Phytochemical Profiling and Pharmacological Evaluation of Dichloromethane Extract From Aerial Parts of Ferula ferulaeoides for Antithrombotic, Anti‐Inflammatory, and Analgesic Activities

ABSTRACT

This study aims to elucidate the chemical composition of the dichloromethane extract from the aerial parts of Ferula ferulaeoides (DEAFF) and to explore its biological activities. The composition of DEAFF was analyzed by UHPLC‐Q‐Orbitrap‐MS/MS. Then, the carrageenan‐induced tail thrombosis model, xylene‐induced ear swelling model, and acetic acid‐induced writhing model were established to evaluate the relevant activities of DEAFF. Network pharmacology research and molecular docking were conducted to elucidate the pathways and key targets underlying the multiple activities of DEAFF. A total of 30 chemical constituents were tentatively identified in DEAFF based on UHPLC‐Q‐Orbitrap‐MS/MS analysis. Pharmacodynamic results showed that DEAFF significantly reduced the proportion of thrombus in the tail of mice, effectively alleviated ear swelling, improved the degree of ear tissue lesions, and significantly reduced the number of writhing movements in mice, indicating that it has multiple pharmacological effects such as antithrombosis, anti‐inflammation, and analgesia. Network pharmacology studies have shown that multiple pathways such as the PI3K‐Akt signaling pathway and the MAPK signaling pathway play a crucial role in the pharmacological effects of DEAFF. In this study, the chemical components of DEAFF were preliminarily identified, and its effects on thrombosis prevention, anti‐inflammation, and analgesia were systematically investigated.

Abbreviations

ASP‐1

aspirin 100 mg/kg

ASP‐2

aspirin 200 mg/kg

COX‐2

cyclooxygenase‐2

DEAFF

dichloromethane extract from aerial parts of Ferula ferulaeoides

DXM

dexamethasone acetate

PGE2

prostaglandin E2

UHPLC‐Q‐Orbitrap‐MS/MS

ultraperformance liquid chromatography‐quadrupole‐electrostatic field Orbitrap mass spectrometry

β‐EP

β‐endorphin

1. Introduction

Ferula ferulaeoides (Steud.) Korov. (F. ferulaeoides) is a perennial herb of the genus Ferula in the Apiaceae family that bears fruit only once. It is also known as “Fragrant Ferula” due to its distinctive aroma, which lacks the onion‐ or garlic‐like odor typical of some related species (Tian et al. 2025). Its aerial parts emerge in early spring, undergo approximately 2 months of growth, and then gradually senesce. Meanwhile, the underground parts enter a dormant state, forming a unique “spring growth ‐ summer dormancy” cycle pattern. After vegetative growth for up to 7–8 years, the plant can reach a height of 1–1.5 m, with abundant accumulation of aerial resources, and finally die after one‐time flowering and fruiting. F. ferulaeoides grows in arid habitats including sand dunes, sandy areas, and gravel deserts. It is mainly distributed in Xinjiang, China, particularly along the Junggar Basin fringe, with occasional occurrences extending into Kazakhstan and Mongolia (Chen et al. 2023; Guo et al. 2025). The medicinal value of plants in the genus Ferula was first documented in the Newly Revised Materia Medica of the Tang Dynasty and has been recorded in subsequent materia medica classics (Jia et al. 2024). As a traditional ethnic medicine in China, the use of F. ferulaeoides is also well established, with a history dating back hundreds of years (X. X. Li et al. 2018). In traditional Uyghur and Kazakh medicine, the resin from its roots and aerial parts is utilized to promote blood circulation, relieve rheumatic pain, and treat various conditions including chronic gastroenteritis, gastric ulcers, and arthritis (Meng et al. 2013; M. M. Liu, Zhao, et al. 2022). Modern research reveals that F. ferulaeoides possesses a diverse phytochemical profile, including sesquiterpenoids, coumarins, volatile oils, and polysaccharides (Chen et al. 2023). These compounds contribute to a range of pharmacological activities such as anticoagulant, anti‐inflammatory, analgesic, antihypertensive, anticancer, and antibacterial effects (Meng et al. 2013; Yao et al. 2020).

Inflammation is a common immune response produced by the body to harmful stimuli (Chlif et al. 2022; J. Zhang et al. 2024). As a defense mechanism against diseases, inflammation is a complex pathophysiological process (Medzhitov 2008). It is mediated by a variety of signaling molecules produced by immune cells such as leukocytes, macrophages, and mast cells and the activation of complement factors. These factors lead to exudation of fluid and protein and accumulation of leukocytes in inflammatory sites, resulting in edema (C. X. Zhang et al. 2011), destruction of tissue structure and disorder of physiological functions, and a serious imbalance of internal environmental homeostasis, and promote the development of the disease. The persistence of inflammation can lead to a variety of diseases, including digestive system diseases, neurodegenerative diseases, arthritis, diabetes, cardiovascular diseases, cancer, and autoimmune diseases (Z. Zhang et al. 2021). ROS is an important mediator of the inflammatory response, which can not only stimulate and aggravate inflammation but also lead to vascular damage and increase adhesion molecules, thus inducing thrombosis (Islam et al. 2025). Once thrombosis is formed, it will affect blood circulation and cardiovascular function. Thrombosis may also lead to ischemia, hypoxia, softening, and thrombosis necrosis of tissues and organs in the body. If not treated in time, it may lead to death. In particular, the mortality rate of cerebrovascular diseases is very high, which has become a major disease threatening human health (P. Wang et al. 2022). Pain has been described as a classic warning of the immune system's response to inflammation, which can lead to abnormal pain or hyperalgesia, namely, nociception (Azad et al. 2024). After the occurrence of inflammation, if it is not handled properly or in time, it may cause a variety of diseases, such as pain caused by chemical mediators such as bradykinin, serotonin, and prostaglandins released during the development of inflammation (Jin et al. 2022). Pain is processed by special neurons in the central nervous system called nociceptors. When receiving harmful stimuli, these neurons will transmit pain‐related information to the brain, thus causing people to feel uncomfortable or even painful physiological and emotional reactions, which seriously affect the overall quality of life (Chlif et al. 2022; Ema et al. 2023). Pain has become a common pathological condition in human life, with severe social and economic impacts due to hospital visits, painkillers, and productivity loss every year (R. Zhang et al. 2014). These three diseases are interrelated and influence each other.

Only two Ferula species are monographed as medicinal materials in the Chinese Pharmacopoeia: Ferula sinkiangensis K. M. Shen and Ferula fukanensis K. M. Shen. However, due to the long growth cycles and severe ecological degradation in recent years, these two medicinal Ferula species are now endangered, leading to a severe shortage that fails to meet the market demand. In response to the supply deficit, Uygur medicine utilizes the resin of F. ferulaeoides as an alternative resource to fulfill the clinical demand for Ferula. As a result, the wild resource reserves of F. ferulaeoides resin have experienced a steep decline. With a long‐term focus on Ferula species, our group previously demonstrated a high similarity in chemical profiles between the dichloromethane extract of F. sinkiangensis aerial parts and its resin. Further pharmacological evaluation indicated parallel anti‐inflammatory (J. Wang, Huo, et al. 2023; J. Wang, Zheng, et al. 2023) and antiacute gastric ulcer activities (L. Liu et al. 2026). These findings suggest its potential to serve as a replacement for the traditional medicinal parts. Given the relative abundance of its aerial resources, F. ferulaeoides holds significant potential to alleviate the shortage of Ferula medicinal resources. Precedent from our previous work on F. sinkiangensis, where the dichloromethane fraction was identified as the most bioactive fraction, this study investigated the chemical composition and pharmacological effects of the dichloromethane extract from the aerial parts of F. ferulaeoides (DEAFF). UHPLC‐Q‐Orbitrap‐MS/MS analysis was employed to characterize its chemical profile, whereas carrageenan‐induced tail thrombosis, xylene‐induced acute ear swelling, and acetic acid‐induced writhing experiments were used to evaluate its antithrombotic, anti‐inflammatory, and analgesic activities. This integrated approach aims to establish a scientific basis for utilizing these aerial resources.

2. Materials and Methods

2.1. Materials and Reagents

Reagents such as 95% ethanol, petroleum ether, and dichloromethane were of analytical grade. For ultrahigh‐performance liquid chromatography, formic acid, methanol, and acetonitrile were MS grade. Dextrin (Shanghai Yuanye Bio‐Technology Co. Ltd., China), sodium carboxymethyl cellulose (CMC‐Na) (Shanghai Macklin Biochemical Co. Ltd., China), carrageenan (C1013, Sigma‐Aldrich, USA), aspirin (BJ74640, Bayer Healthcare Co. Ltd., China), dexamethasone acetate (LB2478, Zhejiang Xianju Pharmaceutical Co. Ltd., China), hematoxylin and eosin (H&E) staining kit (GP1031, Wuhan Servicebio Technology Co. Ltd., China), and ELISA kits for PGE2, COX‐2, and β‐EP (MM‐0062M1, MM‐0356M1, and MM‐0232M1, Jiangsu Enzyme Exemption Industry Co. Ltd., China) were used.

2.2. Collection and Extraction of Plant Material

2.2.1. Collection of Plant Material

The aerial parts of F. ferulaeoides were collected from Fuhai County, Altay Prefecture (47°10′34.313″ N, 88°39′47.365″ E), Xinjiang Uygur Autonomous Region of China, in May 2023. They were identified by Prof. Congzhao Fan, Xinjiang Institute of Chinese Materia Medica and Ethnodrug, Urumqi, China. The voucher specimen (DSAWDS‐202305‐S) is deposited in the herbarium of the same institute.

2.2.2. Preparation of Extract

Dried and powdered aerial parts of F. ferulaeoides (500 g) were extracted twice by heating under reflux with 95% ethanol (5 L × 2, each for 2 h). The combined ethanol extracts were filtered and concentrated under reduced pressure at 50°C using a rotary evaporator to yield the crude ethanol extract. The crude extract was then suspended in water (500 mL) and sequentially partitioned with petroleum ether (500 mL × 3) and dichloromethane (500 mL × 3). The dichloromethane layer was collected, dried over anhydrous Na₂SO₄, filtered, and concentrated under reduced pressure at 40°C. The resulting residue (DEAFF, yield: 7.98 g, 15.96% w/w) was dried in vacuo and stored at −20°C until use.

2.2.3. Preparation of Animal Administration

The dichloromethane extract of the aerial parts of F. ferulaeoides was dissolved in a small amount of dichloromethane and then mixed with dextrin according to the weight ratio of 1:2.5, fully mixed, and volatilized. The sample was obtained after grinding and passing through a 50‐mesh sieve.

2.3. Phytochemical Analysis

The sample was accurately weighed and dissolved in 50% methanol to prepare a sample with a concentration of 1.0 mg/mL. The sample was analyzed in positive and negative ion modes using UHPLC‐Q‐Orbitrap‐MS/MS, and the ionization mode for each compound was selected based on signal intensity and spectral quality. The UHPLC‐Q‐Orbitrap liquid mass spectrometry system consisted of an Ultimate 3000 ultrahigh‐performance liquid chromatograph (Dionex Company, USA) coupled with a Thermo Q Exactive Plus high‐resolution mass spectrometer (Thermo Fisher Scientific Company, USA) and CD (Compound Discoverer 3.3) compound analysis and identification software (Thermo Fisher Scientific, USA).

2.3.1. Chromatographic Conditions

The column was ACQUITY UPLC HSS T3 C18 (2.1 mm × 100 mm, 1.8 μm; Waters Corporation, USA); the column temperature was 35°C, and the flow rate was 0.2 mL·min⁻¹. The mobile phase consisted of 0.1% formic acid acetonitrile (A)–0.1% formic acid water (B), with gradient elution: 0–10 min, 100% B; 10–20 min, 100%–70% B; 10–25 min, 70%–60% B; 25–30 min, 60%–50% B; 30–40 min, 50%–30% B; 40–45 min, 30%–0% B; 45–60 min, 0% B; 60–60.1 min, 0%–100% B; 60.1–70 min, 100% B.

2.3.2. Mass Spectrometry Conditions

The ion source was a heated electrospray ionization (HESI) source; sheath gas flow was 40 arb, auxiliary gas flow was 15 arb, capillary temperature was 320°C, auxiliary gas heater temperature was 350°C, positive spray voltage was 3.2 kV, and negative spray voltage was 3.0 kV. The resolution of MS was 70,000, the resolution of MS/MS was 17,500, the scanning mode was full scan mode, positive and negative ion modes were detected separately, and the mass spectrum recorded the positive ion spectrum scanning range of m/z 100–1500. Unknown compounds were identified using Compound Discoverer 3.3, mzCloud, and mzVault databases.

2.4. Animals

The experiment used SPF‐grade male ICR mice weighing 18–22 g. The mice were purchased from SPF (Beijing) Biotechnology Co. Ltd. and Beijing HFK Bioscience Co. Ltd. They were raised in a room with a constant temperature of 25°C ± 1°C, a relative humidity of 55%–65%, and a light cycle of 12 h and were allowed to eat freely. Before the experiment, the animals were acclimatized to the environment for 3 consecutive days. All experimental procedures were approved by the Laboratory Animal Ethics Committee of the Chinese Academy of Medical Sciences (Ethics Number: SLXD‐20240829016).

2.5. Carrageenan‐Induced Mouse Tail Thrombosis Model

2.5.1. Grouping

Fifty male ICR mice were randomly divided into five groups (n = 10): the control group (Control), the model group (Model), the positive drug aspirin group (ASP‐1, 100 mg/kg), and the low‐dose and high‐dose groups of DEAFF (DEAFF‐L, 200 mg/kg, and DEAFF‐H, 400 mg/kg).

2.5.2. Administration

The control group and model group mice were respectively administered with 0.5% CMC‐Na suspension containing 1 g/kg dextrin (0.1 mL/10 g) by gavage. The positive drug group was administered with 0.5% CMC‐Na suspension containing 100 mg/kg ASP and 1 g/kg dextrin by gavage. The other drug groups were administered with 0.5% CMC‐Na suspension of the DEAFF. Gavage was performed once daily for 7 consecutive days.

2.5.3. Modeling

The body weight of mice in each group was recorded before gavage every day. One hour after the last administration, the model group and the treatment group underwent intraperitoneal injection of a 0.4% carrageenan saline suspension (0.1 mL/10 g), whereas the control group received an intraperitoneal injection of an equivalent dose of saline. Subsequently, all mice were housed at a low temperature of 17°C and allowed to feed and drink freely. After 24 h, the tail length and thrombus length of each group of mice were measured, and the relative length of the black tail in each group was calculated. The relative length of the black tail (%) = thrombus length of tail/total tail length × 100%.

2.6. Xylene‐Induced Ear Swelling in Mice

2.6.1. Grouping

Fifty male ICR mice were randomly divided into five groups (n = 10): the control group (Control), the model group (Model), the positive drug dexamethasone acetate group (DXM, 20 mg/kg), and the low‐dose and high‐dose groups of DEAFF (DEAFF‐L, 200 mg/kg, and DEAFF‐H, 400 mg/kg).

2.6.2. Administration

Mice in the control group and the model group were respectively gavaged with 0.5% CMC‐Na suspension containing 1 g/kg dextrin (0.1 mL/10 g). The positive drug group was gavaged with a 0.5% CMC‐Na suspension containing 20 mg/kg DXM + 1 g/kg dextrin. The other administration groups were given a 0.5% CMC‐Na suspension of DEAFF by gavage once a day for 7 consecutive days.

2.6.3. Modeling

One hour after the last administration, except for the control group, 40 μL of xylene was evenly applied to the inner and outer auricles of the right ear of mice in the other groups to cause inflammation, whereas the left ear was not applied as a control. The control group was applied an equal amount of normal saline to the right ears. Thirty minutes after modeling, the mice were sacrificed. Both ears were cut along the baseline of the auricle. Circular ear slices were made at the same position of the left and right ears using a 9‐mm‐diameter punch. The mass was weighed by an analytical balance. The weight difference between the two ear slices (weight of the right ear slice − weight of the left ear slice) was taken as the degree of ear swelling, and the inhibition rate of ear swelling was calculated. The inhibition rate (%) = [(swelling degree of model group − swelling degree of drug group)/swelling degree of model group] × 100%.

Right ear slice samples were soaked in 4% paraformaldehyde tissue fixative for 48 h, then dehydrated, and paraffin‐embedded. The wax blocks were sliced using a slicer, stained with H&E, and then dehydrated and sealed. Finally, the histopathological changes of ear tissue injury were detected using a 200× optical microscope.

2.7. Acetic Acid‐Induced Writhing Test

2.7.1. Grouping

Fifty male ICR mice were randomly divided into five groups (n = 10): the control group (C), the model group (M), the positive drug aspirin (ASP‐2, 200 mg/kg), and the low‐dose and high‐dose groups of DEAFF (DEAFF‐L, 200 mg/kg, and DEAFF‐H, 400 mg/kg).

2.7.2. Administration

Mice in the control group and the model group were respectively gavaged with 0.5% CMC‐Na suspension containing 1 g/kg dextrin (0.1 mL/10 g). The positive drug group was gavaged with a 0.5% CMC‐Na suspension containing 200 mg/kg ASP + 1 g/kg dextrin. The other administration groups were given a 0.5% CMC‐Na suspension of DEAFF by gavage once a day for 7 consecutive days.

2.7.3. Modeling

One hour after the last administration, except for the control group, mice in the other groups were intraperitoneally injected with 0.6% acetic acid normal saline solution at 0.1 mL/10 g, whereas the control group was injected with the same amount of normal saline. The writhing times within 15 min after injection were recorded, and the inhibition rate of writhing reaction was calculated. The writhing response inhibition rate (%) = (mean writhing response in the model group − mean writhing response in each treatment group)/mean writhing response in the model group × 100%.

The collected mice blood was left to stand at 4°C for 2 h. The blood was then separated by centrifugation at 3000 rpm for 10 min, the upper serum was collected, and it was stored at −80°C. The levels of COX‐2, PGE2, and β‐EP in the serum of mice in each group were detected according to the instructions of the ELISA kits.

2.8. Statistical Analyses

SPSS software (version 26.0) was utilized for conducting data analysis, with the outcomes presented in the format of mean ± standard deviation (SD). A one‐way ANOVA was utilized to assess differences among three or more groups. When the variances were found to be homogeneous, the least significant difference (LSD) method was used; if not, the Games–Howell test was applied instead. Statistical significance was set at p < 0.05. Statistical mappings were performed using GraphPad 9.0 software.

2.9. Network Pharmacology Analysis

2.9.1. Acquisition of Core Targets and Construction of PPI Network

The ETCM database (http://www.tcmip.cn/ETCM/), TCMSP database (https://tcmsp‐e.com/tcmsp.php), SymMap database (http://www.symmap.org/), BATMAN database (http://bionet.ncpsb.org.cn), and Swiss Target Prediction database (http://www.swisstargetprediction.ch/) were used to retrieve the compound effect targets. The DisGeNET (http://www.disgenet.org/), GeneCards (https://www.genecards.org/), and OMIM (https://omim.org/) databases were searched for the targets involved in inflammation, pain, and thrombosis, respectively. Then, the compound targets and disease‐related targets were compared and analyzed, and the intersection targets were used as the core targets for subsequent research. Finally, the core targets were uploaded to the STRING database (http://string‐db.org) to obtain the interaction relationship between core targets, and the PPI network was constructed using Cytoscape software.

2.9.2. Functional Enrichment Analysis and Construction of Compound–Core Target–Signaling Pathway Networks

The core targets were input into the DAVID (https://david.ncifcrf.gov/) database for GO enrichment analysis and KEGG pathway analysis. The results were visualized by an online platform (https://www.bioinformatics.com.cn). Subsequently, according to the results of KEGG pathway analysis, the relevant interaction relationships among signaling pathways, core targets, and compounds were sorted out. The “compound–core target–signaling pathway” network was constructed using Cytoscape software (Dong et al. 2022; J. Liu, Dong, et al. 2022).

2.10. Molecular Docking

Ligand preparation was performed using ChemBio3D Ultra 14.0 software to draw the chemical structure, optimize the structure for energy minimization, and then save it. Receptor preparation was performed by downloading the 3D structure of the protein from the RCSB protein structure database, and it was stored after pretreatment with water molecules and nonstandard amino acid residues. For docking, the ligand files and receptor files were imported into AutoDock Vina docking software for semiflexible docking, and the results were visualized by PyMOL software (Dong et al. 2024, 2025).

3. Results

3.1. DEAFF Chemical Composition Analysis

The chemical composition of DEAFF was analyzed by UHPLC‐Q‐Orbitrap‐MS/MS, as shown in Figure 1. Coupled with reference standard comparison, the analysis led to the identification of 30 compounds in DEAFF (for detailed identification process, please refer to Supporting Information). The identified constituents encompass phenolic acids, coumarins, flavonoids, fatty acid derivatives, and terpenoids, as detailed in Table 1.

FIGURE 1.

Component analysis of DEAFF by UHPLC–MS (up: negative mode; down: positive mode).

TABLE 1.

Identification results of chemical components in DEAFF by UHPLC‐Q‐Orbitrap‐MS/MS.

No.	RT (min)	Name and CAS	Formula	Molecular structure	Delta mass (ppm)	Calc. MW	m/z	mzCloud best match	mzVault best match	Reference ion
1	1.587	d‐(−)‐Quinic acid 77‐95‐2	C7H12O6		2.51	191.0556	191.0560	94.6	96.1	[M − H]−
2	3.169	Nicotinamide 98‐92‐0	C6H6N2O		−3.09	123.0558	123.0555	90.6	90.6	[M + H]+
3	6.537	Mesaconic acid 498‐24‐8	C5H6O4		3.72	129.0188	129.0193	83.5	90.9	[M − H]−
4	19.348	2,4‐Dihydroxybenzoic acid 89‐86‐1	C7H6O4		3.14	153.0188	153.0193	92.7	97.7	[M − H]−
5	19.703	Benzoic acid 65‐85‐0	C7H6O2		4.38	121.0290	121.0295	95.4	91.4	[M − H]−
6	20.636	2,2′,4,4′‐Tetrahydroxybenzophenone 131‐55‐5	C13H10O5		1.92	245.0450	245.0455	85.4	86.6	[M − H]−
7	32.136	Cyclo(phenylalanyl‐prolyl) 14705‐60‐3	C14H16N2O2		−1.39	245.1290	245.1287	81.7	89.3	[M + H]+
8	21.468	4′,7‐Dihydroxyflavanone 69097‐97‐8	C15H12O4		−1.17	257.0814	257.0811	78.1	76.2	[M + H]+
9	21.699	Ferulic acid 1135‐24‐6	C10H10O4		3.11	193.0501	193.0507	96.5	97.6	[M − H]−
10	17.955	2,5‐Dihydroxybenzaldehyde 1194‐98‐5	C7H6O3		3.72	137.0239	137.0244	80	63.6	[M − H]−
11	22.658	Isorhamnetin‐3‐O‐glucoside 5041‐82‐7	C22H22O12		0.73	477.1033	477.1037		92.9	[M − H]−
12	22.980	Azelaic acid 123‐99‐9	C9H16O4		4.17	187.0970	187.0978	71.9	80.4	[M − H]−
13	23.034	Isoferulic acid 537‐73‐5	C10H10O4		3.11	193.0501	193.0507	81	89.8	[M − H]−
14	24.897	4‐Methoxysalicylic acid 2237‐36‐7	C8H8O4		4.01	167.0344	167.0351	84.6	88.4	[M − H]−
15	20.474	Germacrone 6902‐91‐6	C15H22O		−2.05	219.1749	219.1745	89.8	86.8	[M + H]+
16	25.817	Ethyl caffeate 102‐37‐4	C11H12O4		2.51	207.0657	207.0663		87	[M − H]−
17	27.050	Corchorifatty acid F 95341‐44‐9	C18H32O5		1.47	327.2172	327.2176	93.2	90	[M − H]−
18	27.035	19‐Nortestosterone 434‐22‐0	C18H26O2		−1.67	275.2011	275.2007	90.2	79.4	[M + H]+
19	31.400	Arglabin 84692‐91‐1	C15H18O3		−1.34	247.1334	247.1331	79.5	72	[M + H]+
20	32.136	Linderalactone 728‐61‐0	C15H16O3		−1.26	245.1178	245.1175		74.9	[M + H]+
21	42.487	α‐Cyperone 473‐08‐5	C15H22O		−2.05	219.1749	219.1745	91.5	86.9	[M + H]+
22	21.219	7‐Methoxycoumarin 531‐59‐9	C10H8O3		−2.49	177.0552	177.0548	76.9	69.9	[M + H]+
23	21.892	Scopoletin 92‐61‐5	C10H8O4		−2.18	193.0501	193.0497	96.4	95.4	[M + H]+
24	25.197	Curcumol 4871‐97‐0	C15H24O2		−2.32	237.1855	237.1850	70.4	83.7	[M + H]+
25	46.519	Hexadecanamide 629‐54‐9	C16H33NO		−1.87	256.2640	256.2635	82	58	[M + H]+
26	21.592	7‐Hydroxycoumarin 93‐35‐6	C9H6O3		−2.88	163.0395	163.0390	94.2	91.9	[M + H]+
27	43.244	Levistilide A 88182‐33‐6	C24H28O4		−1.60	381.2066	381.2060		73.7	[M + H]+
28	45.768	16‐Hydroxyhexadecanoic acid 506‐13‐8	C16H32O3		3.36	271.2273	271.2282	79.6	82.2	[M − H]−
29	45.888	5,7‐Dihydroxychromone 31721‐94‐5	C9H6O4		−1.90	179.0344	179.0341	77	69.2	[M + H]+
30	49.186	Stearamide 124‐26‐5	C18H37NO		−1.23	284.2953	284.2950	85.1	79.4	[M + H]+

3.2. Potential Toxicity of DEAFF

Body weight is an important indicator reflecting the growth and development, metabolic status, and potential toxic effects of drugs in animals. During the experiment, the weight changes of mice in different models were recorded to evaluate the potential toxicity of DEAFF. From the weight change line graphs (Figures 2A, 3A, and 4A), it can be seen that under three different activities, the weight of mice in each DEAFF dose group steadily increased every day, and there was no significant change compared to the blank group. During the preadministration process, the mental state of the mice was good, and no signs of toxicity such as activity, aggression, alertness, tremor, sleep, vomiting, or diarrhea were observed. Moreover, none of the test mice died at the test doses (Ed‐Dahmani et al. 2025). Preliminary results indicated that DEAFF did not cause severe toxic reactions at selected doses (200 and 400 mg/kg).

FIGURE 2.

DEAFF can alleviate carrageenan‐induced tail thrombosis. (A) Body weight change of mice over 7 days (n = 10 per group). (B) Analysis of the length of tail thrombus (n = 10 per group). (C) Representative image of thrombus injury in the tails of mice. ^### p < 0.001 compared with the Control group. *p < 0.05, **p < 0.01, compared with the Model group.

FIGURE 3.

Effects of DEAFF on xylene‐induced ear swelling in mice. (A) Body weight change of mice over 7 days (n = 10 per group). (B) Analysis of ear swelling (n = 10 per group). (C) H&E‐stained ear histopathological sections (n = 3 per group, scale bar = 200 μm). ^### p < 0.001 compared with the Control group. **p < 0.01, ***p < 0.001, compared with the Model group.

FIGURE 4.

Effect of DEAFF on acetic acid‐induced writhing in mice. (A) Body weight change of mice over 7 days (n = 10 per group). (B) Number of writhing (n = 10 per group). (C) Effects on the contents of PGE2, COX‐2, and β‐EP in the serum of acetic acid‐induced writhing in mice (n = 10 per group). ^### p < 0.001 compared with the Control group. *p < 0.05, **p < 0.01, ***p < 0.001, compared with the Model group.

3.3. Antithrombotic Activity of DEAFF

As shown in Figure 2B,C, after mice were intraperitoneally injected with 0.4% carrageenan and placed in a low‐temperature environment, blood clots began to form at the tip of their tails, resulting in black tails. The tails of the mice in the control group were normal and intact in shape. Compared with the control group, the tails of the mice in the model group were mostly black, with signs of necrosis at the tail tips, indicating the formation of thrombosis. The relative length of the black tails reached 61.13% ± 10.02% (p < 0.001). Compared with the model group, both the low‐dose (200 mg/kg) and high‐dose (400 mg/kg) DEAFF groups significantly reduced thrombosis in the tails of mice (p < 0.05, p < 0.01), and the reduction was dose dependent. Preliminary results indicate that DEAFF can effectively prevent carrageenan‐induced tail thrombosis and has the potential to be used as an antithrombotic drug.

3.4. Anti‐Inflammatory Activity of DEAFF

The statistical results of the inhibitory effect of DEAFF on mice with ear swelling are shown in Figure 3B. Compared with the control group, the degree of ear swelling in the model group mice increased significantly (p < 0.001), indicating the successful establishment of the ear swelling model. Compared with the model group, the ear swelling degree of mice in the low‐dose (200 mg/kg) and high‐dose (400 mg/kg) DEAFF groups was significantly reduced (p < 0.01, p < 0.001), and it was dose dependent. As shown in Table 2, the swelling inhibition rates reached 38.90% and 57.08%, respectively. The results show that DEAFF has a significant inhibitory effect on acute inflammation.

TABLE 2.

Experimental results of swelling degree and swelling inhibition rate in mice with ear swelling ($\overline{x}$ ± s, n = 10).

Group	Dose (mg·kg−1)	Ear swelling (mg)	Swelling inhibition rate (%)
Control	—	0.48 ± 0.23	—
Model	—	21.18 ± 3.05 ###	—
DXM	20	11.45 ± 2.86***	45.94
DEAFF‐L	200	12.94 ± 3.83**	38.90
DEAFF‐H	400	9.09 ± 3.56***	57.08

^### p < 0.001 compared with the control group.

^** p < 0.01.

^*** p < 0.001 compared with the model group.

The effect of DEAFF on the histopathology of mice with ear swelling is shown in Figure 3C. From H&E staining of mice ear tissue sections, it can be found that the connective structures of the ears in the control group of mice are intact and the capillaries are clear, whereas in the model group, the connective tissue is severely edematous, the capillaries are congested and dilated, and there are multiple inflammatory cell infiltrations in the tissue, suggesting that the inflammatory model has been successfully established. Compared with the model group, the degree of connective tissue edema, the amplitude of capillary dilation, and the infiltration of inflammatory cells were significantly reduced in the positive drug group and the low‐dose (200 mg/kg) and high‐dose (400 mg/kg) DEAFF groups, indicating that each administration group significantly improved the inflammatory response of mouse ear tissue.

3.5. Analgesic Activity of DEAFF

The statistical results of the inhibitory effect of DEAFF on acetic acid‐induced writhing in mice are shown in Figure 4B. Compared with the control group, the number of writhing mice in the model group increased significantly (p < 0.001), indicating the successful establishment of the analgesic model. Compared with the model group, the number of writhing in each administration group of mice decreased significantly (p < 0.001, p < 0.001, p < 0.001), and the low‐dose (200 mg/kg) and high‐dose (400 mg/kg) DEAFF groups were dose dependent. As shown in Table 3, the writhing inhibition rates reached 36.86% and 47.73%, respectively. The results show that DEAFF has a significant inhibitory effect on pain.

TABLE 3.

Experimental results on the number of writhing and inhibition rate of acetic acid‐induced writhing in mice ($\overline{x}$ ± s, n = 10).

Group	Dose (mg·kg−1)	Number of writhing	Writhing inhibition rate (%)
Control	—	0	—
Model	—	33.10 ± 5.82 ###	—
ASP‐2	200	11.50 ± 4.72***	65.26
DEAFF‐L	200	20.90 ± 6.50***	36.86
DEAFF‐H	400	17.30 ± 5.76***	47.73

^### p < 0.001 compared with the control group.

^*** p < 0.001 compared with the model group.

To further evaluate the regulatory effect of DEAFF on pain indicators in model mice, the content changes of PGE2, COX‐2, and β‐EP in the serum of mice in each group were detected by ELISA kits. The experimental results are shown in Figure 4C. Compared with the control group, the contents of COX‐2 and PGE2 in the model group were significantly increased (p < 0.001, p < 0.001), and the content of β‐EP was significantly decreased (p < 0.001). Compared with the model group, both the low‐dose (200 mg/kg) and high‐dose (400 mg/kg) DEAFF groups could significantly inhibit the increase of COX‐2 and PGE2 contents (p < 0.001, p < 0.001, p < 0.001, p < 0.001) and simultaneously significantly increase the content of β‐EP (p < 0.05, p < 0.01). It shows a dose‐dependent pattern. The results indicate that DEAFF has the effect of regulating pain factors in mice.

3.6. Analysis Results of Network Pharmacology

3.6.1. Identification of Core Targets and PPI Network Construction

In the compound target database, 1982 targets of DEAFF compounds were sorted out. In the disease target database, 5392 targets for inflammation, 9322 targets for pain, and 1206 targets for thrombosis were summarized. Using the Venn diagram (Figure 5A), 110 overlapping targets were determined among DEAFF, inflammation, pain, and thrombosis. These targets are considered as the core targets for DEAFF to generate various biological activities. Subsequently, the interaction relationships among the core targets were obtained from the STRING database, thereby constructing a protein–protein interaction (PPI) network (Figure 5B).

FIGURE 5.

Network pharmacological analysis. (A) Venn diagram of the targets between DEAFF and thrombus, inflammation, and pain. (B) Protein–protein interaction (PPI) network. (C) GO enrichment analysis histogram. (D) KEGG pathway analysis bubble chart. (E) The DEAFF component–target–pathway network.

3.6.2. Functional Enrichment Analysis

The GO gene function analysis and KEGG pathway analysis were conducted on the core target. The GO function analysis covered three aspects: biological process (BP), molecular function (MF), and cellular component (CC). This study presented the top 10 results for each function (Figure 5C). In the KEGG pathway analysis, a total of 421 pathways were enriched. This study, in combination with literature reports, selected 10 signaling pathways related to the biological activity of DEAFF and with high enrichment levels. The visualization results are shown in Figure 5D. The size of the bubbles in the figure represents the number of targets in the pathway, whereas the color shade reflects the size of the p‐value.

Based on the results of KEGG pathway analysis, the core targets enriched in the pathways and the corresponding compounds were sorted out, thereby constructing a compound–core target–activity pathway network (Figure 5E). The topological structure of this network was analyzed, combined with Degree, Closeness Centrality, and Betweenness Centrality, and a total of 14 key nodes, including Rap1 signaling pathway, PI3K‐Akt signaling pathway, Ras signaling pathway, MAPK signaling pathway, platelet activation, signaling and aggregation, KDR, AKT1, APP, PIK3CA, TNF, and HGF, were selected. These nodes have higher weights in the network and play important roles in the activation process of DEAFF.

3.7. Molecular Docking

In order to evaluate the protein targets KDR (PDB ID: 3WZD), AKT1 (PDB ID: 3MVH), APP (PDB ID: 6HGU), PIK3CA (PDB ID: 7L1C), TNF (PDB ID: 7YPC), and HGF (PDB ID: 5UAB), the affinity between the compounds and these proteins was examined in the experiment using molecular docking technology to test the binding status between key proteins and compounds. In the experiment, the binding energy was used as a reference index to evaluate the docking results. The lower the binding energy, the stronger the binding affinity between the compound and the protein. The docking results indicated that the compound could bind to the key protein through hydrogen bonds. The thermal map of the binding energy between the compound and the target is shown in Figure 6A. It can be seen from the heat map that the binding energies between key proteins and compounds are different. According to the level of binding energy, the best docking compound for each key protein was selected for visualization in this experiment. Figure 6B shows the best conformation between them.

FIGURE 6.

Molecular docking results. (A) Heat map shows the binding relationship between the components and the core targets. The better the binding activity, the more orange‐red the color. (B) The docking model of the key protein and the molecule with the optimal docking activity. The ligand is represented by the pink sticks; the hydrogen bonds are shown by the red dotted lines.

4. Discussion

In view of the diverse chemical structures and unique pharmacological activities of medicinal plants, people have always maintained strong research interest in medicinal plants, and their related extracts and products have been widely used in the fields of pharmaceuticals and health products. However, due to the rapid growth of market demand, many medicinal plant resources have been reduced year by year due to environmental changes, excessive reclamation, and other factors, and some species are even on the verge of extinction. It is worth noting that traditional medicinal raw materials are often taken from a certain medicinal part of medicinal plants, whereas nonmedicinal parts such as flowers, stems, leaves, and fruits produced during the growth of plants have not been effectively developed and utilized but are discarded as waste materials. Existing studies have shown that different parts of the same medicinal plant have great similarities in chemical composition and pharmacological effects, and their differences mainly lie in the amount of chemical composition content and the strength of medicinal effect (da Silva et al. 2007; Zeng et al. 2017). Therefore, the nonmedicinal parts of medicinal plants still have potential research value.

In this study, UHPLC‐Q‐Orbitrap‐MS/MS technology was employed to conduct qualitative chemical component analysis of DEAFF. A total of 30 chemical substances were identified, including 7‐methoxycoumarin, 4′,7‐dihydroxyflavanone, 5,7‐dihydroxychromone, ferulic acid, azelaic acid, 16‐hydroxyhexadecanoic acid, and 7‐hydroxycoumarin, covering various types of compounds such as flavonoids, coumarins, sesquiterpenes, and organic acids. Some of these compounds overlap with the chemical components of Ferula resin (L. Liu et al. 2026), indicating that there is a certain similarity in chemical components between nonmedicinal parts and traditional medicinal parts. Therefore, it is speculated that DEAFF has potential medicinal value, and a series of pharmacological experiments were carried out for exploration.

Inflammation is a complex pathophysiological process, and its occurrence and development are mainly triggered by the excessive secretion and cascading drive of multiple inflammatory mediators (Q. L. Zhang et al. 2022). When the inflammatory response is excessive or out of control, it will continue to damage the body's tissues, thus causing asthma, cardiovascular disease, cancer, autoimmune diseases, and other diseases (Z. Zhang, Jiang, et al. 2021). Because xylene can cause the release of inflammatory mediators such as histamine, kinin, and plasmin (Z. Zhang, Li, et al. 2021), it is often used to induce ear edema in mice to establish an acute inflammatory response model. In this study, after prophylactically administering DEAFF to mice, xylene was given to establish an acute inflammatory model in mice. The study found that DEAFF could significantly reduce the degree of ear swelling in mice, and further pathological sections showed that DEAFF could significantly reduce the degree of tissue edema and capillary dilation in the ear and reduce inflammatory cell infiltration. These results suggest that DEAFF may exert anti‐inflammatory effects in the early stage of acute inflammation by inhibiting vascular dilation and reducing plasma exudation.

During the continuous process of inflammation, not only are large amounts of pro‐inflammatory mediators released, but also the cells are lysed to release internal components, and lactic acid is produced to acidify the internal environment. The synergistic effect of the two will activate pain receptors at the nerve endings, thereby producing a sense of pain (Muley et al. 2016). The acetic acid‐induced writhing test in mice has become a classic model for studying inflammatory pain (Z. Zhang, Li, et al. 2021). This model stimulates the release of inflammatory mediators such as cytokines, prostaglandins, and bradykinin through intraperitoneal injection of acetic acid, thereby sensitizing visceral pain and causing pain (Muley et al. 2016). This study found that preadministration of DEAFF could significantly and dose‐dependently inhibit the writhing response after intraperitoneal injection of acetic acid in mice. Further kit tests indicated that DEAFF not only could reduce the contents of COX‐2 and PGE2 but also stimulate the secretion of endogenous opioid peptide (β‐EP). It is speculated that DEAFF could alleviate pain by inhibiting the expression of pain factors in the body and blocking the transmission of pain signals.

During the inflammatory process, a large number of inflammatory factors are released. When these inflammatory factors enter the bloodstream, they will damage the vascular endothelial cells and induce thrombosis (P. Wang et al. 2022). Once a thrombus forms, it will seriously threaten human health, causing circulatory disorders and abnormal cardiovascular functions (Xu et al. 2021). Chronic thrombi may further lead to ischemia, hypoxia, softening, and necrosis of brain tissue (Laufs et al. 2010). Carrageenan can trigger thrombosis related to vascular oxidative stress injury and is often used to construct animal thrombosis models. After intraperitoneal injection of carrageenan in mice, mixed thrombi appear in the tail's small veins, small arteries, and capillaries, thereby causing blood circulation disorders and tissue ischemia and necrosis in the tail. Therefore, the length of the blackened tail can be an important and intuitive indicator for evaluating the degree of thrombosis (Q. Li et al. 2020). Studies have shown that DEAFF, when given pretreatment, can effectively reduce the black tail length of model mice, and the reduction amplitude is positively correlated with the dosage of administration. It is noteworthy that the therapeutic effect of the high‐dose DEAFF group (400 mg/kg) is comparable to that of the positive drug group (ASP‐1, 100 mg/kg), demonstrating a strong antithrombotic effect.

In order to explore the potential mechanisms by which DEAFF exerts multiple pharmacological effects, this study conducted a network pharmacology investigation targeting the core targets that intersect between the identified compounds and inflammation, pain, and thrombotic diseases. The study revealed the main enriched signaling pathways of the core target. Among them, the Ras signaling pathway can phosphorylate MAPK through a series of kinase cascades, thereby activating transcription factor NF‐κB and exacerbating the development of inflammation (W. Wang et al. 2017; Zhao et al. 2024). The activation of the PI3K‐Akt/mTOR signaling pathway can induce and maintain pain sensitivity responses, and it participates in the regulation of synaptic plasticity in the central nervous system (Kondo et al. 2018; Wei et al. 2022), whereas neurotrophin acts as a peripheral pain mediator and participates in pain regulation at multiple levels (Pezet and McMahon 2006). Platelets play an important role in hemostasis and thrombosis formation. Appropriate activation and aggregation help with hemostasis at the site of vascular injury, and the released coagulation factors from activated platelets can also activate the complement and coagulation cascades, thereby accelerating thrombosis (Kanthi et al. 2014; Asif et al. 2019; Chatterjee et al. 2020). The discovery of these pathways reveals the potential signaling pathways of DEAFF's anti‐inflammatory, analgesic, and antithrombotic activities.

Subsequently, based on the enriched signaling pathways, a compound–core target–signaling pathway network was constructed, and through topological structure analysis of this network, six key proteins were identified, including TNF, PIK3CA, APP, HGF, AKT1, and KDR. Among them, TNF is a pleiotropic pro‐inflammatory cytokine that can directly act or stimulate the secretion of pro‐inflammatory mediators (Yuk et al. 2024). PIK3CA plays a key role in the signal cascade reactions of cell growth, survival, proliferation, and morphology, and its phosphorylation helps to inhibit inflammation development (You et al. 2025). APP is a cell surface receptor that has physiological functions such as promoting neural synapse growth and neuronal adhesion and plays an important role in neural signal transduction (Baumkötter et al. 2014). HGF is a secreted protein that participates in various life activities such as angiogenesis, neuroprotection, and anti‐inflammation and can regulate the expression of pro‐inflammatory cytokines to alleviate neuropathic pain (Nho et al. 2022). AKT1 is one of the three closely related serine/threonine protein kinases that regulates various BPs and can reduce the expression of selective protein on platelets and inhibit thrombosis (Su et al. 2016). KDR is a cell surface receptor for VEGFA, VEGFC, and VEGFD and plays a key role in various activities such as angiogenesis, vascular development, vascular permeability, and embryonic hematopoietic regulation (Terman et al. 1992). The excavation of these key proteins provides important evidence for a deeper understanding of the mechanism of DEAFF.

5. Conclusion

In order to fully develop the biological resources of the nonmedicinal parts of Ferula, improve economic benefits, and promote the development of the Ferula industry, this study conducted a systematic research on the chemical components and pharmacological activities of the dichloromethane extract from the nonmedicinal parts of F. ferulaeoides. The complex chemical composition spectrum of DEAFF was revealed by liquid chromatography–mass spectrometry. Through pharmacological experiments and network pharmacology studies, it was demonstrated that DEAFF has pharmacological effects in anti‐inflammation, analgesia, and antithrombosis, and the potential signaling pathways through which it exerts its effects were also revealed.

Author Contributions

Lina Liu: writing – original draft, methodology, formal analysis. Qinghai Dong: software, validation, investigation. Qi Zheng: methodology, formal analysis. Jieyu Shi: visualization, methodology. Shusen Liu: software, investigation. Zhihui Wang: formal analysis, visualization. Min Wang: methodology, project administration. Jianyong Si: methodology, investigation, resources. Jingxue Ye: investigation, formal analysis. Wenlan Li: writing – review and editing, validation. Junchi Wang: formal analysis, supervision, resources. Guibo Sun: funding acquisition, writing – review and editing.

Funding

This study was supported by the CAMS Innovation Fund for Medical Sciences (CIFMS, No. 2022‐I2M‐1‐017) and the Fundamental Research Funds in Universities of Heilongjiang Province (No. XL0211).

Ethics Statement

All experimental procedures were approved by the Laboratory Animal Ethics Committee of the Chinese Academy of Medical Sciences (Ethics Number: SLXD‐20240829016).

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Figure S1: MS/MS spectra comparing reference standards (D‐(‐)‐Quinic acid, down) and sample (up) peaks.

Figure S2: MS/MS spectra comparing reference standards (Nicotinamide, down) and sample (up) peaks.

Figure S3: MS/MS spectra comparing reference standards (Mesaconic acid, down) and sample (up) peaks.

Figure S4: MS/MS spectra comparing reference standards (2,4‐Dihydroxybenzoic acid, down) and sample (up) peaks.

Figure S5: MS/MS spectra comparing reference standards (Benzoic acid, down) and sample (up) peaks.

Figure S6: MS/MS spectra comparing reference standards (2,2′,4,4′‐Tetrahydroxybenzophenone, down) and sample (up) peaks.

Figure S7: MS/MS spectra comparing reference standards (Cyclo (phenylalanyl‐prolyl), down) and sample (up) peaks.

Figure S8: MS/MS spectra comparing reference standards (4′,7‐Dihydroxyflavanone, down) and sample (up) peaks.

Figure S9: MS/MS spectra comparing reference standards (Ferulic acid, down) and sample (up) peaks.

Figure S10: MS/MS spectra comparing reference standards (2,5‐Dihydroxybenzaldehyde, down) and sample (up) peaks.

Figure S11: MS/MS spectra comparing reference standards (Isorhamnetin‐3‐O‐glucoside, down) and sample (up) peaks.

Figure S12: MS/MS spectra comparing reference standards (Azelaic acid, down) and sample (up) peaks.

Figure S13: MS/MS spectra comparing reference standards (Isoferulic acid, down) and sample (up) peaks.

Figure S14: MS/MS spectra comparing reference standards (4‐Methoxysalicylic acid, down) and sample (up) peaks.

Figure S15: MS/MS spectra comparing reference standards (Germacrone, down) and sample (up) peaks.

Figure S16: MS/MS spectra comparing reference standards (Ethyl caffeate, down) and sample (up) peaks.

Figure S17: MS/MS spectra comparing reference standards (Corchorifatty acid F, down) and sample (up) peaks.

Figure S18: MS/MS spectra comparing reference standards (19‐Nortestosterone, down) and sample (up) peaks.

Figure S19: MS/MS spectra comparing reference standards (Arglabin, down) and sample (up) peaks.

Figure S20: MS/MS spectra comparing reference standards (Linderalactone, down) and sample (up) peaks.

Figure S21: MS/MS spectra comparing reference standards (α‐Cyperone, down) and sample (up) peaks.

Figure S22: MS/MS spectra comparing reference standards (7‐Methoxycoumarin, down) and sample (up) peaks.

Figure S23: MS/MS spectra comparing reference standards (Scopoletin, down) and sample (up) peaks.

Figure S24: MS/MS spectra comparing reference standards (Curcumol, down) and sample (up) peaks.

Figure S25: MS/MS spectra comparing reference standards (Hexadecanamide, down) and sample (up) peaks.

Figure S26: MS/MS spectra comparing reference standards (7‐Hydroxycoumarin, down) and sample (up) peaks.

Figure S27: MS/MS spectra comparing reference standards (Levistilide A, down) and sample (up) peaks.

Figure S28: MS/MS spectra comparing reference standards (16‐Hydroxyhexadecanoic acid, down) and sample (up) peaks.

Figure S29: MS/MS spectra comparing reference standards (5,7‐Dihydroxychromone, down) and sample (up) peaks.

Figure S30: MS/MS spectra comparing reference standards (Stearamide, down) and sample (up) peaks.

Data Availability Statement

Data will be made available on request.