Anti-inflammatory Sesquiterpene Coumarins from the Active Fractions of Ferula assa-foetida: In Silico Analysis Endorse Experimental data

Anti-inflammatory Sesquiterpene Coumarins from the Active Fractions of Ferula assa-foetida: In Silico Analysis Endorse Experimental data | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Anti-inflammatory Sesquiterpene Coumarins from the Active Fractions of Ferula assa-foetida: In Silico Analysis Endorse Experimental data Mubarak A. Alamri, Gamal A. Soliman, Mohammed A. Alamri, Rehab F. Abdel-Rahman, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7355100/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Ferula assa-foetida known as Asafoetida has a long-established history in folk medicine as a therapeutically useful drug in many disorders. The current paper explored the in vivo and in vitro anti-inflammatory activities of the plant. Liquid ethanol crude extract was subjected to liquid-to-liquid extraction, and the fractions so obtained were evaluated against the carrageenan-induced acute paw edema model in rats, to determine the anti-inflammatory effects. The fractions that gave the greatest activity-ethyl acetate and hexane- afforded four sesquiterpene coumarins: auraptene ( 1 ), umbelliprenin ( 2 ), galbanic acid ( 3 ), and kamolonol ( 4 ). The overall structure was determined through detailed spectroscopic investigation, 1 H NMR, 13 C NMR, DPET135, COSY, HSQC, HMBC, HRESIMS, and other references to the literature. Evaluation of the in vitro activity of the LPS stimulated RAW 264.7 macrophages showed that the compound 4 (ethyl acetate fraction) exhibited maximum inhibitory action against the generation of nitric oxide (NO), followed by the compounds 1 and 2 of the hexane fraction. Internet Pharmacology, Molecular Docking and Molecular dynamic simulation analysis were used to identify the target genes and explain the potential differences between the active compounds. As far as the authors know, there are no earlier reports that mention the anti-inflammatory action of kamolonol ( 4 ). Biological sciences/Biochemistry Biological sciences/Chemical biology Physical sciences/Chemistry Biological sciences/Computational biology and bioinformatics Biological sciences/Drug discovery Biological sciences/Plant sciences Asafoetida sesquiterpene coumarins anti-inflammatory internet pharmacology molecular docking molecular dynamic Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Introduction Inflammation is the first line of defense of the body in response to infection or tissue damage resulting in organ structural stability, normal physiology and homeostasis within the injured tissue 1 . Over the past few years, it has become one of the most prominent objects of biomedical research in the world and this is mostly because it is clearly linked to a vast diversity of human illnesses 2 . The commonly used medical treatments of inflammatory disorders include glucocorticoids and nonsteroidal anti-inflammatory drugs (NSAIDs). These medications are linked with some adverse effects such as high blood pressure, stomach pain and ulcers, fragile bones, kidney failure, Cushing’s syndrome, diabetes, and vulnerability to infections 3 . There is therefore urgent need to establish safer and more effective methods of handling inflammatory pathology. The process of inflammation is a complicated list of physiological events whereby a network of cellular events and a coordinated sequence of molecular events orchestrate immune activation and maintain homeostasis in tissues. The core of this process involves the cyclooxygenase (COX) pathway, in which COX-1 regulates and controls normal physiologic activity, at the same time as COX-2 is preferentially induced during an inflammatory event, to promote the constructive formation of prostaglandins, and hence exaggerate the inflammatory response 4 , 5 .The (NF-κB) signaling pathway is major transcriptional regulator of pro-inflammatory effectors including tumor necrosis factor-alpha TNF-α ,interleukin-6 (IL-6) in agreement with this system. NF-κB activation begins with proteolytic removal of anti- inflammatory proteins (IκB), subsequently permitting the process of translocation of the complex to the nucleus to facilitate transmission of inflammation-linked genes 6 , 7 . Moreover, a balance between pro-inflammatory cytokines, such as IL-1b, IL-6 and TNF-α, and anti-inflammatory molecules including IL-10 is important to regulate the attraction of immune cells and control excessive inflammatory processes 8 . Such complexly interlinked web of molecular networks forms the ideal target of therapeutic interventions in inflammatory disorders. Traditional medicine has great repositories of bioactive secondary metabolites present in herbs that can be used to draw out pharmacologically useful agents. Therefore, plant-based preparations still serve as a major source in the discovery of new drugs. Genus Ferula L. (with over 170 species formally described) is the third largest in its family. Most representatives of this genus are well represented in ethnomedicine, and several of them have proved to be significant sources of biologically active materials 9 . Asafoetida is the oleo-gum-resin secreted by the roots of Ferula assa-foetida , traditionally used to treat a wide range of conditions including whooping cough, bronchitis, asthma, influenza, stomachache, flatulence, ulcers, intestinal parasites, spasms, digestive weakness, and epilepsy 10 . Multiple biological activities were reported for essential oils and extracts of the genus, including anticancer, antioxidant, anticonvulsant, antinociceptive, antidepressant, aphicidal, antiprotozoal, anthelmintic, antibacterial, anti-inflammatory, antihypertensive, antiulcer, and antispasmodic activities. In addition, asafoetida expressed many biological activities including antiviral, antifungal, molluscicidal, antidiabetic, antiobesity, hepatoprotective, neuroprotective, memory enhancing, and digestive aid 10 – 12 . The extract containing ethanol was rich in the anti-inflammatory action on the tumor necrosis factor-alpha (TNF-α–) stimulated human umbilical vein endothelial cells (HUVECs) 3 . Phytochemically, Ferula species are rich in the bioactive sesquiterpene coumarins derivatives 13 – 17 . Although sesquiterpene coumarins are present in 12 plant genera, they are mainly reported from Ferula species 13 . Many members of the sesquiterpene coumarin family were reported to have anti-inflammatory activity 13 – 17 . Two sesquiterpenes with anti-inflammatory activity were reported from F. hermonis 14 . Sesquiterpene coumarins were reported from the aerial parts of F. sinkiangensis expressed anti-inflammatory activities in lipopolysaccharide-stimulated RAW 264.7 macrophages 15 . Anti-neuroinflammatory sesquiterpene coumarins were identified from the resin of F. sinkiangensis and the whole plants of F. bungeana 16 , 17 . The current study was targeted at investigating the anti-inflammatory properties of assafoetida, both in vivo , in vitro , in silico and identifying the active metabolites responsible for this effect via biologically guided phytochemical study. We also aim to identify the potential molecular targets and mechanisms of action of its isolated compounds. Results Characterization of the isolated compounds Auraptene ( 1 ): pale yellow solid, UV λ max MeOH: 226, 290, 322 nm, 1 H and 13 C NMR : Tables 1 , 2 , Figures S1 - S10, High Resolution Electrospray Ionization Mass Spectrometry (HRESIMS) m/z [M-H] + 297.1483 (calcd for C 19 H 22 O 3 -H, 297.1500), [M + H] + 299.1640 (calcd for C 19 H 22 O 3 + H, 299.1647) (Figures S1 1, S12). Umbelliprenin ( 2 ): White powder, UV λ max MeOH: 223, 288, 325 nm, 1 H and 13 C NMR Tables 1 , 2 , Figures S1 3- S22, HRESIMS m/z [M + 1] + m/z 367.2263 (calcd for C 24 H 30 O 3 + H, 367.2273), [M + Na] + m/z 389.2081 (calcd for C 24 H 30 O 3 + Na, 389.2093) (Figure S23). Galbanic acid ( 3 ): White matrix, UV λ max MeOH: 224, 289, 324 nm, 1 H and 13 C NMR Tables 1 , 2 , Figures S24- S44, HRESIMS m/z [M-1] + m/z 397.2016 (calcd for C 24 H 30 O 5 -H, 397.2015), [M + 1] + m/z 399.2162 (calcd for C 24 H 30 O 5 + H, 399.2171), [M + Na] + m/z 421.1981 (calcd for C 24 H 30 O 5 + Na, 421.1991) (Figure S45, S46). Kamolonol ( 4 ): White amorphous powder, UV λ max MeOH: 225, 285, 326 nm, 1 H and 13 C NMR Tables 1 , 2 , Figures S47- S60, HRESIMS m/z [M + 1] + m/z 399.2166 (calcd for C 24 H 30 O 5 + H, 399.2171), [M + Na] + m/z 421.1986 (calcd for C 24 H 30 O 5 + Na, 421.1991) (Figure S61). Table 1 1 H-NMR data (δ ppm, J in parentheses in Hz) of compounds 1–4 in C 6 D 6 . 1 2 3 3* 4* 4** 3 5.91 (d, 9.5) 5.91 (d, 9.5) 5.88 (d, 9.5) 6.21 (d, 9.5) 6.25 (d, 9.5) 6.35 (d, 9.5) 4 6.78 (d, 9.5) 6.95 overl 6.63 (d, 9.5) 7.85 (d, 9.5) 7.88 (d, 9.5) 7.72 (d, 9.5) 5 6.73 (d, 8.4) 6.95 overl 6.65 (d, 8.6) 7.49 (d, 8.6) 7.55(d, 8.5) 7.48 (d, 8.2) 6 6.60 (dd, 2.4, 8.4) 6.95 overl 6.56 (dd, 2.3, 8.6) 6.89 (dd, 1.8, 8.6) 6.96 overl 7.01 overl 8 6.62(d, 2.4) 6.95 overl 6.22(d, 1.8) 6.22(d, 1.8) 6.95 overl 7.02 overl 1’ 4.21 (d, 6.5) 4.15 (d, 6.3) 1.12 overl 1.85 m 1.90 (dd, 4.6, 13.0), 1.99 m 1.82 m 2’ 5.39 (t, 6.5) 5.40 (t, 6.5) 2.11 m, 2.17 m 2.12 m 2.35 (dd, 3.0, 12.5), 2.48 m 2.51 m 4’ 1.95 m 1.94–2.16 m - - 2.64 m 2.63 m 5’ 2.05 m 1.94–2.16 m - - - - 6’ 5.09 (t, 6.9) 5.21 (t, 6.5) 1.70 m, 2.33 (bd, 18.6) 1.92 m 2.53 (bd, 13.5) 3.88 m 4.13 m 7’ - - 0.97m, 1.30m, 1.28 m, 1.57 m 1.61 m, 1.99 m 1.82 m, 2.16 m 8’ 1.62 s 1.94–2.16 m 1.46 m 1.28 m 1.99 m 1.96 m 9’ 1.49 s 1.94–2.16 m - - - - 10’ 1.48 s 5.17 (t, 6.5) 2.96 (dd, 4.5, 11.5) 3.03 (t, 8.0) 2.23 (bd, 9.7) 2.23 (bt, 7.3) 11’ - 3.42 (d, 8.3), 3.70 (d, 8.3) 3.75 (d, 8.5), 3.95 (d, 8.5) 3.88 m 3.85 (d, 9.0), 3.86 (d, 9.0) 12’ 1.44 s 1.04 s 1.17 s 1.14 s 1.09 s 13’ 1.55 s 1.45 s 1.46 s 1.12 overl 1.58 (d, 6.6) 14’ 1.67 s 1.49 s 1.62 s 0.83 s 1.08 s 15’ 1.55 s 0.69 (d, 6.7) 0.95 (d, 9.0) 1.12 overl 1.11 (d, 7.2) *Data were measured in CD 3 OD. **Data were measured in Pyridine d 5 . Table 2 13 C-NMR data (δ ppm) of compounds 1–4 in C 6 D 6 . 1 2 3 3* 4* 4** 2 160.1 159.8 160.1 162.0 161.9 162.0 3 112.9 113.0 111.9 111.8 112.0 111.8 4 142.6 142.2 142.3 144.4 144.4 144.4 5 128.5 128.3 128.3 129.0 129.1 129.0 6 112.8 112.9 112.5 112.9 112.9 112.9 7 162.0 161.9 162.5 163.0 162.5 163.0 8 101.0 101.0 100.8 100.6 100.9 100.6 9 156.1 156.3 156.2 155.7 155.8 155.7 10 112.2 112.1 112.2 112.4 112.7 112.4 1’ 65.1 65.0 22.0 21.8 23.1 23.4 2’ 119.0 119.0 31.7 31.7 40.8 41.6 3’ 141.2 141.2 172.6 176.8 214.2 211.7 4’ 39.4 39.4 129.7 130.0 57.8 58.4 5’ 26.2 26.1 125.9 125.5 47.2 47.5 6’ 123.9 124.5 24.3 24.2 72.0 71.8 7’ 131.4 135.2 32.0 31.6 35.8 36.8 8’ 17.4 39.8 34.5 34.7 36.3 36.3 9’ 25.5 26.8 40.5 40.5 39.1 39.3 10’ 16.2 123.7 42.4 42.4 43.3 43.7 11’ 130.9 75.4 75.8 12’ 16.2 18.8 19.6 13’ 15.8 9.4 11.1 14’ 25.5 8.2 9.5 15’ 17.4 14.5 15.5 *Data were measured in CD 3 OD. **Data were measured in Pyridine d 5 . In vivo anti-inflammatory testing Carrageenan-induced acute paw edema model for extract and fractions The anti-inflammatory in vivo testing of full and fractionated Ferula assa-foetida extracts compared in Table 3 and shown in Fig. 2. In control group, after injection of carrageenan, there was a progressive paw swelling with an edema of 56.88%, 62.93% and 58.08% at the 1st, 2nd and 3rd hours following, of injection respectively. Conversely, the total extract (AST) was used as pretreatment which resulted in a significant swelling reduction with edema ratios of 37.48%, 35.56%, and 28.71% ±1.55%, at corresponding time points. It was similarly observed that the animals that were treated to the hexane fraction, (ASH) showed percentages of 33.27, 32.35 and 27.79 but ethyl acetate fraction (ASE) gave a percentage of 26.94, 27.11 and 24.90. Indomethacin (IND) resulted in 20.76%, 22.27%, and 20.16% edema rates as the reference drug. It is important to report that ASE showed almost the same anti-inflammatory profile as IND. Of all the samples, ASE 0.2g/kg administered showed the most significant inhibitory properties of carrageenan-induced paw edema, as evidenced by the inhibitory effects indicated by 52.63%, 56.63%, and 56.82% at 1, 2, and 3 hours, respectively (Fig. 4). When compared, the chloroform extraction of ASC and the solubility insoluble residual, ASI made no apparent change in paw volume as compared with the untreated samples. Table 3 Effect of AST and its fractions on the edema rate percentage produced by carrageenan in rat’s paw. Groups Dose (mg/kg) Edema rate (%) 1 h 2 h 3 h CONT 00 56.88 ± 5.16# 62.93 ± 1.68# 58.08 ± 0.62# IND 10 20.76 ± 1.13* 22.27 ± 0.96* 20.16 ± 0.93* AST 400 37.48 ± 3.66*# 35.56 ± 2.04*# 28.71 ± 1.55*# ASI 400 51.58 ± 4.60# 55.75 ± 4.54# 53.73 ± 2.05# ASH 200 33.27 ± 2.23*# 32.35 ± 2.03*# 27.79 ± 2.47*# ASC 200 46.71 ± 1.58# 54.65 ± 2.11# 52.62 ± 1.07# ASE 200 26.94 ± 1.08* 27.11 ± 0.80* 24.9 ± 0.69* Values are presented as mean ± S.E of 6 animals for each group. *Statistically significant from control: P ≤ 0.05. #Statistically significant from IND: P ≤ 0.05. In vitro anti-inflammatory testing for pure compounds 1–4 Lipopolysaccharide-Induced Inflammation in RAW 264.7 Mouse Macrophages The cytotoxicity of the isolated compounds on the production of nitric oxide (NO) inhibition as well as assessing their in vitro anti-inflammatory activities was determined via the sulforhodamine B (SRB)) assay on LPS-induced RAW 264.7 macrophages first. Concentration range in the test was 0.001 to 10 µM. The macrophage toxicity of the compounds tested was not significant at any of the doses tested with near full cell viability observed at the highest dose nearly 99% as shown in Fig. 3, compared with LPS-treated control. As a result, the following concentration ranges were chosen to perform the further inhibition experiments of nitric oxide. Nitric oxide inhibition test in vitro As shown in Fig. 4, compound 4 was the most effective nitric oxide (NO) inhibitor, with an IC 50 value of 3.165 ± 0.12 µM. Furthermore, compounds 1 and 2 also demonstrated potent NO inhibition activity, displaying nearly the same IC 50 values of 8.388 ± 0.24 µM and 8.754 ± 0.17 µM, respectively. The three compounds 1 , 2 and 4 showed NO inhibition activity more than the positive control (quercetin with an IC 50 value of 22.10 ± 0.11 µM). The least NO inhibitor in this series was compound 3 with an IC 50 value of 33.59 ± 2.65 µM. Computational analysis of physicochemical and pharmacokinetic properties Virtual analysis of physicochemical properties by the SwissADME database revealed that the most active compound 4 possesses the lowest lipid solubility and a high number of possible hydrogen-bonding compounds 1 and 2 (Table 4). While compounds 3 and 4 had similar number of hydrogen-bond acceptors and donors, their anti-inflammatory activity was dissimilar. Within the isolated compounds, only compound 4 was found to interact with the efflux pump P-glycoprotein (Pgp). Interactions with microsomal enzymes were variable with each compound having a different interaction profile than the other. Compound 2 interactions could not be determined by the SwissADME database. Table 4 Relative anti-inflammatory activity (designated as NO inhibition), and computational analysis of physicochemical and pharmacokinetic properties. Compound NO inhibition (10 µM) LogP H-bond acceptors H-bond donors Pgp substrate CYP1A2 inhibitor CYP2C9 inhibitor CYP2D6 inhibitor CYP3A4 inhibitor 1 ++ 4.86 3 0 No Yes Yes No No 2 ++ 6.59 3 0 ND ND ND ND ND 3 + 5.43 5 1 No No Yes No Yes 4 +++ 4.20 5 1 Yes No No Yes Yes ND: could not be determined by SwissADME database. The symbols (+, ++, +++) indicate different levels of activity: low, moderate, and high, respectively. Inflammation-related and compounds gene targets A total of 16,356 genes were identified by the GeneCards database when using the search term “inflammation”. For this study, only the top 2,500 genes were considered to provide a stringent criterion for detection. The gene targets of compounds 1–4 were determined by the “SwissTargetPrediction” database. Collectively, the compounds 1–4 had a total of 96 gene targets, some of which were exclusive to some compounds, while others were common (Table 5). Compound 3 had no predicted gene targets. Venn diagrams identified 39 gene targets overlapping between the top 2,500 inflammation genes, and the isolated compounds. Table 5 The number of compounds’ gene targets predicted by the SwissTargetPredict database, and the number of target genes common with inflammation. Compound Gene targets Overlapping with top 2,500 inflammation-related genes 1 76 29 2 53 22 3 0 0 4 9 2 All 96 39 The Cytoscape software was utilized to construct a network highlighting the common and exclusive gene targets of each compound (Fig. 5). Interestingly, compounds 1 , 2 , and 4 had 2 common targets: monoamine oxidase-A (MAOA) and monoamine oxidase-B (MAOB). Protein-protein interactions A network highlighting the protein-protein interactions (PPIs) of the 39 inflammation-related gene targets of compounds 1 , 2 , and 4 was constructed by the STRING database (Fig. 6). This aims to analyze known and predicted interactions between these genes and has assigned an enrichment p-value of < 8.02e-9, where a small p-value indicates a significant interaction probability. The Cytoscape software was used to analyze and highlight the 39 gene targets identifying the core genes with the highest degree of centrality (DC) (Fig. 7). The top 4 genes based on DC were found to be highly involved in immunogenic responses and inflammatory cytokines on several fronts (Table 6). Table 6 Brief description of the genes with the highest DC. Gene symbol Description DC HSP90AA1 Heat shock protein 90 alpha family class A member 1. Chaperone protein that aids in folding other proteins. Found to promote inflammation and immune cell activation 18,19 . 12 NR3C1 Nuclear receptor subfamily 3 group C member 1. Encodes glucocorticoid receptor, which is known to be involved in inflammatory responses and cellular proliferation 20,21 . 11 APP Amyloid beta precursor protein. Encodes the bases of amyloid plaques, which were found to have synergistic pro-inflammatory activity 22,23 . 11 ABL1 ABL proto-oncogene 1. Encodes a protein kinase involved in cell division and adhesion. Also modulates innate immunity by regulating ubiquitination of other proteins 24 . 10 Enrichment analysis of the gene targets Analysis of the 39 inflammation genes identified previously was performed by the ShinyGO database. Analysis of the “biological process” revealed the targeted genes to be involved in several biological processes, including the cellular response to several molecular structural aspects such as oxygen-containing compounds, organic cyclic compounds, cytokines in general, lipids, organic hydroxy compounds, and carboxylic acids (Fig. 8). Molecular docking analysis of target proteins with compounds For the molecular docking analysis, the common target genes MAOA and MAOB were selected after analyzing the Cytoscape software network due to these genes being common targets to compounds 1 , 2 , and 4 . The docking protocol was initially validated by redocking the co-crystalized ligands namely, Clorgyline and CS-0379511 against their target proteins, MAOA and MAOB, respectively. Both ligands adapted similar binding conformations to crystalized once with high binding energy scores, -12.90 and − 12.60 kcal/Mol respectively (Table 7). For MAOA, compound 4 showed the highest binding energy score of -12.00 kcal/mol, while compound 2 showed the highest score (-11.40 kcal/mol) with MAOB enzyme. Remarkably, compound 3 showed low energy scores against both proteins supporting the previous prediction of non-interaction with MAOA and MAOB. The compounds interacted with the active sites of MAOA and MAOB via multiple interactions forces (Figs. 9 and 10). For compound 4 , which is the most active one, it showed better binding with MAOA compared with MAOB. For MAOA, compound 4 involved in hydrogen binding with Ser209 with the carbonyl of hydronaphthalenone and multiple hydrophobic interactions such as Gly67, Tyr69, Ile180, Phe208, Ile335, Leu337, Phe352, Tyr407, and Tyr444 (Fig. 9). Similarly, compound 4 interacted with MAOB through formation of hydrogen bond with Tyr435 the carbonyl of hydronaphthalenone and other hydrophobic bonds with Pro104, His115, Ile164, Leu171, Ile199, Gln206, Ile316 and Tyr320 (Fig. 10). Molecular dynamic simulation analysis of compound 4 with MAOA and MAOB The most active compound, compound 4 , was subjected to 20 ns molecular dynamic (MD) simulation to determine its interaction behavior with both proteins, MAOA and MAOB, in a manner mimicking physiological conditions. For the binding of compound 4 with MAOA, both protein backbone and ligand root mean square deviation (RMSD) showed a behavior without major fluctuations over the simulation-time suggesting a stable binding condition (Fig. 11A and B). The root means square fluctuation (RMSF) analysis showed that in addition to the high fluctuations in the incompatible residues located in the N-terminal (amino acids up to No. 12) as well as in the C-terminal (459–463), some fluctuation was seen in loop regions around residue 102–125 and 251–252 (Fig. 11C). The analysis of intermolecular hydrogen bond formation between compound 4 and MAOA indicated that this compound can form a maximum of 3 bonds. Hence, the formation of hydrogen bonds contributes significantly to the binding energy of interaction (Fig. 11D). Similarly, it can be seen in Fig. 12A and 12B that the interaction behavior of compound 4 with MAOB follows the same fluctuation pattern as shown with MAOA. No major disrupted fluctuations with backbone RMSD between 0.15–0.25 nm and ligand RMSD being stable around 0.15 nm. In addition, The RMSF analysis showed that compound 4 binding residues (Pro104, His115, Ile164, Leu171, Ile199, Gln206, Ile316, Tyr320, and Tyr435) have very low fluctuations behavior. The significant fluctuations can be seen in the c-terminal region (490–501) (Fig. 12C). The analysis of intermolecular hydrogen bond formation between compound 4 and MAOB showed that there can be up to 5 stable hydrogen bonds between the ligand and protein (Fig. 12D). Discussion Inflammation is an inherent natural physiological defense mechanism through which the organism responds to tissue injury or infection and the main goal of which is the restoration of both structural and functional integrity 1 . Although steroidal and non-steroidal anti-inflammatory drugs (NSAIDs) are common in the clinical world to treat inflammation-related conditions, the drug delivery process is often surrounded by unwanted side effects and its possible complications 25 . Plant-based natural agents, especially secondary metabolites of medicinal plants, have therefore gained attraction as alternate sources of anti-inflammatory. The carrageenan-induced paw edema model in rodents has been found as one of the most frequently used experimental methods in studying the potential response of an experimental animal by administering carrageenans as an anti-inflammatory agent under laboratory conditions. It is a common model of acute inflammation, during which there is infiltration of polymorphonuclear neutrophils with an increase in prostaglandin production 26 . Inflammatory process caused by carrageenan involves neutrophilic leukocyte recruitment and the production of prostaglandins which further instigate the production of histamine, serotonin, bradykinin, among other inflammatory mediators 27 . The volume increase of the paws is normally used to indicate the level of inflammation in experimental assessment. This experiment aimed to study the anti-inflammatory properties of the total extract of Ferula assa-foetida (AST) and its fractions which are derived through the carrageenan-induced paw edema test in rats. There was a significant inhibition of paw swelling in the AST treated groups 34.10%, 43.12%, and 50.21% 1 hour, 2 hours, and 3 hours following induction of inflammation respectively. The hexane fraction (ASH) exhibited a significant activity as well with inhibition values of 41.65%, 53.33%, and 54.44% over the same periods of time. In the previous pharmacodynamic studies, it was reported that when administered orally, the ethyl acetate fraction (ASE) used at 200 mg/kg demonstrated greater anti-inflammatory effect, than the reference NSAIDs indomethacin (IND) at 10 mg/kg 28 . IND is quite known as having an analgesic, antipyretic, and inflammation inhibitory effect. The simple in vivo analysis of ASE versus IND answers via the similar, and in some cases even better, performance illustrates the therapeutic potential of the tested extract. Conversely, the insoluble residue fraction (ASI) and the chloroform fraction (ASC) did not lead to a serious anti-inflammatory reaction in any case, according to the same experimental conditions. Phytochemical study of the most active ASH and ASE resulted in the isolation of four coumarins coupled with various terpene moieties 1–4 . The four compounds showed five signals in the aromatic region assigned for H-3, H-4, H-5, H-6 and H-8 (Table 2 ) with their correlated carbons (Table 3 ) were diagnostic for 7-oxygenated coumarin skeleton common in Ferula species 15 – 17 . Compound 1 showed in the HRESIMS an [M-H] + at 297.1483 m/z in the negative mode and [M + H] + at 299.1640 m/z for the molecular formula C 19 H 22 O 3 (Figures S1 1, S12). The additional 10 carbon signals over the coumarin skeleton were sorted by DEPT135 experiment (Figure S8) into CH 3 X 3, CH 2 X 3, CH X 2 and 2 quaternary carbons. The molecular formula indicated 9 degrees of unsaturation. As the coumarin skeleton fulfill 7 unsaturation degrees, the monoterpene moiety was left with only 2 degrees of unsaturation. Two double bonds were observed in the 1 HNMR and 13 CNMR of 1 at δ H 5.39 (t, J = 6.5 Hz), δ C 119.0, 141.2 ppm and δ H 5.09 (t, J = 6.9 Hz), δ C 123.9, 131.4 ppm and assigned for C-2’ and C-6’ respectively (Tables 2 , 3 , Figures S1 - S8). These features were diagnostic for acyclic monoterpene moiety coupled to the coumarin skeleton. The data of 1 were identical with those reported for auraptene 29 , 30 . Auraptene was reported to be effective for the management of inflammatory disorders, dysentery, wounds, scars, keloids, and pain 31 . 13 CNMR and DEPT135 of 2 (Table 3 , Figures S1 6- S20) displayed extra 5 carbon signals over 1 . The three degrees of unsaturation left for the terpenoid moiety were fulfilled by 3 double bonds. Signals at δ H 5.40 (t, J = 6.5 Hz), δ C 119.0, 141.2 ppm, δ H 5.21 (t, J = 6.5 Hz), δ C 124.5, 135.2 ppm and δ H 5.17 (t, J = 6.5 Hz), δ C 123.7, 130.9 ppm were assigned for C-2’, C-6’ and C-10’ double bonds, respectively in an acyclic sesquiterpene structure (Tables 2 , 3 , Figures S1 3- S20). HRESIMS showed [M + H] + at 367.2263 m/z and [M + Na] + at 367.2263 m/z (Figure S23) for the molecular formula C 24 H 30 O 3 . The data of 2 showed close similarity with those reported for umbelliprenin 32 . Umbelliprenin is reported to possess cancer chemopreventive, anti-bacterial, anti-protozoal, anti-fungal, anti-inflammatory, neuroprotective, and antioxidant 33 . Compound 3 showed in the HRESIMS an [M-H] + at 397.2016 m/z in the negative mode and [M + H] + at 399.2162 m/z and [M + Na] + 421.1981 in the positive mode m/z for the molecular formula C 24 H 30 O 5 (Figures S45, S46). In the 13 CMR in addition to the coumarin skeleton, 15 carbon resonances were observed and categorized by DEPT135 experiment into CH 3 X 4, CH 2 X 5, CH X 2 and 4 quaternary carbons (Table 3 , Figures S27- S30, S37- S39). The molecular formula revealed 10 degrees of unsaturation’s three of them were for the terpenoid moiety. Compound 3 showed two extra oxygen atoms over 2 . These two oxygen atoms were assigned for a carboxylic group at δ C 172.6 ppm. Two olefinic carbons at δ C 129.7 and 125.9 ppm constituted one double bond. The left unsaturation degree indicated a ring structure in the terpene part. Spectral data of 3 expressed close similarity with galbanic acid literature data 34 . Among the reported biological activity of galbanic acid are the anticancer, cancer chemopreventive, anticoagulant, hepatoprotective, antiviral, acetylcholinesterase inhibitory and antileishmanial activities 35 . The HRESIMS of 4 was identical with 3 showing an [M + H] + at 399.2165 and [M + Na] + 421.1982 m/z (Figure S61). The 13 CNMR spectra showed carbonyl signal at δ C 214.2 ppm diagnostic for a ketone function 9. Another oxygen was involved in the formation of secondary alcohol function at δ C 72.6 ppm. There was no indication of the presence of double bonds in the terpenoid part and consequently, there must be two ring structures (Table 3 , Figures S49- S51, S57-S60). Comparison with literature data enables the identification of 4 as the sesquiterpene coumarin kamolonol 36 . Cytotoxicity antimicrobial and antioxidant activity were reported for Kamolonol acetate 37 . Kamolonol showed antibacterial activity against Heliobacter pylori and Staphylococcus aureus 36 . Nitric oxide (NO) is regarded as a central pro-inflammatory factor in the development and progressive evolution of various inflammatory illnesses. High levels of NO have been observed in instances of increased severity of disease, and this shows that it is a good parameter in the treatment of inflammation by way of monitoring 38 , 39 . Prevention of excessive formation of NO is thus a logical mode of treatment of inflammatory diseases. The current in vitro experiment evaluated the inhibitory activity of isolated components on NO production in the case of lipopolysaccharide (LPS)-activated macrophages. The in vitro NO inhibition assay demonstrated that compounds 1, 2 , and 4 showed higher NO inhibition activity compared to the positive control quercetin (IC₅₀ = 22.10 ± 0.11 µM). In contrast, compound 3 exhibited the weakest inhibition, with an IC₅₀ value of 33.59 ± 2.65 µM. The physiochemical behavior of these compounds 3 and 4 was found to have almost the same parameters (Table 4 ), but the anti-inflammatory activity of the two compounds varied decisively. This discrepancy could be attributed to the carboxylic acid moiety in compound 3 ( galbanic acid), which may ionize at physiological pH, compromising membrane permeability and intracellular uptake. This hypothesis aligns with previous reports on methyl galbanate, where esterification enhances bioavailability by preventing ionization 35 . Compounds 1 and 2 lack the hydroxyl and carbonyl functions in compound 4 enable better binding of the latter at the molecular targets. Compound 2 had no prediction of pharmacokinetic interactions. This can be attributed to the lack of structural similarity with known ligands currently within the SwissADME database. The SwissTargetPrediction database failed to detect gene targets for compound 3 (Table 5 ). The remaining isolated compounds 1 , 2 , and 4 had common targets of MAOA and MAOB (Fig. 5 ), both of which are implicated in immunity and inflammatory responses 40 – 42 . Targeting these genes could mediate the observed anti-inflammatory properties. Analysis of PPIs revealed a high degree of interaction revolving around inflammation and immunity-related genes (Table 6 ). This is consistent with the observed anti-inflammatory properties. Even though the common gene targets (MAOA and MAOB) were not the top genes in terms of interactions, they still had a relatively high DC (Fig. 7 ). Biological processes in gene ontology describe and categorize overarching cellular events rather than specific pathways or biological components, in this study compounds 1 , 2 , and 4 were predicted to interact with a plethora of biological targets with the common trait of being responsive to oxygen-containing compounds, whether these compounds are exogenous or endogenous. Enrichment analysis of the 39 genes targeted by compounds 1 , 2 , and 4 also suggests involvement with a variety of cellular responses affecting cell activity, cellular movement, secretions, and metabolic states. This is due to targeting several receptor pathways and binding of many enzymes including kinases (Fig. 8 ). This encompasses a wide variety of cellular functions, not excluding inflammatory responses 43 . Molecular docking revealed that all isolated compounds are localized within the pharmacophores of both MAOA and MAOB in a manner like known controls (Figs. 9 and 10 ). Compound 4 had highest binding affinity, a characteristic that was associated with its maximum anti-inflammatory activity compared to compound 3 that was characterized by the weakest interaction. The docking findings were consistent with the molecular dynamics’ simulations of the compound 4 with MAO-A and MAO-B in which the established ligand-protein interaction was stable over the simulation time. The above findings (Figs. 11 and 12 ), together argue that the compound could be stable and suitable in physiological conditions. Conclusion This study shows that Ferula assa-foetida has anti-inflammatory properties, especially in the EtOAc fraction, which supports its usage in ethnomedicine. The most promising pharmacological characteristics of the isolated sesquiterpene coumarins were demonstrated by kamolonol (compound 4), which exhibited substantial affinity for monoamine oxidase A (MAOA) and B (MAOB), superior nitric oxide (NO) inhibition, and sustained molecular interactions in physiologically simulated settings. The anti-inflammatory effect of 4 is reported for the first time. These results establish compound 4 as a viable candidate for additional drug development initiatives in addition to identifying MAOA and MAOB as anti-inflammatory targets. In vivo models of chronic inflammation, thorough pharmacokinetic characterization, and synergistic studies with established anti-inflammatory drugs.Such investigations could further affirm the therapeutic relevance of compound 4 and support its progression toward clinical application. Methods General The tools and materials used in the process of this study have been sufficiently outlined in the previous studies 44 . Asafoetida oleo-gum-resin In 2023, oleo-gum-resin of Ferula assa-foetida (asafoetida) was obtained in one of the Riyadh markets, Saudi Arabia. Extraction and isolation An amount of 1000 g oleo-gum-resins underwent exhaustive extraction using alcoholic content of 95%. Aggregation of the combination of ethanol extracts obtained yielded 600.45 g of the total ethanol extract (AST). Ethanol-soluble fraction (ASI) had the mass of 399.55 g as is the case with the remaining quantity of the initial starting material. AST (28 g) was dissolved in 300 mL of 40% aqueous ethanol, fractionated by successive liquid-liquid extraction using an aliquot part. Hexane (3 x 400 mL) partitioning gave 13.45 g of the hexane-soluble fraction (ASH). Extraction with chloroform (CHCl 3 ) (4 x 400 mL) yielded 3.60 g of the CHCl 3 -soluble fraction (ASC) and ethyl acetate (EtOAc) ( 2 x 400 mL) gave rise to 5.00 g of the EtOAc-soluble fraction (ASE). The ASH fraction (10 g) was used as the sample under the column chromatography (gravity) using silica gel (250 g) over packed gravity column (150 x 5 cm i.ds.). Hexane was used to elute the column followed by hexane/EtOAc gradient. Fractions of 200 ml were taken and attached through thin layer chromatography (TLC). Fractions exhibiting the same TLC patterns were pooled into 4 fractions, namely ASH -A to and ASH -D. Reversed-phase RP-18 medium-pressure liquid chromatography (MPLC) (45 x 1 cm i.d.) in a water/methanol gradient was used to purify the fraction of ASH-B (1.38 g) sediment that remains purified after chromatography through the silica gel to a greater extent (fraction ASH-B). A 70% methanol elution provided 66 mg of compound 1. Fractions eluted with 75% MeOH (72 mg) were further purified via preparative TLC (CHCl₃/MeOH, 9.5:0.5), affording 34 mg of compound 2. Fraction D (0.78 g), eluted with hexane/EtOAc (1:1), was purified using a flash chromatography column (45 cm × 1 cm i.d., 30 g silica gel) with CHCl₃ followed by CHCl₃/MeOH gradient.Fractions eluted with CHCl₃/MeOH (95:5) afforded 75 mg of compound 3. Column chromatography on silica gel (75 x 3 cm i.d., 150 g) was applied to a 4.34 g sample of an ASE fraction. The ethyl acetate (EtOAc), followed through the use of ethyl acetate (EtOAc)-methanol (MeOH) mixture gradients. Fractions were obtained after filtration under yellow light in 5% MeOH in EtOAc (252 mg) which were then purified by adsorption chromatography over a reversed-phase RP-18 flash column and using a mobile phase of 70% MeOH 30% H₂O to give 35 mg of compound 4 . The higher the polar fractions the more 200 mg of glucose. Experimental animals This animal experiment was conducted in accordance with the ARRIVE 2.0 guidelines for reporting animal research 45 . Forty-two male Wistar rats of 4 month to 7-month-old and weighing about 180–200 g (some attained 210–220 g), were obtained in the Laboratory Animal Unit (LBU) of Prince Sattam bin Abdulaziz University, Al Kharj, Saudi Arabia. The animals had a one-week acclimatization prior to the beginning of the experiment; during the acclimatization period animals were kept in ventilated cages (Rat IVC Blue Line, Techniplast, Buguggiate VA, Italy) which had sawdust bedding with moisture-absorbing characteristics. Housing was in constant condition of controlled temperature of 25 ± 1°C, 12:12 h of light dark cycle and free access to standard laboratory diet and filtered water were offered in stainless steel drinking bottles. Fuel cleaning was also a common practice and allowed the bedding to be changed on a regular basis, therefore sanitary conditions in housing were to be maintained. Animal handling during the work was carried out following the ARRIVE guidelines. Animal Ethics Statement The animal experiments obeyed all the ethical considerations of laboratory animal care spelled out by the Scientific Research Ethics Committee at Prince Sattam bin Abdulaziz University. Approval was given by the issuance of authorization number SCBR-319/2024 and the procedures undertaken were in conformity to the national guidelines when treating animals with humane treatment and welfare of animals. Carrageenan-induced acute paw edema model The anti-inflammatory effects of the crude extract (AST) and three major fractions (ASI, ASC, ASE) of Ferula assa-foetida were evaluated using the carrageenan-induced paw edema model in adult male Wistar rats (7 months old, 180–200 g). Forty-two rats were randomly divided into seven groups (6 rats each). Indomethacin (10 mg/kg, oral) served as the positive control, while the negative control received saline (2 mL/kg). Treatments included oral administration of AST or ASI (400 mg/kg) and ASH, ASC, or ASE (200 mg/kg). One hour post-treatment, inflammation was induced by injecting 0.1 mL of 1% λ-carrageenan into the right hind paw supplanter region. Paw volumes were recorded pre-injection and at 1, 2, and 3 hours post-injection using a digital plethysmometer. Edema volume and percentage inhibition were calculated following Abdel-Rahman et al 46 . All assessments were performed by an independent, blinded observer: Where V0 is the paw volume (mL) before carrageenan injection and Vt is the paw volume (mL) at t hour after carrageenan injection. Ec and Et are the edema rates of control and treated groups, respectively. Extensive monitoring practices were established in the entire study to identify any possible indications of disaffection, sickness or mood swings. Not a single subject was omitted in the experiment as well as repeated during the study period. In vitro anti-inflammatory testing Cell culture Murine macrophage RAW 264.7 cells were purchased in Nawah Scientific Inc. (Mokatam, Cairo, Egypt). The cells were grown in Dulbecco Modified Eagle Medium (DMEM) that had additional components: streptomycin (100 100 g/mL), penicillin (100 U/mL) and 10% heat-inactivated fetal bovine serum. Cultures were maintained in a humidified incubator at 37°C in an atmosphere of 5% CO₂. Cytotoxicity assay Sulforhodamine B (SRB) assay was used in determining cell viability. In a nut shell, 100 µL of cell suspension (5 x 10^3 cells) was seeded in 96 well plates and culture was incubated to reach 24 hours to adhere to the plate. Then the cells were exposed to 100 µL of media with different doses of the test compounds. Fixed, cells were added 150 µL, 10%Trichloroacetic acid (TCA) and placed in 4°C condition one hour. Five times, Wells were cleaned with distilled water and were desiccated in air. Thereafter, 0.4 per cent SRB solution (70mL) was added into the wells and incubated in the dark at room temperature, 10 minutes. Three washes using 1 percent acetic acid were done to eliminate excess dye and plates allowed to dry overnight. The 150 µL of 10 mM TRIS buffer was added to bound dye and absorbance was read at 540 nm on Infinite F50 microplate reader (TECAN, Switzerland) 47 , 48 . In vitro anti-inflammatory assay In order to test the anti-inflammatory activity, RAW 264.7 cells were incubated to grow in 96 well plates by seeding them over the 24 hours. Lipopolysaccharide (LPS) at the concentration of 1 µg/mL caused inflammation. Control wells had fresh medium added to them after untreated cells and the LPS group did not have any treatment added to the LPS. Test compounds were either tested alone or in combination with LPS at concentrations between 0. 001to 10 uM (LPS + Drug). Quercetin was used as the positive control. Mean production of nitric oxide (NO) was measured through the Griess reagent assay, whereby the same amounts of supernatant culture contents and reagent were combined, incubated with room temperature at darkness by ten minutes and the optical density of the mixture determined at 540 nm with the use of ELISA microplate reader 49 , 50 . Statistical Analysis The means are reported as the standard error of the mean ± (SE). One-way analysis of variance (ANOVA) was conducted as a measure to make statistical comparisons. Dunnett post hoc test was used where it showed a significant F-value ( p ≤ 0.05). The analysis was done on data with SPSS software version 17.0 (Chicago, IL, USA). Determination of physicochemical properties and pharmacokinetic interactions The SwissADME database was utilized to predict the following physicochemical and pharmacokinetic properties for compounds 1 – 4 : lipid solubility calculated (LogP), hydrogen-bonding, interaction with Pgp, and interaction with several microsomal enzymes (CYP1A2, CYP2C9, CYP2D6, CYP3A4) 51 . Virtual screening of inflammation-related genes The GeneCards® database was utilized to identify genes associated with inflammation, using the keyword “inflammation” 52 . Microsoft Excel was used to collect and process data for later steps. In silico screening of gene targets of compounds 1–4 The possible targets of compounds 1–4 on genes were discovered with the assistance of the SwissTargetPrediction platform 40 . The tool predicts probable targets by contrasting the molecular structure of each compound with that of the known ligand of individual proteins based on both two-dimensional and three-dimensional structural similarities, and on the number of ligands having analogous properties. A probability score is created that will show the probability of interaction. This study identified that any predicted targets whose probability value was larger than zero were used further in analyses. Identification of common genes between inflammation and compounds 1–4 Venn diagrams were utilized to identify common targets between the isolated test compounds, and inflammation genes obtained from the previous steps. Overlapping genes for individual compounds were identified 41 . The Cytoscape bioinformatics software (version 3.10.1) was used to highlight common, as well as exclusive gene targets of each compound 42 . Protein–Protein Interaction (PPI) Analysis The target genes of the screened compounds 1–4 were scrutinized as well as the possible and known protein-protein interactions based on the STRING functional protein association networks database 53 . This process allowed identification of a small number of inflammation associated genes having most extensive interaction profiles. It only included interactions with a confidence score having a value greater than 0.4. A visualization of the resulting PPI network together with its analysis in terms of Cytoscape software was performed where all the genes were ranked based on their degree centrality (DC) value which is the cumulative number of PPIs associated to a given gene. Short descriptions about the highest DC value genes were created Enrichment analysis of targeted genes The ShinyGO database analyzed the inflammation-related gene targets of compounds 1–4 54 . This analysis is based on gene ontology and is performed to determine the biological processes influenced by these genes. This analysis determines the number of genes related to a biological aspect, and assigns an FDR significance score. Lower FDR values indicate a stronger prediction, or higher significance. Molecular docking procedure Molecular docking simulations of the binding interactions of compounds 14 in the MAOA and MAOB isoforms of monoamine oxidase have been carried out. They were picked on the basis that both MAOA and MAOB were used as widely predicted targets of compounds 1 , 2 , and 4 , and the enzymes otherwise coded by them significantly contribute to the inflammatory pathways. The compounds 2D chemical structures were initially drawn in ChemDraw then exported in Mol 3D format. These were then transformed to PDB files using BIOVIA discovery studio 2022 visualizer. Crystal structures of MAOA (PDB ID: 2BXR) and MAOB (PDB ID: 7P4F) have been retrieved at the Protein Data Bank 55 . The preparation of protein structures involved isolation of monomeric form and deletion of co-crystallized ligands as well as water molecules in BIOVIA Discovery Studio Visualizer 2022 56 . The ligand and protein files were then converted to Autodock PDBQT using the Autodock Tools that was also used in defining the active site by modifying the grid box such that important amino acid residues that interact with the native ligands were included in the grid box. Autodock Vina was used to do docking and the lowest binding energy compounds-protein complexes were further analyzed. 3D interaction visualization images were then created with Discovery Studio visualizer and UCSF ChimeraX 57 . Molecular dynamic simulation Molecular dynamics (MD) simulations in GROMACS 2018 with the OPLS-AA/L force field were carried out in the current study. Two monoamine oxidase (MAO-A and MAO-B) isoforms were explored, where the three-dimensional structures were improved through the usage of the DockPrep tool 58 . Compound 4 was parameterized using the SwissParam webserver 59 . The MD simulations were performed for 20 ns, as following the same method in a previous study 60 . Essential MDS parameters including RMSD, RMSF, and Hydrogen bonding analysis were evaluated. Declarations Acknowledgments: The researcher gratefully acknowledges the financial support received from Prince Sattam bin Abdulaziz University, which made this study possible. This work was funded under the research project number PSAU/2024/03/31571, and such backing significantly contributed to the successful execution of all research phases. Funding: This study was financially supported by the Deanship of Scientific Research (DSR) at Prince Sattam bin Abdulaziz University as part of project PSAU/2024/03/31571. Declarations of Competing interests The authors declare no competing interests. Data Availability All data generated or analysed during this study are included in this published article and its supplementary information files. Additional information Supplementary Information: The online version contains supplementary material available at XXXXXXXXXXX References Laranjeira, I., Gonçalves, J., Gonçalves, C., Silva, M., Mouta, N., Dias, A. & Pinto-Ribeiro, F. Anti-inflammatory effect of Pterospartum tridentatum leaf extract in acute and chronic inflammation. Appl. Sci. 13 , 4494 (2023). https://doi.org/10.3390/app13074494 Morales, G., Paredes, A., Olivares, A. & Bravo, J. Acute oral toxicity and anti-inflammatory activity of hydroalcoholic extract from Lampaya medicinalis phil in rats. Biol. Res . 47 , 6 (2014). http://doi.org/10.1186/0717-6287-47-6 Mobasheri, L., Khorashadizadeh, M., Safarpour, H., Mohammadi, M., Anani Sarab G. & Askari, V.R. Anti-Inflammatory activity of Ferula assafoetida oleo-gum-resin (Asafoetida) against TNF-α-stimulated human umbilical vein endothelial cells (huvecs). Mediators. Inflamm . 2022 , 5171525 (2022). https://doi.org/10.1155/2022/5171525 Krakauer, T. Molecular therapeutic targets in inflammation: cyclooxygenase and NF-κB. Curr. Drug Targets Inflamm. Allergy. 3 , 317-324 (2004). https://doi.org/10.2174/1568010043343714 Sabry, M.M., Abdel-Rahman, R.F., Fayed, H.M., Taher, A.T., Ogaly, H.A.., Albohy, A., El-Gayed, S.H. & Ibrahim, R.M. Impact of Eucalyptus maculata hook resin exudate constituents on reducing COX-2 gene expression: In-vivo anti-inflammatory, molecular docking and dynamics studies. J. Ethnopharmacol. 314 , 116631 (2023). https://doi.org/10.1016/j.jep.2023.116631 Althurwi, H.N., Abdel-Rahman, R.F., Soliman, G.A., Ogaly, H.A., Alkholifi, F.K., Abd-Elsalam, R.M., Alqasoumi, S.I. & Abdel-Kader, M.S. Protective effect of beta-carotene against myeloperoxidase-mediated oxidative stress and inflammation in rat ischemic brain injury. Antioxidants 11 , 2344 (2022). https://doi.org/10.3390/antiox11122344 Park, M.H. & Hong, J.T. Roles of NF-κB in cancer and inflammatory diseases and their therapeutic approaches. Cells 5 , 15 (2016). https://doi.org/10.3390/cells5020015 Oh, S.Y. & Hyun, C.G. Anti-inflammatory potential of Umckalin through the inhibition of iNOS, COX-2, pro-inflammatory cytokines, and MAPK signaling in LPS-stimulated RAW 264.7 cells. Future Pharmacol. 5 , 6 (2025). https://doi.org/10.3390/futurepharmacol5010006 Yaqoob, U. & Nawchoo, I.A. Distribution and taxonomy of Ferula L.: a review. Res. Rev. J. Bot. 5 , 15 (2016). Mahendra, P. & Bisht, S. Ferula asafoetida : traditional uses and pharmacological activity. Pharmacogn. Rev. 6 , 141-146 (2012). https://doi.org/10.4103/0973-7847.99948 Mohammadhosseini, M.; Venditti, A.; Sarker, S.D.; Nahar, L.; Akbarzadeh, A. The genus Ferula : ethnobotany, phytochemistry and bioactivities – a review. Ind Crops Prod , 2019 , 129 , 350-394. https://doi.org/10.1016/j.indcrop.2018.12.012 Sahebkar, A. & Iranshahi, M. Volatile constituents of the genus Ferula (Apiaceae): a review. J. Essent. Oil. Bear. Plants 14 , 504-531 (2011). http://dx.doi.org/10.1080/0972060X.2011.10643969 Li, N., Guo, T. & Zhou, D. Bioactive Sesquiterpene Coumarins From Plants. In Studies in Natural Products Chemistry , Atta-ur-Rahman, Eds, Elsevier: 2018, Volume 59, pp. 251-282. https://doi.org/10.1016/B978-0-444-64179-3.00008-6. Geroushi, A., Auzi, A.A., Elhwuegi, A.S., Elzawam, F., Elsherif, A., Nahar, L. & Sarker, S.D. Antiinflammatory sesquiterpenes from the root oil of Ferula hermonis . Phytother. Res. 25 , 774-777 (2011). https://doi.org/10.1002/ptr.3324 Wang, J., Huo, X., Wang, H., Dong, A., Zheng, Q. & Si, J. Undescribed sesquiterpene coumarins from the aerial parts of Ferula sinkiangensis and their anti-inflammatory activities in lipopolysaccharide-stimulated RAW 264.7 macrophages. Phytochemistry 210 , 113664 (2023). https://doi.org/10.1016/j.phytochem.2023.113664 Dang, W., Guo, T., Zhou, D., Meng, Q., Fang, M., Chen, G., Lin, B., Hou, Y. & Li, N. Structure-guided isolation of anti-neuroinflammatory sesquiterpene coumarins from Ferula sinkiangensis. Chin. J. Nat. Med. 22 , 643-653 (2024). https://doi.org/10.1016/s1875-5364(24)60619-9 Guo, T., Dang, W., Zhou, Y., Zhou, D., Meng, Q., Xu, L., Chen, G., Lin, B., Qing, D., Sun, Y., Hou, Y. & Li, N. Sesquiterpene coumarins isolated from Ferula bungeana and their anti-neuroinflammatory activities. Bioorg. Chem. 128 , 106102 (2022). https://doi.org/10.1016/j.bioorg.2022.106102. Zhang, H., Huang, J., Fan, X., Miao, R. & Wang, Y. HSP90AA1 promotes the inflammation in human gingival fibroblasts induced by Porphyromonas gingivalis lipopolysaccharide via regulating of autophagy. BMC Oral Health 22 , 366 (2022). https://doi.org/10.1186/s12903-022-02304-0 Tukaj, S. & Węgrzyn, G. Anti-Hsp90 therapy in autoimmune and inflammatory diseases: a review of preclinical studies. Cell Stress Chaperones 21 , 213-218 (2016). https://doi.org/10.1007/s12192-016-0670-z Li, L., Xing, W., Jiang, L., Chen, D. & Zhang, G. NR3C1 overexpression regulates the expression and alternative splicing of inflammation-associated genes involved in PTSD. Gene 859 , 147199 (2023). https://doi.org/10.1016/j.gene.2023.147199 Newton, R. Anti-inflammatory glucocorticoids: changing concepts. Eur. J. Pharmacol. 724 , 231-236 (2014). https://doi.org/10.1016/j.ejphar.2013.05.035 LaRocca, T.J., Cavalier, A.N., Roberts, C.M., Lemieux, M.R., Ramesh, P., Garcia, M.A. & Link, C.D. Amyloid beta acts synergistically as a pro-inflammatory cytokine. Neurobiol. Dis. 159 , 105493 (2021). https://doi.org/10.1016/j.nbd.2021.105493 Liu, P., Zhao, B., Wei, M., Li, Y., Liu, J., Ma, L., Shang, S., Huo, K., Wang, J., Li, R. & Qu, Q. Activation of inflammation is associated with amyloid-β accumulation induced by chronic sleep restriction in rats. J. Alzheimers Dis. 74 , 759-773 (2020). https://doi.org/10.3233/jad-191317 Xu, F., Yao, W., Xue, Y., Sun, Q. & Cao, C. The oncogene ABL1 regulates the inflammatory response of innate immunity via mediating TRAF6 ubiquitination. Immunobiology 227 , 152262 (2022). https://doi.org/10.1016/j.imbio.2022.152262 Scheiman, J.M. NSAID-induced gastrointestinal injury: a focused update for clinicians. J. Clin. Gastroenterol. 50 , 5-10 (2016). https://doi.org/10.1097/mcg.0000000000000432 Xiang, L., Huang, Q., Chen, T., He, Q., Yao, H. & Gao, Y. Ethanol extract of Paridis rhizoma attenuates carrageenan-induced paw swelling in rats by inhibiting the production of inflammatory factors. BMC Complement Med Ther . 23 , 437 (2023). https://doi:10.1186/s12906-023-04264-6 Crunkhorn, P. & Meacock, S.C. Mediators of the inflammation induced in the rat paw by carrageenin. Br. J. Pharmacol. 42 , 392-402 (1971). https://doi.org/10.1111/j.1476-5381.1971.tb07124.x Nalamachu, S. & Wortmann, R. Role of indomethacin in acute pain and inflammation management: a review of the literature. Postgrad. Med. 126 , 92-97 (2014). https://doi.org/10.3810/pgm.2014.07.2787 Tun, K.N.W., Aminah, N.S., Kristanti, A.N., Ramadhan, R. & Takaya, Y. Cytotoxic prenyl and geranyl coumarins from the stem bark of Casimiroa edulis. Lett. Org. Chem. 17 , 680-687 (2020). http://dx.doi.org/10.2174/1570178616666191019121437 Tjahjandarie, T.S. Coumarins from the stem bark of Feronia limonia . J. Chem. Pharm. Res. 6 , 499-504 (2014). Bibak, B., Shakeri, F., Barreto, G.E., Keshavarzi, Z., Sathyapalan, T. & Sahebkar, A. A review of the pharmacological and therapeutic effects of auraptene. Biofactors 45 , 867-879 (2019). https://doi.org/10.1002/biof.1550 Iranshahi, M., Shahverdi, A.R., Mirjani, R., Amin, G. & Shafiee, A. Umbelliprenin from Ferula persica roots inhibits the red pigment production in Serratia marcescens. Z. Naturforsch. C. J. Biosci. 59 , 506-508 (2004). https://doi.org/10.1515/znc-2004-7-809 Fiorito, S., Preziuso, F., Sharifi-Rad, M., Marchetti, L. & Epifano. F., Genovese, S . Auraptene and Umbelliprenin: a review on their latest literature acquisitions. Phytochem. Rev. 21 , 317–326 (2022). https://doi.org/10.1007/s11101-020-09713-5 Eruçar, F.M., Senadeera, S.P.D., Wilson, J.A., Goncharova, E., Beutler, J.A. & Miski, M. Novel cytotoxic sesquiterpene coumarin ethers and sulfur-containing compounds from the roots of Ferula turcica . Molecules 28 , 5733 (2023). https://doi.org/10.3390/molecules28155733 Kasaian, J., Iranshahy, M. & Iranshahi, M. Synthesis, biosynthesis and biological activities of galbanic acid – A review. Pharm. Biol. 52 , 524–531 (2013). https://doi.org/10.3109/13880209.2013.846916 Dastan, D., Salehi, P., Reza Gohari, A., Ebrahimi, S.N., Aliahmadi, A. & Hamburger, M. Bioactive sesquiterpene coumarins from Ferula pseudalliacea. Planta Med. 80 , 1118-1123 (2014). https://doi.org/10.1055/s-0034-1382996 Mahaki, H., Tanzadehpanah, H., Abou-Zied, O.K., Moghadam, N.H., Bahmani, A., Salehzadeh, S., Dastan, D. & Saidijam, M. Cytotoxicity and antioxidant activity of Kamolonol acetate from Ferula pseudalliacea, and studying its interactions with calf thymus DNA (ct-DNA) and human serum albumin (HSA) by spectroscopic and molecular docking techniques. Process Biochem . 79 , 203-213 (2019). https://doi.org/10.1016/j.procbio.2018.12.004 Abbas, Z., Tong, Y., Zhang, J., Wang, J., Guo, H., Cheng, Q., Marhaba, Zhou, Y., Ahmad, B., Wei, X., Si, D. & Zhang, R. Enhancing the antioxidant and anti-inflammatory potentials of mulberry-derived postbiotics through submerged fermentation with B. subtilis H4 and B. amylolique faciens LFB112. Food Biosci . 60 , 104252 (2024). https://doi.org/10.1016/j.fbio.2024.104252 Saijo, F., Milsom, A.B., Bryan, N.S., Bauer, S.M., Vowinkel, T., Ivanovic, M., Andry, C., Granger, D.N., Rodriguez, J. & Feelisch, M. On the dynamics of nitrite, nitrate and other biomarkers of nitric oxide production in inflammatory bowel disease. Nitric Oxide 22 , 155-167 (2010). https://doi.org/10.1016/j.niox.2009.11.009 Daina, A., Michielin, O. & Zoete, Z. SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules. Nucleic Acids Res. 47 , W357-W364 (2019). https://doi.org/10.1093/nar/gkz382 https://bioinformatics.psb.ugent.be/webtools/Venn/ Kohl, M., Wiese, S. & Warscheid, B. Cytoscape: software for visualization and analysis of biological networks. Methods Mol. Biol. 696 , 291-303 (2011). https://doi.org/10.1007/978-1-60761-987-1_18 Zarrin, A.A., Bao, K., Lupardus, P. & Vucic, D. Kinase inhibition in autoimmunity and inflammation. Nat. Rev. Drug Discov. 20 , 39-63 (2021). https://doi.org/10.1038/s41573-020-0082-8 Alqarni, M.H., Soliman, G.A., Salkini, M.A., Alam, P., Yusufoglu, H.S., Baykan S., Ozturk, B. & Abdel-Kader, M.S. The potential aphrodisiac effect of Ferula drudeana korovin extracts and isolated sesquiterpene coumarins in male rats. Pharmacogn. Mag. 16 , 404-409 (2020). http://dx.doi.org/10.4103/pm.pm_551_19 Percie du Sert, N., et al. The ARRIVE guidelines 2.0: Updated guide-lines for reporting animal research. PLoS Biol, 18 , e3000410 (2020). https://doi.org/10.1371/journal.pbio.3000410 Abdel-Rahman, R.F., Alqasoumi, S.I., El-Desoky, A.H., Soliman, G.A., Paré, P.W. & Hegazy, M.E. Evaluation of the anti-inflammatory, analgesic and anti-ulcerogenic potentials of Achillea fragrantissima (Forssk.). S. Afr. J. Bot. 98 , 122-127 (2015). https://doi.org/10.1016/j.sajb.2015.02.009 Skehan, P., Storeng, R., Scudiero, D., Monks, A., McMahon, J., Vistica, D., Warren, J.T., Bokesch, H., Kenny, S. & Boyd, M.R. New colorimetric cytotoxicity assay for anticancer-drug screening. J. Natl. Cancer Inst. 82 , 1107-1112 (1990). https://doi.org/10.1093/jnci/82.13.1107 Allam, R.M., Al-Abd, A.M., Khedr, A., Sharaf, O.A., Nofal, S.M., Khalifa, A.E., Mosil, H.A. & Abdel-Naim, A.B. Fingolimod interrupts the cross talk between estrogen metabolism and sphingolipid metabolism within prostate cancer cells. Toxicol. Lett. 291 , 77-85 (2018). https://doi.org/10.1016/j.toxlet.2018.04.008 Kim, C.E., Le, D.D. & Lee, M. Diterpenoids isolated from Podocarpus macrophyllus inhibited the inflammatory mediators in LPS-induced HT-29 and RAW 264.7 cells. Molecules 26, 4326 (2021). https://doi.org/10.3390/molecules26144326 Ahmed, A.H.H., Mohamed, M.F.A., Allam, R.M., Nafady, A., Mohamed, S.K., Gouda, A.E. & Beshr, E.A.M. Design, synthesis, and molecular docking of novel pyrazole-chalcone analogs of lonazolac as 5-LOX, iNOS and tubulin polymerization inhibitors with potential anticancer and antiinflammatory activities. Bioorg. Chem. 129, 106171 (2022). https://doi.org/10.1016/j.bioorg.2022.106171 Daina, A., Michielin, O. & Zoete, V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci. Rep. 7 , 42717 (2017). https://doi.org/10.1038/srep42717 Safran, M., Dalah, I., Alexander, J., Rosen, N., Stein, T.I., Shmoish, M., Nativ, N., Bahir, I., Doniger, T., Krug, H., Sirota-Madi, A., Olender, T., Golan, Y., Stelzer, G., Harel, A. & Lancet, D. GeneCards Version 3: the human gene integrator. Database 2010 , baq020 (2010). https://doi.org/10.1093/database/baq020 Szklarczyk, D., Kirsch, R., Koutrouli, M., Nastou, K., Mehryary, F., Hachilif, R., Gable, A.L., Fang, T., Doncheva, N.T., Pyysalo, S., Bork, P., Jensen, L.J. & Mering, C.V. The STRING database in 2023: protein– protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 51 , D638-D646 (2023). https://doi.org/10.1093/nar/gkac1000 Ge, S.X., Jung, D. & Yao, R. ShinyGO: a graphical gene-set enrichment tool for animals and plants. Bioinform . 36 , 2628-2629 (2020). https://doi.org/10.1093/bioinformatics/btz931 Kouranov, A., Xie, L., de la Cruz, J., Chen, L., Westbrook, J., Bourne, P.E. & Berman, H.M. The RCSB PDB information portal for structural genomics. Nucleic Acids Res. 34 , D302-D305 (2006). https://doi.org/10.1093/nar/gkj120 Systèmes D (2021) Discovery studio visualizer. v16, 1, 15350. Pettersen, E.F., Goddard, T.D., Huang, C.C., Meng, E.C., Couch, G.S., Croll, T.I., Morris, J.H. & Ferrin, T.E. UCSF ChimeraX: Structure visualization for researchers, educators, and developers. Protein Sci . 30 , 70-82 (2021). https://doi.org/10.1002/pro.3943 Van Der Spoel, D., Lindahl, E., Hess, B., Groenhof, G., Mark, A.E. & Berendsen, H.J.C. GROMACS: fast, flexible, and free. J. Comput. Chem. 26 , 1701-1718 (2005). https://doi.org/10.1002/jcc.20291 Zoete, V., Cuendet, M.A., Grosdidier, A. & Michielin, O. SwissParam: a fast force field generation tool for small organic molecules. J. Comput. Chem. 32 , 2359-2368 (2011). https://doi.org/10.1002/jcc.21816 Alamri, M.A. & Alamri, M.A. Adamantane-derived scaffolds targeting the sigma-2 receptor, an in vitro and in silico study. Saudi Pharm. J. 29 , 1166-1172 (2021).‏ https://doi.org/10.1016/j.jsps.2021.08.016 Table 7 Table 7 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files SupplementarySciRep.docx Table7.docx Cite Share Download PDF Status: Published Journal Publication published 26 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 07 Oct, 2025 Reviews received at journal 06 Oct, 2025 Reviews received at journal 27 Sep, 2025 Reviewers agreed at journal 23 Sep, 2025 Reviewers agreed at journal 17 Sep, 2025 Reviewers invited by journal 09 Sep, 2025 Editor assigned by journal 08 Sep, 2025 Editor invited by journal 08 Sep, 2025 Submission checks completed at journal 02 Sep, 2025 First submitted to journal 02 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7355100","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":515343648,"identity":"32947b36-b970-405c-9b95-6c6a17c1eeea","order_by":0,"name":"Mubarak A. Alamri","email":"","orcid":"","institution":"Prince Sattam Bin Abdulaziz University","correspondingAuthor":false,"prefix":"","firstName":"Mubarak","middleName":"A.","lastName":"Alamri","suffix":""},{"id":515343649,"identity":"9b5583f8-6fd2-4783-a39e-d3110f58796d","order_by":1,"name":"Gamal A. Soliman","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYLCCBwZAgr0ByjtAjJYEkBYemFLitIAIiQQitcg7sD98kFCwTd5c8u3hDz/bGOT4biQwf/iBR4vhAR5jgwSD24Y7Z+elSfa2MRhL3khgk+zBp6WBh00CqIVxw+0cMwbeNobEDUAtDDx4tbA/A2mx33DzjPHHv20M9UAtzB//4PMLA4MZSAvQcB4DaaAtCQY3Ehik8dliwAzxS/KGM3lp0jLnJAxnnnnYJi2Dz5b29ocPPvy5bbvh+NnDH9+U2cjzHU8GMvDZchjOBDtGAogZG/BoANqCkMbn/lEwCkbBKBjRAAAmQE+Xn6aBgQAAAABJRU5ErkJggg==","orcid":"","institution":"Prince Sattam Bin Abdulaziz University","correspondingAuthor":true,"prefix":"","firstName":"Gamal","middleName":"A.","lastName":"Soliman","suffix":""},{"id":515343650,"identity":"15d4e794-2837-4b60-ae12-472149543bd9","order_by":2,"name":"Mohammed A. Alamri","email":"","orcid":"","institution":"Prince Sattam Bin Abdulaziz University","correspondingAuthor":false,"prefix":"","firstName":"Mohammed","middleName":"A.","lastName":"Alamri","suffix":""},{"id":515343651,"identity":"f8136549-b325-4197-b594-9c89d3b156a0","order_by":3,"name":"Rehab F. Abdel-Rahman","email":"","orcid":"","institution":"National Research Centre","correspondingAuthor":false,"prefix":"","firstName":"Rehab","middleName":"F.","lastName":"Abdel-Rahman","suffix":""},{"id":515343652,"identity":"4430ff2a-66c5-4068-82bc-aee05f4391d4","order_by":4,"name":"Ahmed W. Alhalabi","email":"","orcid":"","institution":"Prince Sattam Bin Abdulaziz University","correspondingAuthor":false,"prefix":"","firstName":"Ahmed","middleName":"W.","lastName":"Alhalabi","suffix":""},{"id":515343653,"identity":"bfffd05f-549d-48df-96ca-8a291cb50ccd","order_by":5,"name":"Raid S. Almahmoud","email":"","orcid":"","institution":"Prince Sattam Bin Abdulaziz University","correspondingAuthor":false,"prefix":"","firstName":"Raid","middleName":"S.","lastName":"Almahmoud","suffix":""},{"id":515343654,"identity":"fadae9b3-f3de-4b30-8262-bb67ec1483cb","order_by":6,"name":"Ibrahim M. Alsagheir","email":"","orcid":"","institution":"Prince Sattam Bin Abdulaziz University","correspondingAuthor":false,"prefix":"","firstName":"Ibrahim","middleName":"M.","lastName":"Alsagheir","suffix":""},{"id":515343655,"identity":"84200fc5-f940-441f-b9ff-0a7fd039906f","order_by":7,"name":"Abdulrahman G. Alharbi","email":"","orcid":"","institution":"Ministry of Health","correspondingAuthor":false,"prefix":"","firstName":"Abdulrahman","middleName":"G.","lastName":"Alharbi","suffix":""},{"id":515343657,"identity":"da195b41-cd3c-478c-8f32-e3620c07cb21","order_by":8,"name":"Maged S. Abdel-Kader","email":"","orcid":"","institution":"Prince Sattam Bin Abdulaziz University","correspondingAuthor":false,"prefix":"","firstName":"Maged","middleName":"S.","lastName":"Abdel-Kader","suffix":""}],"badges":[],"createdAt":"2025-08-12 11:23:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7355100/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7355100/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-26010-3","type":"published","date":"2025-11-26T15:57:16+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":91816898,"identity":"38c961e5-7af5-445a-b75d-699603b09f1e","added_by":"auto","created_at":"2025-09-22 06:52:56","extension":"xml","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":217441,"visible":true,"origin":"","legend":"","description":"","filename":"cffcb34856444ea489afe19aa1301b3a1enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7355100/v1/c17711cfbba51bd7b891f9a9.xml"},{"id":91465170,"identity":"e4131b41-bffd-4a41-802d-a96da3163fff","added_by":"auto","created_at":"2025-09-16 18:31:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":137106,"visible":true,"origin":"","legend":"\u003cp\u003eStructures of compounds \u003cstrong\u003e1\u003c/strong\u003e-\u003cstrong\u003e4\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7355100/v1/3334f0a31b1359581b240d6f.png"},{"id":91465733,"identity":"76850f19-caf2-4914-9702-bf6c83e6e4c9","added_by":"auto","created_at":"2025-09-16 18:39:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":110343,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of \u003cstrong\u003eAST\u003c/strong\u003e and its fractions on the edema inhibition percentage of rat’s paw edema.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7355100/v1/3adf85be1d831afad9a8af1b.png"},{"id":91465734,"identity":"34382f45-3da7-4f64-8c85-e208e8f55ba1","added_by":"auto","created_at":"2025-09-16 18:39:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":63357,"visible":true,"origin":"","legend":"\u003cp\u003eCytotoxic assessment of compounds \u003cstrong\u003e1-4\u003c/strong\u003e (10 uM) in LPS-induced RAW 264.7 cells. The Cell viability was conducted using SRB assay. The results are presented as mean ± SD (n = 3). The statistical analysis revealed no significant differences (\u003cem\u003eP \u003c/em\u003e≤ 0.05) when compared to the LPS-induced cells.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7355100/v1/2f4cb546f2ad0372ebcee2f9.png"},{"id":91464637,"identity":"b2948f43-cf9f-4723-94f5-cfb7ef2964a7","added_by":"auto","created_at":"2025-09-16 18:23:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":128225,"visible":true,"origin":"","legend":"\u003cp\u003eThe inhibition rates of NO release from RAW 264.7 cells after treatment\u003cbr\u003e\nwith \u003cstrong\u003e1-4\u003c/strong\u003e for 48 hr.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7355100/v1/77a3714bb08ab200e3fcbd54.png"},{"id":91465173,"identity":"3ecba2ff-f6cc-4e38-9b62-2e493fbc8940","added_by":"auto","created_at":"2025-09-16 18:31:02","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":261589,"visible":true,"origin":"","legend":"\u003cp\u003eNetwork of the gene targets of compounds \u003cstrong\u003e1\u003c/strong\u003e, \u003cstrong\u003e2\u003c/strong\u003e, and \u003cstrong\u003e4\u003c/strong\u003e constructed by the Cytoscape software to highlight commonality of gene targets. Compound \u003cstrong\u003e3 \u003c/strong\u003ehad no predicted gene targets.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7355100/v1/562f6f2a3fe017544c3c8a75.png"},{"id":91466593,"identity":"c6d95fd8-1f18-4c8a-bf8f-648c99747c0a","added_by":"auto","created_at":"2025-09-16 18:47:03","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":871243,"visible":true,"origin":"","legend":"\u003cp\u003ePPI network of the inflammation genes targeted by compounds \u003cstrong\u003e1\u003c/strong\u003e, \u003cstrong\u003e2\u003c/strong\u003e, and \u003cstrong\u003e4\u003c/strong\u003e constructed by the STRING database.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7355100/v1/2a0be14d6b9bdc2068b66e46.png"},{"id":91465180,"identity":"3d864ef8-aa95-40ad-b0b9-0826a9fdf8b7","added_by":"auto","created_at":"2025-09-16 18:31:03","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":300778,"visible":true,"origin":"","legend":"\u003cp\u003eCytoscape network highlighting the genes with the highest DC (red: highest, light yellow: lowest). Higher DC indicates a higher number of predicted and known PPIs.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7355100/v1/266daa1dafed9729dadd6a96.png"},{"id":91465193,"identity":"f71a7f38-7158-4424-9963-e702cff099f1","added_by":"auto","created_at":"2025-09-16 18:31:03","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":260886,"visible":true,"origin":"","legend":"\u003cp\u003eShinyGO database analysis of the biological processes involving the inflammation-related gene targets of the isolated compounds \u003cstrong\u003e1\u003c/strong\u003e, \u003cstrong\u003e2\u003c/strong\u003e, and \u003cstrong\u003e4\u003c/strong\u003e. FDR: false discovery rate, smaller FDR indicates high statistical significance.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7355100/v1/5beec6c76aa1fd642a1cd44e.png"},{"id":91464656,"identity":"0fd7fa8e-30c7-4492-bd9b-e891ed3a779e","added_by":"auto","created_at":"2025-09-16 18:23:03","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":255651,"visible":true,"origin":"","legend":"\u003cp\u003eThe docked complexes of compounds with MAOA protein (PDB ID: 2BXR). Compound \u003cstrong\u003e1\u003c/strong\u003e: Cyan, Compound \u003cstrong\u003e2\u003c/strong\u003e: Yellow, Compound \u003cstrong\u003e3\u003c/strong\u003e: Red, Compound \u003cstrong\u003e4\u003c/strong\u003e: Blue.\u003c/p\u003e","description":"","filename":"floatimage15.png","url":"https://assets-eu.researchsquare.com/files/rs-7355100/v1/7d5b6745ae093c4c08e775fc.png"},{"id":91464648,"identity":"ad1d2799-eb11-40b6-ba18-b7df0992493d","added_by":"auto","created_at":"2025-09-16 18:23:03","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":264742,"visible":true,"origin":"","legend":"\u003cp\u003eThe docked complexes of compounds with MAOB protein (PDB ID: 7P4F). Compound \u003cstrong\u003e1\u003c/strong\u003e: Cyan, Compound \u003cstrong\u003e2\u003c/strong\u003e: Yellow, Compound \u003cstrong\u003e3\u003c/strong\u003e: Red, Compound \u003cstrong\u003e4\u003c/strong\u003e: Blue.\u003c/p\u003e","description":"","filename":"floatimage16.png","url":"https://assets-eu.researchsquare.com/files/rs-7355100/v1/651ddc0f5ac8598891164a64.png"},{"id":91464659,"identity":"7d939fdb-f47b-47c4-ac79-64859c302c32","added_by":"auto","created_at":"2025-09-16 18:23:03","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":358573,"visible":true,"origin":"","legend":"\u003cp\u003eMD simulation analysis of compound \u003cstrong\u003e4\u003c/strong\u003ebinding to active site of MAOA (PDB ID: 2bxr). (A) Protein backbone RMSD, (B) Ligand RMSD, (C) Protein backbone RMSF, (D) Number of hydrogen bonds.\u003c/p\u003e","description":"","filename":"floatimage17.png","url":"https://assets-eu.researchsquare.com/files/rs-7355100/v1/a202a0812a36798428b92380.png"},{"id":91465742,"identity":"4bba16f8-5ded-45a7-ba10-2517cc5d3830","added_by":"auto","created_at":"2025-09-16 18:39:03","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":316205,"visible":true,"origin":"","legend":"\u003cp\u003eMD simulation analysis of compound \u003cstrong\u003e4\u003c/strong\u003e binding to active site of MAOB (PDB ID: 7p4f). (A) Protein backbone RMSD, (B) Ligand RMSD, (C) Protein backbone RMSF, (D) Number of hydrogen bonds.\u003c/p\u003e","description":"","filename":"floatimage18.png","url":"https://assets-eu.researchsquare.com/files/rs-7355100/v1/5db95902c9553fd9759c3a4d.png"},{"id":97178522,"identity":"a944f364-33e1-4dda-a966-187521a6cd64","added_by":"auto","created_at":"2025-12-01 16:10:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5284488,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7355100/v1/db69152d-ab72-4c08-a902-39be92a8a274.pdf"},{"id":91465740,"identity":"22150cad-b1aa-48c3-a4db-ac1c547be3b0","added_by":"auto","created_at":"2025-09-16 18:39:03","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":4366963,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementarySciRep.docx","url":"https://assets-eu.researchsquare.com/files/rs-7355100/v1/fcc926516526a8cd0a1d7529.docx"},{"id":91464633,"identity":"903b194a-1da1-48f5-8116-5851ab7bd742","added_by":"auto","created_at":"2025-09-16 18:23:02","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":49533,"visible":true,"origin":"","legend":"","description":"","filename":"Table7.docx","url":"https://assets-eu.researchsquare.com/files/rs-7355100/v1/2ae96bdb2120930ae014062d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Anti-inflammatory Sesquiterpene Coumarins from the Active Fractions of Ferula assa-foetida: In Silico Analysis Endorse Experimental data","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eInflammation is the first line of defense of the body in response to infection or tissue damage resulting in organ structural stability, normal physiology and homeostasis within the injured tissue \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Over the past few years, it has become one of the most prominent objects of biomedical research in the world and this is mostly because it is clearly linked to a vast diversity of human illnesses \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The commonly used medical treatments of inflammatory disorders include glucocorticoids and nonsteroidal anti-inflammatory drugs (NSAIDs). These medications are linked with some adverse effects such as high blood pressure, stomach pain and ulcers, fragile bones, kidney failure, Cushing\u0026rsquo;s syndrome, diabetes, and vulnerability to infections \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. There is therefore urgent need to establish safer and more effective methods of handling inflammatory pathology.\u003c/p\u003e\u003cp\u003eThe process of inflammation is a complicated list of physiological events whereby a network of cellular events and a coordinated sequence of molecular events orchestrate immune activation and maintain homeostasis in tissues. The core of this process involves the cyclooxygenase (COX) pathway, in which COX-1 regulates and controls normal physiologic activity, at the same time as COX-2 is preferentially induced during an inflammatory event, to promote the constructive formation of prostaglandins, and hence exaggerate the inflammatory response \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.The (NF-κB) signaling pathway is major transcriptional regulator of pro-inflammatory effectors including tumor necrosis factor-alpha TNF-α ,interleukin-6 (IL-6) in agreement with this system. NF-κB activation begins with proteolytic removal of anti- inflammatory proteins (IκB), subsequently permitting the process of translocation of the complex to the nucleus to facilitate transmission of inflammation-linked genes \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Moreover, a balance between pro-inflammatory cytokines, such as IL-1b, IL-6 and TNF-α, and anti-inflammatory molecules including IL-10 is important to regulate the attraction of immune cells and control excessive inflammatory processes \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Such complexly interlinked web of molecular networks forms the ideal target of therapeutic interventions in inflammatory disorders. Traditional medicine has great repositories of bioactive secondary metabolites present in herbs that can be used to draw out pharmacologically useful agents. Therefore, plant-based preparations still serve as a major source in the discovery of new drugs. Genus \u003cem\u003eFerula\u003c/em\u003e L. (with over 170 species formally described) is the third largest in its family. Most representatives of this genus are well represented in ethnomedicine, and several of them have proved to be significant sources of biologically active materials \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAsafoetida is the oleo-gum-resin secreted by the roots of \u003cem\u003eFerula assa-foetida\u003c/em\u003e, traditionally used to treat a wide range of conditions including whooping cough, bronchitis, asthma, influenza, stomachache, flatulence, ulcers, intestinal parasites, spasms, digestive weakness, and epilepsy \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eMultiple biological activities were reported for essential oils and extracts of the genus, including anticancer, antioxidant, anticonvulsant, antinociceptive, antidepressant, aphicidal, antiprotozoal, anthelmintic, antibacterial, anti-inflammatory, antihypertensive, antiulcer, and antispasmodic activities. In addition, asafoetida expressed many biological activities including antiviral, antifungal, molluscicidal, antidiabetic, antiobesity, hepatoprotective, neuroprotective, memory enhancing, and digestive aid \u003csup\u003e\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The extract containing ethanol was rich in the anti-inflammatory action on the tumor necrosis factor-alpha (TNF-α\u0026ndash;) stimulated human umbilical vein endothelial cells (HUVECs) \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003ePhytochemically, \u003cem\u003eFerula\u003c/em\u003e species are rich in the bioactive sesquiterpene coumarins derivatives \u003csup\u003e\u003cspan additionalcitationids=\"CR14 CR15 CR16\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Although sesquiterpene coumarins are present in 12 plant genera, they are mainly reported from \u003cem\u003eFerula\u003c/em\u003e species \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Many members of the sesquiterpene coumarin family were reported to have anti-inflammatory activity \u003csup\u003e\u003cspan additionalcitationids=\"CR14 CR15 CR16\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Two sesquiterpenes with anti-inflammatory activity were reported from \u003cem\u003eF. hermonis\u003c/em\u003e \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Sesquiterpene coumarins were reported from the aerial parts of \u003cem\u003eF. sinkiangensis\u003c/em\u003e expressed anti-inflammatory activities in lipopolysaccharide-stimulated RAW 264.7 macrophages \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Anti-neuroinflammatory sesquiterpene coumarins were identified from the resin of \u003cem\u003eF. sinkiangensis\u003c/em\u003e and the whole plants of \u003cem\u003eF. bungeana\u003c/em\u003e \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe current study was targeted at investigating the anti-inflammatory properties of assafoetida, both \u003cem\u003ein vivo\u003c/em\u003e, \u003cem\u003ein vitro\u003c/em\u003e, \u003cem\u003ein silico\u003c/em\u003e and identifying the active metabolites responsible for this effect via biologically guided phytochemical study. We also aim to identify the potential molecular targets and mechanisms of action of its isolated compounds.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eCharacterization of the isolated compounds\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e\u003cem\u003eAuraptene\u003c/em\u003e (\u003cb\u003e1\u003c/b\u003e): pale yellow solid, UV λ\u003csub\u003emax\u003c/sub\u003e MeOH: 226, 290, 322 nm, \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH and \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003eC NMR : Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e- S10, High Resolution Electrospray Ionization Mass Spectrometry (HRESIMS) \u003cem\u003em/z\u003c/em\u003e [M-H]\u003csup\u003e+\u003c/sup\u003e 297.1483 (calcd for C\u003csub\u003e19\u003c/sub\u003eH\u003csub\u003e22\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e -H, 297.1500), [M\u0026thinsp;+\u0026thinsp;H]\u003csup\u003e+\u003c/sup\u003e 299.1640 (calcd for C\u003csub\u003e19\u003c/sub\u003eH\u003csub\u003e22\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;H, 299.1647) (Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e1, S12).\u003c/p\u003e\u003cp\u003e\u003cem\u003eUmbelliprenin\u003c/em\u003e (\u003cb\u003e2\u003c/b\u003e): White powder, UV λ\u003csub\u003emax\u003c/sub\u003e MeOH: 223, 288, 325 nm, \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH and \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003eC NMR Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e3- S22, HRESIMS \u003cem\u003em/z\u003c/em\u003e [M\u0026thinsp;+\u0026thinsp;1]\u003csup\u003e+\u003c/sup\u003e m/z 367.2263 (calcd for C\u003csub\u003e24\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;H, 367.2273), [M\u0026thinsp;+\u0026thinsp;Na]\u003csup\u003e+\u003c/sup\u003e m/z 389.2081 (calcd for C\u003csub\u003e24\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;Na, 389.2093) (Figure S23).\u003c/p\u003e\u003cp\u003e\u003cem\u003eGalbanic acid\u003c/em\u003e (\u003cb\u003e3\u003c/b\u003e): White matrix, UV λ\u003csub\u003emax\u003c/sub\u003e MeOH: 224, 289, 324 nm, \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH and \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003eC NMR Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Figures S24- S44, HRESIMS \u003cem\u003em/z\u003c/em\u003e [M-1]\u003csup\u003e+\u003c/sup\u003e m/z 397.2016 (calcd for C\u003csub\u003e24\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e-H, 397.2015), [M\u0026thinsp;+\u0026thinsp;1]\u003csup\u003e+\u003c/sup\u003e m/z 399.2162 (calcd for C\u003csub\u003e24\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;H, 399.2171), [M\u0026thinsp;+\u0026thinsp;Na]\u003csup\u003e+\u003c/sup\u003e m/z 421.1981 (calcd for C\u003csub\u003e24\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;Na, 421.1991) (Figure S45, S46).\u003c/p\u003e\u003cp\u003e\u003cem\u003eKamolonol\u003c/em\u003e (\u003cb\u003e4\u003c/b\u003e): White amorphous powder, UV λ\u003csub\u003emax\u003c/sub\u003e MeOH: 225, 285, 326 nm, \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH and \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003eC NMR Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Figures S47- S60, HRESIMS \u003cem\u003em/z\u003c/em\u003e [M\u0026thinsp;+\u0026thinsp;1]\u003csup\u003e+\u003c/sup\u003e m/z 399.2166 (calcd for C\u003csub\u003e24\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;H, 399.2171), [M\u0026thinsp;+\u0026thinsp;Na]\u003csup\u003e+\u003c/sup\u003e m/z 421.1986 (calcd for C\u003csub\u003e24\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;Na, 421.1991) (Figure S61).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH-NMR data (δ ppm, \u003cem\u003eJ\u003c/em\u003e in parentheses in Hz) of compounds \u003cb\u003e1\u0026ndash;4\u003c/b\u003e in C\u003csub\u003e6\u003c/sub\u003eD\u003csub\u003e6\u003c/sub\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3*\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4*\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4**\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.91 (d, 9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.91 (d, 9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.88 (d, 9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.21 (d, 9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.25 (d, 9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6.35 (d, 9.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.78 (d, 9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.95 overl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.63 (d, 9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.85 (d, 9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.88 (d, 9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.72 (d, 9.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.73 (d, 8.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.95 overl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.65 (d, 8.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.49 (d, 8.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.55(d, 8.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.48 (d, 8.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.60 (dd, 2.4, 8.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.95 overl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.56 (dd, 2.3, 8.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.89 (dd, 1.8, 8.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.96 overl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.01 overl\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.62(d, 2.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.95 overl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.22(d, 1.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.22(d, 1.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.95 overl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.02 overl\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.21 (d, 6.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.15 (d, 6.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.12 overl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.85 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.90 (dd, 4.6, 13.0), 1.99 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.82 m\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.39 (t, 6.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.40 (t, 6.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.11 m, 2.17 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.12 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.35 (dd, 3.0, 12.5), 2.48 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.51 m\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.95 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.94\u0026ndash;2.16 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.64 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.63 m\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.05 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.94\u0026ndash;2.16 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.09 (t, 6.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.21 (t, 6.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.70 m, 2.33 (bd, 18.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.92 m\u003c/p\u003e\u003cp\u003e2.53 (bd, 13.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.88 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.13 m\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.97m, 1.30m,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.28 m, 1.57 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.61 m, 1.99 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.82 m, 2.16 m\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.62 s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.94\u0026ndash;2.16 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.46 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.28 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.99 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.96 m\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.49 s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.94\u0026ndash;2.16 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.48 s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.17 (t, 6.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.96 (dd, 4.5, 11.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.03 (t, 8.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.23 (bd, 9.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.23 (bt, 7.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.42 (d, 8.3), 3.70 (d, 8.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.75 (d, 8.5), 3.95 (d, 8.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.88 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.85 (d, 9.0), 3.86 (d, 9.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.44 s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.04 s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.17 s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.14 s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.09 s\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.55 s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.45 s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.46 s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.12 overl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.58 (d, 6.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.67 s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.49 s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.62 s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.83 s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.08 s\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.55 s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.69 (d, 6.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.95 (d, 9.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.12 overl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.11 (d, 7.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e*Data were measured in CD\u003csub\u003e3\u003c/sub\u003eOD. **Data were measured in Pyridine d\u003csub\u003e5\u003c/sub\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003eC-NMR data (δ ppm) of compounds \u003cb\u003e1\u0026ndash;4\u003c/b\u003e in C\u003csub\u003e6\u003c/sub\u003eD\u003csub\u003e6\u003c/sub\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3*\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4*\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4**\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e160.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e159.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e160.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e162.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e161.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e162.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e112.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e113.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e111.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e111.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e112.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e111.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e142.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e142.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e142.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e144.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e144.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e144.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e128.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e128.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e128.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e129.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e129.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e129.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e112.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e112.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e112.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e112.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e112.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e112.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e162.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e161.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e162.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e163.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e162.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e163.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e101.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e101.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e100.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e100.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e100.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e100.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e156.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e156.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e156.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e155.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e155.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e155.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e112.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e112.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e112.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e112.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e112.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e112.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e65.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e65.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e21.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e23.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e23.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e119.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e119.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e31.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e31.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e40.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e41.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e141.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e141.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e172.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e176.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e214.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e211.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e39.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e129.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e130.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e57.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e58.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e125.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e125.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e47.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e47.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e123.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e124.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e24.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e72.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e71.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e131.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e135.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e31.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e35.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e36.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e34.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e34.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e36.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e36.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e25.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e39.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e39.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e123.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e42.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e42.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e43.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e43.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e130.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e75.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e75.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e18.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e19.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e9.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e11.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e8.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e9.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e14.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e15.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e*Data were measured in CD\u003csub\u003e3\u003c/sub\u003eOD. **Data were measured in Pyridine d\u003csub\u003e5\u003c/sub\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv\u003e\u003cem\u003eIn vivo\u003c/em\u003e anti-inflammatory testing\u003c/div\u003e\n\u003cdiv id=\"Sec5\"\u003e\n \u003ch2\u003eCarrageenan-induced acute paw edema model for extract and fractions\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eThe anti-inflammatory \u003cem\u003ein vivo\u003c/em\u003e testing of full and fractionated \u003cem\u003eFerula assa-foetida\u003c/em\u003e extracts compared in Table 3 and shown in Fig. 2. In control group, after injection of carrageenan, there was a progressive paw swelling with an edema of 56.88%, 62.93% and 58.08% at the 1st, 2nd and 3rd hours following, of injection respectively. Conversely, the total extract (AST) was used as pretreatment which resulted in a significant swelling reduction with edema ratios of 37.48%, 35.56%, and 28.71% \u0026plusmn;1.55%, at corresponding time points. It was similarly observed that the animals that were treated to the hexane fraction, (ASH) showed percentages of 33.27, 32.35 and 27.79 but ethyl acetate fraction (ASE) gave a percentage of 26.94, 27.11 and 24.90. Indomethacin (IND) resulted in 20.76%, 22.27%, and 20.16% edema rates as the reference drug. It is important to report that ASE showed almost the same anti-inflammatory profile as IND. Of all the samples, ASE 0.2g/kg administered showed the most significant inhibitory properties of carrageenan-induced paw edema, as evidenced by the inhibitory effects indicated by 52.63%, 56.63%, and 56.82% at 1, 2, and 3 hours, respectively (Fig. 4). When compared, the chloroform extraction of ASC and the solubility insoluble residual, ASI made no apparent change in paw volume as compared with the untreated samples.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eEffect of \u003cstrong\u003eAST\u003c/strong\u003e and its fractions on the edema rate percentage produced by carrageenan in rat\u0026rsquo;s paw.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eDose\u003c/p\u003e\n \u003cp\u003e(mg/kg)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eEdema rate (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1 h\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2 h\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e3 h\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCONT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e56.88\u0026thinsp;\u0026plusmn;\u0026thinsp;5.16#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62.93\u0026thinsp;\u0026plusmn;\u0026thinsp;1.68#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIND\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAST\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37.48\u0026thinsp;\u0026plusmn;\u0026thinsp;3.66*#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35.56\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04*#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.55*#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eASI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51.58\u0026thinsp;\u0026plusmn;\u0026thinsp;4.60#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55.75\u0026thinsp;\u0026plusmn;\u0026thinsp;4.54#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53.73\u0026thinsp;\u0026plusmn;\u0026thinsp;2.05#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eASH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33.27\u0026thinsp;\u0026plusmn;\u0026thinsp;2.23*#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32.35\u0026thinsp;\u0026plusmn;\u0026thinsp;2.03*#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27.79\u0026thinsp;\u0026plusmn;\u0026thinsp;2.47*#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eASC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.58#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54.65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.11#\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07#\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eASE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26.94\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eValues are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;S.E of 6 animals for each group. *Statistically significant from control: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05. #Statistically significant from IND: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cstrong\u003eIn vitro\u003c/strong\u003e \u003cstrong\u003eanti-inflammatory testing for pure compounds 1\u0026ndash;4\u003c/strong\u003e\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003ch3\u003eLipopolysaccharide-Induced Inflammation in RAW 264.7 Mouse Macrophages\u003c/h3\u003e\n\u003cdiv\u003e\n \u003cp\u003eThe cytotoxicity of the isolated compounds on the production of nitric oxide (NO) inhibition as well as assessing their in vitro anti-inflammatory activities was determined via the sulforhodamine B (SRB)) assay on LPS-induced RAW 264.7 macrophages first. Concentration range in the test was 0.001 to 10 \u0026micro;M. The macrophage toxicity of the compounds tested was not significant at any of the doses tested with near full cell viability observed at the highest dose nearly 99% as shown in Fig. 3, compared with LPS-treated control. As a result, the following concentration ranges were chosen to perform the further inhibition experiments of nitric oxide.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n \u003cp\u003e\u003cstrong\u003eNitric oxide inhibition test\u003c/strong\u003e \u003cstrong\u003ein vitro\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAs shown in Fig. 4, compound \u003cstrong\u003e4\u003c/strong\u003e was the most effective nitric oxide (NO) inhibitor, with an IC\u003csub\u003e50\u003c/sub\u003e value of 3.165\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12 \u0026micro;M. Furthermore, compounds \u003cstrong\u003e1\u003c/strong\u003e and \u003cstrong\u003e2\u003c/strong\u003e also demonstrated potent NO inhibition activity, displaying nearly the same IC\u003csub\u003e50\u003c/sub\u003e values of 8.388\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24 \u0026micro;M and 8.754\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17 \u0026micro;M, respectively. The three compounds \u003cstrong\u003e1\u003c/strong\u003e, \u003cstrong\u003e2\u003c/strong\u003e and \u003cstrong\u003e4\u003c/strong\u003e showed NO inhibition activity more than the positive control (quercetin with an IC\u003csub\u003e50\u003c/sub\u003e value of 22.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11 \u0026micro;M). The least NO inhibitor in this series was compound \u003cstrong\u003e3\u003c/strong\u003e with an IC\u003csub\u003e50\u003c/sub\u003e value of 33.59\u0026thinsp;\u0026plusmn;\u0026thinsp;2.65 \u0026micro;M.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eComputational analysis of physicochemical and pharmacokinetic properties\u003c/h3\u003e\n\u003cdiv\u003e\n \u003cp\u003eVirtual analysis of physicochemical properties by the SwissADME database revealed that the most active compound \u003cstrong\u003e4\u003c/strong\u003e possesses the lowest lipid solubility and a high number of possible hydrogen-bonding compounds \u003cstrong\u003e1\u003c/strong\u003e and \u003cstrong\u003e2\u003c/strong\u003e (Table 4). While compounds \u003cstrong\u003e3\u003c/strong\u003e and \u003cstrong\u003e4\u003c/strong\u003e had similar number of hydrogen-bond acceptors and donors, their anti-inflammatory activity was dissimilar.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eWithin the isolated compounds, only compound \u003cstrong\u003e4\u003c/strong\u003e was found to interact with the efflux pump P-glycoprotein (Pgp). Interactions with microsomal enzymes were variable with each compound having a different interaction profile than the other. Compound \u003cstrong\u003e2\u003c/strong\u003e interactions could not be determined by the SwissADME database.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eRelative anti-inflammatory activity (designated as NO inhibition), and computational analysis of physicochemical and pharmacokinetic properties.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCompound\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNO inhibition (10 \u0026micro;M)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLogP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eH-bond acceptors\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eH-bond donors\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePgp substrate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCYP1A2 inhibitor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCYP2C9 inhibitor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCYP2D6 inhibitor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCYP3A4 inhibitor\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e++\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e++\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+++\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eND: could not be determined by SwissADME database.\u003c/p\u003e\n\u003cp\u003eThe symbols (+, ++, +++) indicate different levels of activity: low, moderate, and high, respectively.\u003c/p\u003e\n\u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003eInflammation-related and compounds gene targets\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eA total of 16,356 genes were identified by the GeneCards database when using the search term \u0026ldquo;inflammation\u0026rdquo;. For this study, only the top 2,500 genes were considered to provide a stringent criterion for detection. The gene targets of compounds \u003cstrong\u003e1\u0026ndash;4\u003c/strong\u003e were determined by the \u0026ldquo;SwissTargetPrediction\u0026rdquo; database. Collectively, the compounds \u003cstrong\u003e1\u0026ndash;4\u003c/strong\u003e had a total of 96 gene targets, some of which were exclusive to some compounds, while others were common (Table 5). Compound \u003cstrong\u003e3\u003c/strong\u003e had no predicted gene targets. Venn diagrams identified 39 gene targets overlapping between the top 2,500 inflammation genes, and the isolated compounds.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 5\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eThe number of compounds\u0026rsquo; gene targets predicted by the SwissTargetPredict database, and the number of target genes common with inflammation.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCompound\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGene targets\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOverlapping with top 2,500\u003c/p\u003e\n \u003cp\u003einflammation-related genes\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eThe Cytoscape software was utilized to construct a network highlighting the common and exclusive gene targets of each compound (Fig. 5). Interestingly, compounds \u003cstrong\u003e1\u003c/strong\u003e, \u003cstrong\u003e2\u003c/strong\u003e, and \u003cstrong\u003e4\u003c/strong\u003e had 2 common targets: monoamine oxidase-A (MAOA) and monoamine oxidase-B (MAOB).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003ch3\u003eProtein-protein interactions\u003c/h3\u003e\n\u003cp\u003eA network highlighting the protein-protein interactions (PPIs) of the 39 inflammation-related gene targets of compounds \u003cstrong\u003e1\u003c/strong\u003e, \u003cstrong\u003e2\u003c/strong\u003e, and \u003cstrong\u003e4\u003c/strong\u003e was constructed by the STRING database (Fig. 6). This aims to analyze known and predicted interactions between these genes and has assigned an enrichment p-value of \u0026lt;\u0026thinsp;8.02e-9, where a small p-value indicates a significant interaction probability.\u003c/p\u003e\n\u003cdiv\u003e\n \u003cp\u003eThe Cytoscape software was used to analyze and highlight the 39 gene targets identifying the core genes with the highest degree of centrality (DC) (Fig. 7).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n \u003cp\u003eThe top 4 genes based on DC were found to be highly involved in immunogenic responses and inflammatory cytokines on several fronts (Table 6).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 6\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eBrief description of the genes with the highest DC.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGene symbol\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDescription\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDC\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHSP90AA1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeat shock protein 90 alpha family class A member 1. Chaperone protein that aids in folding other proteins. Found to promote inflammation and immune cell activation \u003csup\u003e18,19\u003c/sup\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNR3C1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNuclear receptor subfamily 3 group C member 1. Encodes glucocorticoid receptor, which is known to be involved in inflammatory responses and cellular proliferation \u003csup\u003e20,21\u003c/sup\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAPP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmyloid beta precursor protein. Encodes the bases of amyloid plaques, which were found to have synergistic pro-inflammatory activity \u003csup\u003e22,23\u003c/sup\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eABL1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eABL proto-oncogene 1. Encodes a protein kinase involved in cell division and adhesion. Also modulates innate immunity by regulating ubiquitination of other proteins \u003csup\u003e24\u003c/sup\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch3\u003eEnrichment analysis of the gene targets\u003c/h3\u003e\n\u003cdiv\u003e\n \u003cp\u003eAnalysis of the 39 inflammation genes identified previously was performed by the ShinyGO database. Analysis of the \u0026ldquo;biological process\u0026rdquo; revealed the targeted genes to be involved in several biological processes, including the cellular response to several molecular structural aspects such as oxygen-containing compounds, organic cyclic compounds, cytokines in general, lipids, organic hydroxy compounds, and carboxylic acids (Fig. 8).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003eMolecular docking analysis of target proteins with compounds\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eFor the molecular docking analysis, the common target genes MAOA and MAOB were selected after analyzing the Cytoscape software network due to these genes being common targets to compounds \u003cstrong\u003e1\u003c/strong\u003e, \u003cstrong\u003e2\u003c/strong\u003e, and \u003cstrong\u003e4\u003c/strong\u003e. The docking protocol was initially validated by redocking the co-crystalized ligands namely, Clorgyline and CS-0379511 against their target proteins, MAOA and MAOB, respectively. Both ligands adapted similar binding conformations to crystalized once with high binding energy scores, -12.90 and \u0026minus;\u0026thinsp;12.60 kcal/Mol respectively (Table 7). For MAOA, compound \u003cstrong\u003e4\u003c/strong\u003e showed the highest binding energy score of -12.00 kcal/mol, while compound \u003cstrong\u003e2\u003c/strong\u003e showed the highest score (-11.40 kcal/mol) with MAOB enzyme. Remarkably, compound \u003cstrong\u003e3\u003c/strong\u003e showed low energy scores against both proteins supporting the previous prediction of non-interaction with MAOA and MAOB.\u003c/p\u003e\n \u003cp\u003eThe compounds interacted with the active sites of MAOA and MAOB via multiple interactions forces (Figs. 9 and 10). For compound \u003cstrong\u003e4\u003c/strong\u003e, which is the most active one, it showed better binding with MAOA compared with MAOB. For MAOA, compound \u003cstrong\u003e4\u003c/strong\u003e involved in hydrogen binding with Ser209 with the carbonyl of hydronaphthalenone and multiple hydrophobic interactions such as Gly67, Tyr69, Ile180, Phe208, Ile335, Leu337, Phe352, Tyr407, and Tyr444 (Fig. 9). Similarly, compound \u003cstrong\u003e4\u003c/strong\u003e interacted with MAOB through formation of hydrogen bond with Tyr435 the carbonyl of hydronaphthalenone and other hydrophobic bonds with Pro104, His115, Ile164, Leu171, Ile199, Gln206, Ile316 and Tyr320 (Fig. 10).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003eMolecular dynamic simulation analysis of compound 4 with MAOA and MAOB\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eThe most active compound, compound \u003cstrong\u003e4\u003c/strong\u003e, was subjected to 20 ns molecular dynamic (MD) simulation to determine its interaction behavior with both proteins, MAOA and MAOB, in a manner mimicking physiological conditions. For the binding of compound \u003cstrong\u003e4\u003c/strong\u003e with MAOA, both protein backbone and ligand root mean square deviation (RMSD) showed a behavior without major fluctuations over the simulation-time suggesting a stable binding condition (Fig. 11A and B). The root means square fluctuation (RMSF) analysis showed that in addition to the high fluctuations in the incompatible residues located in the N-terminal (amino acids up to No. 12) as well as in the C-terminal (459\u0026ndash;463), some fluctuation was seen in loop regions around residue 102\u0026ndash;125 and 251\u0026ndash;252 (Fig. 11C). The analysis of intermolecular hydrogen bond formation between compound \u003cstrong\u003e4\u003c/strong\u003e and MAOA indicated that this compound can form a maximum of 3 bonds. Hence, the formation of hydrogen bonds contributes significantly to the binding energy of interaction (Fig. 11D).\u003c/p\u003e\n \u003cp\u003eSimilarly, it can be seen in Fig. 12A and 12B that the interaction behavior of compound \u003cstrong\u003e4\u003c/strong\u003e with MAOB follows the same fluctuation pattern as shown with MAOA. No major disrupted fluctuations with backbone RMSD between 0.15\u0026ndash;0.25 nm and ligand RMSD being stable around 0.15 nm. In addition, The RMSF analysis showed that compound \u003cstrong\u003e4\u003c/strong\u003e binding residues (Pro104, His115, Ile164, Leu171, Ile199, Gln206, Ile316, Tyr320, and Tyr435) have very low fluctuations behavior. The significant fluctuations can be seen in the c-terminal region (490\u0026ndash;501) (Fig. 12C). The analysis of intermolecular hydrogen bond formation between compound \u003cstrong\u003e4\u003c/strong\u003e and MAOB showed that there can be up to 5 stable hydrogen bonds between the ligand and protein (Fig. 12D).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eInflammation is an inherent natural physiological defense mechanism through which the organism responds to tissue injury or infection and the main goal of which is the restoration of both structural and functional integrity \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Although steroidal and non-steroidal anti-inflammatory drugs (NSAIDs) are common in the clinical world to treat inflammation-related conditions, the drug delivery process is often surrounded by unwanted side effects and its possible complications \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Plant-based natural agents, especially secondary metabolites of medicinal plants, have therefore gained attraction as alternate sources of anti-inflammatory. The carrageenan-induced paw edema model in rodents has been found as one of the most frequently used experimental methods in studying the potential response of an experimental animal by administering carrageenans as an anti-inflammatory agent under laboratory conditions. It is a common model of acute inflammation, during which there is infiltration of polymorphonuclear neutrophils with an increase in prostaglandin production \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Inflammatory process caused by carrageenan involves neutrophilic leukocyte recruitment and the production of prostaglandins which further instigate the production of histamine, serotonin, bradykinin, among other inflammatory mediators \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. The volume increase of the paws is normally used to indicate the level of inflammation in experimental assessment.\u003c/p\u003e\u003cp\u003eThis experiment aimed to study the anti-inflammatory properties of the total extract of \u003cem\u003eFerula assa-foetida\u003c/em\u003e (AST) and its fractions which are derived through the carrageenan-induced paw edema test in rats. There was a significant inhibition of paw swelling in the AST treated groups 34.10%, 43.12%, and 50.21% 1 hour, 2 hours, and 3 hours following induction of inflammation respectively. The hexane fraction (ASH) exhibited a significant activity as well with inhibition values of 41.65%, 53.33%, and 54.44% over the same periods of time. In the previous pharmacodynamic studies, it was reported that when administered orally, the ethyl acetate fraction (ASE) used at 200 mg/kg demonstrated greater anti-inflammatory effect, than the reference NSAIDs indomethacin (IND) at 10 mg/kg \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. IND is quite known as having an analgesic, antipyretic, and inflammation inhibitory effect. The simple in vivo analysis of ASE versus IND answers via the similar, and in some cases even better, performance illustrates the therapeutic potential of the tested extract. Conversely, the insoluble residue fraction (ASI) and the chloroform fraction (ASC) did not lead to a serious anti-inflammatory reaction in any case, according to the same experimental conditions.\u003c/p\u003e\u003cp\u003ePhytochemical study of the most active \u003cb\u003eASH\u003c/b\u003e and \u003cb\u003eASE\u003c/b\u003e resulted in the isolation of four coumarins coupled with various terpene moieties \u003cb\u003e1\u0026ndash;4\u003c/b\u003e. The four compounds showed five signals in the aromatic region assigned for H-3, H-4, H-5, H-6 and H-8 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) with their correlated carbons (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) were diagnostic for 7-oxygenated coumarin skeleton common in \u003cem\u003eFerula\u003c/em\u003e species \u003csup\u003e\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Compound \u003cb\u003e1\u003c/b\u003e showed in the HRESIMS an [M-H]\u003csup\u003e+\u003c/sup\u003e at 297.1483 m/z in the negative mode and [M\u0026thinsp;+\u0026thinsp;H]\u003csup\u003e+\u003c/sup\u003e at 299.1640 m/z for the molecular formula C\u003csub\u003e19\u003c/sub\u003eH\u003csub\u003e22\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e (Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e1, S12). The additional 10 carbon signals over the coumarin skeleton were sorted by DEPT135 experiment (Figure S8) into CH\u003csub\u003e3\u003c/sub\u003e X 3, CH\u003csub\u003e2\u003c/sub\u003e X 3, CH X 2 and 2 quaternary carbons. The molecular formula indicated 9 degrees of unsaturation. As the coumarin skeleton fulfill 7 unsaturation degrees, the monoterpene moiety was left with only 2 degrees of unsaturation. Two double bonds were observed in the \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eHNMR and \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003eCNMR of 1 at δ\u003csub\u003eH\u003c/sub\u003e 5.39 (t, \u003cem\u003eJ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.5 Hz), δ\u003csub\u003eC\u003c/sub\u003e 119.0, 141.2 ppm and δ\u003csub\u003eH\u003c/sub\u003e 5.09 (t, \u003cem\u003eJ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.9 Hz), δ\u003csub\u003eC\u003c/sub\u003e 123.9, 131.4 ppm and assigned for C-2\u0026rsquo; and C-6\u0026rsquo; respectively (Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e- S8). These features were diagnostic for acyclic monoterpene moiety coupled to the coumarin skeleton. The data of \u003cb\u003e1\u003c/b\u003e were identical with those reported for auraptene \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Auraptene was reported to be effective for the management of inflammatory disorders, dysentery, wounds, scars, keloids, and pain \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003eCNMR and DEPT135 of \u003cb\u003e2\u003c/b\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e6- S20) displayed extra 5 carbon signals over \u003cb\u003e1\u003c/b\u003e. The three degrees of unsaturation left for the terpenoid moiety were fulfilled by 3 double bonds. Signals at δ\u003csub\u003eH\u003c/sub\u003e 5.40 (t, \u003cem\u003eJ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.5 Hz), δ\u003csub\u003eC\u003c/sub\u003e 119.0, 141.2 ppm, δ\u003csub\u003eH\u003c/sub\u003e 5.21 (t, \u003cem\u003eJ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.5 Hz), δ\u003csub\u003eC\u003c/sub\u003e 124.5, 135.2 ppm and δ\u003csub\u003eH\u003c/sub\u003e 5.17 (t, \u003cem\u003eJ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.5 Hz), δ\u003csub\u003eC\u003c/sub\u003e 123.7, 130.9 ppm were assigned for C-2\u0026rsquo;, C-6\u0026rsquo; and C-10\u0026rsquo; double bonds, respectively in an acyclic sesquiterpene structure (Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e3- S20). HRESIMS showed [M\u0026thinsp;+\u0026thinsp;H]\u003csup\u003e+\u003c/sup\u003e at 367.2263 m/z and [M\u0026thinsp;+\u0026thinsp;Na]\u003csup\u003e+\u003c/sup\u003e at 367.2263 m/z (Figure S23) for the molecular formula C\u003csub\u003e24\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e. The data of \u003cb\u003e2\u003c/b\u003e showed close similarity with those reported for umbelliprenin \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Umbelliprenin is reported to possess cancer chemopreventive, anti-bacterial, anti-protozoal, anti-fungal, anti-inflammatory, neuroprotective, and antioxidant \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eCompound \u003cb\u003e3\u003c/b\u003e showed in the HRESIMS an [M-H]\u003csup\u003e+\u003c/sup\u003e at 397.2016 m/z in the negative mode and [M\u0026thinsp;+\u0026thinsp;H]\u003csup\u003e+\u003c/sup\u003e at 399.2162 m/z and [M\u0026thinsp;+\u0026thinsp;Na]\u003csup\u003e+\u003c/sup\u003e 421.1981 in the positive mode m/z for the molecular formula C\u003csub\u003e24\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e (Figures S45, S46). In the \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003eCMR in addition to the coumarin skeleton, 15 carbon resonances were observed and categorized by DEPT135 experiment into CH\u003csub\u003e3\u003c/sub\u003e X 4, CH\u003csub\u003e2\u003c/sub\u003e X 5, CH X 2 and 4 quaternary carbons (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Figures S27- S30, S37- S39). The molecular formula revealed 10 degrees of unsaturation\u0026rsquo;s three of them were for the terpenoid moiety. Compound 3 showed two extra oxygen atoms over \u003cb\u003e2\u003c/b\u003e. These two oxygen atoms were assigned for a carboxylic group at δ\u003csub\u003eC\u003c/sub\u003e 172.6 ppm. Two olefinic carbons at δ\u003csub\u003eC\u003c/sub\u003e 129.7 and 125.9 ppm constituted one double bond. The left unsaturation degree indicated a ring structure in the terpene part. Spectral data of \u003cb\u003e3\u003c/b\u003e expressed close similarity with galbanic acid literature data \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Among the reported biological activity of galbanic acid are the anticancer, cancer chemopreventive, anticoagulant, hepatoprotective, antiviral, acetylcholinesterase inhibitory and antileishmanial activities \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe HRESIMS of \u003cb\u003e4\u003c/b\u003e was identical with \u003cb\u003e3\u003c/b\u003e showing an [M\u0026thinsp;+\u0026thinsp;H]\u003csup\u003e+\u003c/sup\u003e at 399.2165 and [M\u0026thinsp;+\u0026thinsp;Na]\u003csup\u003e+\u003c/sup\u003e 421.1982 m/z (Figure S61). The \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003eCNMR spectra showed carbonyl signal at δ\u003csub\u003eC\u003c/sub\u003e 214.2 ppm diagnostic for a ketone function 9. Another oxygen was involved in the formation of secondary alcohol function at δ\u003csub\u003eC\u003c/sub\u003e 72.6 ppm. There was no indication of the presence of double bonds in the terpenoid part and consequently, there must be two ring structures (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Figures S49- S51, S57-S60). Comparison with literature data enables the identification of \u003cb\u003e4\u003c/b\u003e as the sesquiterpene coumarin kamolonol \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Cytotoxicity antimicrobial and antioxidant activity were reported for Kamolonol acetate \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Kamolonol showed antibacterial activity against \u003cem\u003eHeliobacter pylori\u003c/em\u003e and \u003cem\u003eStaphylococcus aureus\u003c/em\u003e \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eNitric oxide (NO) is regarded as a central pro-inflammatory factor in the development and progressive evolution of various inflammatory illnesses. High levels of NO have been observed in instances of increased severity of disease, and this shows that it is a good parameter in the treatment of inflammation by way of monitoring\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Prevention of excessive formation of NO is thus a logical mode of treatment of inflammatory diseases. The current in vitro experiment evaluated the inhibitory activity of isolated components on NO production in the case of lipopolysaccharide (LPS)-activated macrophages. The \u003cem\u003ein vitro\u003c/em\u003e NO inhibition assay demonstrated that compounds \u003cb\u003e1, 2\u003c/b\u003e, and 4 showed higher NO inhibition activity compared to the positive control quercetin (IC₅₀ = 22.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11 \u0026micro;M). In contrast, compound \u003cb\u003e3\u003c/b\u003e exhibited the weakest inhibition, with an IC₅₀ value of 33.59\u0026thinsp;\u0026plusmn;\u0026thinsp;2.65 \u0026micro;M.\u003c/p\u003e\u003cp\u003eThe physiochemical behavior of these compounds \u003cb\u003e3\u003c/b\u003e and \u003cb\u003e4\u003c/b\u003e was found to have almost the same parameters (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), but the anti-inflammatory activity of the two compounds varied decisively. This discrepancy could be attributed to the carboxylic acid moiety in compound \u003cb\u003e3 (\u003c/b\u003egalbanic acid), which may ionize at physiological pH, compromising membrane permeability and intracellular uptake. This hypothesis aligns with previous reports on methyl galbanate, where esterification enhances bioavailability by preventing ionization\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Compounds \u003cb\u003e1\u003c/b\u003e and \u003cb\u003e2\u003c/b\u003e lack the hydroxyl and carbonyl functions in compound \u003cb\u003e4\u003c/b\u003e enable better binding of the latter at the molecular targets. Compound \u003cb\u003e2\u003c/b\u003e had no prediction of pharmacokinetic interactions. This can be attributed to the lack of structural similarity with known ligands currently within the SwissADME database.\u003c/p\u003e\u003cp\u003eThe SwissTargetPrediction database failed to detect gene targets for compound \u003cb\u003e3\u003c/b\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The remaining isolated compounds \u003cb\u003e1\u003c/b\u003e, \u003cb\u003e2\u003c/b\u003e, and \u003cb\u003e4\u003c/b\u003e had common targets of MAOA and MAOB (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), both of which are implicated in immunity and inflammatory responses \u003csup\u003e\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Targeting these genes could mediate the observed anti-inflammatory properties.\u003c/p\u003e\u003cp\u003eAnalysis of PPIs revealed a high degree of interaction revolving around inflammation and immunity-related genes (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). This is consistent with the observed anti-inflammatory properties. Even though the common gene targets (MAOA and MAOB) were not the top genes in terms of interactions, they still had a relatively high DC (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBiological processes in gene ontology describe and categorize overarching cellular events rather than specific pathways or biological components, in this study compounds \u003cb\u003e1\u003c/b\u003e, \u003cb\u003e2\u003c/b\u003e, and \u003cb\u003e4\u003c/b\u003e were predicted to interact with a plethora of biological targets with the common trait of being responsive to oxygen-containing compounds, whether these compounds are exogenous or endogenous. Enrichment analysis of the 39 genes targeted by compounds \u003cb\u003e1\u003c/b\u003e, \u003cb\u003e2\u003c/b\u003e, and \u003cb\u003e4\u003c/b\u003e also suggests involvement with a variety of cellular responses affecting cell activity, cellular movement, secretions, and metabolic states. This is due to targeting several receptor pathways and binding of many enzymes including kinases (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). This encompasses a wide variety of cellular functions, not excluding inflammatory responses \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eMolecular docking revealed that all isolated compounds are localized within the pharmacophores of both MAOA and MAOB in a manner like known controls (Figs.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e and \u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). Compound \u003cb\u003e4\u003c/b\u003e had highest binding affinity, a characteristic that was associated with its maximum anti-inflammatory activity compared to compound \u003cb\u003e3\u003c/b\u003e that was characterized by the weakest interaction. The docking findings were consistent with the molecular dynamics\u0026rsquo; simulations of the compound \u003cb\u003e4\u003c/b\u003e with MAO-A and MAO-B in which the established ligand-protein interaction was stable over the simulation time. The above findings (Figs.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e and \u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e), together argue that the compound could be stable and suitable in physiological conditions.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study shows that \u003cem\u003eFerula assa-foetida\u003c/em\u003e has anti-inflammatory properties, especially in the EtOAc fraction, which supports its usage in ethnomedicine. The most promising pharmacological characteristics of the isolated sesquiterpene coumarins were demonstrated by kamolonol (compound 4), which exhibited substantial affinity for monoamine oxidase A (MAOA) and B (MAOB), superior nitric oxide (NO) inhibition, and sustained molecular interactions in physiologically simulated settings. The anti-inflammatory effect of \u003cb\u003e4\u003c/b\u003e is reported for the first time. These results establish compound 4 as a viable candidate for additional drug development initiatives in addition to identifying MAOA and MAOB as anti-inflammatory targets. In vivo models of chronic inflammation, thorough pharmacokinetic characterization, and synergistic studies with established anti-inflammatory drugs.Such investigations could further affirm the therapeutic relevance of compound 4 and support its progression toward clinical application.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eGeneral\u003c/h2\u003e\n\u003cp\u003eThe tools and materials used in the process of this study have been sufficiently outlined in the previous studies \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch2\u003eAsafoetida oleo-gum-resin\u003c/h2\u003e\n\u003cp\u003eIn 2023, oleo-gum-resin of \u003cem\u003eFerula assa-foetida\u003c/em\u003e (asafoetida) was obtained in one of the Riyadh markets, Saudi Arabia.\u003c/p\u003e\n\u003ch2\u003eExtraction and isolation\u003c/h2\u003e\n\u003cp\u003eAn amount of 1000 g oleo-gum-resins underwent exhaustive extraction using alcoholic content of 95%. Aggregation of the combination of ethanol extracts obtained yielded 600.45 g of the total ethanol extract (AST). Ethanol-soluble fraction (ASI) had the mass of 399.55 g as is the case with the remaining quantity of the initial starting material. AST (28 g) was dissolved in 300 mL of 40% aqueous ethanol, fractionated by successive liquid-liquid extraction using an aliquot part. Hexane (3 x 400 mL) partitioning gave 13.45 g of the hexane-soluble fraction (ASH). Extraction with chloroform (CHCl\u003csub\u003e3\u003c/sub\u003e) (4 x 400 mL) yielded 3.60 g of the CHCl\u003csub\u003e3\u003c/sub\u003e -soluble fraction (ASC) and ethyl acetate (EtOAc) ( 2 x 400 mL) gave rise to 5.00 g of the EtOAc-soluble fraction (ASE).\u003c/p\u003e\n\u003cp\u003eThe \u003cstrong\u003eASH\u003c/strong\u003e fraction (10 g) was used as the sample under the column chromatography (gravity) using silica gel (250 g) over packed gravity column (150 x 5 cm i.ds.). Hexane was used to elute the column followed by hexane/EtOAc gradient. Fractions of 200 ml were taken and attached through thin layer chromatography (TLC). Fractions exhibiting the same TLC patterns were pooled into 4 fractions, namely \u003cstrong\u003eASH\u003c/strong\u003e-A to and \u003cstrong\u003eASH\u003c/strong\u003e-D. Reversed-phase RP-18 medium-pressure liquid chromatography (MPLC) (45 x 1 cm i.d.) in a water/methanol gradient was used to purify the fraction of ASH-B (1.38 g) sediment that remains purified after chromatography through the silica gel to a greater extent (fraction ASH-B). A 70% methanol elution provided 66 mg of compound\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003e1.\u0026nbsp;\u003c/strong\u003eFractions eluted with 75% MeOH (72 mg) were further purified via preparative TLC (CHCl₃/MeOH, 9.5:0.5), affording 34 mg of compound\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003e2.\u0026nbsp;\u003c/strong\u003eFraction \u003cstrong\u003eD\u003c/strong\u003e (0.78 g), eluted with hexane/EtOAc (1:1), was purified using a flash chromatography column (45 cm \u0026times; 1 cm i.d., 30 g silica gel) with CHCl₃ followed by CHCl₃/MeOH gradient.Fractions eluted with CHCl₃/MeOH (95:5) afforded 75 mg of compound\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.\u0026nbsp;\u003c/strong\u003eColumn chromatography on silica gel (75 x 3 cm i.d., 150 g) was applied to a 4.34 g sample of an ASE fraction. The ethyl acetate (EtOAc), followed through the use of ethyl acetate (EtOAc)-methanol (MeOH) mixture gradients. Fractions were obtained after filtration under yellow light in 5% MeOH in EtOAc (252 mg) which were then purified by adsorption chromatography over a reversed-phase RP-18 flash column and using a mobile phase of 70% MeOH 30% H₂O to give 35 mg of compound\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e. The higher the polar fractions the more 200 mg of glucose.\u003c/p\u003e\n\u003ch2\u003eExperimental animals\u003c/h2\u003e\n\u003cp\u003eThis animal experiment was conducted in accordance with the ARRIVE 2.0 guidelines for reporting animal research \u003csup\u003e45\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eForty-two male Wistar rats of 4 month to 7-month-old and weighing about 180\u0026ndash;200 g (some attained 210\u0026ndash;220 g), were obtained in the Laboratory Animal Unit (LBU) of Prince Sattam bin Abdulaziz University, Al Kharj, Saudi Arabia. The animals had a one-week acclimatization prior to the beginning of the experiment; during the acclimatization period animals were kept in ventilated cages (Rat IVC Blue Line, Techniplast, Buguggiate VA, Italy) which had sawdust bedding with moisture-absorbing characteristics. Housing was in constant condition of controlled temperature of 25\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C, 12:12 h of light dark cycle and free access to standard laboratory diet and filtered water were offered in stainless steel drinking bottles. Fuel cleaning was also a common practice and allowed the bedding to be changed on a regular basis, therefore sanitary conditions in housing were to be maintained. Animal handling during the work was carried out following the ARRIVE guidelines.\u003c/p\u003e\n\u003ch2\u003eAnimal Ethics Statement\u003c/h2\u003e\n\u003cp\u003eThe animal experiments obeyed all the ethical considerations of laboratory animal care spelled out by the Scientific Research Ethics Committee at Prince Sattam bin Abdulaziz University. Approval was given by the issuance of authorization number SCBR-319/2024 and the procedures undertaken were in conformity to the national guidelines when treating animals with humane treatment and welfare of animals.\u003c/p\u003e\n\u003ch2\u003eCarrageenan-induced acute paw edema model\u003c/h2\u003e\n\u003cp\u003eThe anti-inflammatory effects of the crude extract (AST) and three major fractions (ASI, ASC, ASE) of \u003cem\u003eFerula assa-foetida\u003c/em\u003e were evaluated using the carrageenan-induced paw edema model in adult male Wistar rats (7 months old, 180\u0026ndash;200 g). Forty-two rats were randomly divided into seven groups (6 rats each). Indomethacin (10 mg/kg, oral) served as the positive control, while the negative control received saline (2 mL/kg). Treatments included oral administration of AST or ASI (400 mg/kg) and ASH, ASC, or ASE (200 mg/kg). One hour post-treatment, inflammation was induced by injecting 0.1 mL of 1% \u0026lambda;-carrageenan into the right hind paw supplanter region. Paw volumes were recorded pre-injection and at 1, 2, and 3 hours post-injection using a digital plethysmometer. Edema volume and percentage inhibition were calculated following Abdel-Rahman et al \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. All assessments were performed by an independent, blinded observer:\u003c/p\u003e\n\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eWhere V0 is the paw volume (mL) before carrageenan injection and Vt is the paw volume (mL) at t hour after carrageenan injection. Ec and Et are the edema rates of control and treated groups, respectively.\u003c/p\u003e\n\u003cp\u003eExtensive monitoring practices were established in the entire study to identify any possible indications of disaffection, sickness or mood swings. Not a single subject was omitted in the experiment as well as repeated during the study period.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn vitro\u003c/strong\u003e \u003cstrong\u003eanti-inflammatory testing\u003c/strong\u003e\u003c/p\u003e\n\u003ch2\u003eCell culture\u003c/h2\u003e\n\u003cp\u003eMurine macrophage RAW 264.7 cells were purchased in Nawah Scientific Inc. (Mokatam, Cairo, Egypt). The cells were grown in Dulbecco Modified Eagle Medium (DMEM) that had additional components: streptomycin (100 100 g/mL), penicillin (100 U/mL) and 10% heat-inactivated fetal bovine serum. Cultures were maintained in a humidified incubator at 37\u0026deg;C in an atmosphere of 5% CO₂.\u003c/p\u003e\n\u003ch2\u003eCytotoxicity assay\u003c/h2\u003e\n\u003cp\u003eSulforhodamine B (SRB) assay was used in determining cell viability. In a nut shell, 100 \u0026micro;L of cell suspension (5 x 10^3 cells) was seeded in 96 well plates and culture was incubated to reach 24 hours to adhere to the plate. Then the cells were exposed to 100 \u0026micro;L of media with different doses of the test compounds. Fixed, cells were added 150 \u0026micro;L, 10%Trichloroacetic acid (TCA) and placed in 4\u0026deg;C condition one hour. Five times, Wells were cleaned with distilled water and were desiccated in air. Thereafter, 0.4 per cent SRB solution (70mL) was added into the wells and incubated in the dark at room temperature, 10 minutes. Three washes using 1 percent acetic acid were done to eliminate excess dye and plates allowed to dry overnight. The 150 \u0026micro;L of 10 mM TRIS buffer was added to bound dye and absorbance was read at 540 nm on Infinite F50 microplate reader (TECAN, Switzerland) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn vitro\u003c/strong\u003e \u003cstrong\u003eanti-inflammatory assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn order to test the anti-inflammatory activity, RAW 264.7 cells were incubated to grow in 96 well plates by seeding them over the 24 hours. Lipopolysaccharide (LPS) at the concentration of 1 \u0026micro;g/mL caused inflammation. Control wells had fresh medium added to them after untreated cells and the LPS group did not have any treatment added to the LPS. Test compounds were either tested alone or in combination with LPS at concentrations between 0. 001to 10 uM (LPS\u0026thinsp;+\u0026thinsp;Drug). Quercetin was used as the positive control. Mean production of nitric oxide (NO) was measured through the Griess reagent assay, whereby the same amounts of supernatant culture contents and reagent were combined, incubated with room temperature at darkness by ten minutes and the optical density of the mixture determined at 540 nm with the use of ELISA microplate reader \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n\u003cp\u003eThe means are reported as the standard error of the mean \u0026plusmn; (SE). One-way analysis of variance (ANOVA) was conducted as a measure to make statistical comparisons. Dunnett post hoc test was used where it showed a significant F-value (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05). The analysis was done on data with SPSS software version 17.0 (Chicago, IL, USA).\u003c/p\u003e\n\u003ch2\u003eDetermination of physicochemical properties and pharmacokinetic interactions\u003c/h2\u003e\n\u003cp\u003eThe SwissADME database was utilized to predict the following physicochemical and pharmacokinetic properties for compounds \u003cstrong\u003e1\u003c/strong\u003e\u0026ndash;\u003cstrong\u003e4\u003c/strong\u003e: lipid solubility calculated (LogP), hydrogen-bonding, interaction with Pgp, and interaction with several microsomal enzymes (CYP1A2, CYP2C9, CYP2D6, CYP3A4) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch2\u003eVirtual screening of inflammation-related genes\u003c/h2\u003e\n\u003cp\u003eThe GeneCards\u0026reg; database was utilized to identify genes associated with inflammation, using the keyword \u0026ldquo;inflammation\u0026rdquo; \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Microsoft Excel was used to collect and process data for later steps.\u003c/p\u003e\n\u003ch2\u003eIn silico screening of gene targets of compounds 1\u0026ndash;4\u003c/h2\u003e\n\u003cp\u003eThe possible targets of compounds \u003cstrong\u003e1\u0026ndash;4\u003c/strong\u003e on genes were discovered with the assistance of the SwissTargetPrediction platform \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. The tool predicts probable targets by contrasting the molecular structure of each compound with that of the known ligand of individual proteins based on both two-dimensional and three-dimensional structural similarities, and on the number of ligands having analogous properties. A probability score is created that will show the probability of interaction. This study identified that any predicted targets whose probability value was larger than zero were used further in analyses.\u003c/p\u003e\n\u003ch2\u003eIdentification of common genes between inflammation and compounds 1\u0026ndash;4\u003c/h2\u003e\n\u003cp\u003eVenn diagrams were utilized to identify common targets between the isolated test compounds, and inflammation genes obtained from the previous steps. Overlapping genes for individual compounds were identified \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. The Cytoscape bioinformatics software (version 3.10.1) was used to highlight common, as well as exclusive gene targets of each compound \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch2\u003eProtein\u0026ndash;Protein Interaction (PPI) Analysis\u003c/h2\u003e\n\u003cp\u003eThe target genes of the screened compounds \u003cstrong\u003e1\u0026ndash;4\u003c/strong\u003e were scrutinized as well as the possible and known protein-protein interactions based on the STRING functional protein association networks database \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. This process allowed identification of a small number of inflammation associated genes having most extensive interaction profiles. It only included interactions with a confidence score having a value greater than 0.4. A visualization of the resulting PPI network together with its analysis in terms of Cytoscape software was performed where all the genes were ranked based on their degree centrality (DC) value which is the cumulative number of PPIs associated to a given gene. Short descriptions about the highest DC value genes were created\u003c/p\u003e\n\u003ch3\u003eEnrichment analysis of targeted genes\u003c/h3\u003e\n\u003cp\u003eThe ShinyGO database analyzed the inflammation-related gene targets of compounds \u003cstrong\u003e1\u0026ndash;4\u003c/strong\u003e \u003csup\u003e54\u003c/sup\u003e. This analysis is based on gene ontology and is performed to determine the biological processes influenced by these genes. This analysis determines the number of genes related to a biological aspect, and assigns an FDR significance score. Lower FDR values indicate a stronger prediction, or higher significance.\u003c/p\u003e\n\u003ch2\u003eMolecular docking procedure\u003c/h2\u003e\n\u003cp\u003eMolecular docking simulations of the binding interactions of compounds 14 in the MAOA and MAOB isoforms of monoamine oxidase have been carried out. They were picked on the basis that both MAOA and MAOB were used as widely predicted targets of compounds \u003cstrong\u003e1\u003c/strong\u003e, \u003cstrong\u003e2\u003c/strong\u003e, and \u003cstrong\u003e4\u003c/strong\u003e, and the enzymes otherwise coded by them significantly contribute to the inflammatory pathways. The compounds 2D chemical structures were initially drawn in ChemDraw then exported in Mol 3D format. These were then transformed to PDB files using BIOVIA discovery studio 2022 visualizer. Crystal structures of MAOA (PDB ID: 2BXR) and MAOB (PDB ID: 7P4F) have been retrieved at the Protein Data Bank \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. The preparation of protein structures involved isolation of monomeric form and deletion of co-crystallized ligands as well as water molecules in BIOVIA Discovery Studio Visualizer 2022 \u003csup\u003e56\u003c/sup\u003e. The ligand and protein files were then converted to Autodock PDBQT using the Autodock Tools that was also used in defining the active site by modifying the grid box such that important amino acid residues that interact with the native ligands were included in the grid box. Autodock Vina was used to do docking and the lowest binding energy compounds-protein complexes were further analyzed. 3D interaction visualization images were then created with Discovery Studio visualizer and UCSF ChimeraX \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch2\u003eMolecular dynamic simulation\u003c/h2\u003e\n\u003cp\u003eMolecular dynamics (MD) simulations in GROMACS 2018 with the OPLS-AA/L force field were carried out in the current study. Two monoamine oxidase (MAO-A and MAO-B) isoforms were explored, where the three-dimensional structures were improved through the usage of the DockPrep tool \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. Compound \u003cstrong\u003e4\u003c/strong\u003e was parameterized using the SwissParam webserver \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. The MD simulations were performed for 20 ns, as following the same method in a previous study \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. Essential MDS parameters including RMSD, RMSF, and Hydrogen bonding analysis were evaluated.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e The researcher gratefully acknowledges the financial support received from Prince Sattam bin Abdulaziz University, which made this study possible. This work was funded under the research project number PSAU/2024/03/31571, and such backing significantly contributed to the successful execution of all research phases.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This study was financially supported by the Deanship of Scientific Research (DSR) at Prince Sattam bin Abdulaziz University as part of project PSAU/2024/03/31571.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;of Competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article and its supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Information:\u0026nbsp;\u003c/strong\u003eThe online version contains supplementary material available at XXXXXXXXXXX\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLaranjeira, I., Gon\u0026ccedil;alves, J., Gon\u0026ccedil;alves, C., Silva, M., Mouta, N., Dias, A. \u0026amp; Pinto-Ribeiro, F. Anti-inflammatory effect of \u003cem\u003ePterospartum tridentatum\u003c/em\u003e leaf extract in acute and chronic inflammation. \u003cem\u003eAppl. Sci. \u003c/em\u003e\u003cstrong\u003e13\u003c/strong\u003e, 4494 (2023). https://doi.org/10.3390/app13074494 \u003c/li\u003e\n\u003cli\u003eMorales, G., Paredes, A., Olivares, A. \u0026amp; Bravo, J. Acute oral toxicity and anti-inflammatory activity of hydroalcoholic extract from \u003cem\u003eLampaya medicinalis\u003c/em\u003e phil in rats. \u003cem\u003eBiol. Res\u003c/em\u003e. \u003cstrong\u003e47\u003c/strong\u003e, 6 (2014). http://doi.org/10.1186/0717-6287-47-6 \u003c/li\u003e\n\u003cli\u003eMobasheri, L., Khorashadizadeh, M., Safarpour, H., Mohammadi, M., Anani Sarab G. \u0026amp; Askari, V.R. Anti-Inflammatory activity of \u003cem\u003eFerula assafoetida\u003c/em\u003e oleo-gum-resin (Asafoetida) against TNF-\u0026alpha;-stimulated human umbilical vein endothelial cells (huvecs). \u003cem\u003eMediators. Inflamm\u003c/em\u003e. \u003cstrong\u003e2022\u003c/strong\u003e, 5171525 (2022). https://doi.org/10.1155/2022/5171525 \u003c/li\u003e\n\u003cli\u003eKrakauer, T. Molecular therapeutic targets in inflammation: cyclooxygenase and NF-\u0026kappa;B. \u003cem\u003eCurr. Drug Targets Inflamm. Allergy.\u003c/em\u003e\u003cstrong\u003e 3\u003c/strong\u003e, 317-324 (2004). https://doi.org/10.2174/1568010043343714 \u003c/li\u003e\n\u003cli\u003eSabry, M.M., Abdel-Rahman, R.F., Fayed, H.M., Taher, A.T., Ogaly, H.A.., Albohy, A., El-Gayed, S.H. \u0026amp; Ibrahim, R.M. Impact of Eucalyptus maculata hook resin exudate constituents on reducing COX-2 gene expression: In-vivo anti-inflammatory, molecular docking and dynamics studies. \u003cem\u003eJ. Ethnopharmacol.\u003c/em\u003e \u003cstrong\u003e314\u003c/strong\u003e, 116631 (2023). https://doi.org/10.1016/j.jep.2023.116631 \u003c/li\u003e\n\u003cli\u003eAlthurwi, H.N., Abdel-Rahman, R.F., Soliman, G.A., Ogaly, H.A., Alkholifi, F.K., Abd-Elsalam, R.M., Alqasoumi, S.I. \u0026amp; Abdel-Kader, M.S. Protective effect of beta-carotene against myeloperoxidase-mediated oxidative stress and inflammation in rat ischemic brain injury. \u003cem\u003eAntioxidants\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 2344 (2022). https://doi.org/10.3390/antiox11122344 \u003c/li\u003e\n\u003cli\u003ePark, M.H. \u0026amp; Hong, J.T. Roles of NF-\u0026kappa;B in cancer and inflammatory diseases and their therapeutic approaches. \u003cem\u003eCells\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 15 (2016). https://doi.org/10.3390/cells5020015 \u003c/li\u003e\n\u003cli\u003eOh, S.Y. \u0026amp; Hyun, C.G. Anti-inflammatory potential of Umckalin through the inhibition of iNOS, COX-2, pro-inflammatory cytokines, and MAPK signaling in LPS-stimulated RAW 264.7 cells. \u003cem\u003eFuture Pharmacol.\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 6 (2025). https://doi.org/10.3390/futurepharmacol5010006 \u003c/li\u003e\n\u003cli\u003eYaqoob, U. \u0026amp; Nawchoo, I.A. Distribution and taxonomy of \u003cem\u003eFerula\u003c/em\u003e L.: a review. \u003cem\u003eRes. Rev. J. Bot.\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 15 (2016). \u003c/li\u003e\n\u003cli\u003eMahendra, P. \u0026amp; Bisht, S. \u003cem\u003eFerula asafoetida\u003c/em\u003e: traditional uses and pharmacological activity. \u003cem\u003ePharmacogn. Rev.\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 141-146 (2012). https://doi.org/10.4103/0973-7847.99948 \u003c/li\u003e\n\u003cli\u003eMohammadhosseini, M.; Venditti, A.; Sarker, S.D.; Nahar, L.; Akbarzadeh, A. The genus \u003cem\u003eFerula\u003c/em\u003e: ethnobotany, phytochemistry and bioactivities \u0026ndash; a review. \u003cem\u003eInd Crops Prod\u003c/em\u003e, \u003cstrong\u003e2019\u003c/strong\u003e, \u003cem\u003e129\u003c/em\u003e, 350-394. https://doi.org/10.1016/j.indcrop.2018.12.012 \u003c/li\u003e\n\u003cli\u003eSahebkar, A. \u0026amp; Iranshahi, M. Volatile constituents of the genus \u003cem\u003eFerula\u003c/em\u003e (Apiaceae): a review. \u003cem\u003eJ. Essent. Oil. Bear. Plants\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 504-531 (2011). http://dx.doi.org/10.1080/0972060X.2011.10643969 \u003c/li\u003e\n\u003cli\u003eLi, N., Guo, T. \u0026amp; Zhou, D. Bioactive Sesquiterpene Coumarins From Plants. In \u003cem\u003eStudies in Natural Products Chemistry\u003c/em\u003e, Atta-ur-Rahman, Eds, Elsevier: 2018, Volume 59, pp. 251-282. https://doi.org/10.1016/B978-0-444-64179-3.00008-6. \u003c/li\u003e\n\u003cli\u003eGeroushi, A., Auzi, A.A., Elhwuegi, A.S., Elzawam, F., Elsherif, A., Nahar, L. \u0026amp; Sarker, S.D. Antiinflammatory sesquiterpenes from the root oil of \u003cem\u003eFerula hermonis\u003c/em\u003e. \u003cem\u003ePhytother. Res.\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 774-777 (2011). https://doi.org/10.1002/ptr.3324 \u003c/li\u003e\n\u003cli\u003eWang, J., Huo, X., Wang, H., Dong, A., Zheng, Q. \u0026amp; Si, J. Undescribed sesquiterpene coumarins from the aerial parts of \u003cem\u003eFerula sinkiangensis \u003c/em\u003eand their anti-inflammatory activities in lipopolysaccharide-stimulated RAW 264.7 macrophages. \u003cem\u003ePhytochemistry\u003c/em\u003e \u003cstrong\u003e210\u003c/strong\u003e, 113664 (2023). https://doi.org/10.1016/j.phytochem.2023.113664 \u003c/li\u003e\n\u003cli\u003eDang, W., Guo, T., Zhou, D., Meng, Q., Fang, M., Chen, G., Lin, B., Hou, Y. \u0026amp; Li, N. Structure-guided isolation of anti-neuroinflammatory sesquiterpene coumarins from \u003cem\u003eFerula sinkiangensis.\u003c/em\u003e \u003cem\u003eChin. J. Nat. Med.\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 643-653 (2024). https://doi.org/10.1016/s1875-5364(24)60619-9 \u003c/li\u003e\n\u003cli\u003eGuo, T., Dang, W., Zhou, Y., Zhou, D., Meng, Q., Xu, L., Chen, G., Lin, B., Qing, D., Sun, Y., Hou, Y. \u0026amp; Li, N. Sesquiterpene coumarins isolated from \u003cem\u003eFerula bungeana \u003c/em\u003eand their anti-neuroinflammatory activities. \u003cem\u003eBioorg.\u003c/em\u003e \u003cem\u003eChem.\u003c/em\u003e \u003cstrong\u003e128\u003c/strong\u003e, 106102 (2022). https://doi.org/10.1016/j.bioorg.2022.106102.\u003c/li\u003e\n\u003cli\u003eZhang, H., Huang, J., Fan, X., Miao, R. \u0026amp; Wang, Y. HSP90AA1 promotes the inflammation in human gingival fibroblasts induced by Porphyromonas gingivalis lipopolysaccharide via regulating of autophagy. \u003cem\u003eBMC Oral Health\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 366 (2022). https://doi.org/10.1186/s12903-022-02304-0 \u003c/li\u003e\n\u003cli\u003eTukaj, S. \u0026amp; Węgrzyn, G. Anti-Hsp90 therapy in autoimmune and inflammatory diseases: a review of preclinical studies. \u003cem\u003eCell Stress Chaperones\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, 213-218 (2016). https://doi.org/10.1007/s12192-016-0670-z \u003c/li\u003e\n\u003cli\u003eLi, L., Xing, W., Jiang, L., Chen, D. \u0026amp; Zhang, G. NR3C1 overexpression regulates the expression and alternative splicing of inflammation-associated genes involved in PTSD. \u003cem\u003eGene\u003c/em\u003e \u003cstrong\u003e859\u003c/strong\u003e, 147199 (2023). https://doi.org/10.1016/j.gene.2023.147199 \u003c/li\u003e\n\u003cli\u003eNewton, R. Anti-inflammatory glucocorticoids: changing concepts. \u003cem\u003eEur. J. Pharmacol.\u003c/em\u003e \u003cstrong\u003e724\u003c/strong\u003e, 231-236 (2014). https://doi.org/10.1016/j.ejphar.2013.05.035 \u003c/li\u003e\n\u003cli\u003eLaRocca, T.J., Cavalier, A.N., Roberts, C.M., Lemieux, M.R., Ramesh, P., Garcia, M.A. \u0026amp; Link, C.D. Amyloid beta acts synergistically as a pro-inflammatory cytokine. \u003cem\u003eNeurobiol. Dis.\u003c/em\u003e \u003cstrong\u003e159\u003c/strong\u003e, 105493 (2021). https://doi.org/10.1016/j.nbd.2021.105493 \u003c/li\u003e\n\u003cli\u003eLiu, P., Zhao, B., Wei, M., Li, Y., Liu, J., Ma, L., Shang, S., Huo, K., Wang, J., Li, R. \u0026amp; Qu, Q. Activation of inflammation is associated with amyloid-\u0026beta; accumulation induced by chronic sleep restriction in rats. \u003cem\u003eJ. Alzheimers Dis.\u003c/em\u003e \u003cstrong\u003e74\u003c/strong\u003e, 759-773 (2020). https://doi.org/10.3233/jad-191317 \u003c/li\u003e\n\u003cli\u003eXu, F., Yao, W., Xue, Y., Sun, Q. \u0026amp; Cao, C. The oncogene ABL1 regulates the inflammatory response of innate immunity via mediating TRAF6 ubiquitination. \u003cem\u003eImmunobiology\u003c/em\u003e \u003cstrong\u003e227\u003c/strong\u003e, 152262 (2022). https://doi.org/10.1016/j.imbio.2022.152262\u003c/li\u003e\n\u003cli\u003eScheiman, J.M. NSAID-induced gastrointestinal injury: a focused update for clinicians. \u003cem\u003eJ. Clin. Gastroenterol.\u003c/em\u003e \u003cstrong\u003e50\u003c/strong\u003e, 5-10 (2016). https://doi.org/10.1097/mcg.0000000000000432 \u003c/li\u003e\n\u003cli\u003eXiang, L., Huang, Q., Chen, T., He, Q., Yao, H. \u0026amp; Gao, Y. Ethanol extract of Paridis rhizoma attenuates carrageenan-induced paw swelling in rats by inhibiting the production of inflammatory factors. \u003cem\u003eBMC Complement Med Ther\u003c/em\u003e. \u003cstrong\u003e23\u003c/strong\u003e, 437 (2023). https://doi:10.1186/s12906-023-04264-6\u003c/li\u003e\n\u003cli\u003eCrunkhorn, P. \u0026amp; Meacock, S.C. Mediators of the inflammation induced in the rat paw by carrageenin. \u003cem\u003eBr. J. Pharmacol.\u003c/em\u003e \u003cstrong\u003e42\u003c/strong\u003e, 392-402 (1971). https://doi.org/10.1111/j.1476-5381.1971.tb07124.x \u003c/li\u003e\n\u003cli\u003eNalamachu, S. \u0026amp; Wortmann, R. Role of indomethacin in acute pain and inflammation management: a review of the literature. \u003cem\u003ePostgrad. Med.\u003c/em\u003e \u003cstrong\u003e126\u003c/strong\u003e, 92-97 (2014). https://doi.org/10.3810/pgm.2014.07.2787 \u003c/li\u003e\n\u003cli\u003eTun, K.N.W., Aminah, N.S., Kristanti, A.N., Ramadhan, R. \u0026amp; Takaya, Y. Cytotoxic prenyl and geranyl coumarins from the stem bark of Casimiroa edulis. \u003cem\u003eLett. Org. Chem.\u003c/em\u003e \u003cstrong\u003e17\u003c/strong\u003e, 680-687 (2020). http://dx.doi.org/10.2174/1570178616666191019121437 \u003c/li\u003e\n\u003cli\u003eTjahjandarie, T.S. Coumarins from the stem bark of \u003cem\u003eFeronia limonia\u003c/em\u003e. \u003cem\u003eJ. Chem. Pharm. Res.\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 499-504 (2014). \u003c/li\u003e\n\u003cli\u003eBibak, B., Shakeri, F., Barreto, G.E., Keshavarzi, Z., Sathyapalan, T. \u0026amp; Sahebkar, A. A review of the pharmacological and therapeutic effects of auraptene. \u003cem\u003eBiofactors\u003c/em\u003e \u003cstrong\u003e45\u003c/strong\u003e, 867-879 (2019). https://doi.org/10.1002/biof.1550 \u003c/li\u003e\n\u003cli\u003eIranshahi, M., Shahverdi, A.R., Mirjani, R., Amin, G. \u0026amp; Shafiee, A. Umbelliprenin from \u003cem\u003eFerula persica\u003c/em\u003e roots inhibits the red pigment production in Serratia marcescens. \u003cem\u003eZ. Naturforsch. C. J. Biosci.\u003c/em\u003e \u003cstrong\u003e59\u003c/strong\u003e, 506-508 (2004). https://doi.org/10.1515/znc-2004-7-809 \u003c/li\u003e\n\u003cli\u003eFiorito, S., Preziuso, F., Sharifi-Rad, M., Marchetti, L. \u0026amp; Epifano. F., Genovese, S\u003cem\u003e.\u003c/em\u003e Auraptene and Umbelliprenin: a review on their latest literature acquisitions. \u003cem\u003ePhytochem. Rev.\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, 317\u0026ndash;326 (2022). https://doi.org/10.1007/s11101-020-09713-5\u003c/li\u003e\n\u003cli\u003eEru\u0026ccedil;ar, F.M., Senadeera, S.P.D., Wilson, J.A., Goncharova, E., Beutler, J.A. \u0026amp; Miski, M. Novel cytotoxic sesquiterpene coumarin ethers and sulfur-containing compounds from the roots of \u003cem\u003eFerula turcica\u003c/em\u003e. \u003cem\u003eMolecules \u003c/em\u003e\u003cstrong\u003e28\u003c/strong\u003e, 5733 (2023). https://doi.org/10.3390/molecules28155733 \u003c/li\u003e\n\u003cli\u003eKasaian, J., Iranshahy, M. \u0026amp; Iranshahi, M. Synthesis, biosynthesis and biological activities of galbanic acid \u0026ndash; A review. \u003cem\u003ePharm. Biol.\u003c/em\u003e \u003cstrong\u003e52\u003c/strong\u003e, 524\u0026ndash;531 (2013). https://doi.org/10.3109/13880209.2013.846916\u003c/li\u003e\n\u003cli\u003eDastan, D., Salehi, P., Reza Gohari, A., Ebrahimi, S.N., Aliahmadi, A. \u0026amp; Hamburger, M. Bioactive sesquiterpene coumarins from \u003cem\u003eFerula pseudalliacea.\u003c/em\u003e \u003cem\u003ePlanta Med.\u003c/em\u003e \u003cstrong\u003e80\u003c/strong\u003e, 1118-1123 (2014). https://doi.org/10.1055/s-0034-1382996 \u003c/li\u003e\n\u003cli\u003eMahaki, H., Tanzadehpanah, H., Abou-Zied, O.K., Moghadam, N.H., Bahmani, A., Salehzadeh, S., Dastan, D. \u0026amp; Saidijam, M. Cytotoxicity and antioxidant activity of Kamolonol acetate from \u003cem\u003eFerula pseudalliacea,\u003c/em\u003e and studying its interactions with calf thymus DNA (ct-DNA) and human serum albumin (HSA) by spectroscopic and molecular docking techniques. \u003cem\u003eProcess Biochem\u003c/em\u003e.\u003cstrong\u003e 79\u003c/strong\u003e, 203-213 (2019). https://doi.org/10.1016/j.procbio.2018.12.004\u003c/li\u003e\n\u003cli\u003eAbbas, Z., Tong, Y., Zhang, J., Wang, J., Guo, H., Cheng, Q., Marhaba, Zhou, Y., Ahmad, B., Wei, X., Si, D. \u0026amp; Zhang, R. Enhancing the antioxidant and anti-inflammatory potentials of mulberry-derived postbiotics through submerged fermentation with B. subtilis H4 and B. amylolique faciens LFB112. \u003cem\u003eFood Biosci\u003c/em\u003e. \u003cstrong\u003e60\u003c/strong\u003e, 104252 (2024). https://doi.org/10.1016/j.fbio.2024.104252 \u003c/li\u003e\n\u003cli\u003eSaijo, F., Milsom, A.B., Bryan, N.S., Bauer, S.M., Vowinkel, T., Ivanovic, M., Andry, C., Granger, D.N., Rodriguez, J. \u0026amp; Feelisch, M. On the dynamics of nitrite, nitrate and other biomarkers of nitric oxide production in inflammatory bowel disease. \u003cem\u003eNitric Oxide\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 155-167 (2010). https://doi.org/10.1016/j.niox.2009.11.009\u003c/li\u003e\n\u003cli\u003eDaina, A., Michielin, O. \u0026amp; Zoete, Z. SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules. \u003cem\u003eNucleic Acids Res.\u003c/em\u003e \u003cstrong\u003e47\u003c/strong\u003e, W357-W364 (2019). https://doi.org/10.1093/nar/gkz382 \u003c/li\u003e\n\u003cli\u003ehttps://bioinformatics.psb.ugent.be/webtools/Venn/ \u003c/li\u003e\n\u003cli\u003eKohl, M., Wiese, S. \u0026amp; Warscheid, B. Cytoscape: software for visualization and analysis of biological networks. \u003cem\u003eMethods Mol. Biol.\u003c/em\u003e \u003cstrong\u003e696\u003c/strong\u003e, 291-303 (2011). https://doi.org/10.1007/978-1-60761-987-1_18 \u003c/li\u003e\n\u003cli\u003eZarrin, A.A., Bao, K., Lupardus, P. \u0026amp; Vucic, D. Kinase inhibition in autoimmunity and inflammation. \u003cem\u003eNat. Rev. Drug Discov.\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, 39-63 (2021). https://doi.org/10.1038/s41573-020-0082-8\u003c/li\u003e\n\u003cli\u003eAlqarni, M.H., Soliman, G.A., Salkini, M.A., Alam, P., Yusufoglu, H.S., Baykan S., Ozturk, B. \u0026amp; Abdel-Kader, M.S. The potential aphrodisiac effect of \u003cem\u003eFerula drudeana\u003c/em\u003e korovin extracts and isolated sesquiterpene coumarins in male rats. \u003cem\u003ePharmacogn. Mag.\u003c/em\u003e \u003cstrong\u003e16\u003c/strong\u003e, 404-409 (2020). http://dx.doi.org/10.4103/pm.pm_551_19 \u003c/li\u003e\n\u003cli\u003ePercie du Sert, N., et al. The ARRIVE guidelines 2.0: Updated guide-lines for reporting animal research. \u003cem\u003ePLoS Biol,\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e, e3000410 (2020). https://doi.org/10.1371/journal.pbio.3000410\u003c/li\u003e\n\u003cli\u003eAbdel-Rahman, R.F., Alqasoumi, S.I., El-Desoky, A.H., Soliman, G.A., Par\u0026eacute;, P.W. \u0026amp; Hegazy, M.E. Evaluation of the anti-inflammatory, analgesic and anti-ulcerogenic potentials of Achillea fragrantissima (Forssk.). \u003cem\u003eS. Afr. J. Bot.\u003c/em\u003e \u003cstrong\u003e98\u003c/strong\u003e, 122-127 (2015). https://doi.org/10.1016/j.sajb.2015.02.009 \u003c/li\u003e\n\u003cli\u003eSkehan, P., Storeng, R., Scudiero, D., Monks, A., McMahon, J., Vistica, D., Warren, J.T., Bokesch, H., Kenny, S. \u0026amp; Boyd, M.R. New colorimetric cytotoxicity assay for anticancer-drug screening. \u003cem\u003eJ. Natl. Cancer Inst.\u003c/em\u003e \u003cstrong\u003e82\u003c/strong\u003e, 1107-1112 (1990). https://doi.org/10.1093/jnci/82.13.1107 \u003c/li\u003e\n\u003cli\u003eAllam, R.M., Al-Abd, A.M., Khedr, A., Sharaf, O.A., Nofal, S.M., Khalifa, A.E., Mosil, H.A. \u0026amp; Abdel-Naim, A.B. Fingolimod interrupts the cross talk between estrogen metabolism and sphingolipid metabolism within prostate cancer cells. \u003cem\u003eToxicol. Lett.\u003c/em\u003e \u003cstrong\u003e291\u003c/strong\u003e, 77-85 (2018). https://doi.org/10.1016/j.toxlet.2018.04.008 \u003c/li\u003e\n\u003cli\u003eKim, C.E., Le, D.D. \u0026amp; Lee, M. Diterpenoids isolated from Podocarpus macrophyllus inhibited the inflammatory mediators in LPS-induced HT-29 and RAW 264.7 cells. \u003cem\u003eMolecules\u003c/em\u003e 26, 4326 (2021). https://doi.org/10.3390/molecules26144326 \u003c/li\u003e\n\u003cli\u003eAhmed, A.H.H., Mohamed, M.F.A., Allam, R.M., Nafady, A., Mohamed, S.K., Gouda, A.E. \u0026amp; Beshr, E.A.M. Design, synthesis, and molecular docking of novel pyrazole-chalcone analogs of lonazolac as 5-LOX, iNOS and tubulin polymerization inhibitors with potential anticancer and antiinflammatory activities. \u003cem\u003eBioorg. Chem.\u003c/em\u003e 129, 106171 (2022). https://doi.org/10.1016/j.bioorg.2022.106171 \u003c/li\u003e\n\u003cli\u003eDaina, A., Michielin, O. \u0026amp; Zoete, V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. \u003cem\u003eSci. Rep.\u003c/em\u003e \u003cstrong\u003e7\u003c/strong\u003e, 42717 (2017). https://doi.org/10.1038/srep42717 \u003c/li\u003e\n\u003cli\u003eSafran, M., Dalah, I., Alexander, J., Rosen, N., Stein, T.I., Shmoish, M., Nativ, N., Bahir, I., Doniger, T., Krug, H., Sirota-Madi, A., Olender, T., Golan, Y., Stelzer, G., Harel, A. \u0026amp; Lancet, D. GeneCards Version 3: the human gene integrator. \u003cem\u003eDatabase\u003c/em\u003e \u003cstrong\u003e2010\u003c/strong\u003e, baq020 (2010). https://doi.org/10.1093/database/baq020 \u003c/li\u003e\n\u003cli\u003eSzklarczyk, D., Kirsch, R., Koutrouli, M., Nastou, K., Mehryary, F., Hachilif, R., Gable, A.L., Fang, T., Doncheva, N.T., Pyysalo, S., Bork, P., Jensen, L.J. \u0026amp; Mering, C.V. The STRING database in 2023: protein\u0026ndash; protein association networks and functional enrichment analyses for any sequenced genome of interest. \u003cem\u003eNucleic Acids Res.\u003c/em\u003e \u003cstrong\u003e51\u003c/strong\u003e, D638-D646 (2023). https://doi.org/10.1093/nar/gkac1000 \u003c/li\u003e\n\u003cli\u003eGe, S.X., Jung, D. \u0026amp; Yao, R. ShinyGO: a graphical gene-set enrichment tool for animals and plants. \u003cem\u003eBioinform\u003c/em\u003e. \u003cstrong\u003e36\u003c/strong\u003e, 2628-2629 (2020). https://doi.org/10.1093/bioinformatics/btz931 \u003c/li\u003e\n\u003cli\u003eKouranov, A., Xie, L., de la Cruz, J., Chen, L., Westbrook, J., Bourne, P.E. \u0026amp; Berman, H.M. The RCSB PDB information portal for structural genomics. \u003cem\u003eNucleic Acids Res.\u003c/em\u003e \u003cstrong\u003e34\u003c/strong\u003e, D302-D305 (2006). https://doi.org/10.1093/nar/gkj120\u003c/li\u003e\n\u003cli\u003eSyst\u0026egrave;mes D (2021) Discovery studio visualizer. v16, 1, 15350.\u003c/li\u003e\n\u003cli\u003ePettersen, E.F., Goddard, T.D., Huang, C.C., Meng, E.C., Couch, G.S., Croll, T.I., Morris, J.H. \u0026amp; Ferrin, T.E. UCSF ChimeraX: Structure visualization for researchers, educators, and developers. \u003cem\u003eProtein Sci\u003c/em\u003e. \u003cstrong\u003e30\u003c/strong\u003e, 70-82 (2021). https://doi.org/10.1002/pro.3943 \u003c/li\u003e\n\u003cli\u003eVan Der Spoel, D., Lindahl, E., Hess, B., Groenhof, G., Mark, A.E. \u0026amp; Berendsen, H.J.C. GROMACS: fast, flexible, and free. \u003cem\u003eJ. Comput. Chem.\u003c/em\u003e \u003cstrong\u003e26\u003c/strong\u003e, 1701-1718 (2005). https://doi.org/10.1002/jcc.20291 \u003c/li\u003e\n\u003cli\u003eZoete, V., Cuendet, M.A., Grosdidier, A. \u0026amp; Michielin, O. SwissParam: a fast force field generation tool for small organic molecules. \u003cem\u003eJ. Comput. Chem.\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 2359-2368 (2011). https://doi.org/10.1002/jcc.21816 \u003c/li\u003e\n\u003cli\u003eAlamri, M.A. \u0026amp; Alamri, M.A. Adamantane-derived scaffolds targeting the sigma-2 receptor, an \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein silico\u003c/em\u003e study. \u003cem\u003eSaudi Pharm. J.\u003c/em\u003e \u003cstrong\u003e29\u003c/strong\u003e, 1166-1172 (2021).\u0026rlm; https://doi.org/10.1016/j.jsps.2021.08.016\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 7","content":"\u003cp\u003eTable 7 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Asafoetida, sesquiterpene coumarins, anti-inflammatory, internet pharmacology, molecular docking, molecular dynamic","lastPublishedDoi":"10.21203/rs.3.rs-7355100/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7355100/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eFerula assa-foetida\u003c/em\u003e known as Asafoetida has a long-established history in folk medicine as a therapeutically useful drug in many disorders. The current paper explored the \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e anti-inflammatory activities of the plant. Liquid ethanol crude extract was subjected to liquid-to-liquid extraction, and the fractions so obtained were evaluated against the carrageenan-induced acute paw edema model in rats, to determine the anti-inflammatory effects. The fractions that gave the greatest activity-ethyl acetate and hexane- afforded four sesquiterpene coumarins: auraptene (\u003cb\u003e1\u003c/b\u003e), umbelliprenin (\u003cb\u003e2\u003c/b\u003e), galbanic acid (\u003cb\u003e3\u003c/b\u003e), and kamolonol (\u003cb\u003e4\u003c/b\u003e). The overall structure was determined through detailed spectroscopic investigation, \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eH NMR, \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003eC NMR, DPET135, COSY, HSQC, HMBC, HRESIMS, and other references to the literature. Evaluation of the \u003cem\u003ein vitro\u003c/em\u003e activity of the LPS stimulated RAW 264.7 macrophages showed that the compound \u003cb\u003e4\u003c/b\u003e (ethyl acetate fraction) exhibited maximum inhibitory action against the generation of nitric oxide (NO), followed by the compounds \u003cb\u003e1\u003c/b\u003e and \u003cb\u003e2\u003c/b\u003e of the hexane fraction. Internet Pharmacology, Molecular Docking and Molecular dynamic simulation analysis were used to identify the target genes and explain the potential differences between the active compounds. As far as the authors know, there are no earlier reports that mention the anti-inflammatory action of kamolonol (\u003cb\u003e4\u003c/b\u003e).\u003c/p\u003e","manuscriptTitle":"Anti-inflammatory Sesquiterpene Coumarins from the Active Fractions of Ferula assa-foetida: In Silico Analysis Endorse Experimental data","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-16 18:22:57","doi":"10.21203/rs.3.rs-7355100/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-07T05:09:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-06T18:06:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-27T16:48:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269755771921859397436899665051341865296","date":"2025-09-23T18:00:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"157381114372694473506287925718324172975","date":"2025-09-17T11:01:34+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-09T10:00:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-08T17:59:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-08T12:47:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-02T06:23:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-09-02T06:18:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"47b6fb74-f408-4fca-b1cf-bece5097edfe","owner":[],"postedDate":"September 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":54741002,"name":"Biological sciences/Biochemistry"},{"id":54741003,"name":"Biological sciences/Chemical biology"},{"id":54741004,"name":"Physical sciences/Chemistry"},{"id":54741005,"name":"Biological sciences/Computational biology and bioinformatics"},{"id":54741006,"name":"Biological sciences/Drug discovery"},{"id":54741007,"name":"Biological sciences/Plant sciences"}],"tags":[],"updatedAt":"2025-12-01T16:03:45+00:00","versionOfRecord":{"articleIdentity":"rs-7355100","link":"https://doi.org/10.1038/s41598-025-26010-3","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-11-26 15:57:16","publishedOnDateReadable":"November 26th, 2025"},"versionCreatedAt":"2025-09-16 18:22:57","video":"","vorDoi":"10.1038/s41598-025-26010-3","vorDoiUrl":"https://doi.org/10.1038/s41598-025-26010-3","workflowStages":[]},"version":"v1","identity":"rs-7355100","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7355100","identity":"rs-7355100","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}