Preliminary Exploration of Potential Active Ingredients and Molecular Mechanisms of Yanggan Yishui Granules for Treating Hypertensive Nephropathy Using UPLC-Q-TOF/MS Coupled with Network Pharmacology and Molecular Docking Strategy

Hypertensive nephropathy (HN) is a prevalent complication of hypertension and stands as the second primary reason for end-stage renal disease. Research in clinical settings has revealed that Yanggan Yishui Granule (YGYSG) has significant therapeutic effects on HN. However, the material basis and action mechanisms of YGYSG against HN remain unclear. Consequently, this study utilized a comprehensive method integrating ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS), network pharmacology, and molecular docking to delineate the active ingredients and potential therapeutic mechanisms of YGYSG for treating HN. Firstly, sixty distinct components were recognized in total as potential active ingredients in YGYSG by UPLC-Q-TOF/MS. Subsequently, the mechanisms of YGYSG against HN were revealed for the first time using network pharmacology. 23 ingredients played key roles in the complete network and were the key active ingredients, which could affect the renin-angiotensin system, fluid shear stress and atherosclerosis, HIF-1 signaling pathway, and AGE-RAGE signaling pathway in diabetic complications by regulating 29 key targets such as TNF, IL6, ALB, EGFR, ACE, and MMP2. YGYSG could treat HN through the suppression of inflammatory response and oxidative stress, attenuating the proliferation of renal vascular smooth muscle cells, lessening glomerular capillary systolic pressure, and ameliorating renal dysfunction and vascular damage through the aforementioned targets and pathways. Molecular docking results revealed that most key active ingredients exhibited a high affinity for binding to the key targets. This study pioneers in clarifying the bioactive compounds and molecular mechanisms of YGYSG against HN and offers scientific reference into the clinical application.


Introduction
Hypertension is the most prevalent cardiovascular disease and a primary cause of premature death worldwide [1].Tis condition is linked to organ damage, particularly in the kidneys [2].With progression, hypertension can lead to hypertensive nephropathy (HN), characterized by a spectrum of pathological alterations such as vascular remodeling, interstitial fbrosis, glomerular damage, fbrinoid necrosis, atherosclerosis, oxidative stress, and infammation [3,4].
According to existing research, an appropriate control of high blood pressure is a key strategy for treating HN [5].Te fve principal classes of antihypertensive drugs, including calcium antagonists, β-blockers, angiotensin-converting enzyme (ACE) inhibitors, thiazide diuretics, and angiotensin receptor blockers, are widely recognized for their efcacy in long-term management of hypertension [6].However, these medications are not without side efects, which may include hypokalaemia, bronchial asthma, and lower limb edema [7,8].Considering the swift global rise in HN cases and the constraints of current treatments, it is critically important to identify new medications that ofer efective therapeutic outcomes and minimal side efects.
It is common knowledge that prescriptions of traditional Chinese medicine (TCM) have pharmacological properties due to their multicomponent, multitarget, and multipathway and low side efects [9].Yanggan Yishui Granule (YGYSG) was developed by the famous expert in TCM Professor Yixuan Zhou from the First Hospital Afliated to Anhui University of Traditional Chinese Medicine after gaining extensive clinical experience and knowledge of herbal properties.YGYSG has been clinically applied to the HN for decades with remarkable curative efects, and previous studies of our research group have shown that it has the efects of improving proteinuria and protecting kidneys [10][11][12].Te formula includes Astragali Radix (ASR), Achyranthis Bidentatae Radix (ABR), Salviae Miltiorrhizae Radix et Rhizoma (SMR), Lycii Fructus (LYF), Euryales Semen (EUS), and Cuscutae Semen (CUS).Te detailed information is presented in Table 1.According to the ancient TCM theory, LYF is the monarch drug in YGYSG, which has the efect of nourishing liver and kidney.CUS, ASR, and EUS are the minister drugs in YGYSG.Tereinto, CUS has the efects of consolidating the essence and tonifying the liver and kidney; ASR has the efects of invigorating "qi," promoting "yang," and solidifying the surface; EUS has the efects of strengthening the kidney and stopping spermatorrhea.SMR is the assistant drug and has the efects of promoting blood circulation and eliminating blood stasis.ABR is also an assistant drug that guides blood to the lower parts of the body and enhances the nourishing liver and kidney functions of LYF.Nonetheless, the active constituents of YGYSG and the underlying mechanisms of its therapeutic efect on HN are yet to be completely elucidated.
Ultraperformance liquid chromatography-quadrupole time-of-fight mass spectrometry (UPLC-Q-TOF/MS) has become increasingly useful due to its advantages of sensitivity, high resolution, and throughput.Tese attributes facilitate the swift identifcation and characterization of target components, efectively addressing issues such as component complexity and quantifcation challenges inherent in TCM analysis [13].Network pharmacology is a promising approach in bioinformatics, systems biology, and polypharmacology owing to its cost-efectiveness in drug discovery.Its holistic theory closely aligns with that of the TCM theory [14].Te research process of network pharmacology mainly includes the identifcation of potential active ingredients, prediction of targets for drugs and specifc diseases, and the construction and analysis of TCM prescriptions-targets-diseases network [15].A large number of authoritative databases, such as TCMSP (Traditional Chinese Medicine System Pharmacology, https://old.tcmsp-e.com/tcmsp.php)[16], TCMID (Traditional Chinese Medicines Integrated Database, https://47.100.169.139/tcmid/)[17], BATMAN-TCM (Bioinformatics Analysis Tool for Molecular mechANism of TCM, https:// bionet.ncpsb.org/batman-tcm/)[18], and HERB (a highthroughput experiment-and reference-guided database of TCM, https://herb.ac.cn/) [19], are used to collect potential active ingredients in TCM prescriptions.Databases used for drug-target prediction mainly include SwissTargetPrediction (https://swisstargetprediction.ch/) [20], SEA (similarity ensemble approach, https://sea.bkslab.org/)[21], and Pharm-Mapper (https://www.lilab-ecust.cn/pharmmapper/index.html) [22].Databases used for disease-target prediction mainly include DisGeNET (https://www.disgenet.org/home/)[23], OMIM (Online Mendelian Inheritance in Man, https:// www.ncbi.nlm.nih.gov/omim)[24], and Drugbank (https:// go.drugbank.com/)[25].Cytoscape, a drug-target interaction prediction software [26], is usually used combined with the STRING database (Search Tool for the Retrieval of Interacting Genes/Proteins, https://cn.string-db.org/)[27] to screen key active ingredients and key targets.DAVID database (Database for Annotation, Visualization, and Integrated Discovery, https://David.ncifcrf.gov/)[28] is applied to further screen key signaling pathways.Ten, the network of TCM prescriptionskey active ingredients-key targets-key signaling pathwaysdiseases is constructed by Cytoscape to preliminarily elucidate the molecular mechanisms of TCM prescriptions for treating diseases.Molecular docking is capable of assessing the dependability of outcomes predicted by network pharmacology through analyzing the binding modes and binding forces between drugs and targets [29].Tis fusion of network pharmacology and molecular docking technology has gained widespread application in elucidating molecular mechanisms in TCM formulas in recent years.Ming's team delved into the mechanisms of the Longchai Jiangxue formula involved in treating polycythemia vera by using UPLC/Q-TOF-MS/MS alongside network pharmacology and molecular docking [30].Similarly, Duan's group investigated the antibacterial properties and active components of tea-seed oil through the combined application of UPLC-Q-TOF/MS, network analysis, and molecular docking [31].
In this regard, the present study employed an integrated and comprehensive strategy that combined UPLC-Q-TOF/ MS coupled with network pharmacology and molecular docking to investigate the potential active ingredients and mechanisms underlying the curative efects of YGYSG in the treatment of HN.An optimized UPLC-Q-TOF/MS method was initially utilized to scrutinize the active components within YGYSG.Next, the network of YGYSG-key active ingredients-key targets-key pathways was constructed to uncover the potential mechanisms of YGYSG for treating HN using network pharmacology technology.Molecular docking was then utilized to substantiate the network pharmacology fndings.Tis study lays a foundational theory for the development and clinical application of YGYSG. Figure 1 displays a fowchart representing this study.

Preparation of YGYSG Sample Solutions and Reference
Compound Solutions.Regarding sample preparation, the dried herb samples were ground into uniform powders using a mill.Te decoction piece powder of ASR (2 g), ABR (1 g), EUS (1 g), LYF (1 g), SMR (1 g), and CUS (1 g) were accurately weighed and mixed well.Precisely weighed herbal sample powder was dipped into a 200-mL glass-stoppered conical fask containing 140 mL 70% (v/v) methanol.Te herbs were precisely and accurately weighed and subjected to ultrasonic extraction for 60 min at 25 °C.During this process, to compensate for the loss of solvents, additional 70% (v/v) methanol was employed.After extraction, centrifugation of the extracts occurred at a speed of 13000 rpm for a duration of 15 minutes.Te produced supernatants underwent fltration with a 0.22-μm cellulose membrane flter prior to UPLC-Q-TOF/MS analysis.
For each of the 27 reference standards, stock solutions (around 2 mg/mL concentration) were concocted by dissolving close to 4 mg of every compound in 2 mL of 70% methanol.Subsequently, specifc quantities of the aforementioned 27 reference compound stock solutions were combined to create the reference compound mixture working solution, resulting in an approximate concentration of 71.43 μg/mL per reference compound.Prior to analysis, the reference compound mixture working solution was fltered through a 0.22-μm cellulose membrane flter followed by storage at 4 °C.
A Waters SYNAPT G2-Si QTOF mass spectrometer ftted with an electrospray ionization (ESI) source (Waters MS Technologies, Manchester, UK) was used for the mass spectrometry analysis.Q-TOF-MS analysis was performed in the negative ion mode, and the parameters of mass spectrometry were as follows: source temperature, 120 °C; capillary voltage, 2.5 kV; collision energy, 30-60 V; desolvation temperature, 450 °C; cone voltage, 40 V; cone gas fow rate, 50 L/h; desolvation gas fow rate, 900 L/h; scan time, 0.2 s; and scan range, 50-1500 Da.Te reference lock mass used was the [M − H] − ion of leucine enkephalin (m/z 554.2615).

Target Acquisition of YGYSG and HN.
Te active constituents in YGYSG were characterized by UPLC-Q-TOF/ MS to assist in network pharmacological studies.Te SEA Search Server database (https://sea.bkslab.org/),Swiss target prediction database (https://swisstargetprediction.ch/), and PharmMapper database (https://www.lilab-ecust.cn/pharmmapper/) were used in the prediction of targets of the active ingredients.PubChem database (https://pubchem.ncbi.nlm.nih.gov/)provided the required compounds for the Swiss target prediction database and the SEA Search Server database in the SMILES format.Probable targets were identifed according to the standard SMILES structure, limited to those annotated as "Homo sapiens," and only the results with probability >0 were included.Disease-targets for "hypertensive nephropathy" were curated from the Drug-Bank database (https://go.drugbank.com/),OMIM database (https://www.omim.org/),and DisGeNET database (https:// www.disgenet.org/),with human genes as a reference.All active ingredients-targets and disease-targets were standardized to gene symbols through the UniProt database (https://www.uniprot.org/),and duplicate values were removed.Finally, the common targets between the active components and diseases were considered potential targets of YGYSG for treating HN, as depicted in a Venn diagram.

Construction of Potential Active Ingredients-Targets
Network and Screening of Key Active Ingredients.Te common targets of components and disease, and potential active ingredients were introduced into Cytoscape 3.7.1, and the network of potential active ingredients-targets was constructed.Te "Tools analysis network" feature in Cytoscape was used to screen the key active ingredients of YGYSG for HN based on the topological data, which include degree, closeness centrality (CC), and betweenness centrality (BC).org/) for the creation of a protein-protein interaction (PPI) network.Only protein interactions with a confdence level of >0.4 were considered.After sorting the protein interaction data, the information was prepared in a table format.Cytoscape 3.7.1 was used to analyze the common targets in the PPI network by applying three diferent analytical parameters such as degree, BC, and CC to discern key targets.Key targets, evaluated using various algorithms, were screened based on the parameter value greater than the median of three parameters, and the ultimate key targets were acquired through integration.

GO Function and KEGG Pathway Enrichment Analysis of
Key Targets.For a comprehensive bioinformatics analysis, the key targets of YGYSG and HN were inputted into the DAVID database (https://David.ncifcrf.gov/)for annotation visualization and integrated discovery.Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotations of the key targets of YGYSG for treating HN were performed.Te terms "Gene ofcial symbol" and species "Homo sapiens" were chosen, and a P value under 0.05 was considered a marker of statistical importance.In addition, the top 20 signaling pathways were considered key pathways.

Construction of YGYSG-Key Active Ingredients-Key
Targets-Key Pathways Network.To analyze the association among HN, the key active ingredients of YGYSG, the key targets, and the key signaling pathways, a network of YGYSG-key active ingredients-key targets-key pathways was constructed by Cytoscape 3.7.1.

Molecular Docking.
Te dependability of the outcome from network pharmacology was further verifed through molecular docking techniques.Te three-dimensional confgurations of the top 10 key active ingredients in YGYSG were obtained from the PubChem database (https:// pubchem.ncbi.nlm.nih.gov/).Subsequently, the molecular structures of the top 10 key targets from the PPI network were retrieved from the RCSB PDB database (https://www.rcsb.org/).Te protein receptors were then imported into AutoDockTools version 1.5.7 by adding hydrogen atoms, assigning charges, and removing water molecules.Te AutoDock Vina software program was utilized to perform molecular docking, wherein the afnity of the ligands and protein receptors, the stability of the ligand-receptor binding, and the energy value of the binding process were evaluated.Visualization of the molecular mocking outcomes was achieved using PyMOL software.A docking was considered successful and valid if the binding free energy was at or below −5.0 kcal/mol.

Identifcation of Chemical Constituents in YGYSG by
UPLC-Q-TOF/MS.UPLC-Q-TOF/MS analysis was employed to delineate the chemical constituents of YGYSG.Te total ion current (TIC) plots of YGYSG in negative ion  modes are exhibited in Figure 3. Out of 60 identifed compounds (identifed as 1-60), 27 were clearly determined by contrasting their retention times and precise masses against the reference standards.Te remaining samples were tentatively assigned by aligning their empirical molecular formulas and characteristic fragment ions with those found in existing published compounds from similar studies .Te chromatographic behaviors of certain chemical constituents served as additional information for pinpointing the isomers.Detailed structural identifcation of these components of YGYSG is presented in Table 2.

Acquisition of Potential Active Ingredients and HN
Targets.Upon identifying 60 compounds as potential active constituents, a comprehensive analysis yielded 1683 compoundrelated targets postduplication removal.Ten, from the three specifed online databases, a sum of 474 targets related to HN was amassed after removing duplication, which were further overlapped with the probable targets of the active ingredients in YGYSG.Tis resulted in the identifcation of 91 overlapping targets, posited as candidates for the treatment of HN.Te intersection of YGYSG and HN targets is depicted in a Venn diagram (Figure 4).

Construction of Potential Active Ingredients-Targets
Network and Screening of Key Active Ingredients.Te network of potential active ingredients-targets (Figure 5) with 157 nodes and 803 edges was developed using Cytoscape 3.7.1.Network topology analysis revealed 23 components, including chikusetsusaponin IVa, ginsenoside Ro, soyasaponin I, and astragalin, which exhibited degree values, BC, and CC above the median (Table 3).Tese components are likely key active ingredients in YGYSG for treating HN and demonstrate the synergistic efect inherent in TCM.

Construction of PPI Network and Screening of Key Targets.
Te 91 common targets of YGYSG and HN were integrated into the STRING database to generate a PPI network with 86 nodes and 543 edges (Figure 6(a)).Cytoscape 3.7.1 was employed to delve deeper into how targets interacted.As a target's degree increases, so does its node size and the intensity of its color (Figure 6(b)).With the help of a network analysis function, the target genes greater than the median of degree value (>8.5),BC (>0.006297), and CC (>0.4439) were considered key targets.29 targets met these criteria, suggesting their potential role in treating HN (Figure 6(c)), which includes tumor necrosis factor (TNF), interleukin-6 (IL6), ACE, albumin (ALB), and epidermal growth factor receptor (EGFR), among others.Topological information of key targets in the YGYSG for treating HN is shown in Table 4.

GO Function and KEGG Enrichment Analyses of Key
Targets.Further analysis of the 29 key targets identifed 279 GO functional enrichment analyses and 84 KEGG pathway enrichments.Te gene ontology (GO) study covered 215 biological mechanisms, 31 cellular elements, and 33 molecular activities.Figure 7(a) displays the leading 10 GO terms for every category.Te top 10 GO terms for each category are presented in Figure 7(a).Notably, the leading ten biological processes were the positive regulation of the apoptotic process, positive regulation of smooth muscle cell proliferation, response to xenobiotic stimulus, and positive regulation of infammatory response.Te main cellular components included the extracellular space, plasma membrane, and extracellular region.Te main molecular functions included transcription regulatory region sequence-specifc DNA binding, identical protein binding, and endopeptidase activity.Te main pathways involved were the AGE-RAGE signaling pathway in diabetic complications, HIF-1 signaling pathway, fuid shear stress and atherosclerosis, and renin-angiotensin system (Figure 7(b)).

Construction of YGYSG-Key Active Ingredients-Key
Targets-Key Pathways Network.Te KEGG pathway enrichment results enabled the construction of a network diagram of YGYSG-key active ingredients-key targets-key pathways (Figure 8), mapping the relationships between 29 protein targets, 23 potential bioactive compounds, and 20 signaling pathways.Tis network diagram serves as a foundational model for understanding the therapeutic mechanisms of YGYSG in the treatment of HN.

Discussion
Te current understanding of modern medicine identifes the activation of the renin-angiotensin system, vascular endothelial dysfunction, oxidative stress, and infammation as central pathological processes in HN.It is a high-burden disorder and ranks as the second primary reason for terminal renal disease [53].Given these circumstances, the discovery of safe and efective treatments for patients with HN is critical.YGYSG is benefcial for HN, as established by prior research.Employing a combination of UPLC-Q-TOF/ MS, network pharmacology, and molecular docking validation, this study explored the potentially efective ingredients and mechanisms of YGYSG in the amelioration of HN.Initially, UPLC-Q-TOF/MS was used to profle the chemical constituents of YGYSG, identifying 60 components.Te investigation revealed that YGYSG comprises 23 key active ingredients for treating HN, predominantly favonoids, saponins, and phenolic acids.Further analysis involving the PPI network, KEGG pathway enrichment, and the network of YGYSG-key active ingredients-key targetskey pathways indicated that these active ingredients likely confer therapeutic efects through the modulation of 29 key targets and 20 key signaling pathways.An increasing amount of evidence suggests a signifcant link between infammation and hypertension.Chronic kidney disease features heightened levels of pro-infammatory cytokines, including IL-1, IL-6, and TNF-α [54].TNF-α, a proinfammatory cytokine, is a pathogenic factor implicated in renal injury by inducing apoptosis of renal epithelial cells and exacerbating infammation, which further aggravates renal damage.Moreover, TNF-α has a direct cytotoxic infuence on glomerular cells, mesangial cells, and renal epithelial cells [55].IL-6, a multifunctional cytokine, plays a role in managing acute phase reactions, hematopoiesis, cellular regeneration, and immune responses [56].Te induction of IL-6 by TNF-α contributes to oxidative stress and infammation and the subsequent deterioration of renal tissue [57].Chikusetsusaponin IVa is an active ingredient in ABR and exerts antiinfammatory properties by downregulating infammatory factors such as TNF-α and IL-6 [58].Ginsenoside Ro, an    2.  Journal of Analytical Methods in Chemistry oleanolic saponin of ABR [59], has been demonstrated to inhibit the infammatory response caused by TLR4 [60].Chlorogenic acid, a phenolic acid derived from LYF, SMR, and CUS, signifcantly reduces the levels of TLR4, IL-1β, and TNF-α and renal infammation [61].Ferulic acid, a common plant-based phenolic acid, has renal-protective efects through its antioxidant, anti-infammatory, lipid-lowering, antifbrotic, antiapoptotic, and autophagy-inducing properties [62].Teoretical approaches such as molecular docking have confrmed that ferulic acid inhibited TNF-α and IL-6 at the structural level.Consequently, the presence of ferulic acid in YGYSG could potentially hinder the development and progression of HN by dampening the infammatory response.

Journal of Analytical Methods in Chemistry
Oxidative stress is crucial in the pathology of vascular and renal infammation, serving both as a catalyst and as a byproduct of infammatory responses [63].Vanillic acid is a phenolic acid identifed from LYF, SMR, and ASR in this study and has the efect of improving systolic blood pressure [64].Early study has shown that vanillic acid signifcantly inhibits the activity of oxidative stress markers in kidney tissue [65].Ginsenoside Ro is a crucial ingredient in augmenting the protection of renal function within ABR, exhibiting pharmacological benefts through antiapoptotic and antioxidant activities [66].NFE2L2 is a potential druggable target that can alleviate various redox-induced tissue damage by boosting its activity [67].Formononetin, one of the main active ingredients in ASR, inhibits the excessive production of reactive oxygen species (ROS) and reduces oxidative damage by upregulating the expression of NFE2L2 [67].Oxidative stress, alongside matrix metalloproteinase (MMP) activity, is present in the cardiovascular system during hypertension, contributing to cardiac myocyte hypertrophy and dysfunction.Quercetin, a favonoid, suppresses the MMP-2 activity, thereby mitigating hypertrophic vascular remodeling associated with hypertension [68].Additionally, the accumulation of AGE can accelerate during oxidative stress.Te activation of RAGE by AGEs results in the creation of ROS and amplifes infammation, contributing to the progressive alteration in renal structure and loss of renal function [69].AGEs also bind to RAGE, activating the HIF-1 signaling pathway [70].HIF-1, a central regulator of cellular response to hypoxia, is implicated in various kidney pathologies, including renal fbrosis [71].HIF-1 signaling pathway is linked with the progression of chronic kidney injury.It has been proposed that kidney injury may be improved by inhibiting the HIF-1 signaling pathway [72,73].
Activation of the renin-angiotensin system is recognized as a signifcant pathological factor contributing to HN. Inhibiting this system has been efective in mitigating renal dysfunction and vascular damage [74].ACE, crucial in the renin-angiotensin system [75], manages blood pressure through the transformation of angiotensin I into angiotensin II (Ang II).Suppressing the ACE activity results in a reduction of Ang II production, thereby causing vasodilation and lowered blood pressure, and the antihypertensive efect of ASR was realized in this way [76].Moreover, Ang II directly impacts the cells of renal vascular smooth muscles, wherein it induces vasoconstriction of both eferent and aferent renal arterioles, causing both increased glomerular pressure and decreased renal blood fow.Tis also increases the sensitivity of the tubuloglomerular feedback within the kidneys [5].Soyasaponin I, a bioactive compound present in ASR, belongs to the triterpene saponins.Earlier research has verifed that soyasaponin I was a natural inhibitor of renin and showed inhibitory efects on the renin-angiotensin system [77].Cafeic acid, with its diverse pharmacological efects, which include antioxidant, anti-infammatory, and antihypertensive activities [78], notably inhibits ACE, further infuencing the renin-angiotensin system.Cafeic acid is notable for its capacity to diminish the ACE activity, a crucial bioactive compound in the renin-angiotensin system.Furthermore, studies have shown that cafeic acid can lower systolic blood pressure and attenuate the proliferation of vascular smooth muscle cells [79].
Simultaneous chronic hypertension may lead to the thickening of the intima and narrowing of the lumen in renal arteries and arterioles, as well as tubular atrophy, interstitial fbrosis, and glomerulosclerosis, which usually indicate the occurrence of hypertensive nephropathy [80].Consequently, HN may progress into a distinct clinical entity known as atherosclerotic nephropathy.Fluid shear stress and atherosclerosis is the crucial pathway of inhibiting infammation, vasodilation, and anti-atherosclerosis [81].Shear stress from regions of disease causes the expression and deposition of fbronectin via the infammatory transcription factor NF-κB activation, thus establishing a proinfammatory positive feedback loop that sustains infammation in atherosclerotic lesions [82].Terapeutically, disrupting this loop could prove benefcial in treating HN by decelerating the progression of atherosclerosis.
EGFR activation is linked to damage and loss of podocytes, specialized cells critical for kidney function, while the deletion of EGFR in podocytes mitigates glomerular injury and ofers protection against kidney damage in the context of diabetic nephropathy [83].ALB ranks as the predominant protein found in human blood.Notably, urinary ALB has been identifed earlier as a contributing factor to the development of hypertensive nephrosclerosis [84].Lower ALB levels are associated with decreased activity of transforming

Conclusions
As far as we are aware, this is the frst study to reveal the bioactive compounds and molecular mechanisms of YGYSG in the treatment of HN based on a comprehensive research strategy of UPLC-Q-TOF/MS coupled with network pharmacology and molecular docking.Trough this approach, 60 potential active ingredients within YGYSG, including 19 phenolic acids, 15 saponins, 13 favonoids, 3 fatty acids, 2 sterones, 2 quinones, and 6 other compounds, were detected for the frst time using UPLC-Q-TOF/MS.Further analysis deemed 23 of these constituents as key active ingredients of YGYSG against HN.Tese key active ingredients were suggested to mitigate infammation and oxidative stress, curtail the proliferation of renal vascular smooth muscle cells, decrease the glomerular capillary systolic pressure, and improve the renal dysfunction and vascular injury by acting on the 29 key targets including TNF, IL6, ALB, EGFR, ACE, and MMP2, involving the fuid shear stress and atherosclerosis, HIF-1 signaling pathway, renin-angiotensin system, and AGE-RAGE signaling pathway in diabetic complications.Molecular docking has confrmed a strong afnity between nearly all key active ingredients and key targets.Tis study lays the groundwork for the future targets Potential targets for the treatment of HN Construction of PPI network GO and KEGG analysis

Figure 1 :
Figure 1: Flowchart of this current study.

Figure 2 :
Figure 2: Chemical structures of the 27 reference standards used in this study.

Figure 9 (
a) illustrates the docking specifcs for each target along with the associated free energy expenses.Most of all possess great binding afnity, with binding energies of less than −7.0 kcal/mol.Tese results suggest that nearly all key active ingredients and targets have the ability to bind naturally, showing considerable afnity.Te representative molecular docking interactions of six groups were visualized using PyMOL software 6 Journal of Analytical Methods in Chemistry (Figures 9(b)-9(g)), highlighting the predominant hydrogen bond interactions.For instance, the docking simulation of zingibroside R1 with ACE (Figure 9(b)) demonstrates the establishment of fve hydrogen bonds between the ligand and residues of LYS-118, THR-92, LEU-122, ALA-125, and ARG-124.

Figure 3 :
Figure 3: Representative total ion current chromatograms of the reference standards (a) and the samples of YGYSG (b) in the negative ion mode.Te sequence of the reference standards (S1-S27) is consistent with Figure 2. Te sequence of the identifed ingredients (1-60) is in conformity with Table2.

Figure 4 :
Figure 4: Venn diagram of the common targets of YGYSG and HN.

Figure 5 :
Figure 5: Network construction of the potential active ingredients-targets of YGYSG in the treatment of HN.Triangles represent the TCMs of YGYSG, parallelograms depict the exclusive active components of diferent TCMs, hexagons represent the common active compounds of these TCMs, diamonds symbolize the targets, and blue acronyms represent the gene name of the targets.

Figure 6 :
Figure 6: Key targets obtained from PPI network analysis.(a) Target interaction in the STRING database.(b) PPI network of YGYSG in the treatment of HN.(c) Key targets of YGYSG in the treatment of HN.Each node represents a target in the PPI network, and each edge indicates the interaction between adjacent nodes.Te greater the number of adjacent nodes, the greater the probability of becoming a key target.
apoptotic process response to xenobiotic stimulus positive regulation of inflammatory response positive regulation of chemokine production negative regulation of apoptotic process positive regulation of nitric oxide biosynthetic process positive regulation of sequence-specific DNA binding transcription factor activity

Figure 7 :
Figure 7: GO function analysis (a) and KEGG pathway analysis (b) of the key targets of the YGYSG in the treatment of HN.

Figure 8 :
Figure 8: Network construction of the YGYSG-key active ingredients-key targets-key pathways of YGYSG against HN. Green triangles represent the TCMs of YGYSG, purple parallelograms symbolize the unique key active ingredients of various TCMs, red hexagons denote the common key active ingredients of these TCMs, blue diamonds represent the key targets, orange V shapes represent the key pathways, and yellow circles represent HN.

Figure 9 :
Figure 9: Molecular docking results of top 10 key active ingredients and key targets of YGYSG against HN.(a) Heatmap of the docking scores of top 10 key active ingredients and key targets of YGYSG.Molecular docking diagram of (b) zingibroside R1 with ACE, (c) chikusetsusaponin IVa with IFNG, (d) soyasaponin I with ACE, (e) kaempferol with TNF, (f ) quercetin with ALB, and (g) ferulic acid with EGFR.

Table 1 :
Information on the composition of YGYSG.
*Te chemical constituents unambiguously identifed with reference standards comparison.

Table 3 :
Topological information of key active ingredients in the YGYSG for treating HN.

Table 4 :
Topological information of key targets in the YGYSG for treating HN.