Abstract Simple Summary The aim of the study is to investigate the bioactives of Zanthoxylum piperitum fruits on rheumatoid arthritis. The methodology to identify the relationship between signaling pathways, targets, and bioactives is based on network pharmacology. The results show that Zanthoxylum piperitum fruits might alleviate inflammatory symptoms of rheumatoid arthritis. Thus, we suggest that Zanthoxylum piperitum fruit is a promising herbal plant to reduce the level of cytokines against rheumatoid arthritis. Abstract Zanthoxylum piperitum fruits (ZPFs) have been demonstrated favorable clinical efficacy on rheumatoid arthritis (RA), but its compounds and mechanisms against RA have not been elucidated. This study was to investigate the compounds and mechanisms of ZPFs to alleviate RA via network pharmacology. The compounds from ZPFs were detected by gas chromatography–mass spectrometry (GC-MS) and screened to select drug-likeness compounds through SwissADME. Targets associated with bioactive compounds or RA were identified utilizing bioinformatics databases. The signaling pathways related to RA were constructed; interactions among targets; and signaling pathways-targets-compounds (STC) were analyzed by RPackage. Finally, a molecular docking test (MDT) was performed to validate affinity between targets and compounds on key signaling pathway(s). GC-MS detected a total of 85 compounds from ZPFs, and drug-likeness properties accepted all compounds. A total of 216 targets associated with compounds 3377 RA targets and 101 targets between them were finally identified. Then, a bubble chart exhibited that inactivation of MAPK (mitogen-activated protein kinase) and activation of PPAR (peroxisome proliferator-activated receptor) signaling pathway might be key pathways against RA. Overall, this work suggests that seven compounds from ZPFs and eight targets might be multiple targets on RA and provide integrated pharmacological evidence to support the clinical efficacy of ZPFs on RA. Keywords: Zanthoxylum piperitum fruits, rheumatoid arthritis, network pharmacology, MAPK signaling pathway, PPAR signaling pathway 1. Introduction Rheumatoid arthritis (RA) is a long-term systemic autoimmune disorder that deteriorates the synovial joints and is associated with gradual disability [[28]1]. RA is a progressive inflammation caused by joint damage and its functional loss around the articular [[29]2,[30]3]. RA can present irrespective of age, diagnosed in around 1% of the population, brings huge social-economic burden [[31]4]. The main factor causing RA is uncontrollable cytokine secretion due to bone damage; however, the etiology of RA is unknown [[32]5,[33]6]. Commonly, the anti-RA drugs administered are disease-modifying arthritis drugs (DMARDs) and non-steroidal anti-inflammatory drugs (NSAIDs) in most countries [[34]7]. At present, prolonged administration of these drugs is involved in severe side effects such as upset stomach, nephrotoxicity, and electrolyte imbalance [[35]8,[36]9]. In contrast, an animal test demonstrated that the repeated dose treatment of plant leaf methanolic extraction with anti-RA efficacy did not alter liver and kidney function [[37]10]. It implies that herbal medicine extracts against RA are better clinical safety than unnatural compounds. For a long time, herbal plants treating RA were essential resources due to their excellent clinical efficacy and low adverse effects [[38]11]. Zanthoxylum piperitum (ZP) belongs to the Rutaceae family, which has been chiefly used as a condiment of food in Korea, Japan, and China [[39]12]. It was reported that essential oil in ZP showed a 38% reduction of nitric oxide (NO) related to the occurrence and progression of inflammatory joint disease [[40]13]. Another report demonstrated that the peel of ZP has potent anti-inflammatory activities by suppressing nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and caspase-1 activation in lipopolysaccharide (LPS)-induced RAW264.7 cells [[41]14]. The studies give a hint that ZP might be a herbal medicine to alleviate RA. So far, active compounds and pharmacological mechanisms of ZPFs against RA have not been elucidated. Hence, studies of active compounds and mechanisms of ZPFs against RA should be investigated to prove their therapeutic value. Network pharmacology is an integrated analytical methodology to understand multiple elements such as compounds, targets and pathways [[42]15]. Network pharmacology can unravel the mechanism of compounds in herbal plants with an integrated concept [[43]16]. Additionally, network pharmacology makes a point of “multiple-targets, multiple-compounds”, instead of “one-target, one-compound” [[44]17]. Therefore, network pharmacology is an optimal method to explicate herbal plant issues. Currently, network pharmacology has been utilized to prove bioactive compounds and mechanisms of herbal plants against complex diseases [[45]18,[46]19]. Hence, network pharmacology was utilized to uncover the pharmacological mechanisms of bioactive compounds of ZPFs against RA. Firstly, compounds of ZPFs methanolic extraction identified from GC-MS filtered out drug-likeness candidates on a physicochemical descriptor tool. Secondly, targets related to filtered compounds were retrieved by public bioinformatic databases, and final overlapping targets calculated between compounds and RA targets retrieved by public disease target databases. Thirdly, a key target on protein–protein interaction (PPI) was identified, and two key signaling pathways of ZPFs against RA were identified by analyzing the final overlapping targets. Then, another key target of signaling pathways related to the occurrence and development of RA was identified by analyzing targets associated with signaling pathways. Finally, a molecular docking test (MDT) was carried out to find po from ZPFs against RA on each target related directly to two key signaling pathways. The workflow diagram is exhibited in [47]Figure 1. Figure 1. [48]Figure 1 [49]Open in a new tab Workflow chart of network pharmacology analysis of ZPFs against RA. 2. Materials and Methods 2.1. Plant Material Collection and Classification The Zanthoxylum piperitum fruits (ZPFs) were collected from (latitude: 37.628975, longitude: 126.742978), Gyeonggi-do, Korea, in August 2020, and the plant was identified by Dr. Dong Ha Cho, Plant biologist and Professor, Department of Bio-Health Convergence, College of Biomedical Science, Kangwon National University. A voucher number (UUC 270) has been stored at Kenaf Corporation in the Department of Bio-Health Convergence, and the material can be used only for research purposes. 2.2. Plant Preparation, Extraction The ZPFs were dried in a shady area at room temperature (20–22 °C) for 21 days, and dried ZPFs made powder using an electric blender. Approximately 50 g of ZPFs powder was soaked in 800 mL of 100% methanol (Daejung, Siheung city, Gyeonggi-do, Korea) for 10 days and repeated three times to achieve a high yield rate. The solvent extract was collected, filtered, and evaporated using a vacuum evaporator (IKA- RV8, Staufen city, Germany). The evaporated sample was dried under a boiling water bath (IKA-HB10, Staufen city, Germany) at 40 °C for around 8 h to obtain solid extraction. 2.3. GC-MS Analysis Condition Agilent 7890A was used to carry out GC-MS analysis. GC was equipped with a DB-5 (30 m × 0.25 mm × 0.25 μm) capillary column. Initially, the instrument was maintained at a temperature of 100 °C for 2.1 min. The temperature was rose to 300 °C at the rate of 25 °C/min and maintained for 20 min. Injection port temperature and helium flow rate were ensured as 250 °C and 1.5 mL/min, respectively. The ionization voltage was 70 eV. The samples injected in split mode at 10:1. The MS scan range was set at 35–900 (m/z). The fragmentation patterns of mass spectra were compared with those stored in the using W8N05ST Library MS database (analyzed 28 April 2021). The percentage of each compound was calculated from the relative peak area of each compound in the chromatogram. The concept of integration was used in the ChemStation integrator algorithms (analyzed 28 April 2021) [[50]20]. 2.4. Chemical Compounds Identification and Drug-Likeness Screening The chemical compounds from ZPFs were identified through GC-MS analysis. The compounds detected by GC-MS confirmed “drug-likeness” physicochemical property via Lipinski’s rule on SwissADME ([51]http://www.swissadme.ch/) (accessed on 14 May 2021). The filtered compounds converted into SMILES (simplified molecular input line entry system) (accessed on 14 May 2021) format through PubChem ([52]https://pubchem.ncbi.nlm.nih.gov/) (accessed on 14 May 2021). 2.5. Targets Associated with Compounds from ZPFs or Rheumatoid Arthritis Targets related to the compounds were identified via both Similarity Ensemble Approach (SEA) ([53]http://sea.bkslab.org/) (accessed on 16 May 2021) [[54]21] and SwissTargetPrediction (STP) ([55]http://www.swisstargetprediction.ch/) (accessed on 16 May 2021) [[56]22] with “Homo Sapiens” mode, both of which is founded on SMILES (accessed on 14 May 2021). The RA-associated targets on humans were retrieved with DisGeNET ([57]https://www.disgenet.org/) (accessed on 17 May 2021), OMIM ([58]https://www.omim.org/) (accessed on 17 May 2021) and literature. The overlapping targets between compounds of ZPFs and RA-associated targets indicated by VENNY 2.1 ([59]https://bioinfogp.cnb.csic.es/tools/venny/) (accessed on 18 May 2021). 2.6. PPI Networks and Bubble Chart STRING ([60]https://string-db.org/) (accessed on 19 May 2021) [[61]23] was utilized to analyze the PPI network with final overlapping targets. The RPackage was utilized to identify the degree of value. Then, signaling pathways associated with the occurrence and development of RA were visualized on a bubble chart by RPackage; two key signaling pathways with the highest and the lowest rich factor were selected to analyze the relationships against RA. 2.7. Construction of STC Networks The STC networks were utilized to construct a size plot based on the degree of values. In this size map, green rectangles (nodes) represented signaling pathways; gold triangles (nodes) stood for target proteins, and red circles (nodes) stood for compounds; its size represented degree value. The size of gold triangles represented the amount of connectivity with signaling pathways; the size of red circles represented the amount of connectivity with target proteins. The combined networks were constructed by using RPackage (analyzed 20 May 2021). 2.8. Preparation of Targets for MDT Firstly, two targets of MAPK signaling pathway, i.e., FGF2 (PDB ID: 1IIL), VEGFA (PDB ID: 3V2A), and one target of PPAR signaling pathway, i.e., PPARG (PDB ID: 3E00), were identified on STRING via RCSB PDB ([62]https://www.rcsb.org/) (accessed on 21 May 2021). The final three targets selected as .pdb format were converted into .pdbqt format via Autodock ([63]http://autodock.scripps.edu/) (accessed on 21 May 2021). 2.9. Preparation of Compounds from ZPFs for MDT The ligand molecules were converted .sdf from PubChem into .pdb format using Pymol (accessed on 21 May 2021), and the ligand molecules were converted into .pdbqt format through Autodock (accessed on 21 May 2021). 2.10. Preparation of Positive Standard Ligands for MDT The number of two positive ligands on FGF2 antagonists, i.e., NSC172285 (PubChem ID: 299405), NSC37204 (PubChem ID: 235612), and the number of one positive ligand on VEGFA antagonist, i.e., BAW2881 (PubChem ID: 16004702), the number of three positive ligands on PPARG antagonists, i.e., Pioglitazone (PubChem ID: 4829), Rosiglitazone (PubChem ID: 77999), Lobeglitazone (PubChem ID: 9826451) were selected to verify the docking score. 2.11. Ligand-Protein Docking The ligand molecules were docked with target proteins utilizing autodock4 by setting up four energy ranges and eight exhaustiveness as default to obtain 10 different poses of ligand molecules [[64]24]. The 2D binding interactions were used with LigPlot+ v.2.2 ([65]https://www.ebi.ac.uk/thornton-srv/software/LigPlus/) (accessed on 21 May 2021). After docking, ligands of the lowest binding energy (highest affinity) were selected to visualize the ligand–protein interaction in Pymol (Schrödinger, New York, NY, USA). 2.12. Toxicological Properties Prediction by AdmetSAR Toxicological properties of the key bioactive were established using the admetSAR web-service tool ([66]http://lmmd.ecust.edu.cn/admetsar1/predict/) (accessed on 23 May 2021) because toxicity is an essential factor to develop new drugs. Hence, Ames toxicity, carcinogenic properties, acute oral toxicity, and rat acute toxicity were predicted by admetSAR (East China University of Science and Technology, Shanghai, China). 3. Results 3.1. Chemical Compounds from ZPFs A total of 85 chemical compounds and its seven key chemical compounds in ZPFs were detected by the GC-MS analysis ([67]Figure 2), and the name of compounds, PubChem ID, retention time (mins), and peak area (%) were enlisted in [68]Table 1. Lipinski’s rules accepted all 85 compounds (molecular weight ≤500g/mol; Moriguchi octanol-water partition coefficient ≤4.15; number of nitrogen or oxygen ≤10; number of NH or OH ≤5), and all chemical compounds satisfied with the criteria of “Abbott Bioavailability Score (>0.1)” through SwissADME. The TPSA (topological polar surface area) value of chemical compounds was also accepted ([69]Table 2). Figure 2. [70]Figure 2 [71]Open in a new tab A typical GC-MS peak of ZPFs methanolic extract and the number of seven key compounds. Table 1. A list of 85 chemical compounds identified from ZPFs via GC-MS and profiling of bioactivities. No. Compounds Pubchem ID RT (mins) Area (%) Pharmacological Activities (Reference) 1 Myrcene 31253 3.462 1.49 Antibacterial, Antioxidant, Fungicide 2 3(5)-[[1,2-Dihydroxy-3-propoxy]methyl]-4-hydroxy-1H-pyrazole-5(3)-carbo xamide 135747301 3.683 0.09 No reported 3 β-Phellandrene 11142 3.866 4.28 Fungicide 4 Hex-3-yne 13568 3.971 0.10 No reported 5 3-Hydroxycyclohexanone 439950 4.087 0.06 No reported 6 Isopropyl hexanoate 16832 4.145 0.12 No reported 7 Terpinolene 11463 4.250, 4.318 0.59 Fungicide, Antioxidant 8 Vinylcyclooctane 93331 4.520 0.07 No reported 9 2-Tetradecynoic acid 324386 4.587 0.10 No reported 10 Citronellal 7794 4.721 2.75 Antibacterial, Fungicide 11 3-Hydroxy-2,3-dihydromaltol 119838 4.779 0.67 No reported 12 Pulegol 92793 4.856 0.29 No reported 13 Octanoic acid 379 4.923 0.24 Candidicide, Fungicide 14 (E)-4-Undecenal 5283357 4.981 0.10 No reported 15 4-Isopropyl-2-cyclohexenone 92780 5.087 1.04 No reported 16 Citronellol 8842 5.241 1.20 Antibacterial, Candidicide, Sedative 17 (E)-beta-Ocimene 5281553 5.366 0.39 Insecticide 18 3,7-Dimethylocta-2,6-dien-1-ol 4458 5.414 0.65 No reported 19 Spiro[4 .4]nona-1,3-diene, 1,2-dimethyl- 570800 5.452 0.21 No reported 20 Piperitone 6987 5.529 0.41 Antiasthmatic 21 Nonanoic acid 8158 5.606 0.42 Perfumery 22 8,8-Dimethoxy-2,6-dimethyloct-2-ene 102507 5.721 0.98 No reported 23 p-Isopropylbenzyl formate 105515 5.760 0.40 No reported 24 Citronellic acid 10402 5.895 0.55 No reported 25 α-Terpinene 7462 5.952 0.24 Antispasmodic 26 2,6-Octadiene, 2,6-dimethyl- 5365898 6.000 1.60 No reported 27 Terpinyl propionate 62328 6.048 0.43 No reported 28 Geranyl acetate 1549026 6.193 4.60 Sedative 29 3-Methylcyclohexene 11573 6.250 0.21 No reported 30 1,4-Dimethyl-4beta-methoxy-2,5-cyclohexadien-1α-ol 12561656 6.298 0.33 No reported 31 2-Propenoic acid, 3-phenyl-, methyl ester 7644 6.346 0.49 No reported 32 6-Methylenespiro[4.5]decane 564762 6.471 0.07 No reported 33 β-Caryophyllene 5281515 6.539 0.67 Antibacterial, Antiinflammation 34 Bergamotane 86000267 6.625 0.09 No reported 35 3-Methyl-4,7-dioxo-oct-2-enal 5363705 6.693 0.30 No reported 36 2,6-Dimethyl-3,5,7-octatriene-2-ol, Z,Z- 5363692 6.779 0.24 No reported 37 2-Dodecenoic acid 5282729 6.818 0.12 No reported 38 1,6,10-Dodecatrien-3-ol, 3,7,11-trimethyl- 8888 6.885 0.35 No reported 39 1-Methyldecahydronaphthalene 34193 6.943 0.46 No reported 40 Cadina-1(10),4-diene 10223 7.029 0.34 No reported 41 2-(4-Methylcyclohexyl)prop-2-en-1-ol 543946 7.135 0.42 No reported 42 Tetradec-13-enal 522841 7.250 0.24 No reported 43 9-Octadecenoic acid 965 7.308 0.15 Antiinflammation, Antileukotriene 44 1,2-Di-but-2-enyl-cyclohexane 5367574 7.375 0.10 No reported 45 4,12,12-trimethyl-9-methylene-5-oxatricyclo[8.2.0.04,6]dodecane 73555586 7.433 0.11 No reported 46 3,4-O-Isopropylidene-d-galactose 54504880 7.568 0.08 No reported 47 2-Hexenoic acid, 6-cyclohexyl- 5367614 7.616 0.22 No reported 48 Heptadec-8-ene 520230 7.693 0.35 No reported 49 Octane 356 7.779 0.35 No reported 50 Myristic acid 11005 7.827, 8.096 0.44 Anticancer, Antioxidant 51 D-(-)-Kinic Acid 1064 7.914 1.35 No reported 52 Nonadecanoic acid 12591 8.135 0.35 No reported 53 10-Bromoundecanoic acid 543401 8.337, 8.385 0.77 No reported 54 Stearic acid 5281 8.520 0.23 Hypocholesterolemic 55 Cysteamine S-sulfate 76242 8.587, 9.231, 9.298 1.27 No reported 56 Limonene dioxide 232703 8.635 0.23 No reported 57 2,6-Dimethyl-4-nitro-3-phenyl-cyclohexanone 562366 8.664 0.26 No reported 58 Methyl palmitate 8181 8.731 0.46 No reported 59 2,6-Dimethyl-1,3,6-heptatriene 5368331 8.846 0.68 No reported 60 Palmitic acid 985 8.962, 9.020 2.65 Antioxidant, Pesticide 61 Neral 643779 9.077 1.58 Antibacterial, Antispasmodic 62 2-Methyl-6-methylene-1,7-octadien-3-one 93231 9.125 0.75 No reported 63 Bis(3-benzyl-2,4-pentanedionato)palladium(II) 5363840 9.423 1.03 No reported 64 Pentamethylbenzenesulfonyl chloride 590180 9.491, 9.635 6.52 No reported 65 Myrtenal 61130 9.769 3.77 Antimalarial, Antiplasmodial 66 N,N-Dimethyl-2-phenylethen-1-amine 23277871 10.154, 10.183 20.61 No reported 67 Allyl(chloromethyl)dimethylsilane 556526 10.394 7.64 No reported 68 Cyclohexene, 4-(4-ethylcyclohexyl)-1-pentyl- 543386 10.596 1.64 No reported 69 3-Epicycloeucalenol 543796 10.654 1.09 No reported 70 2,5-Furandione, 3-dodecenyl- 5362708 10.750 0.61 No reported 71 1-cinnamyl-3-methylindole-2-carbaldehyde N/A 10.875 1.35 No reported 72 Glyceryl palmitate 14900 10.962 4.82 No reported 73 2-Methyl-Z,Z-3,13-octadecadienol 5364412 11.414 0.37 No reported 74 Pentadeca-2,3,6,9,12,13-hexaen-8-one, 2,5,5,11,11,14-hexamethyl- 5370200 11.519 0.51 No reported 75 CBMicro_013618 1109374 11.616 1.04 No reported 76 Monoolein 5283468 11.721 2.02 Antioxidant 77 Cyclohexene, 4-(4-ethylcyclohexyl)-1-pentyl- 543386 11.808, 12.596 1.56 No reported 78 Cedrane-8,13-diol 188457 12.654 0.12 No reported 79 26,27-Dinorergosta-5,23-dien-3β-ol 22213488 12.721 0.18 No reported 80 Cholest-4-en-3-one, 14-methyl- 277841 13.279 0.07 No reported 81 (+)-Sesamolin 585998 15.221 0.08 No reported 82 NSC402953 345349 15.308 0.32 No reported 83 Campesterol 173183 15.866 0.12 Antioxidant, Hypocholesterolemic 84 Stigmasta-5,22-dien-3-ol 53870683 16.144 0.06 Antimicrobial, Antioxidant, Antidiabetic 85 Clionasterol 457801 16.923 0.15 Anticancer, Antidaibetic, Antioxidant [72]Open in a new tab Table 2. Physicochemical properties of chemical compounds for good oral bioavailability and cell membrane permeability. No. Compounds Lipinski Rules Lipinski’s Violations Bioavailability Score TPSA(Ų) MW HBA HBD MLog P <500 <10 ≤5 ≤4.15 ≤1 > 0.1 <140 1 Myrcene 136.23 0 0 3.56 0 0.55 0.00 2 3(5)-[[1,2-Dihydroxy-3-propoxy]methyl]-4-hydroxy-1H-pyrazole-5(3)-carbo xamide 231.21 6 5 −2.70 0 0.55 141.69 3 β-Phellandrene 136.23 0 0 3.27 0 0.55 0.00 4 Hex-3-yne 82.14 0 0 3.37 0 0.55 0.00 5 3-Hydroxycyclohexanone 114.14 2 1 0.07 0 0.55 37.30 6 Isopropyl hexanoate 158.24 2 0 2.28 0 0.55 26.30 7 Terpinolene 136.23 0 0 3.27 0 0.55 0.00 8 Vinylcyclooctane 138.25 0 0 4.29 1 0.55 0.00 9 2-Tetradecynoic acid 224.34 2 1 3.58 0 0.85 37.30 10 Citronellal 154.25 1 0 2.59 0 0.55 17.07 11 3-Hydroxy-2,3-dihydromaltol 144.13 4 2 −1.77 0 0.85 66.76 12 Pulegol 154.25 1 1 2.30 0 0.55 20.23 13 Octanoic acid 144.21 2 1 1.96 0 0.85 37.30 14 (E)-4-Undecenal 168.28 1 0 2.88 0 0.55 17.07 15 4-Isopropyl-2-cyclohexenone 138.21 1 0 1.89 0 0.55 17.07 16 Citronellol 156.27 1 1 2.70 0 0.55 20.23 17 (E)--Ocimene 136.23 0 0 3.56 0 0.55 0.00 18 3,7-Dimethylocta-2,6-dien-1-ol 154.25 1 1 2.59 0 0.55 20.23 19 Spiro[4.4]nona-1,3-diene, 1,2-dimethyl- 148.24 0 0 3.56 0 0.55 0.00 20 Piperitone 152.23 1 0 2.20 0 0.55 17.07 21 Nonanoic acid 158.24 2 1 2.28 0 0.85 37.30 22 8,8-Dimethoxy-2,6-dimethyloct-2-ene 200.32 2 0 2.75 0 0.55 18.46 23 p-Isopropylbenzyl formate 178.23 2 0 2.58 0 0.55 26.30 24 Citronellic acid 170.25 2 1 2.47 0 0.85 37.30 25 alpha-Terpinene 136.23 0 0 3.27 0 0.55 0.00 26 2,6-Octadiene, 2,6-dimethyl- 138.25 0 0 3.66 0 0.55 0.00 27 Terpinyl propionate 210.31 2 0 2.92 0 0.55 26.30 28 Geranyl acetate 196.29 2 0 2.95 0 0.55 26.30 29 3-Methylcyclohexene 96.17 0 0 3.33 0 0.55 0.00 30 1,4-Dimethyl-4β-methoxy-2,5-cyclohexadien-1α-ol 154.21 2 1 0.97 0 0.55 29.46 31 2-Propenoic acid, 3-phenyl-, methyl ester 162.19 2 0 2.20 0 0.55 26.30 32 6-Methylenespiro[4.5]decane 150.26 0 0 4.58 1 0.55 0.00 33 beta-Caryophyllene 204.35 0 0 4.63 1 0.55 0.00 34 Bergamotane 208.38 0 0 5.80 1 0.55 0.00 35 3-Methyl-4,7-dioxo-oct-2-enal 168.19 3 0 0.29 0 0.55 51.21 36 2,6-Dimethyl-3,5,7-octatriene-2-ol, Z,Z- 152.23 1 1 2.49 0 0.55 20.23 37 2-Dodecenoic acid 198.30 2 1 3.04 0 0.85 37.30 38 1,6,10-Dodecatrien-3-ol, 3,7,11-trimethyl- 222.37 1 1 3.86 0 0.55 20.23 39 1-Methyldecahydronaphthalene 152.28 0 0 4.72 1 0.55 0.00 40 Cadina-1(10),4-diene 204.35 1 0 4.63 1 0.55 0.00 41 2-(4-Methylcyclohexyl)prop-2-en-1-ol 154.25 1 1 2.30 0 0.55 20.23 42 Tetradec-13-enal 210.36 1 0 3.70 0 0.55 17.07 43 9-Octadecenoic acid 282.46 2 1 4.57 1 0.85 37.30 44 1,2-Di-but-2-enyl-cyclohexane 192.34 0 0 4.37 1 0.55 0.00 45 4,12,12-trimethyl-9-methylene-5-oxatricyclo[8.2.0.04,6]dodecane 220.35 1 0 3.67 0 0.55 12.53 46 3,4-O-Isopropylidene-d-galactose 220.22 6 3 −1.34 0 0.55 88.38 47 2-Hexenoic acid, 6-cyclohexyl- 196.29 2 1 2.65 0 0.85 37.30 48 Heptadec-8-ene 238.45 0 0 6.54 1 0.55 0.00 49 Octane 114.23 0 0 4.20 1 0.55 0.00 50 Myristic acid 228.37 2 1 3.69 0 0.85 37.30 51 D-(-)-Kinic Acid 192.17 6 5 −2.14 0 0.55 118.22 52 Nonadecanoic acid 298.50 2 1 4.91 1 0.85 37.30 53 10-Bromoundecanoic acid 265.19 2 1 3.29 0 0.85 37.30 54 Stearic acid 284.48 2 1 4.67 1 0.85 37.30 55 Cysteamine S-sulfate 157.21 4 2 −1.51 0 0.55 114.07 56 Limonene dioxide 168.23 2 0 1.52 0 0.55 25.06 57 2,6-Dimethyl-4-nitro-3-phenyl-cyclohexanone 247.29 3 0 1.66 0 0.55 62.89 58 Methyl palmitate 270.45 2 0 4.44 1 0.55 26.30 59 2,6-Dimethyl-1,3,6-heptatriene 122.21 0 0 3.26 0 0.55 0.00 60 Palmitic acid 256.42 2 1 4.19 1 0.85 37.30 61 Neral 152.23 1 0 2.49 0 0.55 17.07 62 2-Methyl-6-methylene-1,7-octadien-3-one 150.22 1 0 2.40 0 0.55 17.07 63 Bis(3-benzyl-2,4-pentanedionato)palladium(II) 486.90 4 2 2.69 0 0.85 74.60 64 Pentamethylbenzenesulfonyl chloride 246.75 2 0 3.04 0 0.55 42.52 65 Myrtenal 150.22 1 0 2.20 0 0.55 17.07 66 N,N-Dimethyl-2-phenylethen-1-amine 147.22 0 0 2.40 0 0.55 3.24 67 Allyl(chloromethyl)dimethylsilane 148.71 0 0 2.81 0 0.55 0.00 68 Cyclohexene, 4-(4-ethylcyclohexyl)-1-pentyl- 262.47 0 0 6.61 1 0.55 0.00 69 3-Epicycloeucalenol 426.72 1 1 6.92 1 0.55 20.23 70 2,5-Furandione, 3-dodecenyl- 266.38 3 0 3.53 0 0.55 43.37 71 1-cinnamyl-3-methylindole-2-carbaldehyde 275.34 1 0 3.20 0 0.55 22.00 72 Glyceryl palmitate 330.50 4 2 3.18 0 0.55 66.76 73 2-Methyl-Z,Z-3,13-octadecadienol 280.49 1 1 4.91 1 0.55 20.23 74 Pentadeca-2,3,6,9,12,13-hexaen-8-one, 2,5,5,11,11,14-hexamethyl- 298.46 1 0 4.93 1 0.55 17.07 75 CBMicro_013618 354.40 5 0 1.66 0 0.55 57.90 76 Monoolein 356.54 4 2 3.52 0 0.55 66.76 77 Cyclohexene, 4-(4-ethylcyclohexyl)-1-pentyl- 262.47 0 0 6.61 1 0.55 0.00 78 Cedrane-8,13-diol 238.37 2 2 2.88 0 0.55 40.46 79 26,27-Dinorergosta-5,23-dien-3β-ol 370.61 1 1 6.03 1 0.55 20.23 80 Cholest-4-en-3-one, 14-methyl- 398.66 1 0 6.43 1 0.55 17.07 81 (+)-Sesamolin 370.35 7 0 1.85 0 0.55 64.61 82 NSC402953 386.35 8 0 1.74 0 0.55 73.84 83 Campesterol 400.68 1 1 6.54 1 0.55 20.23 84 Stigmasta-5,22-dien-3-ol 412.69 1 1 6.62 1 0.55 20.23 85 Clionasterol 414.71 1 1 6.73 1 0.55 20.23 [73]Open in a new tab 3.2. Overlapping Targets between SEA and STP Related to Chemical Compounds A total of 470 targets from Similarity Ensemble Approach (SEA) and 629 targets from SwissTargetPrediction (STP) were associated with 85 chemical compounds ([74]Supplementary Table S1). The Venn diagram showed that 215 targets overlapped between the two public databases ([75]Supplementary Table S1) ([76]Figure 3A). Figure 3. [77]Figure 3 [78]Open in a new tab (A) The number of 215 overlapping targets between SEA (470 targets) and STP (629 targets). (B) The number of 101 final overlapping targets between 215 overlapping targets from two databases (SEA and STP) and RA associated with targets (3377 targets). 3.3. Overlapping Targets between RA-Related Genes and the Final 101 Overlapping Targets A total of 3377 targets associated with RA were selected by retrieving from DisGeNET, Online Mendelian Inheritance in Man (OMIM) databases and literature ([79]Supplementary Table S2). Venn diagram’s result displayed 101 overlapping targets that were selected between 3377 targets related to RA and the 215 overlapping targets ([80]Figure 3B) ([81]Supplementary Table S3). 3.4. Acquisition of a Key Target from PPI Networks From STRING analysis, 99 out of 101 overlapping targets were directly associated with RA occurrence and development, indicating 99 nodes and 469 edges ([82]Figure 4). The two removed targets (CA1 and CA3) had no connectivity to the overlapping 101 targets. In PPI networks, Vascular Endothelial Growth Factor A (VEGFA) was the highest degree (42) and is considered a key target ([83]Table 3). Figure 4. [84]Figure 4 [85]Open in a new tab PPI networks (99 nodes, 469 edges). The size of the circle: degree of values. Table 3. The degree value of target in PPI. No. Target Degree of Value No. Target Degree of Value 1 VEGFA 42 51 ENPP2 9 2 MMP9 28 52 PPARA 8 3 TLR4 23 53 PLA2G2A 8 4 IL2 23 54 NLRP3 8 5 FGF2 23 55 MAOA 8 6 PPARG 22 56 F3 8 7 ESR1 21 57 EDNRA 8 8 PTPRC 19 58 AKR1B1 8 9 AR 19 59 SHBG 7 10 CXCR3 18 60 PTPN6 7 11 MMP2 17 61 PRKCA 7 12 CNR1 17 62 DHFR 7 13 LPAR3 16 63 TYR 6 14 ABCG2 16 64 NR1I3 6 15 NR3C1 15 65 MAOB 6 16 LPAR2 15 66 HMGCR 6 17 LPAR1 15 67 HDAC6 6 18 HDAC1 15 68 ESR2 6 19 ABCB1 14 69 RORC 5 20 S1PR1 14 70 HSD11B1 5 21 CYP2C19 14 71 GSR 5 22 CYP1A2 14 72 FGF1 5 23 CYP19A1 14 73 BCHE 5 24 ALOX5 14 74 RARB 4 25 ABCB1 14 75 HSD11B2 4 26 PLA2G1B 13 76 GRK6 4 27 TNFRSF1A 12 77 GPR35 4 28 PLA2G4A 12 78 GPBAR1 4 29 GABBR2 12 79 DHCR7 4 30 GABBR1 12 80 PTGER2 3 31 CNR2 12 81 PPARD 3 32 PTGES 11 82 PDE4B 3 33 PTGER4 11 83 IL6ST 3 34 NOS2 11 84 HEXB 3 35 MTNR1B 11 85 CES2 3 36 LTB4R 11 86 AKR1B10 3 37 GLI1 11 87 TTR 2 38 EDNRB 11 88 RORA 2 39 TLR9 10 89 KCNA3 2 40 S1PR3 10 90 FABP3 2 41 MMP1 10 91 CTRB1 2 42 HDAC3 10 92 CPA1 2 43 G6PD 10 93 CA2 2 44 CYP17A1 10 94 ASAH1 2 45 ALOX12 10 95 ACP1 2 46 ALDH1A1 10 96 PDE4D 1 47 VDR 9 97 PAM 1 48 TRPV1 9 98 HEXA 1 49 SLC6A4 9 99 GSTK1 1 50 SHH 9 [86]Open in a new tab 3.5. Identification of Two Key Signaling Pathways from a Bubble Chart The results of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis unveiled that 19 signaling pathways were connected with 40 out of 101 targets (false discovery rate <0.05). The 19 signaling pathways were directly related to RA, indicating that these 19 signaling pathways might be significant pathways of ZPFs against RA. The description of 19 signaling pathways were shown in [87]Table 4. Additionally, a bubble chart indicated that inactivation of MAPK signaling pathway and activation of PPAR signaling pathway might be key signaling pathways of ZPFs to alleviate RA ([88]Figure 5). Specifically, MAPK signaling pathway is associated with VEGFA (a hub target) in holistic PPI networks while PPAR signaling pathway is not related to VEGFA. Table 4. Targets in 19 signaling pathways associated with RA. KEGG ID & Description Target Genes False Discovery Rate hsa04933:AGE-RAGE signaling pathway in diabetic complications PRKCA,MMP2,VEGFA,F3 0.01010 hsa04926:Relaxin signaling pathway PRKCA,VEGFA,EDNRB,MMP1,MMP2,MMP9, NOS2 0.00018 hsa04919:Thyroid hormone signaling pathway PRKCA,ESR1,HDAC1,HDAC3 0.01460 hsa04917:Prolactin signaling pathway ESR1,ESR2,CYP17A1 0.02200 hsa04915:Estrogen signaling pathway GABBR1,GABBR2,MMP2,MMP9,ESR1,ESR2 0.00110 hsa04912:GnRH signaling pathway PRKCA,MMP2,PLA2G4A 0.03510 hsa04660:T cell receptor signaling pathway IL2,PTPRC,PTPN6 0.03950 hsa04644:Fc epsilon RI signaling pathway PRKCA,ALOX5,PLA2G4A 0.02070 hsa04370:VEGF signaling pathway VEGFA,PRKCA,PLA2G4A 0.01690 hsa04151:PI3K-Akt signaling pathway PRKCA,VEGFA,IL2,TLR4,FGF1,FGF2,LPAR1,LPAR2,LPAR3 0.00110 hsa04072:Phospholipase D signaling pathway PRKCA,MMP2,LPAR1,LPAR2,LPAR3 0.00660 hsa04071:Sphingolipid signaling pathway PRKCA,S1PR1,S1PR3,ASAH1,TNFRSF1A 0.00340 hsa04066:HIF-1 signaling pathway PRKCA,VEGFA,TLR4,NOS2 0.01010 hsa04024:cAMP signaling pathway PPARA,EDNRA,PDE4B,PDE4D,GABBR1,GABBR2,PTGER2,GLI1 0.00023 hsa04020:Calcium signaling pathway PRKCA,NOS2,EDNRB,EDNRA 0.03850 hsa04015:Rap1 signaling pathway PRKCA,VEGFA,FGF1,FGF2,CNR1,LPAR1,LPAR2,LPAR3 0.00025 hsa04014:Ras signaling pathway PRKCA,VEGFA,FGF1,FGF2,PLA2G2A,PLA2G1B 0.00200 hsa04010:MAPK signaling pathway PRKCA,VEGFA,FGF1,FGF2,TNFRSF1A,PLA2G4A 0.01810 hsa03320:PPAR signaling pathway PPARA,PPARD,PPARG,FABP3,MMP1 0.00070 [89]Open in a new tab Figure 5. [90]Figure 5 [91]Open in a new tab Bubble chart of 19 signaling pathways associated with cancer. 3.6. Construction of Signaling Pathway-Target-Compound Network The signaling pathway–target–compound (STC) network is displayed in [92]Figure 6. There were 19 pathways, 40 targets, and 63 compounds (122 nodes, 488 edges). The nodes stood for the total number of relationships between signaling pathways, targets, and compounds. The edges represented the relationship of three elements (19 pathways, 40 targets, and 63 compounds). The STC network suggested that the uppermost target is Protein Kinase C Alpha (PRKCA) with 14 degrees among 19 signaling pathways ([93]Table 5). Figure 6. [94]Figure 6 [95]Open in a new tab STC networks (122 nodes, 488 edges). Green rectangle: signaling pathway; gold triangle: targets; red circle: compounds. Table 5. The degree value of target in STC. No. Target Degree of Value No. Target Degree of Value 1 PRKCA 14 21 TLR4 2 2 VEGFA 8 22 IL2 2 3 MMP2 5 23 PPARD 1 4 PLA2G4A 4 24 PPARG 1 5 FGF2 4 25 FABP3 1 6 FGF1 4 26 ALOX5 1 7 NOS2 3 27 CYP17A1 1 8 ESR1 3 28 S1PR1 1 9 LPAR1 3 29 S1PR3 1 10 LPAR2 3 30 ASAH1 1 11 LPAR3 3 31 GLI1 1 12 PPARA 2 32 PTGER2 1 13 MMP1 2 33 F3 1 14 EDNRB 2 34 CNR1 1 15 MMP9 2 35 HDAC1 1 16 GABBR2 2 36 HDAC3 1 17 GABBR1 2 37 PLA2G2A 1 18 ESR2 2 38 PLA2G1B 1 19 TNFRSF1A 2 39 PTPRC 1 20 EDNRA 2 40 PTPN6 1 [96]Open in a new tab 3.7. KEGG Pathway Enrichment Analysis KEGG pathway enrichment analysis [[97]25] reveals that 19 signaling pathways are associated with the occurrence and development of RA. Out of 19 signaling pathways, MAPK signaling pathway and PPAR signaling pathway were most significantly related to RA ([98]Figure 7). The red rectangles indicated core targets on the two signaling pathways. One of the MAPK signaling pathways, PRKCA (a species of PKC), is an excellent immunomodulatory target, which is linked to the onset of inflammatory arthritis, including RA [[99]26]. It was subsequently shown that inactivation of PRKCA results in the inhibition of c-fos; eventually, the cascade leads to the amelioration of RA in an animal model [[100]27]. One of the PPAR signaling pathways, FABP3, is located in the upstream region to regulate lipid metabolism. It was reported that defective lipid metabolism was observed in RA patients who are persistent to proinflammatory responses [[101]28]. Figure 7. [102]Figure 7 [103]Open in a new tab KEGG pathway enrichment map. (A) MAPK signaling pathway. (B) PPAR signaling pathway. Red rectangles represent key targets: (1) FGF1, FGF2, VEGFA; (2) TNFRSF1A; (3) PRKCA; (4) PLA2G4A; (5) PPARA; (6) PPARD; (7) PPARG; (8) MMP1; (9) FABP3. 3.8. MDT of 6 Targets and 23 Chemical Compounds Associated with MAPK Signaling Pathway From both SEA and STP databases, it was uncovered that FGF1 is associated with two chemical compounds, FGF2 with four chemical compounds, VEGFA with five chemical compounds, TNFRSF1A with two chemical compounds, PRKCA with 16 chemical compounds, and PLA2G4A with four chemical compounds. Out of 33 chemical compounds, 10 chemical compounds overlapped, and finally, 23 chemical compounds were identified on the MAPK signaling pathway. The MDT performed to evaluate affinity between target and ligand displayed the greatest affinity complex, depicted in [104]Figure 8. In detail, campesterol (−8.4 kcal/mol) docked on the FGF1 target (PDB ID: 3OJ2) had the greatest affinity; however, it had a lower affinity than suramin sodium (−19.1 kcal) as a positive control. The 26,27-Dinorergosta-5,23-dien-3β-ol (−8.0 kcal/mol) docked on FGF2 target (PDB ID: 1IIL) had the highest affinity; its affinity was lower than NSC172285 (−14.7 kcal/mol) as a positive control. The 3,4-O-Isopropylidene-d-galactose (−5.3 kcal/mol) docked on VEGFA (PDB ID: 3V2A) had the highest affinity; however, the affinity score was invalid (> −6.0 kcal/mol) [[105]29]. The CBMicro_013618 docked on TNFRSF1A (PDB ID: INCF) had the greatest affinity. Moreover, its score was better than Enamin_004209 (−5.3 kcal/mol) as a positive control. The berberine (−6.6 kcal/mol) as a positive control had a higher affinity than the stearic acid (−4.5 kcal/mol) docked on PLA2G4A (PDB ID: 1BCI). The monoolein (−6.7 kcal/mol) had the greatest affinity on PRKCA (PDB ID: 3IW4). Furthermore, its affinity score was greater than sphingosine (−5.5 kcal/mol) as a positive control. The detailed docking information is listed in [106]Table 6. Figure 8. [107]Figure 8 [108]Figure 8 [109]Figure 8 [110]Open in a new tab (A) MDT of campesterol (PubChem ID: 173183) on FGF1 (PDB ID: 3OJ2). (B) MDT of 26,27-Dinorergosta-5,23-dien-3β-ol (PubChem ID: 22213488) on FGF2 (PDB ID: 1IIL). (C) MDT of CBMicro_013618 (PubChem ID: 1109374) on TNFRSF1A (PDB ID: 1NCF). (D) MDT of monoolein (PubChem ID: 5283468) on PRKCA (PDB ID: 1NCF). Table 6. Binding energy of ligands and positive controls on MAPK signaling pathway. Grid Box Hydrogen Bond Interactions Hydrophobic Interactions Protein Ligand PubChem ID Binding Energy (kcal/mol) Center Dimension Amino Acid Residue Amino Acid Residue FGF1 (PDB ID:3OJ2) ^(★) Campesterol 173183 −8.4 x 9.051 x 40 Asp283, Ser252 Arg251,Phe172, Ile257 y 22.527 y 40 Ser220, Leu258, Ile204 z −0.061 z 40 Ala260, Gln259, Tyr281 3,4-O-Isopropylidene-d-galactose 54504880 −6.1 x 9.051 x 40 Arg255, Thr174, Phe172 Asn350, Asn173, Ala349 y 22.527 y 40 Asn107, Gln348 z −0.061 z 40 Positive control ^(a) Suramin sodium 8514 −19.1 x 9.051 x 40 Ser282, Lys27 Arg203, Ile204, Ala260 y 22.527 y 40 Gln259, Leu258, Tyr281 z −0.061 z 40 Asn22, Tyr23, Asp283 Val249, Pro149, Glu250 His254, Ser252, Ile257 Phe172, Val222, Ser220 FGF2 (PDB ID:1IIL) ^(★) 26,27-Dinorergosta-5,23-dien-3β-ol 22213488 −8.0 x 26.785 x 40 Thr139, Ser137 Glu323, Ser122, Trp123 y 14.360 y 40 Lys313, Leu312, Ile329 z −1.182 z 40 Leu327, Tyr328 Campesterol 173183 −7.9 x 26.785 x 40 Ser137 Thr139, Glu323, Lys313 y 14.360 y 40 Asp336, Tyr328, Ile329 z −1.182 z 40 Leu312, Leu327, Ser122 Trp123, Thr319 Stigmasta-5,22-dien-3-ol 53870683 −7.8 x 26.785 x 40 Tyr340, Asp336 Ile329, Leu312, Ser122 y 14.360 y 40 Trp123, Ser137, Thr319 z −1.182 z 40 Glu323, Asn318, Lys313 Leu327 3,4-O-Isopropylidene-d-galactose 54504880 −5.6 x 26.785 x 40 Glu323, Trp123, Ser137 Ser122 y 14.360 y 40 Thr139, Lys313 z −1.182 z 40 Positive control ^(b) NSC172285 299405 −14.7 x 26.785 x 40 Tyr207 Val209, Asp99, Lys119 y 14.360 y 40 Lys199, Gln200, Glu201 z −1.182 z 40 ^(b) NSC37204 235612 −9.5 x 26.785 x 40 Thr358, Arg210, Thr121 Val209, Asn265, Lys119 y 14.360 y 40 Arg118, Glu201 Asp99, Gln200, Trp356 z −1.182 z 40 VEGFA (PDB ID: 3V2A) ^(★) 3,4-O-Isopropylidene-d-galactose 54504880 −5.3 x 38.009 x 40 Gly312, Ser310 Gly255, Glu44, Ser311 y −10.962 y 40 Ile256, Asp257, Lys84 z 12.171 z 40 Pro85 Glyceryl palmitate 14900 −5.2 x 38.009 x 40 Pro40, Asp276 Arg275, Phe36, Lys286 y −10.962 y 40 Lys48, Asn253, Ile46 z 12.171 z 40 Monoolein 5283468 −5.1 x 38.009 x 40 Asp276, Pro40 Arg275, Asp34, Asn253 y −10.962 y 40 Lys48, Phe47, Ile46 z 12.171 z 40 Phe36, Lys286 Methyl palmitate 8181 −4.0 x 38.009 x 40 n/a Pro40, Arg275, Phe36 y −10.962 y 40 Ile46, Asn253, Lys286 z 12.171 z 40 Asp276 Isopropyl hexanoate 16832 −3.9 x 38.009 x 40 n/a Pro85, Ser310, Gly312 y −10.962 y 40 Glu44, Ser311, Gly255 z 12.171 z 40 Gln87, Lys84, Asp257 Positive control ^(c) BAW2881 16004702 −7.6 x 38.009 x 40 n/a Lys286, Asp34, Ser50 y −10.962 y 40 Asp276, Pro40, Phe36 z 12.171 z 40 Ile46 TNFRSF1A (PDB ID: 1NCF) ^(★) CBMicro_013618 1109374 −6.8 x 21.259 x 40 Lys132, Gln133 Glu109, Tyr106, Gln130 y 14.648 y 40 Gln133 z 34.77 z 40 2-Propenoic acid, 3-phenyl-, methyl ester 7644 −5.0 x 21.259 x 40 Lys35 Ala62, Glu64, His34 y 14.648 y 40 Lys35, Glu64 z 34.77 z 40 Positive control ^(d) Enamine_004209 2340496 −5.3 x 21.259 x 40 Glu109, Cys96, Tyr106 Asn110, Ph112, Val95 y 14.648 y 40 Gln82, Ser74, Thr94 z 34.77 z 40 Arg77, Arg132 PLA2G4A (PDB ID: 1BCI) ^(★) Stearic acid 5281 −4.5 x −0.058 x 40 Gly33, Lys32 Pro42, Val30, Ile67 y 0.077 y 40 Val127, Thr31, Gln126 z 0.285 z 40 Methyl palmitate 8181 −3.9 x −0.058 x 40 Lys58 Phe77, Pro54, Thr53 y 0.077 y 40 Leu79, Tyr16, Glu76 z 0.285 z 40 Ile78 Palmitic acid 985 −3.8 x −0.058 x 40 Thr53 Leu79, Phe77, Ile78 y 0.077 y 40 Tyr16, Glu76, Pro54 z 0.285 z 40 Myristic acid 11005 −3.3 x −0.058 x 40 n/a Asp55, Pro54, Tyr16 y 0.077 y 40 Phe77, Ile78, Thr53 z 0.285 z 40 Positive control ^(e) Berberine 2353 −6.6 x −0.058 x 40 n/a Arg59, Asp99, Asn95 y 0.077 y 40 His62, Phe63, Asn64 z 0.285 z 40 Arg61, Ala94, Tyr45 PRKCA (PDB ID: 3IW4) ^(★) Monoolein 5283468 −6.7 x −14.059 x 40 Asn660, Leu393, Asp395 Pro398, Lys478, Glu418 y 38.224 y 40 Lys396 Pro666, Tyr419, Arg608 z 32.319 z 40 Val664, Gln402 Glyceryl palmitate 14900 −6.6 x −14.059 x 40 Asp395, Lys396, Leu393 Leu394, Gln402, Lys478 y 38.224 y 40 Asn660 Arg608, Pro666, Ile667 z 32.319 z 40 Val664, Pro398, Pro397 Stearic acid 5281 −6.3 x −14.059 x 40 Lys396, Leu393 Pro397, Pro398, Lys478 y 38.224 y 40 Arg608, Ile667, Pro666 z 32.319 z 40 His665, Val664, Gln402 Asn660, Leu394 Nonadecanoic acid 12591 −6.2 x −14.059 x 40 Leu393, Lys396 Asn660, Pro397, Pro398 y 38.224 y 40 Lys478, Pro666, Arg608 z 32.319 z 40 Glu418, Val664, Gln402 Leu394 1,6,10-Dodecatrien-3-ol, 3,7,11-trimethyl- 8888 −6.2 x −14.059 x 40 Lys372, Gln408, Gln650 Val410, Thr409, Gly540 y 38.224 y 40 Ile645, Asp539, Asp503 z 32.319 z 40 Phe538, Glu543 2,5-Furandione, 3-dodecenyl- 5362708 −6.1 x −14.059 x 40 Lys396, Asp395 Asn660, Gln402, Pro397 y 38.224 y 40 Pro398, Glu552, Gln662 z 32.319 z 40 Val664, Leu394 2,6-Dimethyl-3,5,7-octatriene-2-ol, Z,Z- 5363692 −5.3 x −14.059 x 40 Gly540 Val410, Ile645, Asp503 y 38.224 y 40 Pro502, Glu543, Gln650 z 32.319 z 40 Leu546, Asp542 2-Dodecenoic acid 5282729 −5.1 x −14.059 x 40 Lys396, Asn660, Leu393 Leu394, Gln662, Glu552 y 38.224 y 40 Val664, Gln402 z 32.319 z 40 9-Octadecenoic acid 965 −5.0 x −14.059 x 40 Leu393, Lys396 Asn660, Glu552, Gln548 y 38.224 y 40 His553, Ser549, Gln662 z 32.319 z 40 Val664, Gln402, Leu394 Octanoic acid 379 −5.0 x −14.059 x 40 Asn660, Lys396, Gln402 Pro397, Lys478, Pro398 y 38.224 y 40 Val664, Glu552, Arg608 z 32.319 z 40 Methyl palmitate 8181 −5.0 x −14.059 x 40 n/a Gln377, Asn647, Asp373 y 38.224 y 40 Ile648, Asp649, Asn468 z 32.319 z 40 Lys465, Phe350, Asp467 Ile376 Palmitic acid 985 −5.0 x −14.059 x 40 Leu393, Asp395, Lys396 Pro397, Pro398, Val664 y 38.224 y 40 Glu552, His553, Ser549 z 32.319 z 40 Gln548,Gln662, Gln402 Leu394, Asn660 (E)-4-Undecenal 5283357 −4.8 x −14.059 x 40 n/a Gln642, Pro536, Ile645 y 38.224 y 40 Gly540, Val410, Gln650 z 32.319 z 40 Glu543, Asp542, Asp503 Leu546 Myristic acid 11005 −4.8 x −14.059 x 40 Lys396, Gln402 Asp395, Leu393, Leu394 y 38.224 y 40 Pro398, Val664, Gln662 z 32.319 z 40 Asn660 Nonanoic acid 8158 −4.7 x −14.059 x 40 Leu393, Lys396 Leu394, Asn660, Pro397 y 38.224 y 40 Gln402, Gln662, Val664 z 32.319 z 40 Heptadec-8-ene 520230 −4.6 x −14.059 x 40 n/a Asn647, Asp424, Met426 y 38.224 y 40 Gln377,Ile376, Phe350 z 32.319 z 40 Asp467, Asp373 Positive control ^(f) Sphingosine 5280335 −5.5 x −14.059 x 40 Asn660, Gln662, Lys396 Pro397, Gln402, Val664 y 38.224 y 40 Gln548, Glu552, His553 z 32.319 z 40 Leu394, Ser549, Asp395 [111]Open in a new tab ^(★) Compound with the greatest affinity on each target; ^(a) FGF1 antagonist; ^(b) FGF2 antagonist; ^(c) VEGFA antagonist; ^(d) TNFRSF1A antagonist; ^(e) PLA2G4A antagonist; ^(f) PRKCA antagonist. 3.9. MDT of 5 Targets and 43 Chemical Compounds Associated with PPAR Signaling Pathway From both SEA and STP databases, it was revealed that Peroxisome Proliferator-Activated Receptor Alpha (PPARA) is related to 32 chemical compounds, Peroxisome Proliferator-Activated Receptor Delta (PPARD) to 18 chemical compounds, Peroxisome Proliferator-Activated Receptor Gamma (PPARG) to 17 chemical compounds, FABP3 to 26 chemical compounds, and MMP to five chemical compounds. The MDT performed to obtain affinity between targets and ligands exhibited the highest affinity complex, as displayed in [112]Figure 9. Noticeably, β-Caryophyllene (−8.6 kcal/mol) docked on PPARA (PDB ID: 3SP6) had the greatest affinity, which had a higher score than Clofibrate (−6.4 kcal/mol), Gemfibrozil (−6.3 kcal/mol), Ciprofibrate (−5.4 kcal/mol), Bezafibrate (−5.8 kcal/mol), and Fenofibrate (−5.4 kcal/mol) as five positive controls. Stigmasta-5,22-dien-3-ol (−8.6 kcal/mol) docked on PPARD (PDB ID: 5U3Q) had the greatest affinity, which had a better score than Cardarine (−8.5 kcal/mol) as a positive control. NSC402953 (−8.2 kcal/mol) docked on PPARG (PDB ID: 3E00) had the highest affinity, which had better than Pioglitazone (−7.7 kcal/mol), Rosiglitazone (−7.4 kcal/mol), and Lobeglitazone (−7.3 kcal/mol) as three positive controls. Monoolein (−8.9 kcal/mol) docked on FABP3 (PDB ID: 5HZ9) had the greatest affinity; specifically, there was no positive control on FABP3 (PDB ID: 5HZ9). 2-Propenoic acid, 3-phenyl-, methyl ester (−5.0 kcal/mol) docked on MMP1 (PDB ID: 1SU3) had the highest affinity, which had lower affinity than Batimastat (−6.7 kcal/mol), and Ilomastat (−6.5 kcal/mol) as two positive controls. The detailed docking information is listed in [113]Table 7. Figure 9. [114]Figure 9 [115]Figure 9 [116]Open in a new tab (A) MDT of β-Caryophyllene (PubChem ID: 5281515) on PPARA (PDB ID: 3SP6). (B) MDT of Stigmasta-5,22-dien-3-ol (PubChem ID: 53870683) on PPARD (PDB ID: 5U3Q). (C) MDT of NSC402953 (PubChem ID:345349) on PPARG (PDB ID: 3E00). (D) MDT of monoolein (PubChem ID: 5283468) on FABP3 (PDB ID: 5HZ9). Table 7. Binding energy of ligands and positive controls on PPAR signaling pathway. Grid Box Hydrogen Bond Interactions Hydrophobic Interactions Protein Ligand PubChem ID Binding Energy(kcal/mol) Center Dimension Amino Acid Residue Amino Acid Residue PPARA (PDB ID: 3SP6) ^(★) β-Caryophyllene 5281515 −8.6 x 8.006 x 40 n/a Leu321, Leu331, Gly335 y −0.459 y 40 Val324, Met220, Tyr334 z 23.392 z 40 Ala333, Thr279, Asn219 Thr283 Cadina-1(10),4-diene 10223 −7.4 x 8.006 x 40 n/a Met220, Leu331, Val324 y −0.459 y 40 Thr279, Thr283, Leu321 z 23.392 z 40 Ile317, Met320 26,27-Dinorergosta-5,23-dien-3beta-ol 22213488 −7.0 x 8.006 x 40 Lys345 Glu356, Asp353, Pro357 y −0.459 y 40 Leu443, His440, Glu439 z 23.392 z 40 Leu436, Lys358, Asp360 Clionasterol 457801 −6.7 x 8.006 x 40 Lys345 Asp360, Pro357, Glu439 y −0.459 y 40 His440, Leu443, Asp353 z 23.392 z 40 Glu356 Cyclohexene, 4-(4-ethylcyclohexyl)-1-pentyl- 543386 −6.6 x 8.006 x 40 n/a Met320, Phe218, Met220 y −0.459 y 40 Thr279, Val332, Ala333 z 23.392 z 40 Tyr334, Thr283, Asn219 Spiro[4.4]nona-1,3-diene, 1,2-dimethyl- 570800 −6.5 x 8.006 x 40 n/a Leu321, Leu331, Val324 y −0.459 y 40 Met320, Asn219, Thr283 z 23.392 z 40 Thr279, Met220 1-Methyldecahydronaphthalene 34193 −6.4 x 8.006 x 40 n/a Met320, Val324, Met220 y −0.459 y 40 Asn219, Thr279, Thr283 z 23.392 z 40 Leu321 1,3,4,5-Tetrahydroxycyclohexanecarboxylic acid 1064 −6.3 x 8.006 x 40 Ile317, Glu286, Asn219 Met320, Met220, Leu321 y −0.459 y 40 Thr283 z 23.392 z 40 Stigmasta-5,22-dien-3-ol 53870683 −6.3 x 8.006 x 40 n/a Arg465, Glu462, Ser688 y −0.459 y 40 Val306, Asn303, Thr307 z 23.392 z 40 Tyr311, Gly390, Pro389 Lys310, Asp466 Terpinolene 11463 −6.2 x 8.006 x 40 n/a Thr279, Tyr334, Val324 y −0.459 y 40 Met220, Met320, Leu321 z 23.392 z 40 Thr283, Asn219 β-Phellandrene 11142 −6.0 x 8.006 x 40 n/a Leu331, Val324, Leu321 y −0.459 y 40 Ile317, Thr283, Met320 z 23.392 z 40 Thr279 Citronellic acid 10402 −5.9 x 8.006 x 40 Thr283, Glu286, Met220 Met320, Asn219, Tyr334 y −0.459 y 40 Gly335, Leu321, Val324 z 23.392 z 40 Ile317 Stearic acid 5281 −5.7 x 8.006 x 40 n/a Phe361, Asp432, Leu436 y −0.459 y 40 Glu439, His440, Leu443 z 23.392 z 40 Asp353, Gln442, Ile446 Pro357, Lys358 Monoolein 5283468 −5.7 x 8.006 x 40 Asn261, Lys257 Leu258, His274, Cys275 y −0.459 y 40 Ala333, Val255, Cys278 z 23.392 z 40 2,6-Octadiene, 2,6-dimethyl- 5365898 −5.7 x 8.006 x 40 n/a Met320, Phe218, Leu331 y −0.459 y 40 Val324, Met220, Leu321 z 23.392 z 40 Citronellol 8842 −5.5 x 8.006 x 40 Thr283 Leu331, Val324, Ile317 y −0.459 y 40 Leu321, Met320, Thr279 z 23.392 z 40 Myrcene 31253 −5.5 x 8.006 x 40 n/a Val332, Val324, Ile317 y −0.459 y 40 Leu321, Met220, Thr283 z 23.392 z 40 Met320, Leu331 (E)-β-Ocimene 5281553 −5.5 x 8.006 x 40 n/a Thr283, Ile317, Met320 y −0.459 y 40 Tyr334, Val332, Val324 z 23.392 z 40 Gly335, Leu331, Thr279 Leu321 Citronellal 7794 −5.2 x 8.006 x 40 Thr283 Leu321, Met220, Met320 y −0.459 y 40 Val324, Asn219, Thr279 z 23.392 z 40 Ile317 Heptadec-8-ene 520230 −5.2 x 8.006 x 40 n/a Leu321, Ile317, Thr283 y −0.459 y 40 Thr279, Val255, Ala333 z 23.392 z 40 Tyr334, Leu331, Val332 Val324 Myristic acid 11005 −5.2 x 8.006 x 40 Tyr334, Ala333,Thr279 Val332, Met220, Met320 y −0.459 y 40 Ile317, Leu321, Thr283 z 23.392 z 40 Asn219 Nonanoic acid 8158 −5.1 x 8.006 x 40 Ala333 Leu331, Leu321, Val332 y −0.459 y 40 Ile317, Thr283, Met320 z 23.392 z 40 Val324, Thr279 10-Bromoundecanoic acid 543401 −5.1 x 8.006 x 40 n/a Met320, Val324, Leu321 y −0.459 y 40 Thr279, Leu331, Val332 z 23.392 z 40 Asn219, Tyr334, Met220 2-Methyl-Z,Z-3,13-octadecadienol 5364412 −5.0 x 8.006 x 40 n/a Leu254, Ala333, Cys275 y −0.459 y 40 Tyr334, Ile317, Met320 z 23.392 z 40 Thr283, Leu321, Leu331 Val324, Ala250, Thr279 Ile241, Val255 Octanoic acid 379 −5.0 x 8.006 x 40 Asn219, Thr283, Met220 Phe218, Leu321, Val324 y −0.459 y 40 Glu286 Leu331, Met320 z 23.392 z 40 Nonadecanoic acid 12591 −4.9 x 8.006 x 40 n/a Asn336, Leu254, Ala333 y −0.459 y 40 Ala250, Cys275, Val255 z 23.392 z 40 Tyr334 3-Hydroxycyclohexanone 439950 −4.9 x 8.006 x 40 Met220 Met320, Phe218, Asn219 y −0.459 y 40 Glu286 z 23.392 z 40 Palmitic acid 985 −4.9 x 8.006 x 40 n/a Glu251, Val332, Ile241 y −0.459 y 40 Ala333, Thr279, Val255 z 23.392 z 40 Tyr334, Leu258, Cys275 Ala250, Leu254 3-Methylcyclohexene 11573 −4.6 x 8.006 x 40 n/a Met320, Ile317, Leu321 y −0.459 y 40 Thr279, Thr283 z 23.392 z 40 9-Octadecenoic acid 965 −4.4 x 8.006 x 40 n/a Glu251, Ala250, Leu254 y −0.459 y 40 Val255, Ile241, Ala333 z 23.392 z 40 Asn336, Tyr334, Cys275 2-Tetradecynoic acid 324386 −4.1 x 8.006 x 40 Thr307 Glu462, Ser688, Gln691 y −0.459 y 40 Tyr311, Lys310, Asn303 z 23.392 z 40 Val306 Methyl palmitate 8181 −3.7 x 8.006 x 40 n/a Tyr311, Gln691, Pro389 y −0.459 y 40 Lys310, Thr307, Asn303 z 23.392 z 40 Val306, Ser688, Glu462 Positive control ^(a) Clofibrate 2796 −6.4 x 8.006 x 40 Thr283 Ala333, Tyr334, Asn219 y −0.459 y 40 Met320, Leu321, Met220 z 23.392 z 40 Phe218, Val332, Val324 Thr279 ^(a) Gemfibrozil 3463 −6.3 x 8.006 x 40 Tyr468 Tyr464, Lys448, Leu456 y −0.459 y 40 Arg465, Gln442, Ala441 z 23.392 z 40 ^(a) Ciprofibrate 2763 −5.4 x 8.006 x 40 Ala333, Thr279 Lys257, Cys278, Tyr334 y −0.459 y 40 Cys275, Val255, Leu258 z 23.392 z 40 ^(a) Bezafibrate 39042 −5.8 x 8.006 x 40 Thr307, Ser688 Asn303, Glu462, Val306 y −0.459 y 40 Leu690, Lys310, Gly390 z 23.392 z 40 ^(a) Fenofibrate 3339 −5.4 x 8.006 x 40 n/a Gln435, Ala431, Asp360 y −0.459 y 40 Pro357, Leu436, Glu439 z 23.392 z 40 Lys364, Phe361, Asp432 PPARD (PDB ID:5U3Q) ^(★) Stigmasta-5,22-dien-3-ol 53870683 −8.6 x 39.265 x 40 n/a Ala414, Tyr441, Met440 y −18.736 y 40 Pro362, Gly363, Arg361 z 119.392 z 40 Gly359, Asp360, Thr411 Val410 Clionasterol 457801 −7.3 x 39.265 x 40 Met440 Ala414, Tyr441, Tyr284 y −18.736 y 40 Pro362, Arg361, Asp360 z 119.392 z 40 Val410, Thr411 26,27-Dinorergosta-5,23-dien-3beta-ol 22213488 −7.3 x 39.265 x 40 n/a Lys188, Glu262, Lys265 y −18.736 y 40 Ser266, Ser271 z 119.392 z 40 Stearic acid 5281 −6.8 x 39.265 x 40 n/a Glu288, Tyr284, Asp439 y −18.736 y 40 Asp360, Val367, Gly359 z 119.392 z 40 Leu364, Gly363, Arg361 Pro362, Met440, Thr411 Tyr441 1,3,4,5-Tetrahydroxycyclohexanecarboxylic acid 1064 −6.6 x 39.265 x 40 Tyr441, Glu288 Ala414, Thr411, Val410 y −18.736 y 40 Tyr284, Arg361, Arg407 z 119.392 z 40 Met440 Nonadecanoic acid 12591 −5.8 x 39.265 x 40 Asp360 Pro362, Tyr441, Met440 y −18.736 y 40 Val410, Glu288, Arg407 z 119.392 z 40 Thr411, Arg361, Tyr284 Citronellal 7794 −5.7 x 39.265 x 40 n/a Asn307, Ala306, Thr252 y −18.736 y 40 Trp228, Arg248, Val305 z 119.392 z 40 Gln230, Lys229 Nonanoic acid 8158 −5.7 x 39.265 x 40 Thr256 Glu255, Asn307, Lys229 y −18.736 y 40 Trp228, Ala306, Thr252 z 119.392 z 40 Glu259, Asn191 Citronellic acid 10402 −5.3 x 39.265 x 40 n/a Arg361, Tyr441, Thr411 y −18.736 y 40 Met440, Tyr284 z 119.392 z 40 Myristic acid 11005 −5.2 x 39.265 x 40 Tyr441 Ala414, Glu288, Pro362 y −18.736 y 40 Arg361, Asp439, Tyr284 z 119.392 z 40 Arg407, Thr411, Met440 Val410 Octanoic acid 379 −5.1 x 39.265 x 40 Lys229, Gln230, Arg248 Cys251, Trp228, Val305 y −18.736 y 40 Ala306, Thr252 z 119.392 z 40 9-Octadecenoic acid 965 −5.0 x 39.265 x 40 n/a Met440, Thr411, Tyr441 y −18.736 y 40 Pro362, Tyr284, Arg361 z 119.392 z 40 Val410 3-Hydroxycyclohexanone 439950 −5.0 x 39.265 x 40 Arg407, Thr411 Val410, Met440, Tyr441 y −18.736 y 40 z 119.392 z 40 Citronellol 8842 −4.8 x 39.265 x 40 Arg361 Asp439, Met440, Tyr441 y −18.736 y 40 Tyr284, Val410 z 119.392 z 40 Palmitic acid 985 −4.6 x 39.265 x 40 n/a Tyr441, Pro362, Arg361 y −18.736 y 40 Val410, Tyr284, Glu288 z 119.392 z 40 Met440, Thr411, Ala414 Arg407 10-Bromoundecanoic acid 543401 −4.6 x 39.265 x 40 Arg361, Tyr284 Tyr441, Met440, Pro362 y −18.736 y 40 Thr411, Glu288 z 119.392 z 40 Methyl palmitate 8181 −4.5 x 39.265 x 40 n/a Thr411, Tyr441, Pro362 y −18.736 y 40 Met440, Arg361, Tyr284 z 119.392 z 40 Glu288 Positive control ^(b) Cardarine 9803963 −8.5 x 39.265 x 40 Ser271, Ser272 Lys265, Glu262, Ser266 y −18.736 y 40 Lys265, Ser271, Pro268 z 119.392 z 40 Ser269 PPARG (PDB ID: 3E00) ^(★) NSC402953 345349 −8.2 x 2.075 x 40 Lys336 Asn335, Glu203, Arg234 y 31.910 y 40 Asp380, Ala231, Lys230 z 18.503 z 40 Glu378, Asn375, Met334 26,27-Dinorergosta-5,23-dien-3beta-ol 22213488 −8.0 x 2.075 x 40 Asn375 Val372, Asn335, Val205 y 31.910 y 40 Val163, Glu207, Glu208 z 18.503 z 40 Stigmasta-5,22-dien-3-ol 53870683 −7.8 x 2.075 x 40 Asn375 Arg202, Glu203, Lys336 y 31.910 y 40 Val163, Arg164, Gln206 z 18.503 z 40 Lys165, Glu208, Glu207 Val372, Asn335 Clionasterol 457801 −7.7 x 2.075 x 40 Asn375 Asn335, Val372, Lys336 y 31.910 y 40 Val163, Arg164, Glu208 z 18.503 z 40 Asp166, Glu207, Arg202 Glu203 Terpinyl propionate 62328 −6.6 x 2.075 x 40 Glu343 Leu340, Ile341, Leu333 y 31.910 y 40 Leu228, Met329, Arg288 z 18.503 z 40 Nonadecanoic acid 12591 −5.9 x 2.075 x 40 Glu351 Lys354, Thr168, Tyr189 y 31.910 y 40 Tyr169, Thr162, Leu167 z 18.503 z 40 Tyr192, Arg202, Arg350 Asp337, Lys336, Gln193 Stearic acid 5281 −5.9 x 2.075 x 40 Ser342, Cys285 Ile341, Phe226, Ile296 y 31.910 y 40 Glu295, Ala292, Met329 z 18.503 z 40 Leu333, Leu228, Arg288 Citronellic acid 10402 −5.2 x 2.075 x 40 n/a Glu295, Arg288, Ala292 y 31.910 y 40 Leu228, Leu333, Met329 z 18.503 z 40 Palmitic acid 985 −5.1 x 2.075 x 40 Glu291, Arg288 Glu343, Leu333, Leu228 y 31.910 y 40 Met229, Ala292, Ile326 z 18.503 z 40 Glu295 Myristic acid 11005 −5.1 x 2.075 x 40 Glu343 Arg288, Ser342, Leu333 y 31.910 y 40 Met329, Leu228, Glu295 z 18.503 z 40 Pro227, Ala292 Nonanoic acid 8158 −5.0 x 2.075 x 40 Lys354 Arg350, Glu351, Tyr169 y 31.910 y 40 Tyr192, Tyr189, Leu167 z 18.503 z 40 Gln193, Asp337, Lys336 Citronellal 7794 −4.9 x 2.075 x 40 Gln193 Tyr189, Arg202, Leu167 y 31.910 y 40 Thr162, Tyr192, Asp337 z 18.503 z 40 Lys336, Arg350, Lys354 Glu351 (E)-4-Undecenal 5283357 −4.9 x 2.075 x 40 Tyr169 Leu167, Tyr192, Lys336 y 31.910 y 40 Arg350, Glu351, Asp337 z 18.503 z 40 Gln193, Lys354, Tyr189 Octanoic acid 379 −4.7 x 2.075 x 40 Arg202, Leu167 Asp337, Thr168, Tyr192 y 31.910 y 40 Tyr169, Gln193, Tyr189 z 18.503 z 40 Glu351, Lys336 9-Octadecenoic acid 965 −4.1 x 2.075 x 40 Arg164, Glu208 Glu207, Glu203, Asp166 y 31.910 y 40 Lys336, Arg202, Val372 z 18.503 z 40 Asn375, Val163 Methyl palmitate 8181 −3.8 x 2.075 x 40 Glu291, Arg288 Glu343, Leu333, Leu330 y 31.910 y 40 Leu228, Met329, Ala292 z 18.503 z 40 Ile326, Glu295 Positive control ^(c) Pioglitazone 4829 −7.7 x 2.075 x 40 Arg288 Ile326, Leu333, Met329 y 31.910 y 40 Ala292, Ile341, Cys285 z 18.503 z 40 Ser342, Glu343, Glu295 Leu228 ^(c) Rosiglitazone 77999 −7.4 x 2.075 x 40 Tyr169 Glu351, Tyr189, Gln193 y 31.910 y 40 Thr168, Leu167, Glu369 z 18.503 z 40 Lys373, Val372, Arg350 Lys336, Tyr192, Asp337 ^(c) Lobeglitazone 9826451 −7.3 x 2.075 x 40 Arg234 Val372, Asn375, Met334 y 31.910 y 40 Val163, Lys230, Glu203 z 18.503 z 40 Lys157, Val205, Arg164 Arg202, Asp166, Lys336 FABP3 (PDB ID: 5HZ9) ^(★) Monoolein 5283468 −8.9 x −1.215 x 40 Arg31, Thr57, Phe58 Ala29, Gln32, Phe28 y 46.730 y 40 Gly27 z −15.099 z 40 Glyceryl palmitate 14900 −8.7 x −1.215 x 40 Arg31 Thr57, Phe58, Ala29 y 46.730 y 40 Gln32, Phe28, Lys22 z −15.099 z 40 Nonadecanoic acid 12591 −8.3 x −1.215 x 40 Lys22 Ala29, Gln32, Phe28 y 46.730 y 40 Gly27, Gly25 z −15.099 z 40 Stearic acid 5281 −8.3 x −1.215 x 40 n/a Gly27, Asp78, Thr122 y 46.730 y 40 Phe58, Ala29, Phe28 z −15.099 z 40 Lys22, Lys59, Asp77 Thr30 2-Dodecen-1-ylsuccinic anhydride 5362708 −7.8 x −1.215 x 40 Thr30, Gly27 Gly25, Gln32, Ala29 y 46.730 y 40 Phe28 z −15.099 z 40 Heptadec-8-ene 520230 −7.6 x −1.215 x 40 n/a Phe28, Met36, Thr57 y 46.730 y 40 Val33, Ala29, Gln32 z −15.099 z 40 2-Methyl-Z,Z-3,13-octadecadienol 5364412 −7.4 x −1.215 x 40 n/a Lys22, Gly25, Gly27 y 46.730 y 40 Gln32, Phe28, Ala29 z −15.099 z 40 2-Tetradecynoic acid 324386 −7.4 x −1.215 x 40 Arg31, Lys22 Phe58, Ala29, Gln32 y 46.730 y 40 Phe28, Thr57, Lys59 z −15.099 z 40 Methyl palmitate 8181 −7.1 x −1.215 x 40 n/a Phe28, Gly27, Gly25 y 46.730 y 40 Gln32, Ala29 z −15.099 z 40 9-Octadecenoic acid 637517 −7.1 x −1.215 x 40 n/a Ala29, Gly25, Phe28 y 46.730 y 40 Gly27, Gly25, Gln32 z −15.099 z 40 Myristic acid 11005 −6.9 x −1.215 x 40 Phe58 Ala29, Phe28, Gly27 y 46.730 y 40 Lys22 z −15.099 z 40 2-Dodecenoic acid 5282729 −6.8 x −1.215 x 40 Arg31 Lys59, Phe58, Thr57 y 46.730 y 40 Ala29, Gln32, Phe28 z −15.099 z 40 Lys22 Citronellic acid 10402 −6.6 x −1.215 x 40 Phe58 Lys22, Met36, Ala29 y 46.730 y 40 Thr57 z −15.099 z 40 Palmitic acid 985 −6.5 x −1.215 x 40 n/a Val33, Thr57, Lys22 y 46.730 y 40 Phe58, Ala29, Gln32 z −15.099 z 40 (E)-4-Undecenal 5283357 −6.5 x −1.215 x 40 n/a Gln32, Ala29, Gly25 y 46.730 y 40 Gly27, Phe28 z −15.099 z 40 Isopropyl hexanoate 16832 −6.4 x −1.215 x 40 n/a Ala29, Phe28, Val33 y 46.730 y 40 z −15.099 z 40 Octane 356 −6.1 x −1.215 x 40 n/a Phe28 y 46.730 y 40 z −15.099 z 40 10-Bromoundecanoic acid 543401 −6.1 x −1.215 x 40 n/a Thr57, Ala29, Gln32 y 46.730 y 40 Phe28, Lys22, Thr57 z −15.099 z 40 Nonanoic acid 8158 −6.0 x −1.215 x 40 n/a Gln32, Phe28 y 46.730 y 40 z −15.099 z 40 Octanoic acid 379 −5.8 x −1.215 x 40 n/a Gln32, Val33, Gly25 y 46.730 y 40 Gly27, Phe28, Ala29 z −15.099 z 40 1,3,4,5-Tetrahydroxycyclohexanecarboxylic acid 1064 −5.6 x −1.215 x 40 Asn307, Ala306, Lys229 Val305, Thr252, Trp228 y 46.730 y 40 z −15.099 z 40 Citronellol 8842 −5.4 x −1.215 x 40 n/a Ala306, Glu255, Asn307 y 46.730 y 40 Thr252, Trp228, Arg248 z −15.099 z 40 Gln230, Lys229 3-Hydroxycyclohexanone 439950 −5.3 x −1.215 x 40 Thr54, Arg107, His94 Thr61, Leu52, Ile63 y 46.730 y 40 Glu73, Leu105 z −15.099 z 40 Neral 643779 −5.0 x −1.215 x 40 n/a Arg361, Thr411, Tyr441 y 46.730 y 40 Met440 z −15.099 z 40 Citronellal 7794 −4.9 x −1.215 x 40 n/a Thr411, Met440, Pro362 y 46.730 y 40 Asp360, Val410, Tyr284 z −15.099 z 40 MMP1 (PDB ID: 1SU3) ^(★) 2-Propenoic acid, 3-phenyl-, methyl ester 7644 −5.0 x 34.394 x 40 Arg399, Tyr411, Tyr397 Asp418, Phe436, Tyr390 y −44.313 y 40 Phe419, Phe447, Pro449 z 37.396 z 40 Lys413 Geranyl acetate 1549026 −4.5 x 34.394 x 40 Tyr411 Arg399, Asp418, Pro449 y −44.313 y 40 Phe447, Lys452, Phe419 z 37.396 z 40 Tyr390, Tyr397 2-Dodecenoic acid 5282729 −4.3 x 34.394 x 40 Tyr397, Tyr411 Lys413, Tyr390, Pro449 y −44.313 y 40 Phe419, Phe447, Asp418 z 37.396 z 40 Citronellal 7794 −4.0 x 34.394 x 40 Arg399 Phe419, Asp418, Tyr397 y −44.313 y 40 Phe436, Tyr390, Glu383 z 37.396 z 40 Pro449 (E)-4-Undecenal 5283357 −3.6 x 34.394 x 40 n/a Lys452, Asp418, Pro449 y −44.313 y 40 Phe436, Phe419, Phe447 z 37.396 z 40 Tyr390, Tyr397 Positive control ^(d) Batimastat 5362422 −6.7 x 34.394 x 40 Thr112, His113, Lys396 Pro146, Glu110, Arg108 y −44.313 y 40 Thr373 Pro371, Trp398, Pro412 z 37.396 z 40 Val393 ^(d) Ilomastat 132519 −6.5 x 34.394 x 40 His113 Thr145, Ser142, Thr148 y −44.313 y 40 Leu147, Lys413, His417 z 37.396 z 40 Met414, Pro412, Gln264 Pro146 [117]Open in a new tab ^(★) Compound with the greatest affinity on each target; ^(a) PPARA agonist; ^(b) PPARD agonist; ^(c) PPARG agonist; ^(d) MMP agonist. 3.10. Identification of the Uppermost Seven Targets and Eight Compounds from Two Key Signaling Pathways against RA Campesterol on FGF1, 26,27-Dinorergosta-5,23-dien-3β-ol on FGF2, CBMicro_013618 on TNFRSF1A, and monoolein on PRKCA on MAPK signaling pathway had significant valid affinity score to develop new promising ligands. Additionally, β-Caryophyllene on PPARA, Stigmasta-5,22-dien-3-ol on PPARD, NSC0402953 on PPARG, and monoolein on FABP3 had an important valid score on the PPAR signaling pathway. 3.11. Toxicological Properties of 8 Compounds Additionally, toxicological properties of Campesterol; 26,27-Dinorergosta-5,23-dien-3β-ol; CBMicro_013618; monoolein; β-Caryophyllene; Stigmasta-5,22-dien-3-ol; and NSC0402953 were predicted by admetSAR online tool. Our result indicated that chemical compounds did not disclose Ames toxicity, carcinogenic properties, acute oral toxicity, and rat acute toxicity properties ([118]Table 8). Table 8. Toxicological properties of seven key compounds in the MDT. Parameters Compound Name Campesterol 26,27-Dinorergosta-5,23-dien-3β-ol CBMicro_013618 Monoolein β-Caryophyllene Stigmasta-5,22-dien-3-ol NSC0402953 Ames toxicity NAT NAT NAT NAT NAT NAT NAT Carcinogens NC NC NC NC NC NC NC Acute oral toxicity I I III IV III I III Rat acute toxicity 2.8078 2.8078 2.5735 1.0526 1.4345 2.6561 1.9796 [119]Open in a new tab AT: Ames toxic; NAT: Non-ames toxic; NC: Non-carcinogenic; category I means (50mg/kg≤ LD50); category II means (50mg/kg > LD50 < 500mg/kg); category III means (500mg/kg > LD50 < 5000mg/kg); category IV means (LD50 > 5000mg/kg). 4. Discussion PPI network showed that the therapeutic efficacy of ZPFs on RA was associated with 99 targets. The KEGG pathway analysis enrichment of 99 targets revealed that 19 signaling pathways were related closely to the occurrence and progression of RA, suggesting that these signaling pathways might be remedial mechanisms of ZPFs to alleviate RA. The relationships of the 19 signaling pathways with RA are briefly discussed as follows. PPAR signaling pathway: the activation of PPAR is a good strategy to alleviate RA, which can suppress the inflammatory activity of NF-κB in fibroblast-like synoviocytes (FLSs) [[120]30]. Relaxin signaling pathway: the combined relaxin with estrogen exerts anti-inflammatory effects by dampening neutrophil function [[121]31]. Vascular Endothelial Growth Factor (VEGF) signaling pathway: VEGF expression level in RA patients increased significantly, compared with healthy groups; moreover, patients under RA for an extended period exerted higher VEGF expression level in serum [[122]32]. Estrogen signaling pathway: the estrogen treatment might have an inhibitory effect on RA symptoms or delay in the onset of disease, and estrogen has anti-inflammatory activity in an animal test of RA [[123]33]. Fc epsilon RI signaling pathway: Fc epsilon RI signaling pathway is associated with inflammatory etiology, antigen-induced autoimmune reaction, and control of lipid metabolic pathway, and damage in human joint [[124]34]. Prolactin signaling pathway: Prolactin collaborates with other proinflammatory factors to stimulate macrophages through prolactin receptors which might be a potential therapeutic target in RA [[125]35]. Sphingolipid signaling pathway: Sphingolipid expression level in RA elevated in the serum sample, consistent with known roles of sphingolipids related to inflammation [[126]36]. Cyclic AMP (cAMP) signaling pathway: stimuli-induced cAMP production can exert proinflammatory effects in RA [[127]37]. It implies that the activation of the cAMP level might drive inflammatory responses. AGE-RAGE (the receptor for advanced glycation end products) signaling pathway in diabetic complications: the expression of RAGE increased in RA patients, and IL-17 and IL-1β triggered RAGE production [[128]37]. It suggests that the inhibition of RAGE might be a good target for RA treatment. Hypoxia-Inducible Factor-1(HIF-1) signaling pathway: synovial hypoxia is characterized by RA patients, leading to inflammation, cartilage destruction, and oxidative impairment [[129]38]. Ras-associated protein-1 (RAP1) signaling pathway: The downregulation of RAP1 in RA induces ongoing inflammation due to the overproduction of free radicals [[130]39]. Thyroid hormone signaling pathway: joint damages in thyroid gland abnormalities are due to hypothyroidism, and thyroid hormone plays a vital role in antioxidant modulation, as indicated by in vivo and in vitro tests [[131]40,[132]41]. Phospholipase D signaling pathway: phospholipase D1 (PLD1) is a mediator to induce proinflammatory cytokines with a reduction of the regulatory T (Treg) cell and recruitment of Th17 cell in collagen-induced arthritis mice [[133]42]. Gonadotropin-releasing hormone (GnRH) signaling pathway: GnRH is a potent substance to alleviate inflammation in RA patients with a high level of GnRH [[134]43]. Ras signaling pathway: T cells in RA patients show the Ras signalling pathway’s overactivation-related deeply to inflammation [[135]44]. T cell receptor signaling pathway: T cell recruitment to the inflammatory sites can induce chronic inflammation and autoimmunity [[136]45]. Phosphoinositide 3-kinase—Akt (PI3K-Akt) signaling pathway: a report demonstrated that PI3K-Akt signaling pathway was excessively activated, aggravating in overexpression Bcl-2, Mcl-1, and FLIP to result in unbalanced apoptosis of synovial cells, which is associated with occurrence and progression of RA [[137]46,[138]47]. Calcium signaling pathway: it was reported that the cytoplasmic calcium concentration in RA naïve CD4^+ T cells is increased significantly [[139]48]. It implies that the calcium signaling pathway is involved intensely in inflammatory responses. MAPK signaling pathway: a study demonstrated that andrographolide with anti-inflammatory activities has potent anti-RA efficacy, inhibiting MAPK pathway [[140]49]. This report is consistent with our result via network pharmacology analysis. To sum things up, the relationship between compounds and targets through the network pharmacology concept was clarified, and ligands with the most excellent affinity out of selective ligands in ZPFs were considered as potential therapeutic candidates against RA, compared with existing ligands via MDT. The PPI network suggested that VEGFA is the highest degree of value (42) on the MAPK signaling pathway. However, the affinity of ZPFs compounds on VEGFA was invalid (> −6.0kcal/mol) [[141]29]; furthermore, existing ligand (BAW2881: −7.6 kcal/mol) had better affinity than a compound (3,4-O-Isopropylidene-d-galactose: −5.3 kcal/mol) with the greatest affinity from ZPFs. The STC network indicated that PRKCA had the greatest degree of value (14) on the MAPK signaling pathway, and monoolein (PubChem ID: 5283468) had the greatest affinity (−6.7 kcal/mol), which was superior to an existing ligand (sphingosine: −5.5 kcal/mol). On PPAR signaling pathway, β-Caryophyllene (−8.6 kcal/mol) on PPARA, Stigmasta-5,22-dien-3-ol (−8.6 kcal/mol) on PPARD, and NSC402953 (−8.2 kcal/mol) on PPARG had better affinity than existing ligands on each target. Specifically, monoolein on FABP3 had the greatest affinity (−8.9 kcal/mol). Moreover, agonists of FABP3 were not reported yet. Furthermore, there were no valid ligands on MMP1 on the PPAR signaling pathway. Taken together, the most noticeable ligand of ZPFs against RA is monoolein with dual effects on RA. Monoolein might be an antagonist on the MAPK signaling pathway or an agonist on the PPAR signaling pathway ([142]Figure 10). A study demonstrated that monoolein treatment in LPS- stimulated primary murine bone marrow-derived dendritic cells (BMDCs) inhibited the activation of MAPK and NF-κB; moreover, it suppressed the production of NO and iNOS in RAW264.7 cells [[143]50]. This suggests that the inactivation of the MAPK signaling pathway is a good strategy to ameliorate inflammation associated with bone damage. Another report indicated that the expression level of PPARG in FLSs of RA patients was significantly reduced compared with healthy FLSs [[144]30]; this implies that the activation of the PPAR signaling pathway might be a therapeutic mechanism against RA. These reports are in line with our results. Additionally, we suggested that monoolein might be an antagonist in activating PRKCA on MAPK signaling pathway and might also be an agonist to activate FABP3 on the PPAR signaling pathway. Figure 10. [145]Figure 10 [146]Open in a new tab Schematic representation of key findings in the study. 5. Conclusions This study provides eight targets, seven compounds, and two key signaling pathways of ZPFs which show promise against RA, which might be useful for multiple target combination therapies on RA. Out of seven compounds from ZPFs, monoolein shows dual effects: inactivation of MAPK signaling pathway and activation of the PPAR signaling pathway. The key pharmacological mechanisms of ZPFs against RA might be to inhibit cytokine production in synovial cells by binding on PRKCA or FABP3. Acknowledgments