 ps under NVT, followed by 100 ps under NPT at 300 K, with a total simulation time of 100 ns. A 1.2 nm cutoff distance was used. System stability and convergence were verified by monitoring RMSD and potential energy. The workflow consisted of initial energy minimization, followed by equilibration, and finally MDs. Free energy calculations were performed using MM/GBSA and MM/PBSA methods. Free energy landscapes were constructed and analyzed based on RMSD, radius of gyration (Rg), and Gibbs free energy, with visualization completed using Origin 2024.

2.6. Data analysis methods

Simca-p software (version 14.1, MKS Umetrics AB, Umeå, Sweden) was used to perform principal component analysis (PCA), hierarchical cluster analysis (HCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). Radar plot and line chart were obtained by Origin Pro (v2022c, Originlab Corporation, Northampton, MA, USA). Other plots were drawn using Adobe Photoshop (v 12.0.3, Adobe Systems Incorporated, California, USA).

3. Results and discussion

3.1. Aroma evaluation results

A conventional sensory quality evaluation was performed to compare aroma differences among TA, TB, TC, and TS (Fig. 1). TC exhibited the highest intensity in freshness (8) and persistence (8), though it showed more grassy notes (3) compared to the other teas. TB displayed the strongest sweet aroma (8) and TS had the highest floral aroma intensity (8). In contrast, TA had consistently low scores across all aroma attributes compared to other teas.

Fig. 1.

Fig. 1

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Radar plots displaying the characteristic aromas of 4 different finished jasmine tea samples.

Sensory evaluation results indicated that jasmine varieties could significantly affect the aroma profile of JT, which preliminarily suggesting the possibility of multi-petal jasmine varieties in shaping diversified JT aroma types. Different jasmine varieties impart distinct aroma characteristics, which may be mainly due to the diverse types and contents of aroma compounds released by jasmine in the process of scenting.

3.2. Volatile profiles identified in JT

HS-SPME-GC–MS was used to analyze the volatility of four JT. A total of 201 volatile components were detected, including 59 hydrocarbons, 28 alcohols, 7 aldehydes, 6 ketones, 39 esters, 29 terpenoids, 5 aromatic hydrocarbons, 2 heterocycles, 1 ether, 12 olefins and 13 other compounds (Fig. 2A). 55 compounds, including indole, linalool, α-Farnesene, Methyl anthranilate, etc., were common compounds of 4 kinds of JT, forming their basic aroma profile. TA, TB, TC and TS had 26, 11, 18 and 14 unique volatile components, respectively (Fig. 2B), which like contribute significantly to their distinct aromas. Moreover, the total number of volatile compounds in TA, TB and TC exceeded that in TS, indicating multipetal jasmine may endow JT with a richer aroma.

Fig. 2.

Fig. 2

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The profiles of volatile metabolites from jasmine tea samples. (A) The classification of the nonvolatile metabolites. (B) Comparative analysis of volatile compounds in four different jasmine tea. (C) PCA score plot of different samples. (C) The OPLS-DA model. (E) Hypothesis testing of the OPLS-DA model. (F) The VIP plot.

PCA was used to distinguish the differences of JT. A clear separation trend was observed in the JT samples in the PCA diagram (Fig. 2C), indicating that their volatile profiles were significantly different. To improve separation and characterize differences, OPLS-DA analysis was performed on the identified volatiles (Fig. 2D). The model parameters (R2X = 0.991, R2Y = 0.999, Q2 = 0.986) exhibited high explanatory variance (R2Y) and strong predictive performance (Q2). The results of 200 displacement tests (R2 = 0.657, Q2 = −1.07) showed that the model had a good fitting degree in performance, and could be used for the next screening of differential volatiles (Fig. 2E). Based on the VIP value of OPLS-DA model, 21 differential volatile components (VIP ≥ 1) were screened, which can be used to distinguish the JT scented with different jasmine varieties.

3.3. Analysis of characteristic aroma compounds of JT scented by different jasmine varieties

The overall aroma performance of tea depends on the concentration of volatile compounds and its aroma threshold (Liang et al., 2024). Some volatile compounds with lower thresholds and concentrations still play a significant role in aroma performance. Therefore, in order to assess the exact contribution of a single compound to the overall aroma, this study screened the key aroma active substances with OAV ≥ 1 and VIP ≥ 1 as criteria (Wang et al., 2024). 13 compounds, 3-Hexen-1-ol, benzoate, (Z)-, Indole, Benzoic acid, methyl ester, Linalool, Acetic acid, phenylmethyl ester, α-Farnesene, Methyl anthranilate, 3-Hexen-1-ol, acetate, (Z)-, 4-Hexen-1-ol, acetate, Methyl salicylate, Benzyl alcohol, Benzoic acid, 2-hydroxy-, ethyl ester, and Nerolidol, were identified as characteristic aroma compounds. The specific information of 13 characteristic compounds was supplemented in Table S2.

Fig. 3A showed the content distribution of these 13 compounds in JT. The OAV value of Benzoic acid, 2-hydroxyl -, ethyl ester was greater than 1 only in TB, which has caramel aroma and was considered to contribute more to the sweetness of TB (Huang, Deng, et al., 2025; Huang, Wang, et al., 2025). The content of 3-Hexen-1-ol, benzoate, (Z)-, Indole, Benzoic acid, methyl ester, Acetic acid, phenylmethyl ester, α-Farnesene, 3-Hexen-1-ol, acetate, (Z)-, Methyl salicylate and Nerolidol was higher in TC, which were the characteristic aroma component of TC. 3-Hexen-1-ol, benzoate, (Z)- mainly showed fresh, green and leaf aroma, and methyl salicylate showed mint fragrance. These two compounds may explain why TC possessed a fresher scent compared to the other three JTs (Wang et al., 2025; Zheng et al., 2024). Indole with floral properties has been identified as a key floral component in various teas. (Lin et al., 2024; Wu et al., 2024). Benzoic acid, methyl ester often presents a strong floral and fruity aroma in JT, which affects the aroma concentration of JT to a certain extent (An et al., 2020). Acetic acid, phenylmethyl ester with fruit characteristics serves as a key aroma component of osmanthus tea, enhancing its aromatic richness (Tang et al., 2024). α-farnesene is considered a key floral compound in JT and has a positive correlation with the aroma quality of JT (An et al., 2023). 3-Hexen-1-ol, acetate, (Z)- is recognized as having grassy odor, which may be the sources of grassy odor in TC (You et al., 2023). Nerolidol is commonly found in the flowers, leaves, fruits, and other parts of plants, giving tea a floral scent (Zou et al., 2024). The concentrations of of Linalool, Methyl anthranilate, 4-Hexen-1-ol, acetate, and Benzyl alcohol were higher in TS, which served as a distinctive aromatic component of TS. Linalool is a monoterpenoid alcohol commonly found in all kinds of tea, accounting for 70 % of the major floral scents found in nature (Knudsen et al., 2006). Methyl anthranilate is one of the key floral components affecting the aroma quality of JT (An et al., 2022). 4-Hexen-1-ol, acetate has been identified as the characteristic odor compound of the Staphylea bumalda, which is related to the presentation of floral, fruity and sweet aroma, but it has not been reported in tea (Zheng et al., 2024). Benzyl alcohol has remarkable floral characteristics, which is regarded as the key to the “sweet” and “floral” characteristics of Anji black tea (Wang et al., 2019). There were 10 compounds with OAV > 1 in TA, including 3-Hexen-1-ol, benzoate, (Z)-, Indole, Benzoic acid, methyl ester, Linalool, Acetic acid, phenylmethyl ester, α-Farnesene, Methyl anthranilate, 4-Hexen-1-ol, acetate, and Methyl salicylate. However, their concentrations in TA were lower than in the other three JTs, explaining TA's weaker overall aroma, which is consistent with the results of sensory evaluation. The number of key characteristic volatile compounds in TC was the highest, indicating a richer aroma in TC. In conclusion, these key active volatile components can be roughly divided into floral, sweet and fresh aroma compounds.

Fig. 3.

Fig. 3

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Analysis of characteristic aroma components of jasmine tea scented by different varieties of jasmine. (A) Heatmap analysis of characteristic aroma components in jasmine tea. (B) Structure and content of compounds related to floral fragrance. (C) Structure and content of compounds related to aroma persistence.

To explain the difference in floral concentration of JT samples, the total contents of the above volatile compounds with floral properties was calculate (Fig. 3B).Results showed that the total content of floral compounds in TS is the highest, followed by TC, TB and TA, which explained the more pronounced floral fragrance of TS and the lighter floral fragrance of TA. In addition, studies have shown that Benzoic acid, methyl ester and Benzyl alcohol are key compounds for evaluating the aroma durability of JT (Pang et al., 2025). Therefore, the total content of benzyl alcohol and benzoic acid, methyl ester in four JTs were also calculated in this study (Fig. 3C). The content of these two compounds in TC was the highest, which may be the reason for its relatively long-lasting aroma. However, there was no significant difference in the total content of the two types of compounds between the TS and the TC. The results showed that the double jasmine and Xiangfei 2 could stably release rich floral aroma substances during the scenting process, giving the JT ‘strong and lasting ‘core aroma characteristics.

3.4. Molecular docking of characteristic aroma compounds with ORs

Olfactory receptors (ORs) are members of the G protein-coupled receptor family and have sensitive odor discrimination ability (Yang et al., 2024). The presence of broad-spectrum receptors offers a basis for exploring the interactions between various aromatic compounds (Zhu et al., 2025). OR1A1 and OR1D2 are important receptors of this type and have been widely used in molecular docking of tea aroma compounds. Therefore, these two receptors were selected for this study (Ma et al., 2025). The selected 13 characteristic volatile components were used as ligands for molecular docking to explore the specific binding sites of small molecules with these receptor proteins.

As shown in Table S3, although the amino acid binding sites of ligand-receptor interaction were different, their binding energies were all negative, indicating that olfactory protein receptors could spontaneously bind to aromatic compounds. By comparing the two olfactory receptors, it was found that except for 4-Hexen-1-ol, acetate, the binding energies of the other compounds with OR1A1 receptor were low, which indicated that it had high binding affinity with aromatic molecules (Sun et al., 2024). In addition, the same receptor has different binding energies when binding different aroma compounds. Among them, Nerolidol showed the strongest binding affinity (−6.58 kcal/mol), while 4-Hexen-1-ol, acetate had the weakest binding to the receptor (−2.48 kcal/mol). Binding energy is utilized to assess the interactions between molecules, with a lower value signifying a stronger affinity between them and enhanced structural stability. Aroma compounds might preferentially attach to receptors that have a high affinity, filling up the limited binding sites available on proteins. This could also clarify why aroma compounds have varying aroma profiles and thresholds.

Fig. 4A showed the molecular docking results of 7 pairs of receptors and ligands with binding energies lower than −5 kcal/mol. The results showed that hydrogen bonds and hydrophobic interactions played a key role in the binding of aroma volatiles to olfactory receptors. Nerolidol formed hydrogen bonds with ILE105 of OR1A1 and TYR252 of OR1D2, respectively. The presence of hydrophobic amino acid residues provides a hydrophobic environment for odorants and promotes their stable binding (Sun et al., 2024). α-Farnesene bound to 9 hydrophobic amino acid residues (PHE73, MET104, TYR178, TYR276, TYR258, VAL254, VAL203, ILE181, PHE206) in OR1AI and 5 hydrophobic amino acid residues (TYR259, LEU199, LEU255, LEU208, PHE207) in OR1D2 through hydrophobic interaction. Methyl anthranilate bound to the receptor OR1A1 through hydrophobic residues PHE73, MET104, ILE105, PHE206, VAL203, ILE181, TYR258, VAL254 and TYR276. 3-Hexen-1-ol, benzoate, (Z)- bound to the receptors OR1A1 and OR1D2 through hydrophobic residues MET104, ILE105, ILE181, TYR267, VAL203 and TYR252, LEU255, TYR259, PHE207 respectively.

Fig. 4.

Fig. 4

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Key characteristic aroma compounds interacting with olfactory receptors (ORs). (A) Interaction of 3-Hexen-1-ol, benzoate, (Z)- with the OR1A1. (B) Interaction of α-Farnesene with the OR1A1. (C) Interaction of Nerolidol with the OR1A1. (D) Interaction of Methyl anthranilate with the OR1A1. (E) Interaction of 3-Hexen-1-ol, benzoate, (Z)- with the OR1D2. (F) Interaction of α-Farnesene with the OR1D2. (G) Interaction of Nerolidol with the OR1D2.

It is worth noting that there are some other forces involved in further enhancing the interaction between ligands and receptors. For example, Benzoic acid, methyl ester formed salt bridge with HIS159 of OR1D2, and formed π-Cation interaction with LYS90 of OR1A1. Methyl salicylate formed π-Stacking with TYR259 of OR1D2.

Overall, the characteristic aroma components in JT are combined with olfactory receptors through hydrogen bonds, hydrophobic interactions, salt bridge, π-Stacking and π-Cation interaction, which is the molecular basis for perceiving the diverse aromas of JT. However, molecular docking is based on the static conformational simulation of receptors, without considering the dynamic conformational changes of receptors, multi-receptor synergy and the influence of nasal physiological environment, so it is difficult to fully capture the complexity of real olfactory response. Future work could explore genotype-odorant relationships in greater depth and validate these findings through large-scale sensory and in vivo olfactory experiments, further enhancing the translational value of these results.

3.5. Molecular dynamics simulation

The MDs of 100 ns was applied to explore the dynamic characteristics obtained by molecular docking. In view of this study focusing on the mechanism of action of characteristic aroma, the compounds that contribute to the characteristic aroma types (floral, sweet and fresh aroma) of JT were preferentially selected. Based on the docking results, three complexes with higher docking binding energy were selected for MDs: Benzoic acid, 2-hydroxy-, ethyl ester-OR1A1 (X166-OR1A1), 3-Hexen-1-ol, benzoate, (Z)—OR1A1 (X195-OR1A1) and Methyl anthranilate-OR1A1 (X197-OR1A1). RMSD was used to determine the stability of the complex structure (Feng et al., 2024). It can be seen from Fig. 5A that the RMSD values of the three complexes fluctuated greatly in the early stage, and tended to be stable after about 50 ns, indicating that the simulation system gradually reached equilibrium and the complex structure was relatively stable. The Rg value was 2.08–2.25 nm, and the fluctuation range was not large, indicating that the complex maintained a relatively compact structure during the simulation process. Solvent Accessible Surface Area (SASA) includes hydrophobic and hydrophilic solvent accessible surface areas. SASA values maintained a relatively stable trend, which indicated no significant structural changes during the whole simulation process. Free energy landscape analysis using RMSD (x-axis), Rg (y-axis), and Gibbs free energy (z-axis) showed that the free energy profiles of the three complexes formed a single and sharp minimum energy region, indicating the complex had a compact and stable conformation after binding. By calculating MM/PBSA and MM/GBSA, it was found that van der waals force was the main stabilizing force of the complex (Table S4). The van der Waals forces of the three complexes were − 45.76 ± 0.27, −34.64 ± 0.22, and − 42.36 ± 0.25, respectively. The consistent dominance of van der Waals forces across all complexes underscores the criticality of hydrophobic interactions in shaping the aroma recognition mechanism, providing a molecular basis for the characteristic fragrance profiles of JT scented with multipetal jasmine varieties.

Fig. 5.

Fig. 5

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Molecular dynamics simulation analysis. (A) RMSD analysis results; (B) Rg analysis results; (C) SASA analysis results; (D) Free energy landscape of the X166-OR1A1 complex; (E) Free energy landscape of the X195-OR1A1 complex; (F) Free energy landscape of the X197-OR1A1 complex.

4. Conclusion

This study is the first to use multipetal jasmine to process JT, and to identify the characteristic compounds that produce the differences in aroma profiles. Benzoic acid, 2-hydroxyl-, ethyl ester was the primary contributor to sweet notes in TB, 3-Hexen-1-ol, benzoate, (Z)- and Methyl salicylate gave TC a fresher aroma, Methyl anthranilate, 4-Hexen-1-ol, acetate and Benzyl alcohol was the contributor to the strong floral fragrance in TS. Molecular docking results indicated that hydrogen bonding and hydrophobic interactions were critical forces governing receptor-ligand binding, and MDs further verify the dynamic stability of these interactions. This study provides a new perspective for the innovation of JT products and a theoretical basis for the aroma regulation of new aroma types of JT.

CRediT authorship contribution statement

Yuan Chen: Writing – review & editing, Writing – original draft. Huimin An: Writing – review & editing. Yiwen Huang: Data curation. Youcang Jiang: Methodology. Jiaqi Ying: Investigation. Sirui Wang: Validation. Chunniu Li: Resources. Zhaoyang Bu: Resources. Xianmin Li: Resources. Yuelan Pang: Visualization, Conceptualization. Zhusheng Liu: Visualization. Shi Li: Supervision. Zhonghua Liu: Conceptualization. Jianan Huang: Conceptualization.

Institutional Review Board Statement

According to the prescribed jasmine tea evaluation procedure outlined in the “Tea Sensory Evaluation Methods” (GB/T 23776–2018), the experimental scheme involving sensory evaluation is in line with Chinese national law and does not need ethical approval. In the course of the implementation of this study, no human body, animal violation of law, morality, or “Declaration of Helsinki” was involved. All participants have given written consent.

All participants voluntarily participated in this study and had given written consent.

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.

Acknowledgements

This research was funded by the Project of Hunan Provincial Department of Agriculture and Rural Affairs (XCNZ [2023] No. 0053); Hundred billion tea industry chain key technology innovation demonstration (No. 2021NK1020-4); Agriculture Research System of China (No. CARS-19); Promotion and application of green, efficient, light and simplified cultivation mode of summer and autumn tea (No. 2022YFD1600802); Key Technology Innovation and Demonstration of Jasmine Tea Processing (No.2020NK2026). Tea germplasm innovation and utilization of tea functional components (No.xczx-2024295).

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.fochx.2025.102734.

Contributor Information

Shi Li, Email: lishidodo@163.com.

Zhonghua Liu, Email: zhonghua-liu-ms@hunan.edu.cn.

Jianan Huang, Email: Jian7513@hunau.edu.cn.

Appendix A. Supplementary data

Supplementary material. Table S1. Grid docking parameters in molecular docking. Table S2. Characteristic volatile compounds of jasmine tea scented with different jasmine varieties. Table S3 The docking results between ORs (OR1A1 and OR1D2) and ligands. Table S4. Statistical analysis of the MM/GBSA and MM/PBSA results for complexes (Kcal/mol).

mmc1.docx (29.8KB, docx)

Data availability

Data will be made available on request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary material. Table S1. Grid docking parameters in molecular docking. Table S2. Characteristic volatile compounds of jasmine tea scented with different jasmine varieties. Table S3 The docking results between ORs (OR1A1 and OR1D2) and ligands. Table S4. Statistical analysis of the MM/GBSA and MM/PBSA results for complexes (Kcal/mol).

mmc1.docx (29.8KB, docx)

Data Availability Statement

Data will be made available on request.

Articles from Food Chemistry: X are provided here courtesy of Elsevier

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