Exploring the Molecular Mechanism of the Antioxidant Activity of Medicine and Food Homology Licorice Flavonoids Based on Pharmacophore Theory and Quantum Calculations

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Introduction
Oxygen free radicals (also known as reactive oxygen species) are the primary substances that cause oxidative stress and cellular damage [1].Under normal circumstances, the body produces free radicals while also generating substances that counteract them, maintaining a dynamic balance between free radicals and antioxidant agents [2].However, when free radicals accumulate excessively and cannot be efectively cleared, the surplus free radicals can attack the body's tissues, leading to oxidative stress and cellular damage and ultimately contributing to aging and other diseases [3].Te role of antioxidants is to protect cells from oxidative damage by inhibiting the generation of free radicals or clearing formed free radicals [4].Antioxidants can stabilize free radicals, thereby reducing their damage to biological molecules such as cells, DNA, lipids, and proteins [5].Common antioxidants include vitamin C, vitamin E, glutathione, and favonoids.Tey can exert antioxidant efects through various mechanisms, such as neutralizing free radicals, activating antioxidant enzyme systems, and repairing oxidative damage [6].Terefore, studying the molecular mechanisms of oxidants is crucial for developing efective antioxidant treatment strategies.
Licorice favonoids are a class of favonoid compounds extracted from licorice roots [7].Tey are widely used in traditional Chinese medical and other herbal formulations, exhibiting various biological activities, with antioxidant activity being one of the most prominent and important features [8].Studies have found that licorice favonoids exert antioxidant efects by clearing oxygen free radicals, inhibiting the generation of peroxides, and enhancing the activity of antioxidant enzymes [9].Tese antioxidant mechanisms help protect cells from oxidative stress and maintain the oxidative-antioxidative balance within cells [10].As a natural antioxidant, licorice favonoids have broad prospects for applications.Tey are extensively used in the pharmaceutical and health product industries for the development of antioxidant products, aiming to prevent and treat diseases associated with oxidative damage, such as cardiovascular diseases, cancer, infammatory diseases, and more [11].Moreover, licorice favonoids can also be utilized in the food industry as natural preservatives to extend the shelf life of food [12].Although previous research has found that the antioxidant activity of licorice favonoids can be altered under solvent mediation [13], the molecular mechanism of how the structure of licorice favonoids infuences their antioxidant activity remains not fully understood.
Pharmacophore theory and network pharmacology have been widely used to explore the molecular mechanism of antioxidant activity [14].Pharmacophore theory is a method based on the relationship between specifc structural fragments in compounds and their biological activities, which helps reveal the molecular mechanisms of drugs [15].By identifying and analyzing the key structural features (pharmacophores) of biological activity, we can understand the structure-activity relationships of compounds [16].In antioxidant research, pharmacophore theory is used to identify and optimize molecules with antioxidant activity.Analyzing these key structural features can reveal the interactions and structure-activity relationships between antioxidant molecules and target molecules [17].Network pharmacology is an approach that integrates methods from systems biology, computational biology, and other disciplines to study the overall interactions and molecular networks between drugs and targets [18].In antioxidant research, network pharmacology methods are used to unravel the interactions and signal transduction between antioxidant compounds and multiple molecular targets within cells.By constructing drug-target interaction networks, we can understand the mode of action of antioxidant molecules within cells, the mechanisms of regulating cellular signaling pathways, and their interactions with other molecules [19].Terefore, the application of pharmacophore theory and network pharmacology will contribute to further revealing the molecular mechanisms of antioxidant activity in licorice favonoids.
In this study, we will frst use network pharmacology to screen for the main active components and key targets of antioxidant activity in licorice favonoids.Ten, we will employ pharmacophore theory to identify potential key structural features that may contribute to the antioxidant activity of licorice favonoids.Furthermore, utilizing quantum computing methods, we will calculate the electronic structure, orbital distribution, and relevant physicochemical properties of licorice favonoid molecules to reveal their potential mechanisms of antioxidant activity.Trough these analyses, we aim to elucidate the possible mechanisms of licorice favonoids in antioxidant processes and provide some guidance for the design and development of more potent antioxidant compounds.

Research on Network Pharmacology.
To screen for the active components and key targets of the antioxidant activity of licorice favonoids, we conducted an analysis using network pharmacology methods.Based on the previous analysis of licorice favonoids using UHPLC-Orbitrap-MS, the composition of licorice favonoids was collected [20], and further screening was conducted based on the structural characteristics of favonoid components to identify 34 compounds (Table 1).Identify and download the structures of compounds from the PubChem database, and save them in SDF format.Ten, use the Swiss database to predict the targets for each compound.Search for "antioxidant" in the GeneCards database to collect relevant targets with a relevance score greater than 4. Generate a Venn diagram by comparing the predicted targets of the active components with the predicted targets of licorice favonoids.Take the intersection of the targets (Figure 1(a)) to obtain the potential targets of licorice favonoids for antioxidant activity.Enter the potential targets of licorice favonoids for antioxidant activity in the STRING database, set the organism as "Homo" to flter for human-related proteins, and construct a protein-protein interaction (PPI) network diagram of the potential targets of licorice favonoids for antioxidant activity (Figure 1(b)).Use the DAVID 6.8 database to generate metabolic pathways related to the potential antioxidant targets (Figures 1(c)-1(d)).Finally, use Cytoscape v3.8.2 software to construct a disease network of active components, potential targets, and related pathways of licorice favonoids.Ten, screen and identify the main active components and key targets associated with the antioxidant activity of licorice favonoids.

Building a Pharmacophore Model. A dataset of IC50
values for 50 experimentally identifed tyrosinase inhibitors was obtained from the published literature [21][22][23][24].Te chemical structures of these compounds were sketched using the ChemDraw module in ChemOfce, and energy optimization was performed using Discovery Studio 2019 software (BIOVIA; San Diego, USA).A training set for constructing a QSAR pharmacophore was created using compounds from 32 tyrosinase inhibitors (Figure 2).Te names of these molecules (Name), their activity (Activ) represented by IC50 values (μM), and an uncertainty in activity (Uncert) were selected as 1.5.According to the pharmacophore construction algorithm, the top two compounds in terms of ranking are defned as active compounds.

2
Journal of Food Biochemistry where "MA" stands for the Molecular Activity Score, which signifes the pharmacophore activity rating attributed to a compound.A higher MA value suggests that the compound is assessed to possess a higher potential for activity."Unc MA " represents the uncertainty of the MA value for a compound.It indicates the level of uncertainty associated with the estimation of the compound's activity.A higher Unc MA value suggests that there is a certain degree of uncertainty in the assessment of the compound's activity."UnAc A " represents the uncertainty of activity for a compound.Tis value is specifc to the measurement method used to evaluate the compound's activity.When the value of "UnAc A " is lower, it indicates a more certain determination of the compound's activity.Te 10 compounds with the lowest ranking are defned as nonactive compounds.
"log(A)" represents the logarithm of the activity value."log(MA)" indicates the logarithm of the predicted activity value.
Te training set molecules were subjected to pharmacophore generation using the 3D QSAR Pharmacophore Generation feature of Discovery Studio 2019 software.A maximum of 255 conformations were generated for each small molecule to characterize its conformational space.Only the conformations whose energy values are within the energy threshold of 10 kcal/mol are preserved [23].Eighteen tyrosinase inhibitors were selected to construct a test set to verify QSAR pharmacophore (Figure 3).In order to guarantee the accuracy of the model, the selection of tyrosinase inhibitor activity values across four magnitude sets.

Molecular Docking.
Selecting TYR as the receptor protein, four licorice favonoid compounds with good activity identifed through pharmacophore screening are chosen as ligand molecules.Molecular docking was performed using Discovery Studio 2019 (BIOVIA; San Diego, USA).Obtain the threedimensional structure of the target protein from the RCSB-PDB website (https://www.rcsb.org/).Acquire the threedimensional structure of the ligand molecules from the Pub-Chem database (https://pubchem.ncbi.nlm.nih.gov/).Make minor modifcations to the method based on the previous reports from the research team [13].In brief, the approach involves frst conducting structure optimization for small molecules.Ten, the receptor protein is subjected to structural processing.Finally, molecular docking is performed using the LibDock module.Among them, where Libdockscore is greater than or equal to 90, it indicates a good afnity between the receptor and ligand.Te formula for calculating the docking score is as follows: 2.4.DFT Calculation.Te three-dimensional structures of licochalcone B, retrochalcone, isoliquiritin, and isoliquiritigenin were obtained using the PubChem database (https://pubchem.ncbi.nlm.nih.gov/)(Figure S1).To perform theoretical calculations, the DMOL3 module of Materials Studio 2019 software (Accelrys Software Inc., US) was utilized [25,26].Te calculations were performed using a combination of the generalized gradient approximation (GGA) and the BLYP functional with gradient correction functions [14].In addition, no constraints were applied during the geometry optimization calculations.Te molecular structure and radicals of licorice favonoids were optimized using the DND3.5 version.Termodynamic calculations were conducted to analyze the relationship between the antioxidant activity of licorice favonoids and reaction-free energies.edges (Figure 4).In the diagram, red circles represent the active components of licorice favonoids, green diamonds represent the potential targets associated with the antioxidant activity, yellow triangles represent signaling pathways, and blue squares represent licorice favonoids.Te active components ranked in descending order by degree value and identifed as the top 10 compounds are isoliquiritigenin, 4′-Methoxyfavone, moslofavone, isoliquiritin, 7-Hydroxyfavone, retrochalcone, nobiletin, corylin, licochalcone B, and licofavone A. Tese compounds are speculated to be the main active components involved in the antioxidant activity of licorice favonoids (Table 2).In addition, both the PPI network graph and the H-T-P-C network graph indicate that TYR is one of the core targets for the antioxidant activity of licorice favonoids.Terefore, considering these fndings collectively, it is advisable to select TYR as a key target for conducting a structure-activity relationship (SAR) model study.

Building a 3D-QSAR Pharmacophore Model with
Predictive Capability.A 3D-QSAR pharmacophore model with predictive capability is constructed using a training set consisting of known active compounds.Figure S2 illustrates the alignment of the compound with the highest predicted activity with the pharmacophore model.It can be observed   Journal of Food Biochemistry the pharmacophore model to varying degrees.Terefore, this phenomenon indicates that the pharmacophore model has a good discriminatory ability between active and nonactive molecules.Figure S4 displays the Δcost values of these pharmacophore models, all of which are greater than 400.Tis indicates that these models have a high level of confdence.Te Δcost (null cost-total cost) is an important indicator for evaluating a pharmacophore model.When this value is less than 40, the confdence interval of the model falls below 50%.A value between 40 and 60 indicates a confdence interval of 75%-90%, while a value greater than 60 indicates a confdence interval of over 90% for the model.Figure S5 demonstrates the predictive ability of the pharmacophore models for the compounds in the training set.It can be observed that these 10 pharmacophore models exhibit correlation coefcients (r 2 ) for predicting activity in the training set as follows: 0.922, 0.896, 0.880, 0.876, 0.874, 0.866, 0.860, 0.857, 0.859, and 0.853.Tis phenomenon indicates that all of these pharmacophore models have good predictive capabilities.Figure S6 displays the 10 pharmacophore models constructed using the training set.It includes the statistical data   6 shows the conformations of these licorice favonoid compounds that have the highest FitValue (lowest Estimate) when matched with the 10 models.Table 3 presents the activity prediction results of the 10 pharmacophore models for licorice favonoids.Among them, pharmacophore model 10 predicts an activity value of 1.77 μM for licochalcone B, and this compound exhibits good matching with all the feature elements of the model (Figure S7).Pharmacophore model 10 predicts an activity value of 786.13 μM for nobiletin, and this compound only partially matches the feature elements of the model (Figure S8).Additionally, retrochalcone, isoliquiritin, and isoliquiritigenin exhibit low predicted activity values, indicating that these compounds are key components of licorice favonoids in the antioxidant process.

Molecular Docking Verifcation.
To validate the predicted activity of the licorice favonoid compounds in antioxidant activity, molecular docking is used for confrmation.Table 4 displays the docking scores and docking energies of licochalcone B, retrochalcone, isoliquiritin, and isoliquiritigenin with the TYR (PDB: 7RK7) target protein.Te results demonstrate that these compounds exhibit docking scores above 90 when docked with the TYR target protein, indicating a strong binding afnity between these compounds and the target protein.Figure 7 displays the visualized molecular docking results of these active compounds with the target protein.It can be observed that the binding of these compounds with the target protein primarily occurs through hydrogen bonds, van der Waals forces, and π-π interactions, and the interaction groups are similar to the pharmacophore model.For example, the OH group on licochalcone B forms hydrogen bond interactions with the GLU amino acid residue on the TYR (PDB: 7RK7) target protein at distances of 2.19 Å and 3.02 Å (Figure 7(a)).
Te benzene ring of retrochalcone forms π-π interactions with the VAL and ARG amino acid residues on the TYR (PDB: 7RK7) target protein at distances of 4.81 Å and 3.80 Å, respectively (Figure 7(b)).Te benzene ring of isoliquiritin forms π-π interactions with the TRP amino acid residue on the TYR (PDB: 7RK7) target protein at distances of 4.45 Å and 5.08 Å, respectively (Figure 7(c)).Te functional groups on isoliquiritigenin interact with the VAL, CYS, and HIS amino acid residues on the TYR (PDB: 7RK7) target protein through van der Waals forces (Figure 7(d)).In addition, the pharmacophore model's active functional groups, such as benzene ring, OH, and C�O, derived from the training set, form hydrogen bond interactions with the amino acid residues of the TYR target protein.Tis phenomenon validates the rationality of the 3D QSAR pharmacophore model in predicting the antioxidant activity of licorice favonoids.

Molecular Electrostatic Potential (MEP) Analysis.
Molecular electrostatic potential (MEP) is an efective tool for predicting molecular interactions and reaction behavior between molecules.In this section, the MEP of licochalcone B, retrochalcone, isoliquiritin, and isoliquiritigenin will be used to predict the potential reactive functional groups of these compounds with free radicals.Te molecular structures of licochalcone B, retrochalcone, isoliquiritin, and isoliquiritigenin all contain common functional groups such as benzene rings, carbonyl groups, and hydroxyl groups.Among them, the hydroxyl group is a functional group composed of oxygen and hydrogen atoms, which appears in the molecule as an oxygen atom connected to a hydrogen atom and possesses certain oxidative and reductive abilities.Figure 8 shows the MEP distribution maps of licochalcone B, retrochalcone, isoliquiritin, and isoliquiritigenin.It can be observed that the MEP mapping range of charge density goes from the highest electron density (shown as the deepest red) to the lowest electron density (shown as the deepest blue).Te carbonyl groups on licochalcone B, retrochalcone, isoliquiritin, and isoliquiritigenin are regions with higher electron density and can act as electron-donating functional groups, making them prone to undergoing electrophilic reactions with free radicals.Te hydroxyl groups on licochalcone B, retrochalcone, isoliquiritin, and isoliquiritigenin are regions with the lowest electron density and can act as electron-accepting groups, making them prone to undergoing nucleophilic substitution reactions with free radicals.In addition, these functional groups are also the main active moieties in 3D QSAR and molecular docking.
3.6.Molecular Frontier Orbital Analysis.HOMO (highest occupied molecular orbital) and LUMO (lowest unoccupied molecular orbital) are the most important orbitals in molecular frontier orbital analysis.Tese orbitals determine the way molecules interact with other substances and play a crucial role in chemical reactivity.Te HOMO and LUMO orbitals of licochalcone B, retrochalcone, isoliquiritin, and isoliquiritigenin are shown in Figure 9.It can be observed that the -OH and C�O of the favone skeleton structure of these molecules exhibit higher activity in the HOMO and LUMO orbitals.For example, the -OH (5) on licochalcone B Journal of Food Biochemistry is distributed on the LUMO (Figure 9(a)).Te -OH (4) on retrochalcone, -OH (8, 9) on isoliquiritin, and -OH (2) on isoliquiritigenin are distributed in both the HOMO and LUMO orbitals.Tis phenomenon may be due to the conjugation and orbital overlap between the -OH, and the surrounding system [27] (Figures 9(b)-9(d)).Similarly, the C�O (4) on licochalcone B, C�O (3) on retrochalcone, and the C�O (7) on isoliquiritin are also distributed in both the HOMO and LUMO orbitals.Tis phenomenon may be attributed to the conjugation between the C�O on the favone skeleton structure and the neighboring phenyl ring, resulting in the rearrangement of electronic levels and contributing to both the HOMO and LUMO orbitals [28] (Figure 9(a)-9(c)).Tis phenomenon indicates that licochalcone B, retrochalcone, isoliquiritin, and isoliquiritigenin molecules may exert their antioxidant efects by undergoing        chemical reactions with free radicals through the C�O and OH functional groups on the favone skeleton structure.In addition, the energy gaps of licochalcone retrochalcone, isoliquiritin, and isoliquiritigenin are 2.46, 2.48, 2.42, and 2.34 eV, respectively (Figure 9).Tis result indicates that these compounds all possess certain chemical reactivity.Among them, isoliquiritigenin has the smallest energy gap, indicating that it may possess higher biological activity and play a crucial role in the antioxidant process.Terefore, further calculations will be conducted to explore the relationship between diferent licorice favonoid compounds and their antioxidant activities.

Analysis of Reaction-Free Energy of Licorice Flavonoids.
Although the above results demonstrate that licochalcone B, retrochalcone, isoliquiritin, and isoliquiritigenin have good antioxidant activity, the previous research conducted by the research team has revealed the structure-activity and doseresponse relationships between licorice favonoids and their antioxidant activity.However, the molecular mechanism regarding the impact of active groups at diferent positions on their antioxidant activity is still unclear.Terefore, this section will utilize DFT calculations to investigate the molecular mechanisms of antioxidant activity in licorice favonoids.Figure 10 illustrates that licorice favonoids eliminate free radicals through chemical reactions with hydroxyl free radicals in the hydrogen atom transfer (HAT) reaction path.Among them, hydroxyl free radicals are hydrogen-oxygen groups (OH) that contain an unpaired electron.Tey are highly reactive intermediates that can easily react with other molecules and participate in various biochemical processes and cellular signaling pathways.When there is an excessive amount of hydroxyl free radicals or when oxidative stress persists, it can lead to oxidative stress, resulting in cell damage and the occurrence of diseases.Table 5 displays the reaction-free energies between licochalcone B, isoliquiritigenin, retrochalcone, and isoliquiritin with hydroxyl free radicals under the HAT reaction path as determined by quantum calculations.It can be found that the reaction-free energy between the para-phenol hydroxyl group and hydroxyl radical on the left benzene ring structure of licochalcone B, isoliquiritigenin, retrochalcone, and isoliquiritin is lower than that of the ortho and metaphenol hydroxyl groups.Moreover, the reaction-free energy between the para-phenol hydroxyl group and hydroxyl radical on the left benzene ring structure is less than 0. Specifcally, the reaction-free energy of the para-phenol hydroxyl group (R-OH (3)) on the left side of licochalcone B's benzene ring is −2.53 kcal/mol, while the reactionfree energy of the meta-phenol hydroxyl group (R-OH (2)) on the same ring is 11.27 kcal/mol.Te reaction-free energy of the para-phenol hydroxyl group (R-OH (2)) on the left side of isoliquiritigenin's benzene ring is −1.29 kcal/mol, while the reaction-free energy of the ortho-phenol hydroxyl group (R-OH (1)) on the same ring is 27.31 kcal/mol.Te reaction-free energy of the para-phenol hydroxyl group (R-OH (2)) on the left side of retrochalcone's benzene ring is −6.30kcal/mol.Te reaction-free energy of the para-phenol hydroxyl group (R-OH (9)) on the left side of isoliquiritin's benzene ring is −11.49kcal/mol, while the reaction-free energy of the ortho-phenol hydroxyl group (R-OH ( 8)) on the same ring is −0.87 kcal/mol.Tis phenomenon indicates that the reaction-free energies in the HAT reaction path of the para-phenol hydroxyl groups on the same benzene ring structure of these licorice favonoid compounds are lower than those of the ortho and meta-phenol hydroxyl groups.Tis could be due to the following two   reasons: (1) Te presence of the para-phenol hydroxyl group can increase the electron density of favonoid compounds and enhance their electron afnity, resulting in a stronger ability scavenge free radicals.(2) Te para-phenol hydroxyl group is directly attached to the aromatic ring, which makes them more prone to interact with surrounding molecules, thereby increasing their efciency in capturing free radicals and transferring electrons [14,29].Terefore, this study suggests that the para-phenol hydroxyl groups on the same benzene ring structure of licorice favonoid compounds may play an important role in antioxidant activity.Tis indicates that the para-phenol hydroxyl group could be one of the key functional groups contributing to the antioxidant activity of favonoid compounds.

Conclusion
Tis study focuses on investigating the molecular mechanisms of antioxidant activity in licorice favonoids using pharmacophore theory and quantum computing.First, we used network pharmacology methods to screen for the main active components and key targets with antioxidant activity in licorice favonoids.Next, we employed pharmacophore theory to identify potential key structural features in licorice favonoids that may contribute to their antioxidant activity and validate them using molecular docking.Finally, we utilized quantum computing methods to calculate the electronic structure, orbital distribution, and related physicochemical properties of licorice favonoid molecules.Network pharmacology studies have shown that isoliquiritigenin, 4′-methoxyfavone, moslofavone, isoliquiritin, 7-hydroxyfavone, retrochalcone, nobiletin, corylin, licochalcone B, and licofavone A are the main active components responsible for the antioxidant activity of licorice favonoids.TYR has been identifed as the primary target of antioxidant activity for licorice favonoids.Te pharmacophore studies have shown that, compared to other pharmacophore models, pharmacophore 10 exhibits the highest correlation coefcient in predicting activity.Tis indicates that pharmacophore 10 has a high accuracy in predicting activity.In addition, licochalcone B, retrochalcone, isoliquiritin, and isoliquiritigenin have low IC50 predictive activity values, suggesting that these compounds are crucial components of licorice favonoids in antioxidant processes.Molecular electrostatic potential (MEP) studies have shown that hydroxyl groups on licochalcone B, retrochalcone, isoliquiritin, and isoliquiritigenin are the regions with the lowest electron density.Tese hydroxyl groups can act as electron acceptor groups and are prone to nucleophilic substitution reactions with free radicals.Molecular frontier orbital studies have shown that licochalcone B, retrochalcone, isoliquiritin, and isoliquiritigenin have energy gaps of 2.46, 2.48, 2.42, and 2.34 eV, respectively.Tis indicates that these compounds possess certain chemical reactivity.Quantum computing research has found that the reaction-free energy between the para-phenol hydroxyl group and hydroxyl radical on the core structure of licochalcone B, isoliquiritigenin, retrochalcone, and isoliquiritin is lower than that of the ortho and meta-phenol hydroxyl groups in the HAT reaction path.Te reaction-free energy between the para-phenol hydroxyl group and hydroxyl radical on the core structure is less than 0. Tis indicates that the para-phenol hydroxyl group is a crucial functional group for the antioxidant activity of favonoid compounds.In conclusion, this study successfully revealed the possible mechanism of action of licorice favonoids in the antioxidant process, providing some guidance for the synthesis of new antioxidant compounds.

Figure 3 :
Figure 3: Molecular structure of the test set composed of 18 tyrosinase inhibitors.

Figure 5 :
Figure 5: Matched heatmaps of the 10 pharmacophore models of the training set for each of the 18 test set molecules.

Figure 6 :
Figure 6: Matching of 10 pharmacophore models in the training set to each molecule of 10 licorice favonoids small molecules.

Table 1 :
Pubchem ID of 34 screened compounds with favonoid structure.
3.1.Network Pharmacology Analysis.Use Cytoscape_v3.8.2 software to generate a network diagram for the antioxidant activity of licorice favonoids, involving 166 nodes and 958

Table 3 :
10 Prediction of activity of 10 licorice favonoids by pharmacophore model.