Chemical Characterization, Network Pharmacology, Molecular Docking, and Comparative Anti‐Colitic Activity of Polar and Nonpolar Fractions From Raphanus Sativus L. Seeds

ABSTRACT

The bioactive material basis of Raphanus sativus L. seeds (Raphani Semen) against ulcerative colitis (UC) remains unclear. This study compared the chemical profiles and anti‐colitic efficacy of its nonpolar volatile oil (RSO) and polar ethanol extract (RSEE). Chemical profiling using GC‐MS and UPLC‐MS/MS revealed RSO was dominated by phytosterols, whereas RSEE was enriched in phenolic alkaloids, particularly sinapine. In a dextran sulfate sodium (DSS)‐induced murine colitis model, RSEE demonstrated superior efficacy in reducing disease activity and restoring mucosal barriers compared to RSO. Biochemically, RSEE significantly suppressed myeloperoxidase (MPO) and pro‐inflammatory cytokines while enhancing antioxidant defense. Molecular docking confirmed sinapine as a pivotal compound with high binding affinity for MPO and Keap1. Consequently, the polar fraction is identified as the primary active component, with sinapine serving as the key material basis for treating colitis via oxidative stress modulation.

This study elucidates the material basis of Raphanus sativus L. seeds against ulcerative colitis (UC). By comparing nonpolar volatile oils and polar ethanol extracts through integrated chemical profiling, network pharmacology, and in vivo validation, the findings reveal the polar fraction as the primary active component driving therapeutic efficacy.

1. Introduction

Ulcerative colitis (UC) is a chronic, nonspecific inflammatory bowel disease characterized by continuous mucosal inflammation starting from the rectum, with an incidence that is rising globally [1]. The pathogenesis of UC is multifactorial, involving complex interactions between genetic predisposition, environmental factors, and dysregulated immune responses [2]. Within this complex pathological network, accumulating evidence highlights that persistent oxidative stress and impaired colonic barrier function are critical drivers of tissue injury [3]. At the molecular level, activation of the nuclear factor kappa‐light‐chain‐enhancer of activated B cells (NF‐κB) signaling axis drives the overproduction of pro‐inflammatory cytokines, including tumor necrosis factor‐alpha (TNF‐α), interleukin‐6 (IL‐6), and interleukin‐1 beta (IL‐1β), which collectively orchestrate the characteristic cytokine storm of UC [4]. Simultaneously, excessive reactive oxygen species (ROS) generated during neutrophil activation deplete antioxidant defenses and elevate myeloperoxidase (MPO) activity, further damaging the mucosal epithelium and disrupting tight junction proteins [5]. The convergence of this inflammatory cascade and oxidative stress creates a self‐perpetuating cycle underlying the chronicity and mucosal injury characteristic of UC. Currently, the clinical management of UC relies primarily on 5‐aminosalicylic acid (5‐ASA) and biological agents to induce remission. However, the long‐term use of these agents is often limited by secondary loss of response and potential adverse effects [2]. Consequently, there is a growing interest in identifying novel therapeutic agents from natural sources that can effectively mitigate oxidative stress and restore the intestinal barrier [3].

The dried ripe seed of Raphanus sativus L. (Brassicaceae), pharmacologically known as Raphani Semen (“Laifuzi”), holds a prominent position in traditional medical systems across Asia. Its medicinal use spans over a millennium, having been first recorded in the Tang Materia Medica (Tang Bencao) and currently listed in the Pharmacopoeia of the People's Republic of China [6]. In Traditional Chinese Medicine (TCM), Raphani Semen is classically prescribed for its “Xiaoshi Chuzhang” (dispersing food stagnation and eliminating distension) and “Jiangqi Huatan” (descending Qi and resolving phlegm) functions, often used to treat digestive disorders such as diarrhea and dysentery [6, 7]. Similarly, in Korean traditional medicine, it has been documented for managing chronic intestinal complaints, including indigestion and abdominal pain [8]. This extensive ethnopharmacological history, particularly its efficacy in managing symptoms synonymous with intestinal inflammation, provides a compelling rationale for investigating its therapeutic potential in modern inflammatory pathologies of the gut, specifically UC.

The connection between the traditional use of Raphani Semen and UC received its first key scientific validation from a study demonstrating that a water extract (RWE) of Raphani Semen successfully ameliorated experimental colitis in rats via the inhibition of the p38 MAPK/NF‐κB signaling pathway [8]. While this foundational work confirmed the plant's anti‐colitic potential, critical questions regarding its specific chemical constituents remain. Traditional medicines are, by nature, chemically complex matrices. Raphani Semen, for instance, comprises the polar ethanol extract (RSEE), which mirrors the composition of water extracts, and the nonpolar volatile oil (RSO), which is rich in lipids and sterols. It remains unknown whether the therapeutic effect is exclusively driven by the polar constituents, or if the nonpolar fraction also plays a contributory, or perhaps distinct, role. A comparative study to understand the relative contributions of these chemically distinct fractions has not yet been performed. Furthermore, a comprehensive, side‐by‐side phytochemical profile of these distinct polar (RSEE) and nonpolar (RSO) fractions is necessary to correlate specific chemical classes with their biological functions.

Based on the traditional application of Raphani Semen as a water‐based decoction, we hypothesized that its anti‐colitic activity is primarily mediated by the polar constituents (RSEE), with the nonpolar volatile oil (RSO) playing a distinct or supplementary role due to their fundamental chemical differences. To validate this hypothesis and bridge the knowledge gap regarding the material basis of efficacy, the present study employed an integrated strategy combining comprehensive phytochemical profiling, network pharmacology, and in vivo validation. We conducted a head‐to‐head comparison of RSO and RSEE in a DSS‐induced murine colitis model, specifically evaluating their effects on macroscopic symptoms, mucosal barrier integrity, and key oxidative biomarkers. Furthermore, molecular docking was utilized to pinpoint specific bioactive compounds, notably sinapine, and to elucidate their molecular interactions with critical signaling targets, thereby providing a mechanistic rationale for the superior efficacy of the active fraction.

2. Results

2.1. Chemical Characterization Reveals Distinct Phytochemical Profiles of RSEE and RSO

To establish the chemical basis for potential differences in bioactivity, the phytochemical compositions of the polar ethanol extract (RSEE) and the nonpolar volatile oil (RSO) were systematically analyzed using high‐resolution mass spectrometry techniques (Figure 1). The GC‐MS total ion chromatogram of RSO is presented in Figure 2. A total of 33 compounds were identified by comparison with the NIST 14 database, accounting for 82.58% of the total peak area. As detailed in Table 1, the chemical profile of RSO was dominated by nonpolar lipidic constituents. The most abundant compounds were identified as β‐sitosterol (18.76%), ethyl docos‐13‐enoate (14.69%), cis‐Vaccenic acid (11.93%), and ethyl oleate (11.38%). Other notable components included γ‐Tocopherol (5.45%) and Campesterol (5.55%). This analysis confirms that RSO is primarily composed of fatty acids, fatty acid esters, and phytosterols, defining its distinct nonpolar chemical signature.

FIGURE 1.

Preparation protocol for the volatile oil (RSO) and ethanol extract (RSEE) from Raphani Semen. (A) Schematic flowchart illustrating the sequential extraction process. RSO was extracted using supercritical fluid CO2 extraction (SFE), and the resulting residue was subsequently subjected to ultrasonic extraction with 75% ethanol to obtain RSEE. (B) Macroscopic appearance of the obtained volatile oil (RSO), exhibiting a characteristic brownish‐yellow color.

FIGURE 2.

Total ion chromatogram (TIC) of the volatile oil from Raphanus sativus L. seeds (RSO) analyzed by GC‐MS. The x‐axis represents the retention time (min), and the y‐axis represents the relative abundance (Counts %).

TABLE 1.

Chemical composition and relative content of the volatile oil from Raphanus sativus L. seeds (RSO) identified by GC‐MS.

No.	RT(min)	Compounds	Area%	MF	MW	CAS
O1	6.628	Atractylon	0.54	C15H20O	216.319	6989‐21‐5
O2	8.122	Palmitic acid	1.46	C16H32O2	256.424	57‐10‐3
O3	8.174	Staflex BOP	0.46	C20H30O4	334.45	84‐78‐6
O4	8.279	Ethyl palmitate	1.73	C18H36O2	284.477	628‐97‐7
O5	9.171	cis‐Vaccenic acid	11.93	C18H34O2	282.461	506‐17‐2
O6	9.265	Ethyl linoleate	4.26	C20H36O2	308.50	544‐35‐4
O7	9.296	Ethyl Oleate	11.38	C20H38O2	310.514	111‐62‐6
O8	9.428	Ethyl Stearate	0.81	C20H40O2	312.53	111‐61‐5
O9	10.367	Gondoic acid	0.69	C20H38O2	310.514	5561‐99‐9
O10	10.524	n‐Propyl 11‐eicosenoate	4	C23H44O2	352.6
O11	10.56	2,2‐Dimethyl‐3‐(4‐methyl‐4‐pentenyl)‐1‐cyclopropanecarboxylic acid	0.37	C12H20O2	196.286	74779‐63‐8
O12	10.671	Ethyl icosanoate	0.6	C22H44O2	340.584	18281‐05‐5
O13	10.952	2,2‐Methylenebis(6‐Tert‐Butyl‐4‐Methylphenol)	0.5	C23H32O2	340.499	119‐47‐1
O14	11.342	1‐(2,3‐dihydro‐1H‐inden‐1‐yl)hexadecane	0.2	C25H42	342.601	55334‐29‐7
O15	11.69	Erucic acid	1.59	C22H42O2	338.568	112‐86‐7
O16	11.831	Ethyl docos‐13‐enoate	14.69	C24H46O2	366.621	37910‐77‐3
O17	11.971	Ethyl behenate	0.5	C24H48O2	368.637	5908‐87‐2
O18	12.684	trans‐9‐Octadecenoic acid, pentyl ester	1.23	C23H44O2	352.594	142‐57‐4
O19	13.06	cis‐13,16‐Docasadienoic acid	0.51	C22H40O2	336.552	7370‐49‐2
O20	13.137	cis‐15‐Tetracosenoic acid, propyl ester	0.67	C27H52O2	408.7	914306‐07‐3
O21	13.275	Ethyl tetracosanoate	0.42	C26H52O2	396.690	24634‐95‐5
O22	13.372	diisooctyl sebacate	0.21	C26H50O4	426.673	122‐62‐3
O23	13.935	3‐Ethyl‐5‐(2‐ethylbutyl)octadecane	0.47	C26H54	366.707	55282‐12‐7
O24	14.156	isopropyl linoleate	2.08	C21H38O2	322.525	22882‐95‐7
O25	15.056	γ‐Tocopherol	5.45	C28H48O2	416.68	7616‐22‐0
O26	15.161	15‐Nonacosanone	0.39	C29H58O	422.77	2764‐73‐0
O27	15.658	Epicholesterol	0.73	C27H46O	386.654	474‐77‐1
O28	16.047	(24S)‐ergosta‐5,22(E)‐dien‐3beta‐ol	2.6	C28H46O	398.664	17472‐78‐5
O29	16.578	Campesterol	5.55	C28H48O	400.68	474‐62‐4
O30	17.459	β‐sitosterol	18.76	C29H50O	414.707	83‐46‐5
O31	17.627	(14β,20β,22R,25R)‐3β‐Hydroxy‐5α‐spirost‐8‐en‐11‐one	1.14	C27H40O4	428.61	58072‐54‐1
O32	18.273	9β,19‐Cyclolanostane‐3β,25‐diol	1.84	C30H52O2	444.73	26525‐84‐8
O33	20.118	[R‐[R,R‐(E)]]‐3,7,11,15‐tetramethylhexadec‐2‐enyl palmitate	0.8	C36H70O2	534.94	53950‐58‐6

In stark contrast, the UPLC‐Q‐Orbitrap‐MS/MS analysis of RSEE, conducted in both positive and negative ion modes (Figure 3), revealed a complex mixture of polar and medium‐polarity compounds. As summarized in Table 2, a total of 58 compounds were putatively identified based on their retention times, accurate mass‐to‐charge ratios (m/z), and MS/MS fragmentation patterns, with reference to existing literature (Figures S1–S58). The identified compounds belonged to diverse chemical classes, including phenolic acids, glucosinolates, alkaloids, and small organic acids. To further characterize the key components, an HPLC fingerprint was established (Figure 4), and preliminary quantification of eleven representative markers was performed (Table S1). This analysis highlighted that the alkaloid sinapine (3.32 µg/200 µg RSEE) and the phenolic acid sinapic acid (2.02 µg/200 µg RSEE) were among the most abundant constituents in the extract. These comprehensive chemical analyses unequivocally demonstrate the fundamental chemical divergence between the two preparations, setting the stage for a comparative evaluation of their biological activities.

FIGURE 3.

Total ion chromatograms (TIC) of the ethanol extract of Raphanus sativus L. seeds (RSEE) analyzed by UPLC‐Q‐Orbitrap‐MS/MS. (A) TIC acquired in negative ion mode. (B) TIC acquired in positive ion mode.

TABLE 2.

Identification of compounds in RSEE by UPLC‐Q‐Orbitrap‐MS/MS.

NO.	RT(min)	Ion	Observed (m/z)	Formulas	Fragment ions (MS/MS)	Identifications
EE1	0.532	[M+ACN+H]+	235.18080	C14H22N2O	86, 58	Lidocaine [9]
EE2	0.808	[M‐H]−	133.01453	C4H6O5	115, 89, 73, 71	D‐(+)‐Malic acid [10]
EE3	0.852	[M+Cl]−	171.00681	C6H12O7	159, 129, 99, 87, 75	Gluconic acid [11]
EE4	0.858	[M‐H]−	199.03816	C8H12N2S2	171, 153, 125, 79	N,N‐dimethyl‐N'‐(2‐thienylmethyl)thiourea
EE5	0.864	[M‐2H+K]−	333.06027	C15H14N2O5S	241, 171, 152	N‐[3‐(aminosulfonyl)phenyl]‐2,3‐dihydro‐1,4‐benzodioxine‐2‐carboxamide
EE6	0.906	[M‐H]−	191.02020	C6H8O7	173, 129, 111, 87	Isocitric acid [12]
EE7	0.917	[M+H]+	104.10713	C5H13NO	86, 60, 58	Choline [13]
EE8	0.920	[M+H]+	266.16016	C18H19NO	248, 207, 104	4‐(dimethylamino)‐1,1‐diphenylbut‐3‐en‐2‐one
EE9	0.92	[M+H‐H2O]+	266.15925	C14H20NO4 +	248, 207, 104	Caffeoylcholine [14]
EE10	0.955	[M+H]+	126.05517	C6H7NO2	108	5‐Hydroxy‐2‐pyridinemethanol
EE11	0.98	[M+H]+	251.09166	C11H16O5	207, 175	chlamydospordiol
EE12	0.99	[M+H]+	221.08118	C12H14O5	177, 145	10‐Norparvulenone
EE13	0.992	[M+H]+	310.16528	C16H23NO5	251	Sinapine [15]
EE14	1.032	[M‐H]−	137.02464	C7H6O3	93	Salicylic acid [16]
EE15	1.05	[M+H]+	149.07345	C8H4O3	121, 108	Phthalic anhydride [17]
EE16	1.086	[M+H]+	208.13354	C12H18NO2 +	149, 117, 105	Benzoylcholine [14]
EE17	1.11	[M‐H+HAc]−	179.05653	C6H12O6	119, 113, 89, 71, 59	D‐(+)‐Galactose [18]
EE18	1.149	[M‐H]−	289.11243	C10H18N4O6	258, 209, 96	Argininosuccinic acid [19]
EE19	1.202	[M+H]+	127.03924	C6H6O3	109, 81	5‐(Hydroxymethyl)furfural [17]
EE20	1.34	[M+FA‐H]−	387.16588	C12H22O11	341, 221, 179, 161, 143, 101, 89	α,α‐Trehalose [20]
EE21	1.348	[M+H]+	176.02017	C6H9NOS2	169, 159, 144, 128, 112	Sulforaphene [17]
EE22	1.742	[M‐H‐H2O]−	113.02468	C5H8O4	95, 85, 57	Monoethyl malonic acid [12]
EE23	7.739	[M‐H]−	753.22644	C34H42O19	547, 223, 205	1,2‐disinapoylgentiobiose [21]
EE24	7.768	[M+H+MeOH]+	207.06552	C11H12O5	175, 157, 147, 119, 91	Sinapinic acid [22]
EE25	10.125	[M‐H]−	311.22354	C18H32O4	293, 275, 223, 87	9‐HpODE [23]
EE26	10.855	[M+H]+	236.16476	C14H21NO2	208, 124, 113, 96, 86, 71	4'‐Methoxy‐α‐ethylaminovalerophenone
EE27	11.835	[M+H]+	415.21210	C24H30O6	135, 119	Bis(4‐ethylbenzylidene)sorbitol
EE28	12.509	[M+H]+	274.27423	C16H32O2	256	Palmitic Acid [24]
EE29	14.422	[M+H]+	318.30051	C18H39NO3	300, 282, 60	Phytosphingosine [25]
EE30	15.553	[M‐H]−	295.22833	C18H32O3	277, 195, 183	9‐Hydroxy‐10,12‐octadecadienoic acid [17]
EE31	15.898	[M‐H]−	277.21774	C18H30O2	233, 169	γ‐Linolenic acid [26]
EE32	16.225	[M+H]+	295.22702	C18H30O3	277, 179, 161, 135, 99, 71	9‐Oxo‐10(E),12(E)‐octadecadienoic acid [27]
EE33	16.722	[M+H+MeOH]+	357.30029	C21H40O4	339, 296, 265, 247	Monoolein [28]
EE34	17.259	[M+H]+	337.27390	C21H38O4	319, 263, 245, 175	1‐Linoleoyl glycerol
EE35	17.862	[M+H]+	510.35611	C25H52NO7P	492, 184, 104, 86	1‐heptadecanoyl‐2‐hydroxy‐sn‐glycero‐3‐phosphocholine
EE36	17.945	[M‐H]−	295.22842	C18H32O3	277, 251, 183	Coriolic acid [29]
EE37	18.484	[M+H]+	324.29007	C20H37NO2	306, 263, 245, 62	Linoleoyl ethanolamide
EE38	18.83	[M+H‐H2O]+	313.27393	C20H34O2	257, 239, 123, 109	Linolenic acid ethyl ester
EE39	19.082	[M+H]+	333.28967	C22H36O2	265, 247, 205, 149, 135, 121, 109	Ethyl Arachidonate [30]
EE40	19.36	[M+H]+	524.37170	C26H54NO7P	184, 104	1‐Stearoyl‐sn‐glycero‐3‐phosphocholine
EE41	20.261	[M+FA‐H]−	489.30759	C24H44O7	323, 295, 281	Stearyl citrate [12]
EE42	20.386	[M‐H]−	277.21768	C18H30O2	259, 233	α‐Linolenic acid [31]
EE43	20.63	[M+H]+	326.30548	C20H39NO2	309, 62	Oleoyl ethanolamide
EE44	20.861	[M+FA‐H]−	271.22836	C16H32O3	225	16‐Hydroxyhexadecanoic acid [12]
EE45	21.273	[M+H]+	256.26367	C16H33NO	239, 205	N,N‐Diethyldodecanamide
EE46	21.828	[M+H]+	277.21640	C16H30O2	259, 235, 207, 107, 93, 81	Palmitoleic Acid [32]
EE47	22.462	[M‐H]−	279.23340	C18H32O2	267, 233, 209	Rumenic acid
EE48	22.519	[M‐H]−	379.15918	C23H24O5	361, 333, 116, 99, 71	7‐[(2E)‐3,7‐dimethylocta‐2,6‐dienoxy]‐1,3‐dihydroxyxanthen‐9‐one
EE49	23.892	[M‐H]−	479.33868	C28H48O6	429, 381, 347	Brassinolide [17]
EE50	25.056	[M‐H]−	428.31729	C27H43NO3	292, 280, 164,147	N‐Oleoyl‐Phenylalanine
EE51	25.491	[M+H]+	341.30505	C22H38O2	285, 267,123,109, 85	Dihomo‐γ‐linolenic acid ethyl ester
EE52	25.514	[M‐H]−	281.24911	C18H34O2	224	Oleic acid [33]
EE53	25.522	[M+H]+	284.29501	C18H37NO	181	Stearamide [27]
EE54	26.158	[M‐H]−	407.19034	C19H32O7	403, 395, 364, 125, 116, 99	Byzantionoside B
EE55	26.913	[M+H]+	224.07422	C9H7NO	160,132, 118	Indole‐3‐carboxaldehyde [34]
EE56	27.079	[M+H]+	310.31064	C20H41NO2	251, 218	Stearoyl Ethanolamide [35]
EE57	29.26	[M‐H]−	283.26489	C18H36O2	240, 216	Stearic acid [36]
EE58	29.91	[M+NH4]+	338.34177	C22H43NO	321, 303	Erucamide [37]

FIGURE 4.

HPLC profile and chemical structures of key constituents in RSEE. (A) Stacked chromatograms showing the separation of the ethanol extract of Raphanus sativus L. seeds (RSEE, top trace) compared with eleven mixed reference standards (1‐11, bottom traces). (B) Chemical structures of the identified compounds. Peak identification: 1, Niacin; 2, Gallic acid; 3, 5‐Hydroxymethylfurfural (5‐HMF); 4, Protocatechuic acid; 5, Sinapine; 6, Sulforaphane; 7, Sulforaphene; 8, Sinapic acid; 9, Indole‐3‐carboxaldehyde; 10, Salicylic acid; 11, 7‐Methoxycoumarin.

2.2. Comparative Efficacy of RSEE and RSO in Ameliorating Macroscopic Symptoms and Colonic Atrophy in DSS‐Induced Colitis

Based on the distinct chemical profiles established above, we conducted a comparative evaluation of the therapeutic efficacy of RSEE and RSO in a DSS‐induced murine colitis model. As illustrated in Figure 5A, mice in the DSS model group suffered from a progressive and significant decline in body weight starting from day 3. This physical deterioration was accompanied by severe disease symptoms, including diarrhea and gross rectal bleeding, culminating in a sharp elevation of the Disease Activity Index (DAI) scores (Figure 5B).

FIGURE 5.

Comparative effects of RSEE and RSO on macroscopic symptoms and colonic atrophy in DSS‐induced colitis. (A) Daily body weight changes expressed as a percentage of the initial weight on day 0. (B) DAI scores assessed on day 7. (C) Representative macroscopic images of colons excised from each group, showing the severity of hyperemia and shortening. (D) Statistical quantification of colon length. Data are expressed as mean ± SD (n = 6). Significance is indicated as *p < 0.05, **p < 0.01, and ***p < 0.001 compared with the DSS model group (MC); ns, not significant.

Oral administration of the extracts yielded divergent therapeutic outcomes. Both RSO and RSEE treatments were effective in mitigating these symptoms. RSO treatment provided significant symptom relief compared to the model group. However, RSEE demonstrated a significantly more profound protective effect. Notably, high‐dose RSEE treatment (RSEE‐H, 200 mg/kg) potently attenuated weight loss and suppressed the DAI score to a level even lower than that of the positive control drug, sulfasalazine (SASP) (Figure 5B). This suggests that while the volatile oil (RSO) contributes to the bioactivity, the polar constituents (RSEE) possess superior efficacy in managing the macroscopic manifestations of colitis.

Colonic shortening serves as a hallmark macroscopic indicator of intestinal inflammation and edema. As shown in Figure 5C,D, the colon length in the model group was markedly reduced, presenting with visible hyperemia and tissue swelling. Both RSEE and RSO treatments counteracted this pathological shortening. Consistent with the macroscopic observations, the RSEE‐H group exhibited robust preservation of colonic morphology, maintaining colon lengths comparable to the control group. Collectively, these findings provide the first line of evidence that while RSO exhibits partial anti‐colitic activity, the therapeutic potency of Raphanus sativus L. seeds is predominantly driven by its polar constituents (RSEE).

2.3. RSEE and RSO Alleviate Colonic Histopathological Damage and Restore Mucosal Barrier Integrity

To corroborate the macroscopic observations at a microscopic level, colonic tissues were subjected to histological examination. H&E staining (Figure 6A) of sections from the DSS model group revealed severe architectural disruption, characterized by extensive erosion of the mucosal epithelium, widespread loss of crypts, and massive infiltration of inflammatory leukocytes. Treatment with both RSO and RSEE ameliorated these pathological changes, albeit to varying degrees. RSO administration provided partial protection, evidenced by a reduction in inflammatory cell infiltration, although some crypt damage persisted. In contrast, the RSEE‐H group exhibited remarkable preservation of the colonic architecture. The crypts were well‐formed and regularly arranged, closely resembling the histological features of the Normal Control group. Quantitative histopathological scoring (Figure 6C) confirmed these observations, demonstrating that the MC group exhibited significantly elevated scores compared to the NC group, while both RSO and RSEE treatments reduced the scores dose‐dependently, with RSEE‐H achieving the most pronounced reduction.

FIGURE 6.

Histological and immunofluorescence (IF) assessment of colonic tissues. (A) Representative Hematoxylin and Eosin (H&E) staining images of colon sections from distinct experimental groups (Scale bar = 100 µm). (B) Representative Periodic Acid‐Schiff (PAS) staining images indicating mucin‐secreting goblet cells (Scale bar = 100 µm). (C) Quantitative analysis of the histopathological score based on H&E staining. (D) Quantitative analysis of goblet cells per crypt based on PAS staining. (E) IF staining for tight junction proteins. Colon sections were labeled with antibodies against Claudin‐1 (Red) and Occludin (Green). Nuclei were counterstained with DAPI (Blue) (Scale bar = 100 µm). Data are expressed as mean ± SD (n = 6). ***p < 0.001, ****p < 0.0001 indicate statistically significant differences between the marked groups.

The integrity of the intestinal mucosal barrier relies heavily on the mucus layer secreted by goblet cells. PAS staining was employed to visualize these mucin‐producing cells (Figure 6B). In the DSS model group, a near‐total depletion of goblet cells was observed, indicating a severe compromise of the chemical barrier. RSO treatment resulted in a noticeable recovery of goblet cells compared to the model group. However, the restorative effect was most pronounced in the RSEE‐H group, which showed a dramatic restoration of both goblet cell number and mucin secretion, re‐establishing a continuous protective shield over the epithelial surface. Quantitative analysis of goblet cell density (Figure 6D) corroborated these findings: goblet cells per crypt were markedly reduced in the MC group compared to NC, and were dose‐dependently restored by RSEE treatment, with RSEE‐H achieving near‐complete recovery to NC levels.

To further investigate the molecular basis of barrier repair, we assessed the expression of key tight junction proteins, Claudin‐1 and Occludin, via IF (Figure 6E). In DSS‐treated mice, the fluorescence intensity of both proteins was significantly diminished, and their characteristic honeycomb‐like distribution was disrupted. Both RSO and RSEE treatments counteracted this loss. Mice treated with RSO displayed a partial upregulation of these proteins. However, RSEE treatment, particularly at the high dose, was significantly more effective. It not only restored the high expression levels of Claudin‐1 and Occludin but also re‐established their proper continuous localization at the apical cell borders, thereby reinforcing the physical seal of the intestinal barrier.

2.4. Network Pharmacology Unveils the Multi‐Target Synergistic Therapeutic Action of RSEE

To elucidate the molecular mechanisms underlying the distinct therapeutic efficacies observed in vivo, we conducted a comparative network pharmacology analysis. The intersection of potential drug targets and UC‐related disease targets was visualized using a Venn diagram (Figure 7A). RSEE shared a significantly larger number of common targets with UC (26 targets) compared to RSO (12 targets), suggesting a broader pharmacological coverage for the polar fraction.

FIGURE 7.

Comparative network pharmacology analysis elucidates the distinct molecular mechanisms of RSEE and RSO. (A) Venn diagram illustrating the intersection of potential therapeutic targets between RSO, RSEE, and UC. (B) Protein‐Protein Interaction (PPI) network of RSO‐associated targets. (C) PPI network of RSEE‐associated targets. (D) Component‐Target network visualization. The network connects the identified active constituents of RSO (left) and RSEE (right) to their respective gene targets (center). The color of the nodes represents Degree Centrality, ranging from light yellow to dark blue, indicating the relative importance (number of connections) of each component and target within the network.

PPI networks were subsequently constructed to analyze the topological relationships among these targets. The RSO network (Figure 7B) appeared relatively fragmented, primarily revolving around lipid‐sensing and enzymatic nodes such as PPARG, AKT1, and PTGS2 (COX‐2), indicating a more discrete mechanism of action. In sharp contrast, the RSEE network (Figure 7C) exhibited a highly dense and interconnected architecture. Crucially, this network was dominated by central upstream regulators of inflammation, including RELA (NF‐κB p65), TLR4, JAK1, JAK2, and STAT3. The extensive connectivity among these hubs suggests that RSEE exerts its potent anti‐colitic effects by orchestrating a systemic suppression of synergistic signaling pathways, particularly the NF‐κB and JAK‐STAT axes.

To identify the specific material basis responsible for these effects, a Component‐Target network was established (Figure 7D). The visual analysis, color‐coded by degree centrality, revealed that β‐sitosterol and Ethyl Oleate were the primary active ligands in RSO, mainly targeting PTGS2 and PPARG. Notably, β‐sitosterol's interactions with PTGS2 (COX‐2) suggest a mechanism of action primarily through the arachidonic acid metabolism and prostaglandin biosynthesis pathways, providing a molecular rationale for RSO's observed symptomatic relief effects. Its targeting of PPARG further implicates lipid metabolism as a key component of RSO's biological activity^{2 9}. Conversely, the key components of RSEE, specifically sinapine and sinapic acid, emerged as high‐degree nodes with extensive connections to critical inflammatory mediators such as EGFR, NOS2, and RELA. This “multi‐component, multi‐target” interaction pattern provides a robust molecular rationale for the superior efficacy of RSEE in mitigating colonic inflammation and oxidative stress.

2.4.1. GO and KEGG Enrichment Analysis

To further explore the biological functions of the identified targets, Gene Ontology (GO) and KEGG pathway enrichment analyses were performed. The GO analysis for RSO (Figure S1A) revealed a functional profile closely related to enzymatic regulation and response to stress, with significant enrichment in prostaglandin‐endoperoxide synthase activity and cellular response to hypoxia. This aligns with our previous finding that RSO primarily targets PTGS2 (COX‐2) and HIF‐1A. In contrast, the GO analysis for RSEE (Figure 8A) highlighted a broader involvement in signal transduction and tissue repair, characterized by terms such as protein tyrosine kinase activity, epidermal growth factor receptor (EGFR) signaling pathway, and vascular endothelial growth factor signaling pathway. The KEGG pathway enrichment analysis provided more specific mechanistic insights. As shown in Figure S1B, the therapeutic action of RSO is predominantly mediated through metabolic and lipid‐related pathways, including Arachidonic acid metabolism, Regulation of lipolysis in adipocytes, and Lipid and atherosclerosis. This suggests that RSO exerts its anti‐inflammatory effects primarily by modulating lipid mediators and blocking the arachidonic acid cascade.

FIGURE 8.

GO functional annotation and KEGG pathway enrichment analyses. (A) The top enriched GO terms for RSEE targets. Biological Process (blue), Cellular Component (green), and Molecular Function (pink). (B) Bubble charts showing the top enriched KEGG pathways for RSEE. The x‐axis represents the number of genes enriched in each pathway. The size of the bubbles correlates with the gene count, and the color gradient indicates the statistical significance (p‐value).

Conversely, RSEE (Figure 8B) exhibited a comprehensive regulatory capacity over the core immunopathology of UC. Notably, the disease‐specific pathway “Inflammatory bowel disease (IBD)” was significantly enriched, directly validating the relevance of RSEE to the experimental model. Furthermore, RSEE significantly enriched key upstream inflammatory signaling pathways, specifically NF‐κB signaling pathway, TNF signaling pathway, Toll‐like receptor signaling pathway, and JAK‐STAT signaling pathway. Additionally, pathways related to mucosal barrier integrity (Focal adhesion, Adherens junction) and immune balance (Th17 cell differentiation) were also enriched. Collectively, these results indicate that unlike the metabolically‐focused RSO, RSEE functions as a multi‐target systemic modulator, simultaneously suppressing inflammation, restoring immune homeostasis, and promoting mucosal repair.

2.5. Biochemical Validation of Anti‐Inflammatory and Antioxidant Activities and Molecular Docking Analysis

To evaluate the therapeutic effects of the different extracts on colonic inflammation and oxidative stress, quantitative biochemical assays were performed. As illustrated in Figure 9A–C, the DSS model group exhibited a cytokine storm, characterized by significantly elevated protein levels of IL‐6, IL‐1β, and TNF‐α compared to the Normal Control (NC) group. Both RSO and RSEE treatments effectively reversed this trend. Administration of RSO (both low and high doses) significantly downregulated the levels of these pro‐inflammatory cytokines. Similarly, RSEE treatment exerted a potent inhibitory effect, reducing cytokine concentrations to levels comparable to the positive control (SASP).

FIGURE 9.

Effects of RSO and RSEE on colonic inflammatory mediators and oxidative stress markers, and molecular docking analysis. (A–C) Protein levels of pro‐inflammatory cytokines IL‐6 (A), IL‐1β (B), and TNF‐α (C) in colonic tissues determined by ELISA. (D) MPO activity in colonic tissues, indicating neutrophil infiltration. (E) The 3D binding mode of Sinapine (a key component of RSEE) with MPO (PDB: 1MZM). (F) SOD activity in colonic tissues, indicating antioxidant capacity. (G) The 3D binding mode of Sinapine with Keap1 (PDB: 4L7B). Data are presented as mean ± SD (n = 6). Statistical significance was analyzed by one‐way ANOVA: *p < 0.05 and ****p < 0.0001 compared with the Model Control group (MC).

In addition to cytokine suppression, the impact on tissue oxidative status was assessed. The activity of MPO, a marker of neutrophil infiltration, was sharply increased in the model group but was significantly inhibited by both RSO and RSEE treatments (Figure 9D). Notably, the low dose of RSO (RSO‐L) and the high dose of RSEE (RSEE‐H) demonstrated particularly strong efficacy in suppressing MPO activity. Furthermore, the activity of the antioxidant enzyme SOD, which was depleted by DSS, was successfully restored in all treatment groups (Figure 9F). The restoration of SOD activity in the RSO and RSEE groups was statistically significant, indicating that both extracts possess strong antioxidant capabilities. To further explore the molecular basis for these activities, particularly the notable effects of RSEE, molecular docking was performed using sinapine, the major active constituent of RSEE (Full docking scores for all compounds are listed in Table S2). The docking simulation revealed a strong binding affinity between sinapine and MPO, with a docking score of ‐9.225 kcal/mol. As shown in Figure 9E, sinapine occupied the catalytic pocket of MPO and formed hydrogen bonds with Asn 37. Additionally, sinapine exhibited favorable binding to Keap1 (Score: −5.329 kcal/mol), the negative regulator of the antioxidant transcription factor Nrf2. Figure 9G depicts sinapine binding to the Kelch domain of Keap1 via interactions with Ser 602 and Asn 414.

2.6. Discussion

UC is a recalcitrant inflammatory bowel disease characterized by persistent mucosal inflammation and oxidative stress [2, 3]. Raphanus sativus L. seeds (Raphani Semen) have been historically employed in TCM for promoting digestion and alleviating distension, suggesting potential gastrointestinal regulatory effects [6, 7]. While previous studies have indicated the anti‐colitic potential of its water extract, the specific bioactive fractions and their underlying molecular mechanisms remained elusive [8]. In the present study, we successfully deconstructed the therapeutic efficacy of Raphani Semen by isolating its nonpolar volatile oil (RSO) and polar ethanol extract (RSEE). Our comparative investigation provides the first evidence that while both fractions contribute to the anti‐colitic activity, RSEE exerts a superior, systemic therapeutic effect, whereas RSO functions primarily through a distinct metabolic pathway.

Our comparative analysis revealed distinct mechanistic profiles between the two fractions, mirroring their distinct chemical profiles. RSO, dominated by phytosterols such as β‐sitosterol (18.76%), was characterized by network pharmacology as primarily targeting lipid metabolism and enzymatic pathways. Specifically, β‐sitosterol has been widely reported to exert anti‐inflammatory effects by interfering with the NF‐κB and p38 MAPK pathways [38] and inhibiting the synthesis of pro‐inflammatory mediators like iNOS and COX‐2 [39]. In the context of colitis, the overexpression of COX‐2 is a critical driver of mucosal injury and carcinogenesis [40]. Our findings suggest that RSO functions analogously to selective COX‐2 inhibitors [39], effectively mitigating macroscopic symptoms by dampening the prostaglandin cascade. However, while phytosterols like β‐sitosterol can modulate immune responses in specific contexts such as rheumatoid arthritis [41] or viral infection [42], our results indicate that in the acute DSS colitis model, RSO's potency in suppressing the upstream cytokine storm (TNF‐α, IL‐6) was less comprehensive than that of RSEE. This suggests that RSO acts more as a metabolic modulator and symptomatic reliever rather than a broad‐spectrum systemic immune modulator.

In contrast, RSEE, enriched with phenolic acids (sinapic acid) and alkaloids (sinapine), exhibited robust multi‐target efficacy by modulating critical upstream inflammatory regulators, specifically TLR4 and RELA (NF‐κB). The TLR4/NF‐κB signaling axis is the primary driver of the excessive immune response in UC. By blocking this central axis, RSEE potently suppressed the downstream secretion of TNF‐α, IL‐6, and IL‐1β. This aligns with previous reports that sinapic acid can ameliorate inflammatory damage by suppressing NF‐κB activation and downregulating iNOS and COX‐2 expression [43]. Furthermore, sinapic acid has been shown to protect against oxidative injury via the Nrf2/HO‐1 pathway in diabetic cardiomyopathy [44], which corroborates our observation of restored SOD levels and reduced MPO activity in the RSEE group. Thus, RSEE acts as a systemic immune modulator, offering a more fundamental resolution to the inflammatory pathology by simultaneously blocking the NF‐κB‐driven cytokine storm and activating Nrf2‐mediated antioxidant defense.

Beyond inflammation suppression, mucosal healing, which is characterized by the regeneration of goblet cells and the integrity of tight junctions, is now considered a key therapeutic goal in UC management, as it predicts a lower risk of colectomy and cancer [45]. We observed that RSEE was significantly more effective than RSO in restoring the intestinal barrier, evidenced by the preservation of mucin‐secreting goblet cells and the re‐organization of Claudin‐1 and Occludin. This superior efficacy may be attributed to specific constituents enriched in RSEE, particularly Indole‐3‐carboxaldehyde (I3A), which was identified in our LC‐MS analysis. Indole derivatives are known ligands for the Aryl Hydrocarbon Receptor (AhR). Recent studies have demonstrated that Indole‐3‐aldehyde can reduce inflammatory cytokines (IL‐6, TNF‐α) and significantly improve gut permeability by upregulating tight junction proteins via AhR activation [46]. While further validation is required, the presence of such barrier‐protective ligands suggests that RSEE combats colitis not only by suppressing inflammation but also by actively promoting tissue regeneration through the AhR signaling pathway.

Oxidative stress driven by neutrophil infiltration is a recognized hallmark of DSS‐induced colitis, contributing significantly to mucosal injury and epithelial barrier dysfunction [47]. In the present study, we highlighted sinapine, the most abundant constituent of RSEE, as a pivotal bioactive molecule responsible for the observed dramatic reduction in MPO activity and the restoration of SOD levels. Our molecular docking analysis provided a compelling structural rationale for these protective effects, suggesting a dual mechanism of action. First, sinapine exhibited an exceptionally high binding affinity (−9.225 kcal/mol) for the catalytic pocket of MPO. While specific reports on MPO inhibition by sinapine are limited, sinapine has been identified as the most abundant antioxidant in Brassica species, exhibiting potent radical scavenging and DNA protective activities [48]. Furthermore, its hydrolytic metabolite, sinapic acid, has been shown to effectively mitigate tissue injury by suppressing MPO activity and inhibiting NF‐κB signaling [49]. Consistent with these structural properties, our docking data suggest that sinapine may directly occupy the active site of MPO, thereby preventing the generation of hypochlorous acid (HOCl), a potent tissue‐damaging oxidant. Second, the interaction between sinapine and the Kelch domain of Keap1 points to the activation of the Nrf2 pathway. It is well‐established that disrupting the Nrf2‐Keap1 interaction facilitates the nuclear translocation of Nrf2, triggering the transcription of cytoprotective genes. Previous studies have demonstrated that sinapine can modulate key signaling pathways, including the downregulation of NF‐κB activation [50], and that sinapic acid exerts protective effects specifically via the Nrf2/HO‐1 axis [49]. Our docking model supports a mechanism of competitive inhibition by sinapine, which aligns with the observed upregulation of downstream antioxidant enzymes, particularly SOD, in RSEE‐treated mice. Collectively, these findings propose sinapine as a promising lead compound for targeting the oxidative axis in IBD therapeutics.

Despite the promising findings, this study has several important limitations. Most critically, the mechanistic conclusions regarding RSEE's action through the NF‐κB/TLR4 signaling axis and the Nrf2/Keap1 pathway are based primarily on network pharmacology predictions and molecular docking simulations. However, a limitation of the current study is the lack of direct molecular‐level validation; specific techniques such as Western blotting, qPCR, or immunohistochemical analyses were not conducted to experimentally confirm the protein or gene expression of key targets, including TLR4, NF‐κB p65, and Nrf2. Therefore, these pathway‐level conclusions should be interpreted as mechanistic hypotheses requiring further experimental confirmation. Second, while molecular docking predicts high binding affinity between sinapine and MPO/Keap1, direct enzymatic inhibition assays or surface plasmon resonance (SPR) experiments are warranted to physically validate these interactions. Third, although the presence of I3A suggests an AhR‐mediated mechanism for barrier restoration, the specific activation of the AhR pathway requires confirmation via Western blotting or gene knockout models. Finally, the pharmacokinetic profile of RSEE and its active metabolites in the colon needs further investigation to bridge the gap between in vitro potential and in vivo bioavailability. We further note that, although the biochemical assays confirmed that both fractions attenuated the inflammatory and oxidative burden, the downstream markers examined here (the pro‐inflammatory cytokines, MPO, and SOD; Figure 9) did not fully discriminate the effect of RSEE from that of RSO; rather, the fraction‐specific differences were most evident at the levels of overall in vivo efficacy, mucosal‐barrier restoration, and the breadth of the predicted target networks. In particular, the phosphorylation status of the core NF‐κB signalling nodes and other upstream biomarkers were not directly assessed in this study. Targeted protein‐level analyses of these phosphorylated mediators therefore represent an important next step to formally delineate the divergent mechanisms of the polar (RSEE) and nonpolar (RSO) fractions.

In summary, this study provides a comprehensive comparative analysis of the polar and nonpolar fractions of Raphanus sativus L. seeds. We demonstrated that the polar ethanol extract (RSEE) is the primary active fraction responsible for the anti‐colitic efficacy, driven by a synergistic mechanism involving NF‐κB/TLR4 pathway suppression, mucosal barrier restoration, and Nrf2‐mediated antioxidant defense. The RSO plays a supplementary role, likely through lipid metabolism and COX‐2 inhibition. Furthermore, we identified sinapine as a key material basis for the observed therapeutic effects. These insights not only validate the traditional use of Raphani Semen but also provide a scientific basis for its potential application as a modern phytomedicine or dietary supplement for the management of UC.

3. Conclusions

In conclusion, this study deconstructed the anti‐colitic efficacy of Raphanus sativus L. seeds by systematically comparing its nonpolar volatile oil (RSO) and polar ethanol extract (RSEE). Our experimental findings demonstrate that RSEE is the predominant active fraction, exhibiting superior efficacy in ameliorating macroscopic disease symptoms, preserving colonic morphology, and restoring the intestinal mucosal barrier compared to RSO. Biochemically, RSEE exerted robust anti‐inflammatory and antioxidant effects by suppressing the cytokine storm (TNF‐α, IL‐6, and IL‐1β) and reversing oxidative stress markers (MPO, SOD). Furthermore, combined chemical profiling and molecular docking identified sinapine as a critical material basis for these observed therapeutic effects. These findings validate the traditional application of Raphani Semen and highlight RSEE, enriched with sinapine, as a promising candidate for the treatment of UC.

4. Experimental Section

4.1. Chemicals and Reagents

Dextran sulfate sodium (DSS; molecular weight 36–50 kDa; Cat. No. 160110) was procured from MP Biomedicals (Irvine, CA, USA). Sulfasalazine (SASP; Cat. No. S0883) was purchased from Sigma‐Aldrich (St. Louis, MO, USA). Acetonitrile and formic acid (HPLC grade), along with dichloromethane (chromatography grade), were obtained from Macklin (Shanghai, China). Ultrapure water was generated in‐house using a laboratory water purification system. Commercial assay kits for the determination of superoxide dismutase (SOD; Cat. No. BC0175) and myeloperoxidase (MPO; Cat. No. BC5715) activities were purchased from Beijing Solarbio Science & Technology Co., Ltd. (Solarbio, Beijing, China). Enzyme‐linked immunosorbent assay (ELISA) kits for tumor necrosis factor‐alpha (TNF‐α; Cat. No. E‐EL‐M3113C), interleukin‐1 beta (IL‐1β; Cat. No. E‐EL‐M0037C), and interleukin‐6 (IL‐6; Cat. No. E‐EL‐M0044C) were supplied by Elabscience Biotechnology Co., Ltd. (Xiamen, China). Primary antibodies against Occludin and Claudin‐1, as well as the Cy3‐conjugated secondary antibody, were sourced from Jackson ImmunoResearch (West Grove, PA, USA). DAPI for nuclear staining was obtained from Beyotime (Shanghai, China). All other chemicals and reagents used were of analytical grade.

4.2. Preparation of Plant Extracts

The dried mature seeds of Raphanus sativus L. (Raphani Semen) were obtained from the Department of Pharmacy, The First Affiliated Hospital of Jinan University (Guangzhou, China). The seeds were pulverized using a grinder (FW100, Taisite Instrument Co., Tianjin, China) and sieved. The resulting powder was stored in sealed bags in a cool, dry place until extraction. The overall preparation workflow is illustrated in Figure 1A.

4.2.1. Preparation of the Volatile Oil (RSO)

Supercritical fluid CO₂ extraction (SFE) was employed to extract the volatile oil. The powdered seeds were loaded into the extraction vessel of an SFE apparatus (HA220‐50‐06‐C, Hua'an Supercritical Extraction Co., Nantong, China). The extraction was conducted under optimized conditions: a temperature of 45°C, pressure of 20 MPa, and a static extraction time of 2.5 h. The resulting oil, exhibiting a characteristic brownish‐yellow appearance (Figure 1B), was collected, weighed, and designated as RSO. The yield of RSO was calculated to be approximately 2.08% (w/w). The oil was stored in airtight containers at 4°C in the dark.

4.2.2. Preparation of the Ethanol Extract (RSEE)

To maximize resource utilization, the residue remaining after the SFE process was collected and subjected to ultrasound‐assisted extraction, as depicted in Figure 1A. The residue was mixed with 75% (v/v) aqueous ethanol at a solid‐to‐liquid ratio of 1:10 (g/mL). Extraction was performed using an ultrasonic cleaner (SK 3200H, Kedao Ultrasonic Instrument Co., Shanghai, China) at 150 W for 40 min. This process was repeated three times. The extracts were combined, filtered, and the supernatant was concentrated under reduced pressure at 47°C using a rotary evaporator. The concentrate was subsequently dried in a vacuum desiccator to yield a paste‐like extract, designated as RSEE. The yield of RSEE was 11.8% (w/w). The extract was stored at 4°C until further biological evaluation.

4.3. Phytochemical Characterization

4.3.1. Gas Chromatography‐Mass Spectrometry (GC‐MS) Analysis of RSO

The GC‐MS analysis was performed in accordance with previously established methods with minor modifications [51]. For chemical profiling, RSO was diluted with dichloromethane to a final concentration of 25 mg/mL. The solution was filtered through a 0.22 µm membrane, and a 1 µL aliquot was injected into an Agilent ATOMX‐7890B‐5977B GC‐MS system (Agilent Technologies, Santa Clara, CA, USA). Chromatographic separation was achieved on an HP‐5MS capillary column (30 m × 0.25 mm × 0.25 µm). High‐purity helium was used as the carrier gas at a constant flow rate of 1.0 mL/min. The injector temperature was set at 250°C with a split ratio of 5:1. The oven temperature was programmed as follows: initial temperature of 80°C, held for 1 min; increased to 230°C at a rate of 20°C/min; then increased to 300°C at a rate of 10°C/min and held for 8 min. The mass spectrometer was operated in electron ionization (EI) mode at 70 eV. The ion source and quadrupole temperatures were maintained at 230°C and 150°C, respectively. Full scan mode was used with a mass range of 50–550 m/z. Compound identification was performed by comparing the mass spectra with the National Institute of Standards and Technology (NIST) 14 library. The relative content of each component was calculated using the peak area normalization method.

4.3.2. UPLC‐Q‐Orbitrap‐MS/MS Analysis of RSEE

RSEE was dissolved in methanol to a concentration of 25 mg/mL and filtered through a 0.22 µm membrane. A 10 µL aliquot was injected into a Thermo Scientific Ultimate 3000 UPLC system coupled to a Q Exactive Orbitrap mass spectrometer (Thermo Scientific, Bremen, Germany). Separation was performed on a Hypersil GOLD C18 column (100 × 2.1 mm, 1.9 µm; Thermo Fisher Scientific). The mobile phase consisted of (A) 0.1% formic acid in water and (B) acetonitrile, delivered at a flow rate of 0.30 mL/min. The gradient elution program was as follows: 5%–8% B (0–5 min), 8%–13% B (5‐6 min), 13%–35% B (6–23 min), 35%–95% B (23–25 min), and 95%–100% B (25–28 min). The mass spectrometer was equipped with a heated electrospray ionization (HESI‐II) source and operated in both positive and negative ion modes. The source parameters were: source voltage, 5 kV; capillary voltage, 40 V; tube lens voltage, 80 V; capillary temperature, 275°C. Data were acquired over a mass range of 50–2000 m/z. Data‐dependent collision‐induced dissociation (CID) was used for fragmentation, with a normalized collision energy of 45 eV. Data acquisition and processing were performed using Xcalibur v.2.0 software.

4.3.3. HPLC Fingerprinting of RSEE

To further identify and semi‐quantify key components, RSEE was analyzed on a Shimadzu LC‐20A‐20AT HPLC system (Shimadzu, Kyoto, Japan). The analysis was performed on a COSMOSIL C18 column (4.6 × 250 mm) at room temperature. The mobile phase and gradient conditions were identical to those described for the UPLC analysis, but with a flow rate of 1.0 mL/min. The chromatogram of RSEE was compared with those of available reference standards.

4.4. In Vivo Anti‐Colitis Study

4.4.1. Animals and Ethical Statement

Male C57BL/6 mice (6–8 weeks old, 18‐22 g) were obtained from the Experimental Animal Service Center of Guangzhou University of Chinese Medicine (Guangzhou, China). The animals were housed in a specific‐pathogen‐free facility under controlled conditions (23 ± 2°C, 12 h light/dark cycle) with ad libitum access to standard laboratory chow and water. All mice were acclimatized for one week prior to the experiment. The animal experiments were approved by the Animal Ethics Committee of Guangdong University of Technology, and all procedures were conducted in strict accordance with the Guidelines for the Care and Use of Laboratory Animals published by the China National Institutes of Health.

4.4.2. Induction of Colitis and Experimental Design

A total of 42 male C57BL/6 mice were randomly divided into seven groups (n = 6 per group): Normal Control (NC), Model Control (MC), Positive Control (SASP, 200 mg/kg), and low‐ and high‐dose groups for RSO (12.5 and 25 mg/kg) and RSEE (100 and 200 mg/kg). A co‐treatment protocol was employed to evaluate the protective effects of the extracts. Except for the NC group, which received normal drinking water, all other groups were challenged with 2% (w/v) DSS in their drinking water for 7 consecutive days to induce acute colitis. Simultaneously (from day 1 to day 7), mice in the treatment groups were administered their respective doses of RSO, RSEE, or SASP via oral gavage once daily. The NC and MC groups received an equivalent volume of distilled water as a vehicle control. On day 8, all animals were sacrificed, and colon tissues were collected for subsequent analysis.

4.4.3. Assessment of Colitis Severity

Throughout the experiment, mice were monitored daily for body weight changes, stool consistency, and the presence of gross rectal bleeding. These parameters were used to calculate the DAI based on a previously established scoring system. Briefly, the DAI was calculated as the mean of three sub‐scores: weight loss (0, none; 1, 1%–5%; 2, 5%–10%; 3, 10%–20%; 4, >20%), stool consistency (0, normal; 2, loose stools; 4, diarrhea), and rectal bleeding (0, normal; 2, occult blood; 4, gross bleeding), yielding a score from 0 (healthy) to 4 (severe colitis) [52]. On day 8, all mice were anesthetized via CO₂ inhalation and subsequently euthanized by cervical dislocation. The entire colon was excised from the cecum to the anus, and its length was measured.

4.4.4. Histopathological and IF Analyses

Distal colon segments were fixed in 10% neutral buffered formalin, dehydrated, and embedded in paraffin. Sections of 5 µm thickness were prepared for staining. For morphological assessment, sections were stained with H&E. To evaluate goblet cell numbers and mucus secretion, sections were stained with PAS. For IF analysis, sections underwent antigen retrieval and were blocked with 3% BSA. They were then incubated overnight at 4°C with primary antibodies against Claudin‐1 and Occludin. Subsequently, sections were incubated with a Cy3‐conjugated secondary antibody for 1 h at room temperature. Nuclei were counterstained with DAPI. All stained sections were scanned and digitized using a fully automated digital slide scanning system (AxioScan.Z1, Carl Zeiss, Germany). For quantitative histological assessment, blinded semi‐quantitative scoring of H&E‐stained sections was performed using a four‐parameter system assessing: (1) degree of inflammatory cell infiltration, (2) crypt damage, (3) epithelial erosion/ulceration, and (4) mucin depletion. Each parameter was scored from 0 to 3, yielding a maximum total score of 12. For goblet cell quantification, PAS‐positive mucin‐secreting cells were counted using ImageJ software (NIH, USA), with a minimum of 10 intact crypts randomly selected and analyzed per animal.

4.5. Selection of Key Active Constituents Based on Chemical Profiling

To elucidate the material basis of the anti‐colitic effects, we screened potential active compounds from both RSO and RSEE for subsequent network pharmacology and molecular docking analyses. The selection criteria were based on the quantitative profiles established by our chemical characterization. For the RSO, candidate compounds were selected based on their relative abundance as determined by GC‐MS. The top six constituents, each with a relative peak area exceeding 5%, were included: β‐sitosterol, ethyl docos‐13‐enoate, cis‐vaccenic acid, ethyl oleate, γ‐tocopherol, and campesterol. For the RSEE, the selection prioritized compounds that were successfully identified and quantified via UPLC‐MS/MS and HPLC analysis. Based on their calculated content and potential biological relevance, eleven representative compounds were selected as key ligands: sinapine, sinapic acid, 5‐hydroxymethylfurfural, gallic acid, salicylic acid, sulforaphane, sulforaphene, niacin, protocatechuic acid, indole‐3‐carboxaldehyde, and 7‐methoxycoumarin. These 17 compounds served as the primary dataset for predicting potential therapeutic targets and verifying molecular interactions.

4.5.1. Target Prediction and Intersection Analysis

To identify the potential biological targets of the selected constituents, their canonical SMILES strings were obtained from the PubChem database and imported into SwissTargetPrediction (http://www.swisstargetprediction.ch/) for target prediction. The organism was restricted to “Homo sapiens”, and targets with a probability > 0.0 were collected. Simultaneously, therapeutic targets associated with UC were mined from the GeneCards database (https://www.genecards.org/) using the keyword “UC”. The top 200 disease targets based on relevance scores were selected to ensure high correlation. The intersection of compound‐related targets and disease‐related targets was visualized using Venn diagrams to identify potential therapeutic candidates for RSO and RSEE.

4.5.2. PPI Network Construction

To explore the functional interactome of the overlapping targets, PPI networks were constructed using the STRING database (Version 11.5, https://string‐db.org/). The organism was set to “Homo sapiens”. To ensure the reliability of the topological analysis and exclude low‐confidence interactions, the minimum required interaction score was set to the highest confidence level (0.900). Disconnected nodes were hidden to simplify the network. The resulting network data were visualized and analyzed to compare the topological differences between RSEE and RSO.

4.5.3. GO and KEGG Pathway Enrichment Analyses

To elucidate the biological functions and signaling pathways associated with the identified targets, enrichment analyses were performed using distinct bioinformatics platforms. GO enrichment analysis, including biological process (BP), cellular component (CC), and molecular function (MF), was conducted using the DAVID database (https://david.ncifcrf.gov/). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed using the Metascape platform (https://metascape.org/). For both analyses, a p‐value < 0.05 was considered statistically significant.

4.6. Biochemical Analyses of Colon Tissue

Excised colon tissues were rinsed with ice‐cold phosphate‐buffered saline (PBS) and homogenized in appropriate buffers. The protein concentration of the homogenates was determined using a BCA protein assay kit. The activities of MPO and SOD were measured using commercial colorimetric assay kits (Solarbio, Beijing, China) according to the manufacturer's instructions. The concentrations of TNF‐α, IL‐6, and IL‐1β in the colon tissue homogenates were quantified using specific ELISA kits (Elabscience, China) as per the manufacturer's protocols.

4.7. Molecular Docking

Molecular docking simulations were performed using the Schrödinger Suite 2023‐4 to predict the binding modes and affinities of bioactive compounds with key protein targets. The crystal structures of TNF‐α (PDB ID: 2AZ5), MPO (PDB ID: 1MZM), and Keap1 (PDB ID: 4L7B) were retrieved from the RCSB Protein Data Bank. Protein structures were prepared using the Protein Preparation Wizard to remove water molecules, add hydrogens, and optimize hydrogen bonds. The 3D structures of the ligands were generated and energy‐minimized using the LigPrep module. Receptor grids were generated using default settings centered on the native ligands. Docking was carried out using the Ligand Docking module in Extra Precision (XP) mode with default parameters. The final binding poses and interactions were visualized using PyMOL.

4.8. Statistical Analysis

Data from the UPLC‐Q‐Exactive‐Orbitrap‐MS were analyzed using Compound Discoverer 3.2 software, which facilitated molecular formula matching and precise molecular weight calculation. All data were analyzed using GraphPad Prism software (GraphPad Software, Inc., La Jolla, CA, USA) and are expressed as the mean ± standard deviation (SD). Comparisons between multiple groups were performed using one‐way analysis of variance (ANOVA) followed by an appropriate post‐hoc test. A p‐value of less than 0.05 was considered to indicate a statistically significant difference. The results of the GO and KEGG enrichment analyses were visualized using the R programming language (Version 4.3.1). Bubble plots and bar charts were generated using the ggplot2 package to illustrate the top enriched terms and pathways, with bubble size representing the gene count and color gradient indicating the significance level (p‐value).

Author Contributions

Wenlin Chen: investigation, methodology, writing – original draft. Yujing Huang: writing – original draft, writing – review and editing. Xin Yu: investigation, supervision. Duntao Zu: investigation. Tingxin Zhang: investigation. Laiyu Tang: investigation. Xinbo He: investigation. Chengyin Huang: investigation. Juntao Xie: investigation. Jianni Yang: investigation, supervision. Junxia Zheng: conceptualization, writing – review and editing, supervision, project administration, funding acquisition.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Supporting File: cbdv71560‐sup‐0001‐SuppMat.docx.

Data Availability Statement

The data that supports the findings of this study are available in the Supporting Information of this article.