Abstract Cisplatin-induced acute kidney injury (AKI) poses a significant clinical challenge lacking specific therapeutic drugs. Arundina graminifolia, a traditional Dai medicine, exhibits notable renoprotective effects; however, its in vivo pharmacodynamic material basis and molecular mechanisms remain unclear. This study aimed to explore its mechanisms against AKI from the perspective of authentic kidney-migrating components. A cisplatin-induced mouse AKI model was established to evaluate the renoprotective effects of the A. graminifolia extract (BYJ) via biochemical markers and histopathology. UPLC-Q-TOF-MS/MS was employed to comparatively analyze the blood and kidney-migrating components between normal and AKI mice. Network pharmacology and molecular docking were subsequently applied to predict and validate the core signaling pathways based on the specific components detected in the injured kidneys. Results showed that BYJ administration significantly ameliorated renal dysfunction, restored antioxidant capacity, and alleviated tubular necrosis. MS analysis identified 93 chemical components in vitro. In vivo tracking revealed a “pathological targeted recruitment” characteristic: only 6 prototype components entered normal kidneys, whereas 16 prototypes penetrated the AKI kidneys, highly enriched in lipophilic flavonoid aglycones such as kaempferol and apigenin. Network pharmacology predicted that these targeted components could potentially interact with 124 key targets (including AKT1, PIK3CA, and EGFR) to putatively exert anti-apoptotic and anti-inflammatory effects via the PI3K-Akt, TNF, and MAPK pathways. Molecular docking confirmed excellent binding affinities between these aglycones and core target proteins (e.g., kaempferol with PIK3CA at −8.9 kcal/mol). Based on actual in vivo distribution, this study reveals the specific accumulation of polyhydroxy flavonoid aglycones in injured kidneys, providing a reliable scientific basis for defining the pharmacodynamic substances of A. graminifolia. 1. Introduction Acute kidney injury (AKI) is a severe clinical emergency characterized by a rapid decline in renal function, leading to the rapid accumulation of metabolic waste products and severe fluid and electrolyte imbalances, with a persistently high mortality rate, which remains between 20% and 50% depending on the clinical setting and severity of the injury, even reaching over 50% in critically ill patients requiring renal replacement therapy [ 1, 2]. Among the numerous pathogenic factors contributing to AKI, drug-induced nephrotoxicity accounts for a significant proportion, with cisplatin-induced kidney injury being particularly typical and challenging [ 3, 4]. Cisplatin, a first-line broad-spectrum chemotherapeutic agent for various solid tumors, is specifically taken up and accumulated by organic cation transporters (OCTs) located on the basolateral membrane of renal tubular epithelial cells during its metabolism in vivo. Such high-concentration accumulation directly damages mitochondrial DNA, disrupts the mitochondrial respiratory chain, and triggers an explosive burst of reactive oxygen species (ROS). Excessive ROS not only causes lipid peroxidation of cell membranes but also activates pro-inflammatory signaling pathways, such as nuclear factor-kappa B (NF-κB) and mitogen-activated protein kinases (MAPK), promoting the release of inflammatory cytokines including tumor necrosis factor-alpha (TNF-α) and interleukin-1 beta (IL-1β) [ 5]. This cascade of reactions ultimately leads to extensive apoptosis and necrosis of renal tubular epithelial cells, resulting in irreversible renal tissue damage. Although the nephrotoxicity of cisplatin is widely recognized, there are currently no approved targeted therapeutic drugs for its prevention and treatment. Clinical management primarily relies on aggressive hydration and symptomatic supportive care. Therefore, identifying active components from natural products capable of intervening in oxidative stress and apoptosis through multiple targets and pathways is of significant clinical importance for the development of anti-AKI drugs. Arundina graminifolia ( D. Don) Hochr. (commonly known as bamboo orchid) is a perennial herb of the Orchidaceae family, with a long history of use in the medical systems of ethnic minorities in China (e.g., the Dai people). In the traditional Dai medical theory of “Ya-Jie” (detoxification), A. graminifolia is considered a key medicinal herb with heat-clearing, detoxifying, and blood-stasis-resolving properties, traditionally used to treat animal and plant poisoning, heat toxins, and nephritic edema [ 6, 7]. Modern phytochemical studies have shown that A. graminifolia contains a variety of secondary metabolites, mainly including stilbenoids (e.g., resveratrol, pterostilbene), flavonoids (e.g., Quercetin-3-O-rutinoside, quercetin, kaempferol), and phenanthrene derivatives [ 8, 9]. Previous in vitro cellular and in vivo animal experiments have demonstrated that the extracts and some monomeric components of A. graminifolia possess significant free radical scavenging, anti-inflammatory, and target organ protective biological activities against oxidative damage [ 10]. However, current research on A. graminifolia intervening in renal injury mainly focuses on the overall pharmacodynamic observation of the extract or in vitro evaluation of single components. The actual pharmacodynamic material basis and multi-target regulatory network responsible for its anti-AKI effects in vivo remain to be systematically elucidated. Elucidating the pharmacodynamic material basis of traditional Chinese medicine (TCM) and ethnomedicine is critical for realizing their modernized application. Traditional material basis research often focuses on the identification and isolation of chemical components in vitro. However, upon oral administration, highly abundant in vitro components (e.g., macromolecular flavonoid glycosides) are often hindered by their large molecular weight and high polarity, leading to restricted gastrointestinal absorption or extensive biotransformation mediated by gut microbiota and hepatic enzymes. Therefore, high-abundance components in vitro may not necessarily enter the bloodstream directly, let alone cross the vascular endothelial barrier to distribute to the target lesion tissue. In recent years, network pharmacology, as an emerging systems biology tool, has been widely applied to predict the multi-target mechanisms of TCM interventions in diseases. Nevertheless, in practical applications, conventional network pharmacology analysis often directly uses all the components identified in vitro as the basis for target prediction, without considering the absorption, distribution, metabolism, and excretion (ADME) processes of the drugs in vivo. Such “static prediction” lacking pharmacokinetic data support is prone to introducing interference from unabsorbed components, leading to predicted results that deviate from the true in vivo mechanism of action, resulting in a high “false positive” rate. Based on the above background, a more rigorous research strategy involves comprehensively integrating in vivo pharmacokinetic distribution with network pharmacology. High-resolution liquid chromatography-tandem mass spectrometry (e.g., UPLC-Q-TOF-MS/MS), owing to its extremely high sensitivity and resolution, has become an effective tool for profiling trace migrating components of TCM in vivo. Therefore, this study aims to systematically investigate the pharmacodynamic material basis and mechanism of action of A. graminifolia against cisplatin-induced AKI from the perspective of the actual components distributed into the kidney in vivo. In this study, a cisplatin-induced mouse AKI model was first established to evaluate the protective effect of A. graminifolia extract (BYJ) on impaired renal function. Secondly, UPLC-Q-TOF-MS/MS technology was employed to comparatively analyze the differences in blood-absorbed and kidney-distributed components between normal mice and AKI model mice, exploring the distribution patterns of BYJ active components locally in the injured kidney. Finally, strictly based on the migrating components actually detected in the injured kidney of AKI mice, combining network pharmacology analysis and computer-aided molecular docking, the key targets and potential signaling pathways involved in its intervention against cell apoptosis and inflammatory responses were investigated. This study not only provides objective experimental data to elucidate the true pharmacodynamic material basis of A. graminifolia against AKI but also offers reference and validation for mechanism research of TCM and ethnomedicine based on actual in vivo distribution characteristics. 2.1. In Vitro Chemical Composition Identification of A. graminifolia To comprehensively characterize the chemical composition of the BYJ extract, UPLC-Q-TOF-MS/MS was employed. The total ion chromatograms (TIC) in positive and negative ion modes are presented in Figure 1B and Figure 1C, respectively. During the data processing stage, common endogenous primary metabolites (e.g., amino acids, basic lipids) were excluded to focus on potentially bioactive secondary metabolites, thereby establishing a foundation for tracking in vivo migrating components. Based on comparisons with reference standards, exact molecular weights (mass error 0.1 was applied as the threshold to acquire highly credible potential targets. Submitting these structures to SwissTargetPrediction yielded 379 potential drug targets. Intersecting these with 2640 AKI-related disease targets (retrieved from GeneCards, DisGeNET, and OMIM) resulted in 124 overlapping target genes ( Figure 12A). 2.5.2. “Disease-Pathway-Target-Component” Multi-Dimensional Network Topological Analysis An interaction network was constructed using Cytoscape ( Figure 12B). Compounds ranking high in degree values primarily included kaempferol, apigenin, isorhamnetin, Sinensetin and (Z)-5,8,11-trihydroxyoctadec-9-enoic acid. The polyhydroxy structural features of these flavonoids confer superior ROS scavenging abilities, helping block the oxidative stress cascade in renal tubules. The most significantly affected key targets included AKT1, PIK3R1, EGFR, PIK3CA, and PIK3CB, suggesting that BYJ’s core mechanism likely involves combating tubular cell apoptosis. 2.5.3. GO and KEGG Pathway Enrichment Analysis GO enrichment analysis ( Figure 12C) showed that biological processes (BP) were concentrated in the positive/negative regulation of apoptosis, inflammatory response regulation, and oxidative stress response, highly consistent with the in vivo phenotypic improvements. KEGG pathway analysis ( Figure 12D) further confirmed that the core signaling cascades were highly enriched in the PI3K-Akt signaling pathway (hsa04151), the TNF signaling pathway (hsa04668), and the MAPK signaling pathway (hsa04010). 2.5.4. Computer-Aided Molecular Docking Verification To validate the binding capacity between BYJ’s core active components and key AKI targets at the spatial structure level, the top 5 core components were docked against 5 key kinase targets. As shown in Figure 13, the binding energies were all below −5.3 kcal/mol, demonstrating excellent molecular recognition and spatial matching. Flavonoid components (apigenin and kaempferol) performed exceptionally well, with binding energies generally ranging from −7.3 to −8.9 kcal/mol against AKT1, EGFR, and PI3K family proteins. Notably, the binding energy of kaempferol with PIK3CA reached −8.9 kcal/mol, and apigenin with AKT1 was −8.1 kcal/mol. These polyhydroxy flavonoids can stably anchor within the active pockets of target kinases, forming robust hydrogen bonds and hydrophobic networks with surrounding amino acid residues, providing thermodynamic structural validation for the network predictions. To further elucidate the binding mechanisms, we analyzed the detailed spatial interactions between the core components and their targets using 2D interaction diagrams. Notably, the flavonoid skeleton of kaempferol anchored deeply into the active pocket of PIK3CA primarily through robust π-interactions (such as π-alkyl and π-π stacking) with key residues including Tyr167, Leu752, Ala758, Arg662, and Pro757. Additionally, extensive van der Waals forces with surrounding residues (e.g., Tyr260, Asp258, and Gln661) further stabilized the complex, contributing to its exceptional binding affinity (−8.9 kcal/mol). Similarly, apigenin exhibited a high affinity (−8.1 kcal/mol) for AKT1. The interaction analysis revealed that apigenin formed a critical conventional hydrogen bond with the Ala390 residue. Furthermore, it engaged in strong π-interactions with Lys389, Leu347, and Gln344, supplemented by a broad network of hydrophobic contacts with residues such as Met388, Phe363, and Ser359 ( Figure 13). 3. Discussion 3.1. Specific Molecular Recruitment Characteristics in the Injured Kidneys The pharmacodynamic results of this study indicated that the BYJ extract effectively ameliorated cisplatin-induced renal failure and microscopic histological damage. To identify the specific molecules exerting renoprotective effects locally at the lesion, this study employed high-sensitivity UPLC-Q-TOF-MS/MS to trace the in vivo distribution rules of the exogenous components. In traditional cognition, the tissue distribution of small-molecule drugs mainly depends on organ blood flow and their own lipophilicity. However, this study observed a significant dynamic shift in distribution: under normal physiological conditions, the renal microvascular barrier exerted non-specific filtration, allowing only trace amounts of 6 BYJ prototype components to be taken up; yet, in the cisplatin-induced AKI pathological state, the number of prototype components entering the kidneys significantly increased to 16. This regional chemotaxis and accumulation phenomenon of specific drug molecules highlights a distribution characteristic of “Pathological Targeted Recruitment.” This phenomenon is likely determined synergistically by the specific pathological microenvironment of AKI and the physicochemical properties of the molecules. Cisplatin’s toxic attack causes renal microcirculatory impairment and abnormally increased microvascular permeability (i.e., the pathological leakage effect). More critically, the severe oxidative stress (ROS burst) induces massive lipid peroxidation of the tubular epithelial cell membranes, destroying the integrity of the dense lipid bilayer structure [ 23, 24]. This study found that the specifically recruited molecules in the damaged kidneys were highly concentrated in flavonoid aglycones such as kaempferol, apigenin, and isorhamnetin. These polyhydroxy flavonoid aglycones possess strong lipophilicity and rigid planar skeletons, and the diseased microenvironment may endow them with high “pathological affinity.” They may physically embed into and stabilize the damaged and loose lipid bilayer via steric hindrance effects, thereby helping to maintain the stability of the tubular microscopic architecture. This microenvironment-driven targeted distribution provides pharmacokinetic theoretical support for understanding the localized intervention of TCM active molecules at the lesion. Additionally, while our mechanistic framework primarily focuses on the kidney-targeted components, the differential components uniquely identified in the serum (but not in the kidneys) should not be overlooked. These circulating metabolites (e.g., specific phenolic acids and highly polar glycosides) may not directly penetrate the renal barrier, but they could putatively exert systemic anti-inflammatory effects, modulate gut microbiota, or serve as circulating antioxidant reservoirs. However, as the core objective of this study was to pinpoint the direct pharmacological effectors at the lesion site, downstream network pharmacology and molecular docking were strictly limited to the authentic kidney-migrating components. 3.2. Significance of the “Glycoside–Aglycone” Conversion Pathway for Targeted Exposure In addition to the direct distribution of prototype components, this study also highlighted the dynamic in vivo biotransformation trajectory of BYJ through MS fragmentation rules and metabolic correlation analysis. The raw herb of BYJ contains a large number of highly water-soluble macromolecular flavonoid O-glycosides (such as Quercetin-3-O-rutinoside). Due to their high polarity and large molecular weight, these components are generally difficult to directly penetrate the gastrointestinal mucosal barrier. The in vitro and in vivo MS correlation analysis suggests that after oral administration, these macromolecular glycosides may undergo deglycosylation reactions under the action of the gut microecology (such as β-glucosidases secreted by gut microbiota), converting into highly lipophilic free aglycones (e.g., quercetin, kaempferol) that enter the bloodstream. Upon entering systemic circulation, these aglycone molecules not only cross the damaged renal tubular capillary barrier more easily but are also prone to generating glucuronide conjugates under the catalysis of abundant UGTs (uridine 5’-diphospho-glucuronosyltransferases) in organs like the liver and kidneys. Related studies indicate that at the target sites of inflammation and tissue damage (such as the local AKI kidney), highly expressed β-glucuronidase may promote a “deconjugation reaction,” releasing active free aglycones in situ. This delivery rule of “gut metabolism → systemic absorption → targeted recruitment → local release” suggests that the flavonoid aglycones and their metabolites, which exhibit high exposure features locally at the lesion, are likely the substantive material basis for BYJ’s efficacy. It is important to emphasize that while this dynamic in vivo biotransformation trajectory is strongly supported by our MS fragmentation rules and current literature, these convergent metabolic pathways remain proposed hypotheses. Precise enzymatic assays and microbiome perturbation models are warranted in future studies for direct mechanistic confirmation. 3.3. Predicted Multi-Pathway Anti-Apoptotic and Anti-Inflammatory Mechanisms Associated with Authentic Kidney-Migrating Components The core molecular events of cisplatin-induced AKI include mitochondrial dysfunction and the upregulated expression of pro-apoptotic proteins like Bax. The molecular docking results suggest that kaempferol and apigenin, relying on their abundant phenolic hydroxyl groups, can form stable hydrogen bonds and hydrophobic networks with key amino acids inside the active pockets of target proteins (such as AKT1) [ 30, 31]. Such binding may help regulate the phosphorylation activation state of Akt, further affecting the functions of downstream pro-apoptotic factors like Bad and Bax, thereby somewhat halting the apoptosis of tubular epithelial cells. Simultaneously, acting as natural antioxidants, these flavonoid aglycones are hypothesized to locally scavenge ROS at the damaged site (which aligns with the recovery of renal SOD activity observed in the animal experiments) [ 32], which is predicted to help block the MAPK and TNF-α inflammatory storms mediated by oxidative stress [ 33]. This dual mechanism of physical cell membrane protection combined with targeted regulation of kinase cascades provides a reference for deciphering the systemic pharmacological essence of BYJ’s “detoxification and renoprotection”. 3.4. Limitations and Future Perspectives While this study innovatively reveals the “pathological targeted recruitment” of BYJ via high-sensitivity LC-MS/MS, several limitations warrant acknowledgment. First, the kidney-migrating components were identified using semi-quantitative MS profiling. Future targeted LC-MS/MS analysis is required for absolute quantification to verify if these recruited aglycones reach pharmacologically effective concentrations in the renal parenchyma. Second, the proposed PI3K-Akt and MAPK mechanisms rely primarily on in silico predictions. Since the in vivo samples were fully consumed for MS mapping, direct protein-level verification (e.g., Western Blotting) is currently lacking. We plan to experimentally validate these kinase cascades using in vitro HK-2 cell models and gene-silencing techniques in follow-up studies. Third, strictly following biochemical assay protocols to prevent chemical interference, kidney homogenates were prepared in cold saline without protease inhibitors, which carries a risk of partial protein degradation. Subsequent molecular validations will address this by utilizing comprehensive lysis buffers. Despite these limitations, defining the material basis based on authentic target-organ distribution provides a robust scientific foundation for the clinical translation of BYJ against AKI. 4.1. Reagents, Reference Standards, and Animals Cisplatin (purity ≥ 99.0%) was purchased from Wuhan Servicebio Technology Co., Ltd. (Wuhan, China). LC-MS grade solvents (acetonitrile, methanol) and formic acid were obtained from Merck (Darmstadt, Germany) and Fisher Scientific (Waltham, MA, USA). Assay kits for serum creatinine (Scr), blood urea nitrogen (BUN), superoxide dismutase (SOD) and glutathione (GSH) were provided by Nanjing Jiancheng Bioengineering Institute (Nanjing, China). Reference standards, including resveratrol, pterostilbene, kaempferol, isorhamnetin, and vitexin (all with HPLC purity ≥ 98%), were purchased from Chengdu Must Bio-Technology Co., Ltd. (Chengdu, China). Specific pathogen-free (SPF) male Kunming (KM) mice (4 weeks old, 22 ± 1 g) were provided by Speford (Beijing, China) Biotechnology Co., Ltd. [License No.: SCXK (Jing) 2024-0001]. The mice were housed in a standard barrier environment (22 ± 2 °C, relative humidity 55 ± 5%, 12 h light/dark cycle) with ad libitum access to food and water. All animal experiments were approved by the Institutional Animal Care and Use Committee (Approval No.: 20260106071). 4.2. Preparation of Arundina graminifolia Extract (BYJ) The dried whole plant of A. graminifolia was purchased from Yunnan Huangya Dai Pharmaceutical Co., Ltd. (Xishuangbanna, China) and authenticated by Researcher Guang Li from the Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences. Based on our preliminary experiments [ 7] and the general principles of natural product extraction [ 34], 50% aqueous methanol was selected as the extraction solvent to provide an optimal polarity balance, ensuring the comprehensive extraction of both hydrophilic (e.g., flavonoid glycosides) and lipophilic (e.g., flavonoid aglycones) constituents. As reported in prior studies, 50% aqueous methanol shows excellent performance in extracting plant polyphenols [ 34]. Briefly, the whole herb was crushed and passed through a 60-mesh sieve. Precisely 500.0 g of the powder was weighed and mixed with this solvent at a solid-liquid ratio of 1:10 (g/mL). The mixture was subjected to ultrasonic extraction (300 W, 40 kHz) for 30 min at room temperature. The extract was filtered, and the solvent was recovered under reduced pressure at 50 °C. The concentrated extract was then lyophilized at −80 °C to yield the A. graminifolia extract (BYJ) dry powder, which was sealed and stored in the dark for future use. 4.3. Establishment of the AKI Animal Model and Intervention Protocol After one week of adaptive feeding, the mice were randomly divided into four groups ( n = 6 per group): the blank control group (Control), the BYJ normal administration group (BYJ-Normal), the AKI model group (Model), and the BYJ treatment group (BYJ-Model). 4.4. Sample Collection and Biochemical/Histopathological Evaluation One hour after the final drug administration on the 10th day, blood was collected via eyeball extirpation. The blood was allowed to stand at 4 °C for 2 h and then centrifuged (15,800× g, 10 min) to separate the serum, which was stored at −80 °C. The mice were euthanized by cervical dislocation. Bilateral kidneys were excised and weighed to calculate the kidney index (kidney weight/body weight × 100%). Biochemical analysis: Serum Scr and BUN concentrations were measured using a Hitachi 7180 automatic biochemical analyzer (Hitachi, Tokyo, Japan). The right kidney was homogenized with cold physiological saline to prepare a 10% ( w/ v) tissue homogenate. This specific homogenization medium, devoid of additional lysis buffers or protease inhibitors, was strictly chosen according to the assay kits’ manufacturer instructions to prevent any chemical interference with the subsequent colorimetric reactions. After centrifugation, the supernatant was collected to determine SOD activity and GSH content according to the manufacturers’ instructions, with normalization by total protein concentration using the BCA method. Histopathology: The left kidney was fixed in 4% paraformaldehyde for 24 h. Following routine dehydration and paraffin embedding, the tissues were sectioned (4 μm) and stained with hematoxylin and eosin (H&E). Renal tubular damage was observed under a light microscope (Olympus, Tokyo, Japan) 200×). 4.5. UPLC-Q-TOF-MS/MS Sample Preparation and Analytical Conditions Sample preparation: A 200 μL aliquot of serum was mixed with 600 μL of methanol-acetonitrile (1:1, v/ v) to precipitate proteins, vortexed, and centrifuged at 4 °C (18,600× g, 10 min). The supernatant was evaporated to dryness under nitrogen at 30 °C, reconstituted in 100 μL of 10% acetonitrile, and filtered prior to analysis. For kidney tissues, 20 mg of the sample was thoroughly homogenized in 100 μL of 0.1% aqueous formic acid. Subsequently, to precipitate proteins and extract the metabolites, 300 μL of cold methanol-acetonitrile (1:1, v/ v) was added to the homogenate. The mixture was vortexed for 3 min and then centrifuged at 4 °C (18,600× g, 10 min). The supernatant was carefully collected, dried under nitrogen at 30 °C, reconstituted in 200 μL of 0.1% aqueous formic acid, and filtered through a 0.22 μm membrane prior to analysis. Chromatographic conditions: Separation was performed on an Acquity UPLC BEH C18 column (100 × 2.1 mm, 1.7 μm). The mobile phases consisted of 0.1% aqueous formic acid (A) and 100% acetonitrile (B). The gradient elution program was as follows: 0–2 min, 5% B; 2–4 min, 5–55% B; 4–5 min, 55–70% B; 5–13 min, 70–82.5% B; 13–14 min, 82.5–95% B; 14–19 min, 95% B; 19–19.1 min, 95–5% B; 19.1–22 min, 5% B. The flow rate was 0.3 mL/min, the injection volume was 2 μL, and the column temperature was 40 °C. Mass spectrometry conditions: An AB SCIEX X500B Q-TOF-MS/MS instrument(AB Sciex, Framingham, MA, USA) equipped with an electrospray ionization (ESI) source was used. Scanning was performed in both positive and negative ion modes, utilizing the Information Dependent Acquisition (IDA) mode and Dynamic Background Subtraction (DBS) algorithm. The parameters were set as follows: ISVF ±5500 V; TEM 550 °C; GS1 and GS2 both at 60 psi; CUR 35 psi; DP 100 V; CE 40 V with CES 20 V. The full scan range was m/ z 100–1200. During the analysis, an automated Calibration Delivery System (CDS) was employed for continuous mass calibration to ensure high mass accuracy, maintaining the mass error strictly within 5 ppm. It should be noted that no internal standard was used in this untargeted qualitative analysis, as the primary objective was to identify the presence of migrating components rather than perform absolute quantification. To ensure system stability and data reproducibility, the instrument performance was verified daily using the manufacturer’s standard calibration solution, and the consistency of the chromatographic peak shapes and retention times was closely monitored throughout the entire sequence. 4.6. MS-DIAL-Based Metabolite Identification Strategy Raw mass spectrometry data were imported into MS-DIAL (v4.9) for peak extraction and alignment. The data filtering strategy was as follows: (1) Background subtraction: Feature peaks with a signal response (Peak Area) > 5 times that of the blank group and a signal-to-noise ratio (S/N) ≥ 10 in the administration group were extracted. (2) Specificity screening: By comparing the chromatograms of the Model and BYJ-Model groups, the core component clusters pathologically recruited to the kidneys in the AKI state were identified. (3) Structural matching: With a mass error limit of < 5 ppm, the MS/MS fragmentation patterns were matched against reference standards and online databases (HMDB, MassBank, METLIN), requiring a matching score ≥ 80%. Based on classical Phase I/II drug metabolism rules, the in vivo metabolic network was delineated. 4.7. Network Pharmacology and Molecular Docking Molecular docking: The 2D structures of the ligands and the 3D crystal structures of the receptors (AKT1, PIK3CA, EGFR) were obtained from the PubChem and RCSB PDB databases, respectively. The protein preparation steps were rigorously performed using PyMOL (v2.4) to remove water molecules and original co-crystallized ligands. Subsequently, the dehydrated proteins were imported into AutoDockTools (v1.5.6) to add polar hydrogens and compute Gasteiger charges. For the docking simulation, a grid box of 20 × 20 × 20 Å was established, with the coordinates centered exactly on the binding site of the original co-crystallized ligands to accurately define the active pockets. The docking calculations were executed using AutoDock Vina (v1.1.2) with the exhaustiveness parameter set to 8. The docking poses with the lowest binding energies (kcal/mol) were recorded and selected for 2D and 3D visualization. 4.8. Statistical Analysis All quantitative data were derived from at least three independent experiments and are expressed as mean ± standard deviation (SD). Statistical analyses were performed using GraphPad Prism 8.0 and SPSS 27.0 software. For data conforming to a normal distribution (evaluated by the Shapiro-Wilk test) and homoscedasticity (assessed by Levene’s test), a one-way analysis of variance (ANOVA) followed by Tukey’s post-hoc test was applied. Non-normally distributed data were analyzed using the Kruskal-Wallis test followed by Dunn’s post-hoc test for multiple comparisons. A p-value < 0.05 was considered statistically significant. 5. Conclusions By integrating in vivo target organ mass spectrometry tracking with network pharmacology prediction, this study explored the action mechanisms and pharmacodynamic material basis of the Dai medicine A. graminifolia (BYJ) in intervening against cisplatin-induced acute kidney injury (AKI). Animal experiments verified that the BYJ extract effectively restored renal antioxidant capacity and alleviated renal tubular damage. Through in vitro and in vivo mass spectrometry cross-analysis, this study discovered a significant distribution shift: under the influence of the damaged AKI microenvironment, highly lipophilic flavonoid aglycones, predominantly kaempferol and apigenin, achieved specific targeted recruitment locally in the kidneys. Network pharmacology and molecular docking analyses based on authentic kidney-migrating components strongly suggested that this core cluster possesses high binding affinities to key targets such as AKT1 and PIK3CA, potentially exerting anti-apoptotic and anti-inflammatory effects primarily by regulating the PI3K-Akt and TNF signaling pathways. This study elucidated the material basis of BYJ from the perspective of actual in vivo distributed components, clarified the rationale for using kaempferol and apigenin as key quality control markers, and provided objective experimental evidence for related research on the action mechanisms of TCM. Supplementary Materials The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/molecules31111951/s1, Supplementary Table S1: Detailed identification of the 93 chemical components characterized in the Arundina graminifolia extract (BYJ) in vitro using UPLC-Q-TOF-MS/MS; Supplementary Table S2: Detailed information and chemical structures of the 18 therapeutic core components used as the input foundation for network pharmacology analysis; Supplementary Figure S1: Schematic illustration of the experimental design and in vivo timeline; Supplementary Figure S2: Heatmap visualization of the relative abundances of the 18 therapeutic core components in the kidneys. Author Contributions Author Contributions: M.C. and Y.Z. contributed equally to this work as co-first authors. Conceptualization, M.C.; methodology, Y.Z.; validation, Y.Z. and J.C.; formal analysis, M.C.; investigation, J.C. and R.Z.; resources, G.L.; data curation, Y.Z.; writing—original draft preparation, M.C. and Y.Z.; writing—review and editing, M.C.; supervision, G.L.; project administration, G.L.; funding acquisition, G.L. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The animal study protocol was approved by the Animal Ethics Committee of the Yunnan Branch of the Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences (protocol codes 20260106071). The study was conducted in accordance with the local legislation and institutional requirements, approved on 6 January 2026. Figure 1. UPLC-Q-TOF-MS/MS identification and classification of chemical components in Arundina graminifolia extract (BYJ) in vitro. ( A) Pie chart illustrating the chemical classification of the 93 identified secondary metabolites (mainly including flavonoids, organic acids, terpenoids, and stilbenes). ( B) Total ion chromatogram (TIC) of BYJ in positive ion mode. ( C) TIC of BYJ in negative ion mode. Figure 1. UPLC-Q-TOF-MS/MS identification and classification of chemical components in Arundina graminifolia extract (BYJ) in vitro. ( A) Pie chart illustrating the chemical classification of the 93 identified secondary metabolites (mainly including flavonoids, organic acids, terpenoids, and stilbenes). ( B) Total ion chromatogram (TIC) of BYJ in positive ion mode. ( C) TIC of BYJ in negative ion mode. Figure 2. Flavonoid, stilbenoid and N-substituted α-amino acid skeleton compounds. Figure 2. Flavonoid, stilbenoid and N-substituted α-amino acid skeleton compounds. Figure 3. Compounds with other unclassified skeletons. Figure 3. Compounds with other unclassified skeletons. Figure 4. Representative MS/MS fragmentation pathways of core flavonoids. ( A) MS/MS fragmentation analysis of isorhamnetin. ( B) MS/MS fragmentation analysis of kaempferol. Figure 4. Representative MS/MS fragmentation pathways of core flavonoids. ( A) MS/MS fragmentation analysis of isorhamnetin. ( B) MS/MS fragmentation analysis of kaempferol. Figure 5. Mass spectrometric analysis of stilbenoids. ( A) Mass spectrometric identification of resveratrol. ( B) Mass spectrometric identification of pterostilbene. Figure 5. Mass spectrometric analysis of stilbenoids. ( A) Mass spectrometric identification of resveratrol. ( B) Mass spectrometric identification of pterostilbene. Figure 6. Mass spectrometric analysis of nucleosides, terpenoids and alkaloids. ( A) Mass spectrometric identification of adenosine. ( B) Mass spectrometric identification of tryptophan. ( C) Mass spectrometric identification of glycyrrhetinic acid. Figure 6. Mass spectrometric analysis of nucleosides, terpenoids and alkaloids. ( A) Mass spectrometric identification of adenosine. ( B) Mass spectrometric identification of tryptophan. ( C) Mass spectrometric identification of glycyrrhetinic acid. Figure 7. Pharmacodynamic evaluation of BYJ in alleviating cisplatin-induced acute kidney injury (AKI) in mice. ( A) Macroscopic appearance of bilateral kidneys from each group. ( B) Representative H&E staining of renal tissues (magnification 200×; arrows indicate necrotic tubules and proteinaceous casts). ( C) Body weight changes during the experiment. ( D) Kidney index. ( E, F) Renal function markers: serum creatinine (Scr) and blood urea nitrogen (BUN) levels. ( G, H) Local oxidative stress markers in renal tissues: superoxide dismutase (SOD) and glutathione (GSH) levels. Data are presented as mean ± SD ( n = 6), and individual biological replicates are overlaid as scatter dots on the bar graphs. Statistical significance was determined using one-way ANOVA followed by Tukey’s post-hoc test. #### p < 0.0001 vs. Control group; *** p < 0.001, **** p < 0.0001 vs. Model group. Figure 7. Pharmacodynamic evaluation of BYJ in alleviating cisplatin-induced acute kidney injury (AKI) in mice. ( A) Macroscopic appearance of bilateral kidneys from each group. ( B) Representative H&E staining of renal tissues (magnification 200×; arrows indicate necrotic tubules and proteinaceous casts). ( C) Body weight changes during the experiment. ( D) Kidney index. ( E, F) Renal function markers: serum creatinine (Scr) and blood urea nitrogen (BUN) levels. ( G, H) Local oxidative stress markers in renal tissues: superoxide dismutase (SOD) and glutathione (GSH) levels. Data are presented as mean ± SD ( n = 6), and individual biological replicates are overlaid as scatter dots on the bar graphs. Statistical significance was determined using one-way ANOVA followed by Tukey’s p
