Chemical AnalysisIsolation and Structure Elucidation

The applied chromatographic techniques managed the isolation of 14 phenolic compounds from T. resupinatum extract. Chemical and physical investigations were used to elucidate their structural composition. In addition, their structural data were compared with previously reported spectroscopic data for more confirmation. In addition to one phenolic acid (chlorogenic acid; 1), three isoflavone aglycones: formononetin (2), pseudobaptigenin (5), and genistein (7); five isoflavone 7-O-β-glucosides; ononin (3; formononetin 7-O-β-glucoside), rothindin (6; pseudobaptigenin 7-O-β-glucoside), genistin (8; genistein 7-O-β-glucoside), daidzin (9; daidzein 7-O-β-glucoside), and sissotrin (10; biochanin A 7-O-β-glucoside) as well as the acetyl derivative; 6''-O-acetyl ononin (4; formononetin 7-O-β-(6''-O-acetyl) glucoside) were established. Furthermore, flavonol aglycones and their 3-O-β-glucoside; kaempferol (11), astragalin (12; kaempferol 3-O-β-glucoside), quercetin (13), and isoquercetin (14; quercetin 3-O-β-glucoside) were isolated. Compounds 4, 8, 9, 10, and 12 were isolated for the first time from T. resupinatum but reported beforehand for other Trifolium species. The physical constants and NMR data were compared with published values for all isolated compounds (see, Supporting Information).

LC-MS Profiling

Analysis of the LC-ESI-MS base peak chromatogram of the 70% aqueous methanol leaf extract of T. resupinatum (Fig. S1) revealed the dominance of pseudobaptigenin (peak 72, isolate 5) and formononetin (peak 73, isolate 2), and their respective 7-O-glucosides (peaks 57 and 58, isolates 6 and 3, respectively). After ingestion, isoflavone glycosides are metabolized by the β-glucosidase enzyme in the small intestine to produce the more efficiently absorbed form of isoflavones with lower hydrophilic properties and smaller molecular weights (corresponding aglycons)(Kassem et al. 2017). Therefore, the two isoflavone aglycones 2 and 5 were selected for the in vitro pancreatic lipase assay along with the total extract.

Metabolite Annotation

In this context, detailed metabolite profiling of T. resupinatum leaf extract via HPLC-ESI-MS/MS was performed using a standard mixture including the isolated compounds (Fig. S1). For a more accurate representation of the species hydroalcoholic extract metabolome, molecular networking was created (Fig. 1). With the aid of GNPS libraries, possible correlations between each MS/MS spectrum were found, thereby enabling additional annotation of unknown but related molecules. About 81 metabolites were distinguished, 69 of which are species-first detection (Table S1). They belong to many chemical classes comprising fatty acids (four metabolites), amino acids (five metabolites), organic acids (two metabolites), and sugars (two metabolites) with phenolics as predominant class (68 compounds) (Fig. 2). The interpretated phenolics included 52 flavonoid compounds (23 isoflavonoids, 16 flavonols, seven flavones, five flavanones, and one flavanonol), along with 11 phenolic acids and aldehydes, as well as five coumarins (Table S1, Fig. 2).

Fig. 1

The molecular network created using MS/MS data (negative ionization mode) of Trifolium resupinatum extract (yellow) and standards mixture (blue)

Fig. 2

Classes of chemical metabolites identified in Trifolium resupinatum leaf extract with ratios of flavonoid subgroup structures in relation to the total of identified compounds

In the negative ionization mode of the constructed molecular network, 425 nodes were grouped in 34 clusters (two linked nodes at least) and 191 self-looped nodes, whereby the interesting clusters A, B, C, and D guided the characterization of various phenolic skeletons (Fig. 1). The yellow nodes represent the targeted extract sample while the blue ones corresponded to the standards mixture ions. The unmatched clusters were analyzed and verified manually. On the other hand, the remaining constituents were tentatively elucidated via their accurate molecular weights, retention time, MS2 fragments combined with GNPS libraries matches, and in parallel with the standards used or comparing their fragmentation picture with the previous reported data (Table S1).

Isoflavonoids are the most prominent constituents of the leguminous plant family (Fabaceae). They were frequently categorized into seven subclasses including isoflavones, isoflavans, isoflavanones, coumestans, rotenoids, pterocarpans, and coumaronochromones (Sohn et al. 2021). Members of the genus Trifolium, in particular red clover, contain significant concentrations of the variable structure patterns of the unique isoflavones in aglycone forms, daidzein (7,4′-dihydroxyisoflavone), genistein (4',5,7-trihydroxyisoflavone), formononetin (7-hydroxy-4´-methoxyisoflavone), biochanin A (5,7-dihydroxy-4′-methoxyisoflavone), and pseudobaptigenin (7-hydroxy-3',4'-methylenedioxyisoflavone), or some of their 7-glucoside forms, daidzin, genistin, ononin, sissotrin, and rothindin, respectively (Malca-Garcia et al. 2022). Less frequently occurring isoflavone aglycones such as prunetin (7-O-methyl-genistein), pratensein (3'-hydroxy biochanin A), and irilone (5,4'-dihydroxy-6,7-methylenedioxyisoflavone) have also been reported. In addition, minor acetylated and malonated glycosyl derivatives have been recorded (Das et al. 2020).

Cluster A of the created molecular network of T. resupinatum gathered 6 isoflavone aglycones encompassing nodes of formononetin (73, m/z 267.02 [M−H]−) connected to biochanin A (34; m/z 283.01 [M−H]−), and pseudobaptigenin (72; m/z 281.01 [M−H]−) connected to irilone (66; m/z 297.01 [M−H]−), both through the mass difference of 16 Da. Moreover, medicarpin (75; m/z 269.03 [M – H]−) and daidzein (76; m/z 253.015 [M−H]−) were grouped in the same cluster. Medicarpin is a benzopyran furanobenzene compound belonging to the pterocarpan phytoalexin group of the isoflavonoids family. It was formerly detected in several Trifolium species (Malca-Garcia et al. 2022) and various leguminous plants (Gampe et al. 2016; Cheng et al. 2019). Oxidation of pterocarpans yields coumestans which were also annotated in T. pratense and T. repens (Malca-Garcia et al. 2022). The most prevalent is coumestrol (54; m/z 267.02 [M−H]−), which is perceived in T. resupinatum extract for the first time. It has an additional furan ring between B and C rings and dicatechol groups that resembles estradiol’s structure to which its positive effects are attributed (Ionescu et al. 2021). Another set of six isoflavone aglycones were observed as self-looped nodes; hydroxy biochanin A (35; m/z 299.01 [M−H]−), genistein (44; m/z 268.97 [M−H]−), pratensein (51; m/z 299.01[M−H]−), and prunetin (64; m/z 283.01 [M−H]−), in addition to pseudobaptigenin-O-sulfate (60; m/z 360.98 [M−H]−) monitored by the daughter ion peak at m/z 281 [M−80]− due to SO3 loss. These compounds were not found in Persian clover beforehand except for isoflavone aglycones 34, 44, 71, 73, and 76.

Besides the isoflavonoid aglycones, some isoflavone glycosides were pictured in clusters B and C (Fig. 1). Pseudobaptigenin 7-O-glucoside (57; m/z 488.912 [M–H + FA (formic acid)]−) is directly attached by a thick edge to 71 (m/z 530.91 [M–H + FA]−) with a mass shift of 42 Da as probable acetyl moiety (−COCH3), confirming the first identification of pseudobaptigenin 7-O-acetylglucoside in the genus Trifolium. On the other hand, both compounds appeared as formic acid adduct ions equivalent to [M−H + HCOOH]− or [M + 45 Da]−, as compound 58 (formononetin 7-O-β-glucoside; m/z 474.93 [M–H + FA]−). The isolated acetyl glucoside isomer of 58; acetylononin (45; m/z 471.03 [M−H]−) was confirmed by the specific fragment at m/z 267 [M–H–acetyl−glucosyl]−. The acetyl glycoside isoflavone conjugates of leguminous plants have already been mentioned (Gampe et al. 2016; Das et al. 2020); however, their presence in the studied species has not been previously reported. Furthermore, the characteristic ion of daidzin (25; m/z 414.96 [M−H]−) was observed connected to that of genistin (33; m/z 430.94 [M−H]−) in cluster C. Other glycosylated isoflavonoids were observed as self-looped nodes in the molecular network and could be annotated as coumestrol-O-hexoside (12; m/z 429.01 [M−H]−), sissotrin (29; m/z 445.01 [M−H]−), irilone-4′-O-glucoside (31; m/z 458.97 [M−H]−), pratensein-O-glucoside (52; m/z 461.01 [M−H]−), and dimethoxy isoflavone-O-hexoside (wistin) (63; m/z 505.01 [M–H + FA]–) designated through the prominent peaks of their precursors’ fragment ions due to loss of the hexoside moiety [M–H–162]–. Numerous peaks were verified by comparing their mass spectra and retention data with those of standards, including the isolated compounds (Table S1). Previous studies characterized these isoflavone glycosides combinations in T. pratense (Malca-Garcia et al. 2022) and other leguminous species (Gampe et al. 2016; Cheng et al. 2019). However, our study is the first to dereplicate them in T. resupinatum except for compounds 33, 57, and 58.

An additional sulfated compound was recognized as a flavone structure and recognized as apigenin-O-sulfate (18; m/z 348.99 [M−H]−). Other flavone aglycones were reported before in some Trifolium species (Malca-Garcia et al. 2022) and identified as apigenin (46; m/z 269.02 [M−H]−), tricin (49; m/z 329.01 [M−H]−), and chrysoeriol (69; m/z 299.01 [M−H]−) confirmed by standard samples. The substitution with methoxy groups was indicated by the (CH2)n subsequent loss (–14 Da)n (Hussein et al. 2018). Apigenin 7-O-glucoside (30; m/z 431.01 [M−H]−), apiin (40; m/z 562.96 [M−H]−), and tricin 7-O-glucoside (37; m/z 491.01 [M−H]−) were eluted earlier than their corresponding aglycones. Their annotation was supported by the elimination of the hexose [M–H−162]− or pentose [M–H−132]− moieties to produce the analogous aglycone anions.

Another acetyl derivative was also detected in cluster C concerning a mono-glycosyl flavonol structure, kaempferol 3-O-(6''-acetyl) glucoside (42; m/z 488.94 [M−H]−) which is directly linked to a node at m/z 446.93 with 42 Da mass difference, that displayed kaempferol 3-O-glucoside (26; m/z 446.93 [M−H]−) based on the standard isolated compound (Fig. 1). Meanwhile, this node was directly connected with its congeners; quercetin 3-O-glucoside (22; m/z 462.96 [M−H]−) and isorhamnetin 3-O-glucoside (28; m/z 476.93 [M−H]−) (Fig. 1). Other peaks sharing the same parent ions of 26 and 28 corresponded to kaempferol 7-O-glucoside (36; m/z 446.93 [M−H]−) and isorhamnetin 7-O-glucoside (61; m/z 477.01 [M−H]−) relying on the base peak ions [Agl−H]− at m/z 285 and 315, respectively. In contrast, these ions of the 3-O-isomers were [Agl−H2]− at m/z 284 and 314 (Farid et al. 2022). The flavonol glycosides were also eluted first followed by their corresponding aglycones: kaempferol (50; m/z 285.01 [M−H]−), quercetin (39; m/z 300.97 [M−H]−), isorhamnetin (62; m/z 315.1 [M−H]−), in addition to myricetin (67; m/z 317.02 [M−H]−) that reported before in T. repens (Agraharam et al. 2022). Flavonols in the genus Trifolium are frequent, mainly kaempferol and quercetin (Malca-Garcia et al. 2022). They were stated earlier in the aerial parts of T. resupinatum (Kassem et al. 2017); however, the levels of different glycosylation and positional isomers are distinguished in the current study through the key fragmentation pathway approach. Two di-O-glycosyl flavonols appeared as a cluster (D) of two connected nodes representing quercetin 3-O-glucoside-7-O-rhamnoside (21; m/z 608.98 [M−H]−) and kaempferol 3-O-glucoside-7-O-rhamnoside (32; m/z 593.02 [M−H]−), further confirmed throughout the GNPS libraries. They produced diagnostic fragment ions at (m/z 463 [M–H–146]− and 447 [M–H−162]−) and (m/z 447 [M–H−146]− and 431 [M–H−162]−), respectively. The higher intensities for their glucosylated fragment ions [M–H+162]− than those for the rhamnosylated ones [M–H + 146]− suggested the substitution at 3-O-glucoside and 7-O-rhamnoside for both compounds (Farid et al. 2022). Further flavonols-O-diglycosides were observed as self-looped nodes and identified as 3-O-rutinoside of quercetin (24; m/z 609.01 [M−H]−) and kaempferol (27; m/z 592.94 [M−H]−). The last isomer was kaempferol 3,7 di-O-rhamnoside (38; m/z 577.01 [M−H]−), which produced two diagnostic signals at m/z 431 [M–H−146]− and 285 [M–H−292]− compatible with the standard reference.

Limited amounts of other flavonoids rarely reported in the genus Trifolium, which correspond to flavanones and flavanonols, were obtained and observed in the molecular network as self-looped nodes. Two flavanone aglycones (47; m/z 255.01 [M−H]−) and (53; m/z 271.01 [M−H]−) suggested to be liquiritigenin and naringenin as described in Trifolium subterraneum L. and T. partense L., respectively (Prati et al. 2007), were also confirmed via GNPS libraries (Table S1). Their corresponding glycosylated derivatives, liquiritoside (19; m/z 416.96 [M−H]−) and naringenin 7-O-glucoside (55; m/z 433.01 [M−H]−), were evidenced by the product ion [M–H−162]−. A further flavanone aglycone was detected as eriodyctiol (70; m/z 287.01 [M−H]−). In addition to a single flavanonol aglycone, taxifolin (20; m/z 303.04 [M−H]−) which was confirmed through a standard compound and previously reported in T. partense (Prati et al. 2007). Excepting rutin (24), quercetin (39), and kaempferol (50), all annotated flavonols, flavanones, and flavanonol are non-previously reported metabolites in T. resupinatum.

Additional minor phenolic derivatives were marked as self-looped nodes and newly characterized in T. resupinatum. They relied on their ion mass spectra, retention times, and mass fragmentation profile aided with GNPS, published literature, and available authentic references. Phenolic acids; caffeic (4; m/z 179.01 [M−H]−), sinapic (7; m/z 223.02 [M−H]−), coumaric (10 and 14; m/z 163.01 [M−H]−), gentisic (17; m/z 153.02 [M−H]−), vanillic (23; m/z 167.01 [M−H]−), ferulic (41; m/z 193.01 [M−H]−), and chlorogenic (80; m/z 353.09 [M−H]−) acids, phenolic benzaldehydes; p-hydroxy benzaldehyde (13; m/z 121.01 [M−H]−) and trimethoxy benzaldehyde (59; m/z 195.09 [M−H]−) as well as dihydrocoumaroyl-O-glucoside (81; m/z 327.22 [M−H]−) were demonstrated. Chlorogenic acid was isolated before from the investigated species by Kassem et al. (2017), while the other phenolic acids and aldehydes were reported previously in T. partense (Prati et al. 2007).

Likewise, coumarins are also reported to occur in forage plants represented herein as hydroxy methyl coumarin (15; m/z 175.01 [M−H]−), dihydroxycoumarin (68; m/z 177.01 [M−H]−), trihydroxy coumarin (56; m/z 193.08 [M−H]−), and dihydroxycoumarin-O-hexoside (43; m/z 339.02 [M−H]−). Compound 68 was identified as esculetin (6,7-dihydroxycoumarin) confirmed through the standard compound, and was characterized before in T. partense (Vlaisavljević et al. 2017). Successively, compound 43 was elucidated as esculetin-O-glucoside via mass difference of 162 Da.

Anti-obesity PotentialPancreatic Lipase Inhibition

Triacylglycerides are hydrolyzed by the pancreatic lipase enzyme into glycerol and fatty acids, aiding in their absorption in the intestine. Lipase inhibition is an effective strategy for preventing triglyceride absorption and obesity. Orlistat inhibits this enzyme professionally but with various harmful effects on the gastric, renal, endocrine, and nervous systems, impairing the other medications’ efficacy (Ragheb et al. 2021). T. resupinatum extract exerted an in vitro inhibition impact on porcine pancreatic lipase inhibition with an IC50 of 471.32 ± 0.8 µg/ml. Comparing the selected compounds, formononetin (2) (IC50 of 47.2 ± 1.1 µg/ml) demonstrated potential enzyme inhibitory activity than pseudobaptigenin (5) (IC50 of 112.8 ± 1.23 µg/ml) considering the efficiency of orlistat (IC50 of 23.8 ± 0.64 µg/ml), as summarized in Table 1.

Table 1 Pancreatic lipase % inhibition of Trifolium resupinatum leaf extract and the major isolated isoflavone aglycones

Many studies have shown that naturally occurring phenolics demonstrated multifunctional properties that can effectually prevent obesity and related metabolic disorders. They are described to regulate digestion and fatty acid oxidation, as well as carbohydrate and lipid metabolism by modulating the activity of digestive enzymes (Oliveira et al. 2022). Pancreatic lipase inhibitory action of some prospective isoflavones has previously been evaluated. Cardullo et al. (2021) proved that modification of formononetin by hydroxylation or bromination improved the in vitro enzyme inhibitory properties. On the other hand, Deng et al. (2020) suggested the inhibitory effect of ethyl acetate fraction of the fungus Grifola frondose (Dicks.) Gray was correlated to its rich content of pseudobaptigenin.

In Vivo Evaluation

Data in Table 2 compared the final total body weight (g) among the control and other groups. They indicated that rats who received a high-fat diet (HFD) significantly increased their total body weight compared with those who received a normal diet (ND). There was significant weight loss in HFD rats treated with T. resupinatum extract (25 mg/kg body weight suspended in 0.5 ml saline) compared with those that received only HFD.Furthermore, the results in Table 2 demonstrated that glucose, triacylglycerides, and total cholesterol levels significantly increased in the sera of rats that received HFD compared with those in a control group. At the same time, these parameters significantly decreased in the group treated with T. resupinatum extract compared to the untreated one (HFD). This potential could be related to flavonoids, particularly isoflavones (formononetin and pseudobaptigenin) that represent major constituents in T. resupinatum leaf extract (Fig. 2) or related to the synergetic interactions of the natural compounds (Liu et al. 2022).

Table 2 Effect of Trifolium resupinatum leaf extract on body weight, serum glucose, serum triacylglycerides, and total cholesterol (mg/dl) in HFD-treated rats

The anti-obesity effects of flavonoids occur through the modulation of proteins, genes, and transcription factors that contribute to reduced lipogenesis, increased lipolysis, and energy expenditure, in addition to moderating inflammatory responses and suppressing oxidative stress (Oliveira et al. 2022). Due to various flavonoid compounds (64.2% of total identified compounds) and their structural variations (Fig. 2, Table S1), the effects varied considerably. Their anti-obesity properties include repressing adipogenesis and lipogenesis by lowering the inflammatory mediators, deactivating the immune cells, enhancing mitochondrial activity by promoting the antioxidant effects, decreasing lipid peroxidation, modifying fat metabolism, regulating apoptosis, and increasing energy consumption (Deng et al. 2020; Oza and Kulkarni 2020; Liu et al. 2022).

Molecular Docking

Molecular docking was carried out to confirm the pancreatic lipase activity of the significant isolates (2 and 5) and predict the affinity of the additional isolated compounds to this enzyme, to which the synergetic effect of the anti-obesity property is attributed. Binding affinity evaluation is used to determine the strength of biomolecular interactions, which is crucial in determining the possibility of an interaction arising in a cell (Odoemelam et al. 2022). Table S2 summarizes the interactions between the amino acids and the ligands at the porcine pancreatic lipase (PPL) binding sites. Docking analysis applied to the PPL protein revealed that all the isolated constituents have better or analogous binding free energies to the control drug (orlistat). The binding affinity of orlistat on pancreatic lipase enzyme is found to be −8.2 kcal/mol. The strongest binding affinity (−9.9 kcal/mol) is afforded by compounds 5, 7, 11, and 13, followed by compounds 2 and 4 (−9.8 kcal/mol), then compound 8 with a binding affinity −9.7 kcal/mol (Table S2). Our findings matched the docking results of Cardullo et al. (2021), who indicated the higher affinity of isoflavone class inhibitors to PPL active sites underlying their interactions. Also, it proved the better fitting of genistein (7) than formononetin (2) on the receptor due to the additional C-5 hydroxyl group which provides an additional hydrogen bond. Li et al. (2023) assumed the higher inhibitory effect of flavonols (quercetin) and isoflavones compared to flavanones and flavan-3-ols. Their inhibitory activity is enhanced by hydroxylation on rings A and B, whereas it is suppressed by glycosylation. In addition, Ahmed et al. (2022) showed a stronger affinity of chlorogenic acid to PPL active sites compared to orlistat.

Two- and three-dimensional illustrations of the interaction between ligand molecules and PPL protein are provided as supplementary material (Figs. S2 and S3). It was revealed from an analysis of docking interactions that all the isolated compounds bind to the same region as orlistat. Moreover, the observed interactions for the orlistat-PPL complex were close to those described in previous literature (de Lima Barros et al. 2022), which implies a good estimate of the present model.

The docking analysis displayed that His152 was involved in the hydrogen bonding interaction of orlistat, as compounds 1, 4, and 8 with the protein active site (Fig. S2 and S3). Additionally, it was found that both compound 11 and orlistat may stabilize the complex with the pancreatic lipase enzyme through a hydrogen bond with the same residue, Gly77 (Figs. S2 and S3). The similarity of the interacting pattern between these phytoconstituents and orlistat indicates that these isolated compounds probably inhibit pancreatic lipase in same pattern as orlistat. The top-scored inhibitors of phytoconstituents presented several π- interactions with Phe78, Tyr115, and Phe216 residues in a similar manner to the hydrophobic interaction of orlistat. A hydrophobic-interaction–based mechanism mainly triggers docking between compound 5 and PPL protein, where the pseudobaptigenin-PPL protein complex may be stabilized with 7 π- interactions. It was implied from previous literature that interaction with His264 is a key element since this residue constitutes the catalytic triad of the PPL active sites (de Lima Barros et al. 2022). Almost all the highly scored constituents formed a hydrophobic interaction with the key residue His264 (Fig. S2 and S3).

Drug-Likeness and Oral Bioavailability

A detailed analysis of the pharmacokinetic properties of the isolated metabolites was performed. Lipinski specified a rule of five (RO5) to predict compounds that could be good drug candidates or drug-like compounds. The RO5 specified that poor absorption or permeation is more probable when there are more than five H-bond donors (HBD), molecular weight (MW) is over 50, Log P is over 5, and the sum of N’s and O’s (HBA) is over 10 (Abdul-Hammed et al. 2021).

As presented in Table S3, the HBD, MW, HBA, and Log P values of most isolated compounds obey the specifications of the RO5. Compounds 1 and 8 have one acceptable violation, as an orally active drug has no more than one violation of the Lipinski criteria (Ivanović et al. 2020). On the other hand, compounds 12 and 14 showed two violations. The bioavailability score aims to predict the possibility of a compound having at least 10% oral bioavailability in rats. The predicted bioavailability of the isolated compounds (Table S3) revealed a bioavailability score of 0.11, 0.17, or 0.55, which means good pharmacokinetic properties and good drug profile (Swain and Hussain 2022).

Distinctive to SwissADME is the bioavailability radar that provides a graphical preliminary glimpse at the drug-likeness parameters of the studied compounds. Figure S4 shows the drug-likeness graph as a hexagon, with each vertex indicating a characteristic that defines a bioavailable drug. The pink zone within the radar hexagon represents the optimal physicochemical space for each property predicted to be orally bioavailable (lipophilicity, XLOGP3 between −0.7 and + 5.0; size, MW between 150 and 500 g/mol; polarity, TPSA between 20 and 130 Å2; solubility, log S not higher than 6; saturation, fraction of carbons in the sp3 hybridization not less than 0.25; and flexibility, no more than nine rotatable bonds) (Ndombera et al. 2019). Most of the constituents fall within the five parameters of the pink area and are considered drug-like.

According to the Molsoft database tool, the scale of a drug-likeness score of isolated compounds ranges from –0.15 to 0.79 (Fig. 3). The isolated compounds, which represent drug-likeness scores with positive values, are to be considered like drugs. On the contrary, compounds 4, 6, and 9 showed negative values, indicating low probabilities of being drugs (Gad et al. 2020).

Fig. 3