Research article

In silico anti-inflammatory activity of lavender (Lavandula officinalis) essential oil bioactive compounds: Molecular docking analysis of COX-1 and COX-2, and ADMET prediction

  • Received: 02 December 2022 Revised: 20 February 2023 Accepted: 14 March 2023 Published: 03 April 2023
  • Advanced investigations are in action worldwide to find medications with improved safety profiles. Natural resources are essential in the creation of innovative treatments and drugs that have fewer side effects. The essential oil (EO) of lavender (Lavandula officinalis) is well-known in alternative and complementary therapies for its use as wound-healing and antimicrobial ingredients. However, the exact pharmacological and anti-inflammatory aspects of naturally produced lavender essential oil (LEO) compounds are still unknown. As a consequence, it is essential to explain LEO drug molecular docking experiments with cyclo-oxygenase enzymes (COX-1 and COX-2). An attempt was developed in this study to discover the anti-inflammatory activity of LEO bioactive components. The online DockThor server was used for in silico molecule docking simulation. Interaction studies of LEO compound binding poses with COX were performed to get an understanding of the interacting amino acids and their inter-molecular bondings. Based on physicochemical attributes and toxicity, the docked compounds with the greatest binding affinities were also investigated for drug similarity utilizing the admetSAR tool and PASS platforms. Molecular docking studies exploring the bioactive principle targeted action revealed that electrostatic interactions and H-bonds make the main causative factor in inter-molecular connections associated with anti-inflammatory action. Seven top-ranked compounds were selected by virtual screening. Molecular docking revealed that limonene has the highest negative binding affinity (−8.536 kcal/mol) in complex with COX-1, followed by α-terpineol (−8.535 kcal/mol) and p-cymene (−8.515 kcal/mol), while two approved anti-inflammatory drugs (celecoxib and betamethasone) produced −8.191 and −8.041 kcal/mol respectively. Similarly, these terpenes can be documented as promising drug candidates based on qualifying Lipinski's rule five. The selected terpenes showed excellent drug-like properties and a percentage of human oral absorption. Besides, it was found to be safe for the human body in toxicological risk assessment. This work gives insight into the anti-inflammatory mechanism of action of LEO terpenes. LEO drugs' pharmacokinetic data and molecular docking patterns may open the way for the development of new COX inhibitors with anti-inflammatory capability and improved pharmacokinetic and pharmacodynamic properties.

    Citation: Bouchra Sarah Boukhatem, Abd-Elmouneim Belhadj. In silico anti-inflammatory activity of lavender (Lavandula officinalis) essential oil bioactive compounds: Molecular docking analysis of COX-1 and COX-2, and ADMET prediction[J]. AIMS Allergy and Immunology, 2023, 7(2): 132-153. doi: 10.3934/Allergy.2023009

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  • Advanced investigations are in action worldwide to find medications with improved safety profiles. Natural resources are essential in the creation of innovative treatments and drugs that have fewer side effects. The essential oil (EO) of lavender (Lavandula officinalis) is well-known in alternative and complementary therapies for its use as wound-healing and antimicrobial ingredients. However, the exact pharmacological and anti-inflammatory aspects of naturally produced lavender essential oil (LEO) compounds are still unknown. As a consequence, it is essential to explain LEO drug molecular docking experiments with cyclo-oxygenase enzymes (COX-1 and COX-2). An attempt was developed in this study to discover the anti-inflammatory activity of LEO bioactive components. The online DockThor server was used for in silico molecule docking simulation. Interaction studies of LEO compound binding poses with COX were performed to get an understanding of the interacting amino acids and their inter-molecular bondings. Based on physicochemical attributes and toxicity, the docked compounds with the greatest binding affinities were also investigated for drug similarity utilizing the admetSAR tool and PASS platforms. Molecular docking studies exploring the bioactive principle targeted action revealed that electrostatic interactions and H-bonds make the main causative factor in inter-molecular connections associated with anti-inflammatory action. Seven top-ranked compounds were selected by virtual screening. Molecular docking revealed that limonene has the highest negative binding affinity (−8.536 kcal/mol) in complex with COX-1, followed by α-terpineol (−8.535 kcal/mol) and p-cymene (−8.515 kcal/mol), while two approved anti-inflammatory drugs (celecoxib and betamethasone) produced −8.191 and −8.041 kcal/mol respectively. Similarly, these terpenes can be documented as promising drug candidates based on qualifying Lipinski's rule five. The selected terpenes showed excellent drug-like properties and a percentage of human oral absorption. Besides, it was found to be safe for the human body in toxicological risk assessment. This work gives insight into the anti-inflammatory mechanism of action of LEO terpenes. LEO drugs' pharmacokinetic data and molecular docking patterns may open the way for the development of new COX inhibitors with anti-inflammatory capability and improved pharmacokinetic and pharmacodynamic properties.



    Nonsteroidal anti-inflammatory drugs (NSAIDs) are one of the most frequently prescribed medicinal classes in old people and children [1],[2]. These medications are typically used to treat inflammatory illnesses and to reduce pain associated with a variety of medical ailments or surgeries [3]. They are used to treat chronic inflammatory disorders such as arthritis, gout, and rheumatoid. NSAIDs work by inhibiting the cyclooxygenase (COX) enzymes, which decrease the production of prostaglandins (PGs), which are believed to be involved in the complicated process of inflammation [4].

    Inflammatory responses caused by the production of histamine, bradykinin, and prostaglandins are part of the host's defense systems. COX are important enzymes in the biosynthesis of prostaglandins, which are the primary mediators of the inflammatory response, pain, and elevated body temperature (hyperpyrexia). The body generates two major isoforms of COX enzymes, namely cyclooxygenases-1 (COX-1) and cyclooxygenases-2 (COX-2). It has been reported that COX-1 is responsible for the production of important biological messengers such as prostaglandins and thromboxanes and is implicated in blood coagulation, pain-causing, and stomach protection, whereas COX-2 is implicated in pain triggered by inflammation and plays a key role in prostaglandin synthesis pathway in inflammatory cells and the nervous system [5],[6]. When COX-1 is blocked, the inflammatory response is decreased, but gastrointestinal lining defense is also reduced. This might result in stomach distress, ulcers, and hemorrhage from the gastrointestinal tract. Whereas COX-2 is normally restricted to inflamed tissue, COX-2 inhibition causes significantly reduced stomach irritation as well as a lower risk of gastric hemorrhage [7]. As a result, selective COX-2 inhibitors such as rofecoxib (Vioxx®) and celecoxib drugs have been designed to alleviate COX-related inflammation [8]. However, Coxib medications have been removed due to an enhanced danger of long-term heart attacks and strokes [9].

    Furthermore, NSAIDs are one of the most popular treatments in the world, however, they are not generally accepted by users, and hence their long-term usage in chronic medical conditions is accompanied with significant undesirable consequences. Long-term NSAIDS medication may cause stomach epithelial injury marked by localized necrosis, bleeding, and in some cases, severe ulceration [10],[11]. The NSAID-induced gastropathy issues that limit the effectiveness of this class of medications are due mainly to the nonselective inhibitory activity of both constitutive (COX-1) and inducible (COX-2) homologs of cyclooxygenase, as well as the existence of corrosive carboxylic acid features and functions in their structure [12].

    As a result, developing effective COX inhibitors from biological compounds is necessary. Medicinal plants, aromatic herbs, and their essential oils (EOs) have lately been recognized to have curative effects and also to have many health benefits. They have been shown to offer a wide range of medicinal benefits, including antibacterial, antifungal, antioxidant, anti-inflammatory, analgesic, and anticancer properties [13][15]. Lavender (Lavandula officinalis (Lamiaceae family)) is a popular aromatic plant in the Mediterranean region, including Algeria. Lavender has mostly been employed in medicinal and domestic culinary applications over the world. The EO extracted from lavender aerial parts is the primary contributor to its distinctive perfume and medicinal function [16],[17]. In ethnomedicine, lavender is used as an anti-inflammatory medication [18],[19]. As a result, it is important to describe the molecular docking study of lavender metabolites with COX-1 and COX-2.

    The current study focuses on identifying potential treatment options that will be regarded as successful anti-inflammatory medication therapy. Molecular docking is a vital computational method in drug design and development projects, and it was used to match a small ligand as a guest with a variety of receptor molecules as hosts. This docking-based technology is often used to estimate a compound's attraction for a target protein. In this paper, molecular docking of various potential anti-inflammatory medicines and numerous terpenes discovered in LEO was done in this research to investigate the inhibition likelihood against COX-1 and COX-2 receptors using the DockThor server and BIOVIA Discovery Studio visualizer software. A total of 29 LEO terpene compounds were virtually screened on the COX-1 (PDB ID 3N8Y) and COX-2 (PDB ID 3LN1) enzymes. The binding affinities were compared to those of other anti-inflammatory medications. The docked compounds with the highest binding affinities were also screened for drug-likeness utilizing the SwissADME and PASS platforms, based on physicochemical, pharmacological, and toxicological features.

    From the protein data bank, the X-ray crystal structures of COX-1 and COX-2 (PDB codes 3N8Y and 3LN1, respectively) were retrieved (Table 1 and Figure 1). The deletion of ligands, water molecules, as well as other heteroatoms was done using the software BIOVIA Discovery Studio visualizer (Dassault Systèmes Corp., Version 2020). The protein's crystal structure was furthered by the addition of hydrogen after missing and incomplete residues were filled in. The PDB file of the improved receptor was then utilized to simulate docking.

    Table 1.  Protein target data.
    PDB ID COX 1 (PDB ID: 3N8Y) COX-2 (PDB ID: 3LN1)
    Title Structure of aspirin acetylated COX-1 in complex with Diclofenac Structure of celecoxib bound at the COX-2 active site
    DOI 10.2210/pdb3N8Y/pdb 10.2210/pdb3LN1/pdb
    Author(s) Sidhu RS, Lee J, Yuan C, et al. Kiefer JR, Kurumbail RG, Stallings WC, et al.
    Deposited 28-05-2010 01-02-2010
    Resolution 2.60 Å 2.40 Å
    Classification Oxidoreductase Oxidoreductase
    Organism Ovis aries Mus musculus
    Expression system Spodoptera frugiperda Spodoptera frugiperda
    Method X-ray diffraction X-ray diffraction
    Molecule Prostaglandin G/H synthase 1 Prostaglandin G/H synthase 2
    Chains A A, B, C, D
    Sequence length 553 amino acids 587 amino acids
    Total structure weight 134.2 kDa 278.19 kDa

     | Show Table
    DownLoad: CSV
    Figure 1.  Three-dimensional crystal structure of the molecular target, COX-1 enzyme (3N8Y) was represented in (a) solid ribbon (b) without hetatoms (c) chaine A.

    LEO's total medicinal effect is provided by a diverse array of bioactive terpenes. Based on the percentage concentration in the LEO fraction, a study of the literature was conducted to identify the most important of these bioactive compounds. A literature search was carried out to obtain information about the LEO and its bioactive compounds from electronic databases such as Google scholar, PubMed, ScienceDirect, Wiley, MDPI, Springer, and other online journal publications and dissertations. There has been a lot of difference in the LEO chemical composition among different Lavandula species. We focused our chemical composition analysis on 29 terpenes that make up the bulk of lavender volatile oil. The compounds focused on in this study include limonene, α-terpineol, p-cymene, β-phellandrene, β-ocimene, myrcene, α-bisabolol, geraniol, germacrene D, β-caryophyllene, linalyl acetate, caryophyllene oxide, lavandulol, lavandulyl acetate, bornyl acetate, neryl acetate, cis-linalool oxide, terpinen-4-ol, linalool, eucalyptol, α-pinene, trans-linalool oxide, geranyl acetate, fenchone, β-pinene, camphene, camphor, borneol, β-farnesene. From the PubChem (pubchem.ncbi.nlm.nih.gov) database, the small molecular structures of the significant bioactive LEO constituents were obtained in sdf format. The application BIOVIA Discovery Studio visualizer was used to compute bond lengths, display receptors, ligand structures, and hydrogen bonding connections. After a comprehensive study of the literature, 34 structures of ligand molecules (Figures 2 and 3) were found and obtained from the PubChem database.

    Figure 2.  Chemical structure of selected anti-inflammatory drugs.
    Figure 3.  Chemical structure of all selected ligand terpenes in docking studies.

    In this research, we used the free DockThor Portal (www.dockthor.lncc.br) created by the Grupo de Modelagem Molecular de Sistemas Biológicos (GMMSB) (www.gmmsb.lncc.br) located at the Laboratório Nacional de Computaço Cientfica (LNCC) in Petrópolis, Brazil, for receptor-ligand dock. The DockThor Portal received the files of the retrieved ligands and receptors for docking simulation. The COX protein's active site with the biggest surface area was chosen for docking when all optimal ligands were applied. The following parameters were included in the docking process: Number of evaluations: 1000000; population size: 750; initial seed: −1985; number of runs: 24; docking: soft; spatial discretization of the energy grid: 0.25 Å; grid points: <1000000. All conformers with the best placements and dock scores for each ligand will be stored in the output folder. The technique additionally emphasizes the ideal conformer positioning for a certain ligand that has the best (minimum) score. The lowest interaction energy for each ligand and COX proteins for the ideal ligand position inside the binding site cavity was discovered once the docking procedure was complete. With the aid of the Discovery Studio visualizer, the interactions of intricate protein-ligand conformations were examined.

    Through examination of pharmacokinetic characteristics, a few molecules from the molecular docking analysis were assessed for their drug-like activity. The admetSAR program (http://lmmd.ecust.edu.cn) was used to estimate the pharmacokinetic profile (absorption, distribution, metabolism, excretion, and toxicity (ADMET)), of the LEO terpenes [20]. The topological polar surface area (TPSA), clog P, fragment-based drug-likeness, and drug score values were determined using the OSIRIS property explorer (www.organic-chemistry.org/prog/peo/). By using criteria such as molecular weight ≤ 500, logP ≤ 5, hydrogen bond donor ≤ 5, hydrogen bond acceptor ≤ 10, and TPSA ≤ 500, the ligands were further tested for the Lipinski rule of five. By inputting SMILES structures from PubChem notations or uploading SDF files, the molecules may be evaluated to determine their toxicological qualities. Toxicological modeling can then be used to generate a plethora of data regarding the effects associated with the structure.

    PASS version, an online system that predicts possible pharmacological effects of a chemical based on its structural information, was used to obtain the biological activity spectra of previously reported LEO phytoconstituents. PASS is a computer-based tool used to predict several types of physiological responses for numerous substances including phytoconstituents. This program compares over 300 pharmacological effects and biochemical pathways of substances and provides probabilities of activity (Pa) and inactivity (Pi). The only constituents deemed to be viable for a certain medical activity are those with Pa greater than Pi [21].

    The project that was submitted to the DockThor Portal makes use of the computing resources offered by the Brazilian SINAPAD (Sistema Nacional de Alto Desempenho) system, which has a high-performance platform. The top models were chosen after the DockThor Portal developed a variety of models for each docking operation between the COX receptor site and phytoconstituents. This computational process begins by docking each ligand molecule, followed by scoring. Using the DockThor server and the Discovery Studio software, docking experiments were conducted to examine the molecular interactions between the available active sites of target enzymes and LEO terpenes in order to determine the affinity of the compounds for COX-1 and COX-2. Based on their minimum binding energies associated with the complex formation at the catalytic activity, limonene, α-terpineol, p-cymene, β-phellandrene, β-ocimene, and terpinen-4-ol were rated in terms of their COX inhibitory activity. The docked chemicals' binding energies on COX-1 were determined to be between −8.536 and −8.438 kcal/mol (Table 2). Celecoxib and diclofenac sodium, two common anti-inflammatory medicines, had noticeably greater binding energies for the COX-2 target, showing that all of the chosen chemicals need less energy to block the protein.

    Table 2.  Docking data generated by DockThor server between various ligands molecules of the reference and LEO compounds with COX-1 & COX-2 enzymes.
    Compound name COX-1 binding affinity (kcal/mol) Compound name COX-2 binding affinity (kcal/mol)
    Limonene −8.536 Celecoxib −8.673
    α-Terpineol −8.535 Myrcene −8.495
    p-Cymene −8.515 α-Bisabolol −8.458
    β-Phellandrene −8.486 β-Caryophyllene −8.400
    β-Ocimene −8.463 β-Ocimene −8.353
    Terpinen-4-ol −8.438 Diclofenac sodium −8.313
    Germacrene D −8.413 Geraniol −8.303
    α-Pinene −8.334 Germacrene D −8.271
    Myrcene −8.332 β-Farnesene −8.257
    β-Pinene −8.274 β-Phellandrene −8.179
    Camphene −8.266 p-Cymene −8.018
    Fenchone −8.265 Betamethasone −7.990
    Celecoxib −8.191 Linalyl acetate −7.979
    Betamethasone −8.041 Caryophyllene oxide −7.893
    β-Farnesene −7.894 α-Terpineol −7.868
    Lavandulol −7.888 Lavandulol −7.731
    Diclofenac sodium −7.792 Lavandulyl acetate −7.586
    Caryophyllene oxide −7.760 Bornyl acetate −7.561
    β-Caryophyllene −7.696 Neryl acetate −7.537
    Geranyl acetate −7.661 cis-Linalool oxide −7.522
    Linalool −7.591 Ketoprofen −7.478
    α-Bisabolol −7.427 Terpinen-4-ol −7.228
    Ibuprofen −7.385 Geranyl acetate −7.211
    Bornyl acetate −7.349 Linalool −7.073
    Neryl acetate −7.329 Eucalyptol −6.999
    Lavandulyl acetate −7.224 trans-Linalool oxide −6.992
    Linalyl acetate −7.208 α-Pinene −6.980
    trans-Linalool oxide −7.133 Borneol −6.945
    cis-Linalool oxide −7.018 β-Pinene −6.929
    Ketoprofen −6.878 Ibuprofen −6.929
    Eucalyptol −6.761 Fenchone −6.917
    Borneol −6.727 Camphene −6.913
    Camphor −6.690 Limonene −6.904
    Geraniol −6.575 Camphor −6.835

     | Show Table
    DownLoad: CSV

    The best predicted binding energies for COX-1 and COX-2 were found to be for β-ocimene (Figure 4), with values of −8.463 and −8.353 kcal/mol, respectively, according to the molecular docking data shown in Table 3. Homnan et al. [22] looked at β-ocimene's ability to reduce inflammation. This hydrocarbon monoterpene strongly suppressed COX-2 activity and reduced prostaglandin E2 (PGE2) amounts in a dose-dependent way, with IC50 of 75.64 and much less than 20 g/mL, respectively. Kim et al. [23] studied the anti-inflammatory efficacy of EOs extracted from the Hallabong flower, which contained 11% β-ocimene. The hydro-distilled natural oils from the Hallabong flower (Citrus medica L. var. sarcodactylis) inhibited the lipopolysaccharide (LPS)-induced production of COX-2 enzyme on LPS-stimulated RAW 264.7 cells. Furthermore, it suppressed PGE2 production in a dose-dependent way, with an IC50 value of less than 0.01%. It is clear that the interaction energy of the limonene compound is lower in COX-2 (−6.904) than in COX-1 (−8.536), indicating that it is a selective COX-1 inhibitor. Nevertheless, only hydrophobic linkages between limonene and COX-1 could be seen, even though many amino acid residues are implicated in a specific binding mechanism.

    Table 3.  Summary of binding interactions and top-ranked LEO phytochemicals screened against COX-1 receptor (PDB ID: 3N8Y) binding site.
    PubChem ID Compound name Binding affinity (kcal/mol) Active amino acids residues Distance (Å) Category Type
    22311 Limonene −8.536 LEU353 5.20786 Hydrophobic Alkyl
    VAL318 4.48233
    LEU321 4.09047
    ILE492 4.95029
    VAL318 4.93115
    ILE492 4.84844
    ALA496 3.85553
    LEU321 5.04185
    ALA496 4.71957
    PHE350 5.39045 Hydrophobic Pi-alkyl
    TYR354 4.42773
    TRP356 4.93007

    17100 α-Terpineol −8.535 VAL318 4.16085 Hydrophobic Alkyl
    LEU321 4.26425
    ILE492 5.17717
    VAL318 4.00893
    ALA496 3.92114
    LEU353 4.90529
    LEU321 5.24608
    ALA496 4.62466
    PHE350 5.37118 Hydrophobic Pi-alkyl
    TYR354 4.48363
    TRP356 4.93781

    7463 p-Cymene −8.515 GLY495 4.23719 Hydrophobic Amide-Pi stacked
    VAL318 4.34579 Hydrophobic Alkyl
    LEU353 4.55204
    LEU321 5.16326 Hydrophobic Pi-alkyl
    ALA496 4.90846
    PHE350 5.35724
    TYR354 4.5216
    TRP356 4.93121

    11142 β-Phellandrene −8.486 VAL318 5.09711 Hydrophobic Alkyl
    ILE492 4.24168
    ALA496 4.4928
    LEU353 5.4746
    LEU321 5.43761
    ILE492 5.36154
    ALA496 4.34849
    TYR354 4.54422 Hydrophobic Pi-alkyl
    TRP356 4.96094

    5281553 β-Ocimene −8.463 ALA171 4.33901 Hydrophobic Alkyl
    LEU359 5.24116
    HIS176 4.48699 Hydrophobic Pi-alkyl
    HIS176 4.8897
    HIS176 4.64473
    PHE179 4.52532
    TYR354 5.19321
    HIS355 4.96911
    HIS355 4.2718
    HIS355 4.50183
    HIS357 4.60123

    11230 Terpinen-4-ol −8.438 VAL318 4.4207 Hydrophobic Alkyl
    ALA496 3.96373
    VAL318 4.88286
    ILE492 5.48398
    ALA496 3.53657

    2662 Celecoxib −8.191 GLU316 1.52341 H bond Conventional H bond
    PHE549 2.06864
    SER548 3.10647 H bond Carbon H bond
    GLN319 3.36899 Halogen Halogen (fluorine)
    GLN327 3.53859
    GLU316 4.45539 Electrostatic Pi-Anion
    HIS550 5.08501 Hydrophobic Pi-Pi stacked
    HIS550 4.31237 Hydrophobic Pi-alkyl

    9782 Betamethasone −8.041 HIS355 1.8315 H bond Conventional H bond
    GLU423 1.68056
    HIS357 3.63158 Halogen Halogen (fluorine)
    HIS355 5.48416 Hydrophobic Pi-alkyl

     | Show Table
    DownLoad: CSV
    Figure 4.  Snapshot represents the interaction between some selected ligands and COX-1.

    By inhibiting the production of the inflammatory genes matrix metalloproteinase (MMP)-2 and -9, limonene significantly reduced clinical symptoms and intestinal mucosa destruction in rats with ulcerative colitis (UC). In addition, limonene treatment increased the expression of the proteins COX-2 and inducible nitric oxide synthase (iNOS) as well as antioxidants in UC rats [24]. In order to comprehend the biological and pharmacological effects of limonene on the production of pro-inflammatory mediators and cytokines in macrophage cells, Yoon et al. [25] performed an in vitro study and revealed that limonene prevents LPS from inducing PGE2 and nitric oxide (NO) production in RAW 264.7 cells. The synthesis of the iNOS and COX-2 enzymes was inhibited by limonene in a dose-dependent way. In addition, limonene dose-dependently reduced the production of TNF-α, IL-1β, and IL-6. These findings lead us to suggest that limonene could be a promising anti-inflammatory component.

    Table 4.  Summary of binding interactions and top-ranked LEO phytochemicals screened against COX-2 receptor (PDB ID: 3LN1) binding site.
    PubChem ID Compound name Binding affinity (kcal/mol) Active amino acids residues Distance (Å) Category Type
    2662 Celecoxib −8.673 GLU257 2.19857 Hydrogen bond Conventional H bond
    GLN256 2.02558
    THR179 3.05721
    ASN189 2.64444
    HIS181 3.09038 Pi-donor H bond
    HIS181 4.93934 Hydrophobic Pi-Pi T-shaped
    ILE241 4.7911 Alkyl
    LYS178 5.34418 Pi-alkyl
    VAL258 4.60764
    VAL258 4.75717
    HIS353 5.2587

    31253 Myrcene −8.495 ALA169 4.05042 Hydrophobic Alkyl
    LEU357 5.31713
    LEU358 4.81577
    HIS174 5.05216 Pi-alkyl
    HIS355 4.8889
    HIS174 5.01
    PHE177 4.71421
    HIS353 4.63097
    HIS174 4.97848
    HIS353 4.03611
    HIS355 4.48883
    TRP354 4.65567
    TRP354 4.85802

    10586 α-Bisabolol −8.458 THR179 2.30299 Hydrogen bond Conventional H bond
    HIS181 2.22428
    VAL258 5.14002 Hydrophobic Alkyl
    LYS178 4.15079
    VAL258 5.05092
    VAL258 5.27629
    HIS174 4.48034 Pi-alkyl
    HIS353 4.90952
    HIS181 5.06576
    HIS174 5.19112
    HIS353 3.61505

    5281515 β-Caryophyllene −8.400 VAL258 3.86278 Hydrophobic Alkyl
    HIS174 5.46788 Pi-alkyl
    HIS174 4.71157
    HIS181 4.93027
    HIS174 5.2873
    HIS174 4.58658
    HIS353 4.28092

    5281553 β-Ocimene −8.353 LEU358 4.86083 Hydrophobic Alkyl
    ALA169 4.49891
    LEU357 5.33171
    HIS174 5.05417 Pi-alkyl
    HIS355 4.23129
    HIS174 4.94839
    PHE177 4.929
    HIS353 4.4817
    HIS174 4.89993
    HIS353 4.2914

    5018304 Diclofenac Na −8.313 GLN170 2.90417 Hydrogen bond Conventional H bond
    HIS174 1.4732
    HIS353 4.37635 Hydrophobic Pi-Pi stacked
    HIS355 5.5618 Pi-Pi T-shaped
    HIS174 5.29974 Pi-alkyl
    HIS353 4.33105
    HIS355 3.98766
    VAL414 4.0637

    637566 Geraniol −8.303 TRP354 1.82951 Hydrogen bond Conventional H bond
    HIS355 2.93434 Hydrophobic Pi-sigma
    ALA169 4.25559 Alkyl
    HIS174 4.49101 Pi-alkyl
    HIS174 4.86783
    PHE177 4.76602
    HIS353 4.24043

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    Myrcene exhibits the greatest binding affinity for COX-2 (−8.495 kcal/mol) when compared to standard medications and other investigated substances (Table 3), despite binding to COX-2 residues ALA169, LEU357, LEU358, HIS174, HIS353, HIS355, PHE177, and TRP354 (Table 4 and Figure 5). Its lower binding affinity to COX-1 (−8.332 kcal/mol) than that of limonene, α-terpineol, and p-cymene, however, suggests that it is more competitive for the COX-2 enzyme. It interacts with hydrophobic residues of amino acids on COX-2 via associations with alkyl and pi-alkyl groups.

    Figure 5.  Snapshot represents the interaction between some selected ligands and COX-2.

    Additionally, EOs extracted from aromatic herbs and medicinal plants that contain 10% or less of myrcene have been found to have anti-inflammatory benefits. There is evidence that the oil of Eremanthus erythropappus reduces edema and leukocyte extravasation in several organs, including the hind paw and lung [26],[27]. Another myrcene-rich EO reduced the levels of pro-inflammatory cytokines and COX-2 within eight hours in a rat model of severe synovitis [28]. In arthritic human chondrocytes, pure myrcene reduced the expression of iNOS and interfered with the IL-1 signaling pathway [29]. These data demonstrate that myrcene and myrcene-containing EOs have potent anti-inflammatory and analgesic properties.

    Drug-likeness characteristics are important in determining the quality of emerging anti-inflammatory compounds. Based on their structure, early predictions of the pharmacokinetic behavior of prospective plant-derived EO compounds should aid in the identification of more safe and more efficient leads for further preclinical studies. In this research, we examined five of the most relevant pharmacokinetic and ADME indicators for LEO compounds to see if they may be used as drugs. These anticipated results would demonstrate the compounds' potential as drugs and point to the likelihood of them serving as an oral anti-inflammatory substitute.

    Table 5 shows the outcomes of using Osiris Property Explorer to estimate the drug-likeness of compounds based on several chemical descriptors. The majority of substances have partition coefficients (clog P) values less than 5, although others (such as β-caryophyllene) defy the Lipinski rule of five for lipophilicity and may have low oral bioavailability and penetration. The Lipinski rule of five is clearly broken by the most powerful molecule (β-caryophyllene), which has a log P value of 5.49. In contrast, the other five compounds are predicted to be orally active and have log P values ranging from 4.47 to 1.81. Additionally, compounds are attractive drug candidates for additional study and development because of their lower TPSA score (zero), which indicates favorable drug-like properties, and their high drug-likeness score. The ADME properties and toxicological profile of the LEO molecules were also investigated using an online admetSAR cheminformatic system to detect prospective and secure drug candidate(s) and to screen out substances that are most likely to fail in successive stages of the development process due to unfavorable ADMET properties.

    Table 5.  Drug-likeness prediction through OSIRIS property explorer.
    Mutagenic Tumorigenic Irritant Reproductive effect clog P TPSA Solubility Drug likeness Drug score
    Celecoxib - - - - 2.59 86.36 −4.17 −8.11 0.37
    Myrcene - + + + 4.29 0 −2.5 −7.82 0.09
    α-Bisabolol - - + - 4.47 20.23 −3.16 −1.47 0.27
    β-Caryophyllene - - - - 5.49 0 −3.66 −6.48 0.31
    β-Ocimene - - + - 4.23 0 −2.33 −5.46 0.24
    Diclofenac Na - - - - 1.81 52.16 −4.64 2.3 0.71
    Geraniol - - + - 3.49 20.23 −1.89 −3.57 0.27

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    Drugs' destiny in vivo, or ADME, has a complete or partial impact on how they behave pharmacologically. The blood/brain partition coefficient (Plog BB), Caco-2 cell permeability (PCaco), human intestinal absorption (log HIA), P glycoprotein nonsubstrate and non-inhibitor (log pGI), and probability of Caco-2 cell permeability (log Papp) are among the in silico projected pharmacokinetic (ADME) attributes of all studied ligands and are shown in Table 6.

    According to the findings in Table 6, the chemical β-caryophyllene is not carcinogenic, whereas myrcene and β-ocimene failed the AMES toxicity test and were therefore found to be carcinogenic. The calculated LD50 dosage (1.4040–1.6722 mol/kg) for the selected terpenes in a rat acute toxicity model appears to be secure enough for research on in vivo anti-inflammatory efficacy. A molecule's degree of intestinal absorption after oral delivery is measured by the HIA score. If the score is below one, the absorption can be quite high. All terpenes in the current investigation had HIA scores that range from 0.9538 to 0.9926, indicating that they will be well assimilated from the gastrointestinal tract [30]. The estimated cell permeability (PCaco-2) of selected terpenes, which ranges from 0.7228 to 0.6327, is also reported to be within the acceptable range (−1 to +1), aiding in the transit of the bioactive compounds to the gut and, thus, improving absorption. It may be deduced from the anticipated log BB score (0.9536–0.9312) that these terpenes have the highest likelihood of crossing the blood-brain barrier and having an effect on the function of the central nervous system.

    Table 6.  ADME prediction for the top-ranked compounds using the admetSAR toolbox.
    Blood-brain barrier Human intestinal absorption Caco-2 permeability P-glycoprotein substrate P-glycoprotein inhibitor Renal organic cation transporter AMES toxicity Carcinogens Caco-2 permeability (LogPapp, cm/s) Rat acute toxicity (LD50, mol/kg)
    Celecoxib BBB+ HIA+ Caco2+ - - - - - 1.0149 2.3719
    0.9713 1 0.8866 0.9287 0.8619 0.8582 0.7185 0.7905
    Myrcene BBB+ HIA+ Caco2+ - - - - + 1.5571 1.404
    0.9478 0.9538 0.7228 0.6521 0.701 0.8183 0.9227 0.5684
    β-Caryophyllene BBB+ HIA+ Caco2+ + - - - - 1.5225 1.4345
    0.9536 0.9926 0.6327 0.5779 0.5989 0.8269 0.9167 0.6863
    β-Ocimene BBB+ HIA+ Caco2+ - - - - + 1.5641 1.6722
    0.9312 0.9764 0.6913 0.6792 0.7425 0.8829 0.8917 0.7261
    Diclofenac Na BBB+ HIA+ Caco2+ - - - - - 1.8481 2.855
    0.9827 0.8998 0.8196 0.8827 0.8557 0.8776 0.8443 0.6747
    Geraniol BBB+ HIA+ Caco2+ - - - - - 1.2481 1.6146
    0.9375 0.9846 0.6445 0.5851 0.8865 0.8179 0.9132 0.5055

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    The biological activity spectra of previously known phytochemical compounds were obtained using the online PASS version. These predictions were assessed and made available in Table 7 for flexible usage. The range of biological activities that a chemical substance exhibits when it interacts with different types of biological entities is known as its biological activity spectrum. It allows us to combine information from several sources in the same training set, which is required since no one publication covers all of the diverse aspects of a compound's biological action.

    Table 7.  The PASS prediction findings reveal the biological activity spectrum and toxicity of the top-ranked LEO terpenes.
    Compound name Pa Pi Biological activity spectrum predicted by PASS Pa Pi Possible adverse & toxic effects
    Celecoxib 0.955 0.002 Cyclooxygenase 1 inhibitor 0.671 0.016 Pseudoporphyria
    0.859 0.003 Non-steroidal anti-inflammatory agent 0.569 0.013 Ulcer, peptic
    0.809 0.007 Antiarthritic 0.571 0.02 Methemoglobinemia
    Myrcene 0.941 0.004 Mucomembranous protector 0.829 0.004 Skin irritation, high
    0.896 0.005 Antineoplastic 0.786 0.01 Hyperglycemic
    0.836 0.012 Antieczematic 0.791 0.026 Toxic, respiration
    α-Bisabolol 0.847 0.005 Apoptosis agonist 0.862 0.016 Behavioral disturbance
    0.83 0.013 Antieczematic 0.843 0.003 Skin irritation, moderate
    0.727 0.006 Antithrombotic 0.822 0.02 Conjunctivitis
    β-Caryophyllene 0.915 0.005 Antineoplastic 0.836 0.004 Sensitization
    0.897 0.005 Antieczematic 0.788 0.005 Irritation
    0.745 0.011 Antiinflammatory 0.545 0.062 Nephrotoxic
    β-Ocimene 0.928 0.004 Antieczematic 0.82 0.004 Skin irritative effect
    0.806 0.004 Carminative 0.777 0.004 Lacrimal secretion stimulant
    0.91 0.004 Mucomembranous protector 0.816 0.004 Skin irritation, high
    Geraniol 0.953 0.003 Mucomembranous protector 0.951 0.002 Skin irritation, moderate
    0.77 0.004 Antiulcerative 0.925 0.005 Anemia
    0.766 0.001 Antiviral (rhinovirus) 0.878 0.004 Hyperglycemic
    Limonene 0.961 0.001 Carminative 0.856 0.005 Gastrointestinal disturbance
    0.896 0.005 Antieczematic 0.811 0.015 Respiratory failure
    0.812 0.01 Antineoplastic 0.675 0.005 Sedative
    α-Terpineol 0.862 0.005 Respiratory analeptic 0.887 0.011 Euphoria
    0.837 0.003 Carminative 0.839 0.015 Ocular toxicity
    0.825 0.014 Antieczematic 0.838 0.019 Behavioral disturbance
    p-Cymene 0.919 0.004 Mucomembranous protector 0.961 0.009 Toxic, respiration
    0.881 0.002 Carminative 0.928 0.003 Hematemesis
    0.884 0.006 Antieczematic 0.878 0.004 Gastrointestinal hemorrhage
    β-Phellandrene 0.916 0.004 Antieczematic 0.827 0.012 Ulcer, aphthous
    0.883 0.002 Carminative 0.799 0.005 Irritation
    0.83 0.009 Antineoplastic 0.725 0.032 Conjunctivitis
    β-Ocimene 0.928 0.004 Antieczematic 0.82 0.004 Skin irritative effect
    0.91 0.004 Mucomembranous protector 0.777 0.004 Lacrimal secretion stimulant
    0.858 0.005 Apoptosis agonist 0.754 0.01 Hypomagnesemia
    Terpinen-4-ol 0.838 0.011 Antieczematic 0.852 0.007 Hematemesis
    0.829 0.003 Carminative 0.779 0.023 Ulcer, aphthous
    0.796 0.02 Antiseborrheic 0.702 0.015 Optic neuritis

     | Show Table
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    Pa (probability “to be active”) estimates the chance that the studied compound is belonging to the sub-class of active compounds. Pi (probability “to be inactive”) estimates the chance that the studied compound is belonging to the sub-class of inactive compounds.

    The probable activity (Pa) values were higher than Pa > 0.5, and the probable inactivity (Pi) scores were extremely near to 0, demonstrating that the compound is highly expected to demonstrate these activities. It is also notable that the selected terpenes have very suitable molecular properties and predictable pharmacological activities against COX-1 and COX-2 enzymes.

    A literature survey corroborates the docking finding, revealing that LEO compounds have antibacterial properties [31] and function as antioxidants by reducing lipid peroxidation [32],[33]. As a result, we believe that the chosen phytoconstituents will boost immunity while inhibiting COX enzymes [34]. Anti-inflammatory phytochemical constituents with stronger docking scores, higher binding energies, and better interaction with conserved catalytic residues that may induce inhibition/blockade of the COX protein pathways might be viable preventive and curative options [35],[36].

    There is a pressing need to create new substances with therapeutic action in order to develop drugs with fewer negative effects. The current work assesses the potential for binding interactions between phytocompounds from LEO and COX enzymes by molecular docking. Molecular docking revealed that limonene has the highest negative binding affinity in complex with COX-1, followed by α-terpineol and p-cymene. Myrcene exhibits the greatest binding affinity for COX-2 when compared to standard medications, followed by α-bisabolol and β-caryophyllene. The LEO's chosen phytochemicals were found to be highly selective, have substantial binding potential, and react strongly with COX-1 and COX-2 receptors by computational screening. Best docking scores, ligand placement at the region of inhibition, interaction profiles with catalytic residues, and appropriate ADMET values all point to the likelihood that myrcene and β-ocimene may be effective COX inhibitors. Based on satisfying Lipinski's rule five, these terpenes can also be identified as prospective therapeutic candidates.



    Conflict of interest



    The authors declare no conflict of interest.

    Author contributions



    B.S.B.: original draft preparation; A.B.: review and editing. All authors have read and agreed to the published version of the manuscript.

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