Insilico Pharmacological Profiling of Endostemon Viscosus Bioactive Compounds Targeting MMP-9 for Wound Healing

Insilico Pharmacological Profiling of Endostemon Viscosus Bioactive Compounds Targeting MMP-9 for Wound Healing | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Insilico Pharmacological Profiling of Endostemon Viscosus Bioactive Compounds Targeting MMP-9 for Wound Healing Kavi Malar Surendran, Saradha Maran, Sugandhi Pugazhendhi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6789028/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Nov, 2025 Read the published version in In Silico Pharmacology → Version 1 posted 7 You are reading this latest preprint version Abstract Plants have been valuable sources of bioactive compounds with therapeutic potential. The exploration of phytochemicals in plant extracts and essential oils has gained attention due to their biological activities and medicinal properties. This study investigated the phytochemicals in methanolic extracts and essential oils by analyzing molecular docking and toxicological profiles of their bioactive and pharmacokinetic properties. Molecular docking using AutoDock Vina, integrated within PyRx version 0.8, was employed to dock the chemicals into MMP-9 protein 1L6J. Among these, the highest-scoring compounds underwent pharmacokinetics, receptor-ligand interactions, and binding affinity analysis after identification by GC-MS analysis. To prepare the grid boxes for docking, the active sites of MMP-9 were predicted using CASTp. The findings revealed that several active ingredients in the methanolic extract, particularly 3-fluoro-5-trifluoromethylbenzoic acid, exhibited significant affinity for MMP-9 and strong interactions, including hydrogen bonding with the key residue TYR 52. Conversely, most interactions formed by the essential oil compounds were hydrophobic. In addition to their biological activity, ADME prediction indicated that both the methanol extract and essential oil possessed adequate drug-likeness characteristics, such as high gastrointestinal absorbability and low permeability through the blood-brain barrier. Based on the toxicological predictions using AdmetSAR 1, the compounds were moderately toxic (class III); however, there were no indications of carcinogenic risk. The observed characteristics of bioactive chemicals derived from E. viscosus support their potential application in wound healing, suggesting that these compounds have favorable pharmacokinetic and safety profiles and exhibit a high MMP-9 inhibitory capacity. MMP-9 E.viscosus. essential oil methanolic extract Molecular docking ADMET wound healing Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Plant-derived bioactive compounds have garnered significant attention in the field of therapeutic research due to their diverse biological activities and potential medicinal applications (Zou et al. 2021 ). These natural substances, extracted from various plant sources, exhibit a wide range of beneficial effects, including anti-inflammatory, antioxidant, antimicrobial, and neuroprotective properties (Gangwar et al. 2021 ). The growing interest in these compounds stems from their systemic pleiotropic effects, minimal side effects, and low toxicity, making them attractive candidates for natural therapeutic agents against various disease conditions. One area of particular interest is the potential application of plant-derived bioactive compounds in wound healing. The wound healing process involves complex interactions between various cellular and molecular components, including matrix metalloproteinases (MMPs). Among these, MMP-9 plays a crucial role in tissue remodeling and wound closure. However, excessive activation of MMP-9 can impede the healing process, especially in chronic wounds (Zhou et al. 2019 ; Lan et al. 2021 ). Therefore, the inhibition of MMP-9 has emerged as a promising strategy to enhance wound healing by reducing excessive tissue breakdown, decreasing inflammation, and restoring the balance between MMPs and their inhibitors. Recent studies have highlighted the potential of natural compounds in inhibiting MMP-9 activity. For instance, flavonoid-rich fractions from plants such as Glycyrrhiza glabra and Sophora japonica have demonstrated wound healing potential, as evidenced by molecular docking studies of their major constituents with wound healing-related proteins (Aly et al. 2023 ). These findings suggest that in silico pharmacological profiling of bioactive compounds from medicinal plants could be a viable approach for identifying potential MMP-9 inhibitors for wound-healing applications. In this context, the present study focuses on Endostemon viscosus , a plant species with potential medicinal properties. Despite the lack of specific information regarding this plant, the study aims to explore its phytochemical composition and evaluate the potential of its bioactive compounds as MMP-9 inhibitors for wound healing applications. The research employs a comprehensive approach, combining GC-MS analysis of methanolic and oil extracts, molecular docking studies, and ADMET property evaluations to assess the pharmacokinetic behaviour and drug-likeness of the identified compounds. By integrating these analytical approaches, this study seeks to provide a thorough understanding of the phytochemical composition, potential biological activities, and safety profile of Endostemon viscosus . The findings may contribute to the development of novel therapeutic agents and inform future investigations of the medicinal properties of this plant species, potentially advancing the field of natural product-based wound healing therapies. Materials and Methods Target protein Preparation MMP-9 The crystallographic three-dimensional structure of human matrix metalloproteinase 9 (MMP-9), identified by PDB ID 1L6J, was sourced from the Protein Data Bank ( http://www.rcsb.org/ ). The protein structure was elucidated and experimentally validated using X-ray diffraction at a resolution of 2.5 Å. Subsequently, the three-dimensional structure was processed using Biovia Studio, where ligands, co-ligands, heteroatoms, and water molecules were removed to create an appropriate environment for docking (Kundu et al. 2022 ). Further optimization of the protein structure was conducted using AutoDock Tools (PyRx), which involved the addition of charges, energy minimization, and conversion to the PDBQT format. These optimized structures were then used for subsequent analyses. Active site prediction and grid generations Active site prediction and grid generation require a precise assessment of the active site during docking. Potential binding sites for amino acid residues associated with the target protein were identified using CASTp. (2018), web service (Computed Atlas for Surface Topography of Proteins). Ligand preparation and retrieval Ligand preparation and retrieval involved selecting the top six compounds from the methanolic extract and six compounds from the essential oil out of 37 and 27 compounds identified by GC-MS, respectively ( https://pubchem.ncbi.nlm.nih.gov/ ). The three-dimensional chemical structures were downloaded in SDF format from the PubChem database of the National Center for Biotechnology Information, 2021. The methanolic extract ligands included Avenanthramide B (Pubchem CID: 10087955), 3-Amino-1-phenyl-2-pyrazolin-5-one (Pubchem CID: 77794), (4,6-Diamino-1,3,5-triazin-2-yl) cyanamide (Pubchem CID: 592015), Heptanoic acid, 4-methoxyphenyl ester (Pubchem CID: 579908), 3-Fluoro-5-trifluoromethylbenzoic acid, 2-nitro-5-fluorophenylester (Pubchem CID: 91730956), and 3,4-Dihydroisoquinoline,1-[3-methoxybenzyl]-6-methoxy (Pubchem CID: 624494). The essential oil ligands comprised (1R,4R)-1-methyl-4-(6-Methylhept-5-en-2-yl) cyclohex-2-enol (Pubchem CID: 13213649), caryophyllene oxide (Pubchem CID: 1742210), 3-Cyclohexen-1-ol, 4-methyl-1-(1-methylethyl)- (R) (Pubchem CID: 5325830), 1-Isopropyl-4,7-dimethyl-1,2,3,5,6,8a-hexahydronaphthalene (Pubchem CID: 10233), d-limonene (Pubchem CID: 440917), and methyleugenol (Pubchem CID: 7127). Molecular docking of MMP-9 Auto Dock Vina (PyRx software version 0.8) was employed to conduct molecular docking between the prepared receptor and ligands (Dallakyan and Olson 2015 ). Utilizing default parameters, the macromolecule (1L6J) was docked against the top five ligands derived from the methanolic and essential oil extracts, with default settings applied. During the docking phase, the ligands were considered flexible, whereas the protein was treated as rigid. A grid parameter configuration file was developed using the binding amino acids analyzed from CASTp. Upon completion of the separate protein-ligand docking and retrieval of the PDBQT output files, binding affinities (kcal/mol) were recorded in a CSV file. It was concluded that the ligand exhibiting the strongest interaction possessed the highest negative binding energy. Visualization and post docking analysis of MMP-9 The three-dimensional and two-dimensional interactions of the docked complexes were visualized and analyzed using the Biovia Discovery Studio Visualizer version 24.1.0.23298 (BIOVIA, Dassault Systemes, 2019). Various receptor-ligand interactions, including hydrogen bonding and hydrophobic interactions, were evaluated. Pharmacokinetic properties analysis of MMP-9 The Swiss ADME web server, a freely accessible tool introduced in 2017, SwissADME. (2017) ( http://www.swissadme.ch/ ) was employed to evaluate the ADME profile of each selected compound. This evaluation encompassed drug-likeness (as per Lipinski's rule of five), solubility profile, lipophilicity, pharmacokinetic properties, medicinal chemistry, and gastrointestinal absorption profile (GIT). Toxicology properties prediction of MMP-9 Prior to the initiation of clinical studies, it is imperative to evaluate the safety profiles of these compounds. The use of in silico toxicity profile prediction offers advantages in terms of speed, accuracy, and accessibility, leading to significant savings in time, cost, and effort. The admetSAR1 (2012), a web-based tool available at http://lmmd.ecust.edu.cn/admetsar1 , which is both user-friendly and cost-free, was employed to analyze the toxicity profiles and potential adverse effects of the selected four compounds. This server provides predictions on carcinogenicity, acute oral toxicity, rat acute toxicity (LD50), biodegradation, and the inhibition of human ether-a-go-go-related genes. Results Active site prediction and grid generation of MMP-9 CASTp analysis has delineated the functional binding regions of MMP-9, identifying critical active site residues: 34, 35, 36, 38, 39, 44, 47, 48, 51, 52, 92, 94–98, 182, 184–187, 209, 213, 215, 216, 232, 233, 242, 334, 338, 366–368, 370, 371, 387–393, 423–425 in Chain A, as illustrated in Table 1 and Fig. 1 . A grid box was configured to encompass these binding sites for the subsequent docking analysis. Table 1 Predicted actives for target protein (1L6J) for wound healing activity. S.No Surface area Volume Site Residues 1 841.248 1233.188 Chain A 34,35,36,38,39,44,47,48,51,52,92,94,95,96,97,98,182,184,185,186,187,209,213,215,216,232,233,242,334,338,366,367,368,370,371,387,388,389,390,391,392,393,423,424,425 Molecular docking The evaluation of bioactive compounds from E. viscosus has focused on assessing their potential as drug candidates. This study examined 37 compounds from the methanolic extract and 27 from the essential oil extract, applying Lipinski's Rule of Five and ADME analysis to determine their drug-likeness. This screening process is crucial in early-stage drug discovery as it helps identify compounds with favorable physicochemical properties that are likely to be orally active in humans. The analysis revealed that 14 compounds from the essential oil extract and 10 compounds from the methanolic extract met these criteria, suggesting their potential for further investigation as drug candidates. Following the initial screening, the selected compounds underwent molecular docking studies against the 1L6J protein (Chain A) using PyRx software. This computational approach aims to predict the binding affinity and interaction modes between compounds and the target protein. The results of these docking studies, presented in Tables 2 and 3 , provide insights into the potential effectiveness of these compounds as inhibitors or modulators of target proteins. Furthermore, Tables 4 and 5 offer a comprehensive list of compounds that not only exhibit drug-like properties but also demonstrate strong binding energies (below − 7 kcal/mol) in their interactions with the protein. This information is valuable for prioritizing compounds for further experimental validation and optimization of the drug discovery pipelines. Table 2 GC-MS identified phyto constituents from methanolic extract of E. viscosus based on Lipinski’s rule and ADME properties for wound healing S.No Compound Name Lipinski’s Rule of 5 (Ro5) violation ADME based exclusion 1* 3,4-Dihydroisoquinoline,1-[3-methoxybenzyl]-6-methoxy No No 2* P - Methoxyheptnophene No No 3* Heptanoic acid, 4-methoxyphenyl ester No No 4* 3 - Fluoro-5-trifluoromethylbenzoic acid, 2-nitro-5-fluorophenylester No No 5* Avenanthramide B No No 6* 3 - Amino-1-phenyl-2-pyrazolin-5-one No No 7* 1-Methyl-1H-imidazole-4-carboxylic acid No No 8* (4,6 - Diamino-1,3,5-triazin-2-yl) cyanamide No No 9* 2-Furancarbodithioic acid, ethyl ester No No 10 Thiophene, 3-methyl Yes (Low HBA) low solubility 11 Methyl acetoxyacetate Yes (Low MW) Rapid Metabolism 12 Benzene, 1,2,3-trimethyl- Yes (High Log P) Low Bioavailability 13 Methoxyacetaldehyde diethyl acetal Yes (High Log P) Poor Absorption 14 Cyclopentanecarboxylic acid, 1-(2-ethyl-1-oxobutoxy)-2-oxo-, ethyl ester Yes (High MW) Poor Solubility 15 1-Nonene, 4,6,8-trimethyl- Yes (High Log P) Poor Permeability 16 5-[4-(Carboxyadamanthyl-3)-phenyl]-10,15,20-triphenyl-21H,23H Yes (High MW, Log P) Poor Absorption 17 Benzene,1-methyl-4(1,2,2-trimethylcyclopentyl) Yes (High Log P) Low Metabolism 18 Cycloocta-1,3,6-triene,2,3,5,5,8,8-hexamethyl- Yes (High MW) Poor Absorption 19 2H-1-benzopyran-2-one, 3,4-dihydro-4,4,6-trimethyl Yes (High Log P) Low Bioavailability 20 Tridecene,5-propyl Yes (High Log P) Poor Absorption 21 Heptadecane,3-methyl Yes (High Log P) Low Metabolism 22 Decane,5-propyl- Yes (High Log P) Poor Permeability 23 Heptacosane Yes (High MW) Low Solubility 24 Pentadecanoic acid, 14-methyl-, methyl ester Yes (High Log P) Poor Absorption 25 Phthalic acid, cis-hex-3-enyl,octadecyl ester Yes (High MW, Log P) Poor Bioavailability 26 3-Penten-2-one Yes (High Log P) Rapid Metabolism 27 2,4-Diamino-6-cyanamino-1,3,5-triazine Yes (High MW) Poor Absorption 28 Eicosane, 1-iodo Yes (High MW, Log P) Poor Solubility 29 Caprolactone oxime, (NB)-O- Yes (High MW) Poor Metabolism 30* Nonane, 5-methyl-5-propyl- No No 31 1-Butyl-1-methyl-1,2,3,4-tetrahydroisoquinoline 2-(dimethylamino) Yes (High Log P) Low Permeability 32 4,4-bi-4H-pyran,2,2,6,6-tetrakis(1,1-dimethylethyl)-4,4-dimethyl- Yes (High MW) Poor Absorption 33 2,2,4,4-Tetrahydroxybenzophenone, tetrakis(tert-butyldimethylsilyl) ether Yes (High MW, Log P) Low Bioavailability 34 Phthalic acid, 4-nitrophenyl 2-propyl ester Yes (High LogP) Poor Solubility 35 Phenyl 4-[(Trimethylsilyl)amino] benzoate Yes (High MW, Log P) Poor Absorption 36 Perfluorobutyramide, N-allyl-N-(hept-2-yl) Yes (High Log P), Poor Permeability 37 I-Leucine, n-pentafluorobenzoyl-,pentadecyl ester Yes (High MW, Log P) Poor Absorption HBA−Hydrogen Bond Acceptor, MW: molecular Weight, LogP− logarithm of the partition coefficient (P) Octanol−Water purification Coefficient, ADME− Absorption, Distribution, Metabolism and Excretion, Ro5−Lipinski’s rule of five . Table 3 GC-MS identified phytoconstituents from essential oil of E. viscosus based on Lipinski’s rule and ADME properties for wound healing S.No Compound Name Lipinski’s Rule of 5 (Ro5) violation ADME based exclusion 1* 3-Carene No No 2* Beta-Phellandrene No No 3* D-Limonene No No 4* γ-Terpinene No No 5* Linalool No No 6* 3-Cyclohexen-1-ol, 4-methyl-1-(1-methylethyl)-,(R) No No 7 α-Cubebene Yes (LogP > 5) low aqueous solubility 8* Methyleugenol No No 9 Bicyclo[5.2.0]nonane, 2-methylene-4,8,8-trimethyl-4-vinyl Yes (LogP > 5) high hydrophobicity 10 1,4,7-Cycloundecatriene, 1,5,9,9-tetramethyl-,z,z,z Yes (LogP > 5) low permrability 11* (1R,2S,6S,7S,8S)-8-Isopropyl-1-methyl-3-methylenetricyclo[4.4.0.02,7] decane-rel No No 12* 1-Isopropyl-4,7-dimethyl-1,2,3,5,6,8a-hexahydronaphthalene No No 13* Nerolidol 2 No No 14* Caryophyllene oxide No No 15* (1R,4R)-1-methyl-4-(6-Methylhept-5-en-2-yl)cyclohex-2-enol No No 16* αR-Turmerone No No 17* Tetradecanoic acid No No 18 Isopimara-9(11),15-diene Yes (LogP > 5) high hydrophobicity 19 1-Napthalenepropanol, α-ethenyldecahydro-α,5,5,8a-tetramethyl-2-methylene Yes (LogP > 5) low water solubility 20 (4as,10aS)-7Isopropyl-1,1,4a-trimethyl-1,2,3,4a,5,6,9,10,10a-decahydrophenanthrene Yes (LogP > 5) high hydrophobicity 21 Phenanthrene, 1,2,3,4,4a,9,10,10a-octahydro-1,1,4a-trimethyl-7-(1-methylethyl) Yes (LogP > 5) poor permeability 22 Trans-Kaur-16-ene Yes (LogP > 5) low metabolic stability 23 1-Naphthalenepropanol, α-ethenyldecahydro-[1α(R),2β,4aβ,8aα] Yes (LogP > 5) low absorption 24 Kaur-16-ene Yes (LogP > 5) high lipophilicity 25* (2S,4aR,5S,8aR)-5-((S)-3-hydroxy-3-methylpent-4-methylenedecahydronaphthalen-2-ol No No 26 1-Phenanthrenemethanol, 1,2,3,4,4a,9,10,10a-octahydro-(1α,4aα,10aβ) Yes (LogP > 5) poor permeability 27 Heneicosane Yes (LogP > 5), high MW extremely poor solubility MW − molecular Weight, LogP− logarithm of the partition coefficient (P) Octanol−Water purification coefficient; ADME − absorption, distribution, metabolism and Excretion, Ro5−Lipinski’s rule of five . Table 4 Binding affinity and hydrogen bond interactions of GC-MS identified bioactive compounds from methanolic extract of E.viscosus for wound healing S.No GCMS compounds Binding affinity No. of H bonds H bonds Hydrophobic interactions 1 10087955 Avenanthramide B -7.5 4 MET 422, ARG 422, PRO 415, ALA 417 LEU 397, LEU 418, VAL 398, MET 422, ALA 417 2 77794 3-Amino-1-phenyl-2-pyrazolin-5-one -7.7 3 ARG 424, PRO 430, GLU 416 VAL 398, MET 422, ALA417, LEU 397, LEU 418 3 592015 (4,6-Diamino-1,3,5-triazin-2-yl) cyanamide -7.2 3 ARG 424, TYR 420, ALA 417 MET 422, LEU418, ALA 417, LEU 397, PHE 425, LEU 188, VAL 398, CYS 99 4 579908 Heptanoic acid, 4-methoxyphenyl ester -7.5 2 HIS 401, ARG 424 LEU 418, LEU 397, MET 422, VAL 398, LEU 188, CYC 99, ALA 189 5 91730956 3-Fluoro-5-trifluoromethylbenzoic acid, 2-nitro-5-fluorophenylester -8.0 1 TYR 52 LEU 187, LEU 39, LEU 44, MET 94 6 624494 3,4-Dihydroisoquinoline,1-[3-methoxybenzyl]-6-methoxy -7.5 1 TYR 52 LEU 44, LEU 187, MET 94, LEU 39 Table 5 Binding affinity and hydrogen bond interactions of GC-MS identified bioactive compounds from essential oil of E.viscosus for wound healing S.No GCMS compounds Binding affinity No. of H bonds Interactions Hydrophobic interactions 1 13213649 (1R,4R)-1-methyl-4-(6-Methylhept-5-en-2-yl)cyclohex-2-enol -7.7 - Van der Waals, alkyl, pi-alkyl VAL 398, LEU 188, CYS99 2 1742210 Caryophyllene oxide -7.5 - Van der Waals, carbon hydrogen bond, alkyl MET 94, LEU 187, LEU 39, LEU 44 3 5325830 3-Cyclohexen-1-ol, 4-methyl-1-(1-methylethyl)-,(R) -7.1 1 MET 94 ALA 417, LEU 188, VAL 398, LEU 397, MET 422, LEU 188 4 10233 1-Isopropyl-4,7-dimethyl-1,2,3,5,6,8a-hexahydronaphthalene -7 - Van der Waals, alkyl LEU 39, MET 94, LEU 187, LEU 44 5 440917 D-Limonene -6.8 - Van der Waals, alkyl, pi-alkyl LEU 418, ALA 417, MET 422, LEU 397, VAL 398, LEU188, CYS 99 6 7127 Methyleugenol -6.8 - Van der Waals, pi-alkyl, alkyl, carbon hydrogen bond, pi-pi stacked, pi-sigma ALA 417, MET 422, LEU 418, LEU 397, LEU188, VAL-398, CYC-99 The in silico analysis revealed significant binding affinities for compounds from both the methanolic extract and essential oil of E. viscosus . In the methanolic extract, 3-fluoro-5-trifluoromethylbenzoic acid demonstrated the highest binding affinity (-8.0 kcal/mol), interacting with TYR 52. Other compounds, such as 3-Amino-1-phenyl-2-pyrazolin-5-one, Avenanthramide B, and 4-methoxyphenyl ester of hexanoic acid, exhibited strong binding affinities and formed hydrogen bonds with key residues. These interactions, along with hydrophobic interactions involving residues like MET 422, ARG 422, and TYR 420, contribute to the stability of the ligand-protein complexes. The essential oil compounds also showed notable binding affinities, with (1R, 4R) 6-Methylhept-5-en-2-yl-1-methyl-4-Cyclohex-2-enol exhibiting the highest at -7.7 kcal/mol. This compound interacted with VAL 398, LEU 188, and CYS 99 through various non-covalent interactions. Other compounds, including Caryophyllene oxide, D-Limonene, and Methyleugenol, primarily engaged in hydrophobic interactions with minimal hydrogen bonding. This suggests that the wound-healing potential of E. viscosus essential oil is predominantly based on hydrophobic interactions rather than hydrogen bonds, providing insight into the mechanism of action for these compounds. The molecular docking analysis revealed intricate interactions between the bioactive compounds from both the methanolic extract and essential oils of E. viscosus with the target protein. Figures 2 and 3 demonstrate that compounds from the methanolic extract effectively occupied the binding pockets of the protein, engaging in multiple types of molecular interactions. These interactions include hydrogen bonding, which provides specificity and directionality to the binding, van der Waals forces that contribute to the overall stability of the complex, and hydrophobic interactions that play a crucial role in the binding affinity. Similarly, Figs. 4 and 5 illustrate that compounds from essential oils also occupied the binding pockets, participating in the same types of molecular interactions. However, a notable difference was observed between the two extracts. The bioactive compounds from the methanolic extract of E. viscosus exhibited a higher number of hydrogen bonds and stronger binding potential compared to those from essential oils. This enhanced binding profile suggests that the methanolic extract compounds may have a more pronounced effect on the target protein, potentially leading to more efficient modulation of its activity. These findings provide molecular-level support for the role of E. viscosus compounds, particularly those from the methanolic extract, in wound healing mechanisms. The stronger interactions observed with the methanolic extract compounds indicate their potential superiority in influencing the biological processes involved in wound repair, although further experimental validation would be necessary to confirm this hypothesis. ADME (Absorption, Distribution, Metabolism, Excretion) properties of MMP-9 The methanolic extract and essential oil components of E. viscosus exhibited promising characteristics for wound healing applications, as demonstrated by in silico pharmacokinetics and drug-likeness analyses (Tables 6 and 7 ). The methanolic substances showed high gastrointestinal absorption (GI), with only one compound (3,4-Dihydroisoquinoline,1-[3-methoxybenzyl]-6-methoxy) capable of crossing the blood-brain barrier. These substances also inhibited key CYP enzymes (CYP2C9, CYP2D6, CYP1A2, CYP2C19, and CYP3A4) but were not substrates of P-glycoprotein. While meeting Lipinski's Rule of Five criteria for drug-likeness, some compounds presented Brenk alerts due to structural concerns. Table 6 In-Silico pharmacokinetics and drug-likeness of bioactive compounds from E.viscosus methanolic extract for wound healing activity Parameters Avenanthramide B 3-Amino-1-phenyl-2-pyrazolin-5-one (4,6-Diamino-1,3,5-triazin-2-yl) cyanamide Heptanoic acid, 4-methoxyphenyl ester 3-Fluoro-5-trifluoromethylbenzoic acid, 2-nitro-5-fluorophenylester 3,4-Dihydroisoquinoline,1-[3-methoxybenzyl]-6-methoxy Physiochemical properties MW (Da) g/mol 329.30 175.19 151.13 236.31 347.19 281.35 H-bond donors 4 1 3 0 0 0 H-bond acceptors 6 2 4 3 9 3 Rotable bonds 6 1 2 8 5 4 Lipophilicity Consensus Logp 1.89 0.78 -0.99 3.54 3.84 3.37 Water solubility Log S (ESOL) -3.44 -1.43 -0.89 -3.63 -4.71 -3.75 Log S (Ali) -4.60 -1.17 -1.85 -4.55 -5.48 -3.50 Pharmacokinetics GI absoorption High High High High High High Bbb permeant NO No No No No Yes P-gp substrate No No No No No No CYP enzymes inhibitor CYP2C9 - - CYP2D6 CYP1A2, CYP2C19, Cyp2C9 CYP1A2, CYP2C19, CYP3A4 Drug likeness Lipinski 0 V 0 V 0V 0V 0V 0V Medicinal chemistry PAINS 0 alert 0 alert 0 alert 0 alert 0 alert 0 alert Brenks 2 alerts: Hydroquinone, Michael acceptor 0 alert 2 alerts: cyanate aminonitrile thiocyanate, enamine 1 alert: phenol ester 3 alerts: nitro group, oxygen nitrogen single bond, phenol ester 0 alert MW (Da)- Molecular Weight (Daltons), 0 V- 0 violations, Consensus LogP- Consensus Partition Coefficient (LogP), Log S (ESOL)- Logarithm of Water Solubility predicted by the ESOL model, Log S (Ali)Logarithm of Water Solubility predicted by Ali model, GI absorption – Gastrointestinal Absorption (High/Low ) , BBB permeant – Blood-Brain Barrier Permeability (Yes/No), P-gp substrate – Substrate of P-glycoprotein, related to drug efflux, PAINS – Pan-Assay Interference Compounds (alerts for potential false positives), CYP enzyme inhibitor – Cytochrome P450 Enzyme Inhibition . Table 7 In-Silico pharmacokinetics and drug-likeness of bioactive compounds from E.viscosus essential oil for wound healing activity Parameters (1R,4R)-1-methyl-4-(6-Methylhept-5-en-2-yl) cyclohex-2-enol Caryophyllene oxide 3-Cyclohexen-1-ol, 4-methyl-1-(1-methylethyl)-,(R) 1-Isopropyl-4,7-dimethyl-1,2,3,5,6,8a-hexahydronaphthalene D-Limonene Methyl eugenol Physiochemical properties MW (Da) g/mol 222.37 220.35 154.25 204.35 136.23 178.23 H-bond donors 1 0 1 0 0 0 H-bond acceptors 1 1 1 0 0 2 Rotable bonds 4 0 1 1 1 4 Lipophilicity Consensus Logp 3.79 3.68 2.60 4.12 3.37 2.58 Log S (ESOL) -3.64 -3.45 -2.78 -3.43 -3.50 -2.61 Log S (Ali) -4.40 -3.51 -3.36 -3.49 -4.29 -2.55 Pharmacokinetics GI absoorption High High High High Low High Bbb permeant Yes Yes Yes No Yes Yes P-gp substrate No No No No No No CYP enzymes inhibitor CYP2C9 CYP2C9, CYP2C19 - CYP2C9, CYP2C19 CYP2C9 CYP1A2 Drug likeness Lipinski 0V 0 V 0V Yes; 1 violation: MLOGP > 4.15 0V 0V Medicinal chemistry PAINS 0 alert 0 alert 0 alert 0 alert 0 alert 0 alert Brenks 1 alert: Isolated alkene 2 alerts: Three-membered heterocycle, isolated_alkene 1 alert: isolated alkene 1 alert: isolated alkene 1 alert: isolated alkene 1 alert: isolated alkene MW (Da)- Molecular Weight (Daltons), Consensus LogP- Consensus Partition Coefficient (LogP), Log S (ESOL)- Logarithm of Water Solubility predicted by the ESOL model, Log S (Ali)Logarithm of Water Solubility predicted by Ali model, GI absorption – Gastrointestinal Absorption (High/Lsow ) , BBB permeant – Blood-Brain Barrier Permeability (Yes/No), P-gp substrate – Substrate of P-glycoprotein, related to drug efflux, PAINS – Pan-Assay Interference Compounds (alerts for potential false positives), CYP enzyme inhibitor – Cytochrome P450 Enzyme Inhibition . The essential oil compounds similarly displayed favorable properties, with most exhibiting high gastrointestinal absorption except for d-limonene. All but one compound (1-Isopropyl-4,7-dimethyl-1,2,3,5,6,8a-hexahydronaphthalene) (Lipinski violation MLOGP > 4.15)showed blood-brain barrier permeability. Several essential oil compounds inhibited specific CYP enzymes (specifically CYP2C9, CYP2C19, and CYP1A2), but none were P-glycoprotein substrates. Although no PAINS alerts were detected, some structures presented Brenk alerts due to solitary alkenes and three-membered heterocycles. Overall, both the methanolic extract and essential oil components of E. viscosus demonstrated favorable pharmacokinetic and drug-likeness properties, suggesting their potential for wound healing applications. Toxicology properties of MMP-9 The methanolic extract and essential oil of E. viscosus have garnered attention for their wound-healing and antioxidant properties. To further assess their potential therapeutic applications, the bioactive compounds derived from these sources were subjected to carcinogenicity and acute oral toxicity evaluations using ADMESAR 1. The results, presented in Tables 8 and 9 , provide valuable insights into the safety profile of these compounds. All evaluated compounds were classified as Class III in terms of wound healing activities, indicating moderate toxicity. This classification suggests that while these compounds may have some level of toxicity, they do not pose significant toxicological concerns, which is promising for their potential use in therapeutic applications. Table 8 Toxicity Profile of Bioactive Compounds from Methanolic Extract of Endostemon viscosus for Wound Healing Activity S.No Compounds Carcinogenicity Acute oral toxicity 1 Avenanthramide B No III-Moderate toxicity 2 3-Amino-1-phenyl-2-pyrazolin-5-one No III-Moderate toxicity 3 (4,6-Diamino-1,3,5-triazin-2-yl) cyanamide No III-Moderate toxicity 4 Heptanoic acid, 4-methoxyphenyl ester No III-Moderate toxicity 5 3-Fluoro-5-trifluoromethylbenzoic acid, 2-nitro-5-fluorophenylester No III-Moderate toxicity 6 3,4-Dihydroisoquinoline,1-[3-methoxybenzyl]-6-methoxy No III-Moderate toxicity Table 9 Toxicity Profile of Bioactive Compounds from Methanolic Extract of Endostemon viscosus for Wound Healing Activity S.No Compounds Carcinogenicity Acute oral toxicity 1 (1R,4R)-1-methyl-4-(6-Methylhept-5-en-2-yl) cyclohex-2-enol No III-Moderate toxicity 2 Caryophyllene oxide No III-Moderate toxicity 3 3-Cyclohexen-1-ol, 4-methyl-1-(1-methylethyl)-,(R) No III-Moderate toxicity 4 1-Isopropyl-4,7-dimethyl-1,2,3,5,6,8a-hexahydronaphthalene No III-Moderate toxicity 5 D-Limonene No III-Moderate toxicity 6 Methyl eugenol No III-Moderate toxicity Furthermore, the evaluation revealed that none of the bioactive compounds exhibited carcinogenic properties, which is a crucial finding for their potential use in medical treatments. The majority of these compounds were found to be generally non-carcinogenic, further supporting their safety profile. The moderate levels of oral toxicity observed in these bioactive compounds from E. viscosus suggest that they may be suitable candidates for therapeutic applications. This combination of wound healing and antioxidant properties, coupled with a favorable toxicity profile, opens up possibilities for developing new treatments or enhancing existing ones using these natural compounds. However, further research and clinical trials would be necessary to fully establish their efficacy and safety for specific medical applications. Discussion The findings of this study highlight the potential of E.viscosus extract as a source of bioactive compounds with therapeutic applications. Through computational methods, researchers have identified compounds that meet drug-likeness criteria and exhibit promising binding affinities to the 1L6J protein. The analysis revealed that both methanolic and essential oil extracts contained compounds capable of interacting with the target protein through various non-covalent interactions, including hydrogen bonding, van der Waals forces, and hydrophobic interactions (Wang et al. 2022 ). Notably, the methanolic extract compounds demonstrated a higher number of hydrogen bonds and stronger binding potential than the essential oil-derived compounds, aligning with the understanding that hydrogen bonding significantly contributes to protein-ligand complex stability (Schiebel et al. 2018 ). This study is part of a broader trend in utilizing computational methods to screen plant-derived compounds for drug discovery. Similar studies have been conducted on various plant species including Gymnema sylvestre (Nganso Ditchou et al. 2024 ), Pleurotus ostreatus (Effiong et al. 2024 ), Wedelia trilobata (Gowtham et al. 2023 ), Teucrium polium (Noumi et al. 2020 ) and Caulerpa racemosa (Tassakka et al. 2023). These studies typically involve extracting compounds from plant materials, identifying them through techniques such as GC-MS or HPLC, conducting in silico molecular docking to predict binding affinities, and assessing drug-likeness properties through ADMET predictions. The consistent identification of promising compounds across these studies underscores the potential of plant-derived bioactive molecules for drug discovery and development. The in silico analyses conducted to assess the pharmacokinetic profiles and drug-likeness of the identified compounds provided crucial insights into their potential as therapeutic agents. These analyses focused on the absorption, distribution, metabolism, and excretion (ADME) properties, as well as the potential interactions with key enzymes and transporters. The results indicated that many compounds from various plant extracts, including Moringa oleifera seed extract and E. viscosus methanolic extract, demonstrated good drug-likeness according to Lipinski's Rule of Five and Veber's rules (Shady et al. 2022 ). This suggests that these compounds possess favorable physicochemical properties for oral bioavailability and drug development. Essential oil compounds, in particular, show promising characteristics, such as high gastrointestinal (GI) absorption and blood-brain barrier (BBB) permeability. Studies on essential oils from plants such as Satureja kitaibelii and Ptychotis verticillata revealed the presence of compounds such as p-cymene, limonene, geraniol, carvacrol, and borneol (Nikolova et al. 2025 ;Taibi et al. 2023 ). Similarly, compounds from guava essential oil exhibit good drug-likeness (Mandal et al. 2022 ). However, it is important to note that many of these compounds also showed potential inhibition of cytochrome P450 (CYP) enzymes, which could lead to drug-drug interactions. This highlights the need for a comprehensive evaluation of both the beneficial properties and potential risks when considering natural compounds for medicinal use, as exemplified by the study of antidiabetic flavonoids (Bitew et al. 2021 ). The safety and efficacy of E. viscosus for wound healing and antioxidant applications have been established along with a broader trend in phytochemical research. Methanolic extracts and essential oils derived from various plants have shown significant potential in these therapeutic areas (Ramasamy et al. 2022 ). The bioactive compounds present in these extracts, including terpenoids, phenolics, and flavonoids, are primarily responsible for their medicinal properties (Bouyahya et al. 2022 ). These compounds often exhibit synergistic effects, which enhance their overall therapeutic potential. The growing interest in plant-derived bioactive compounds stems from their promising therapeutic potential coupled with relatively low toxicity profiles. These characteristics make them attractive candidates for the development of new pharmaceutical products and natural remedies. The antioxidant properties of these compounds play a crucial role in wound healing by neutralizing free radicals and reducing oxidative stress in the damaged tissues. Additionally, many plant extracts possess antimicrobial properties that can prevent infections and promote faster wound closure. As research in this field progresses, more plant-derived compounds will likely be identified and characterized for potential applications in wound healing, antioxidant therapies, and other medical applications. Conclusion In conclusion, this study confirmed the therapeutic potential of Endostemon viscosus bioactive compounds, particularly those from the methanolic extract, in targeting MMP-9 for wound healing. The methanolic compounds exhibited strong binding interactions and hydrogen bonding, supporting their stability and efficacy. The ADME analysis demonstrated favorable pharmacokinetics, and toxicity assessments indicated moderate safety with no carcinogenic risk. These findings suggest that E. viscosus could serve as a natural source of bioactive agents for wound-healing applications, encouraging further experimental validation through in vitro and in vivo studies. Declarations Conflict of Interest declaration : None Funding Statement: None Author Contribution Author contributions: KMS and SM conceived the idea; KMS experimented; KMS analyzed the data; KMS, SM, and SP wrote the manuscript; KMS, SM, and SP edited the manuscript, and all authors approved the manuscript. 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Biomedicines 9:1522. https://doi.org/10.3390/biomedicines9111522 Gowtham HG, Ahmed F, Anandan S, Shivakumara CS, Bilagi A, Pradeep S, Shivamallu C, Shati AA, Alfaifi MY, Elbehairi SEI, Achar RR, Silina E, Stupin V, Murali M, Kollur SP (2023) In Silico Computational Studies of Bioactive Secondary Metabolites from Wedelia trilobata against Anti-Apoptotic B-Cell Lymphoma-2 (Bcl-2) Protein Associated with Cancer Cell Survival and Resistance. Molecules 28:1588. https://doi.org/10.3390/molecules28041588 Kundu P, Debnath SL, Devnath HS, Saha L, Sadhu SK (2022) Analgesic, Anti‐inflammatory, Antipyretic, and In Silico Measurements of Sonneratia caseolaris (L.) Fruits from Sundarbans, Bangladesh. BioMed Res Int 2022:1405821. https://doi.org/10.1155/2022/1405821 Lan B, Zhang L, Yang L, Wu J, Li N, Pan C, Wang X, Zeng L, Yan L, Yang C, Ren M (2021) Sustained delivery of MMP-9 siRNA via thermosensitive hydrogel accelerates diabetic wound healing. J Nanobiotechnology 19:130. https://doi.org/10.1186/s12951-021-00869-6 Mandal AK, Paudel S, Pandey A, Yadav P, Pathak P, Grishina M, Jaremko M, Emwas A-H, Khalilullah H, Verma A (2022) Guava Leaf Essential Oil as a Potent Antioxidant and Anticancer Agent: Validated through Experimental and Computational Study. Antioxidants 11:2204. https://doi.org/10.3390/antiox11112204 Nganso Ditchou YO, Leutcha PB, Miaffo D, Mamoudou H, Ali MS, Amang À Ngnoung GA, Soh D, Agrawal M, Darbawa R, Zondegoumba Nkwengoua Tchouboun E, Meli Lannang A, Siwe Noundou X (2024) In vitro and in silico assessment of antidiabetic and antioxidant potencies of secondary metabolites from Gymnema sylvestre. Biomed Pharmacother 177:117043. https://doi.org/10.1016/j.biopha.2024.117043 Nikolova M, Lyubenova A, Yankova-Tsvetkova E, Georgiev B, Gavrilov G, Gavrilova A (2025) Satureja kitaibelii Essential Oil and Extracts: Bioactive Compounds and Pesticide Properties. 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Nat Commun 9:3559. https://doi.org/10.1038/s41467-018-05769-2 Shady NH, Mostafa NM, Fayez S, Abdel-Rahman IM, Maher SA, Zayed A, Saber EA, Khowdiary MM, Elrehany MA, Alzubaidi MA, Altemani FH, Shawky AM, Abdelmohsen UR (2022) Mechanistic Wound Healing and Antioxidant Potential of Moringa oleifera Seeds Extract Supported by Metabolic Profiling, In Silico Network Design, Molecular Docking, and In Vivo Studies. Antioxidants 11:1743. https://doi.org/10.3390/antiox11091743 Taibi M, Elbouzidi A, Ou-Yahia D, Dalli M, Bellaouchi R, Tikent A, Roubi M, Gseyra N, Asehraou A, Hano C, Addi M, El Guerrouj B, Chaabane K (2023) Assessment of the Antioxidant and Antimicrobial Potential of Ptychotis verticillata Duby Essential Oil from Eastern Morocco: An In Vitro and In Silico Analysis. Antibiotics 12:655. https://doi.org/10.3390/antibiotics12040655 Tassakka ACmar, Iskandar IW, Juniyazaki ABa, Zaenab S, Alam JF, Rasyid H, Kasmiati K, Sinurat E, Dwiany FM, Martien R, Moore AM (2023) Green algae Caulerpa racemosa compounds as antiviral candidates for SARS-CoV-2: In silico study. Narra J 3:e179. https://doi.org/10.52225/narra.v3i2.179 Wang C, Chao C, Yu J, Copeland L, Huang Y, Wang S (2022) Mechanisms Underlying the Formation of Amylose– Lauric Acid−β-Lactoglobulin Complexes: Experimental and Molecular Dynamics Studies. J Agric Food Chem 70:10635–10643. https://doi.org/10.1021/acs.jafc.2c04523 Zhou L, Ren M, Zeng T, Wang W, Wang X, Hu M, Su S, Sun K, Wang C, Liu J, Yang C, Yan L (2019) TET2-interacting long noncoding RNA promotes active DNA demethylation of the MMP-9 promoter in diabetic wound healing. Cell Death Dis 10:813. https://doi.org/10.1038/s41419-019-2047-6 Zou H, Li Y, Liu X, Wu Z, Li J, Ma Z (2021) Roles of plant‐derived bioactive compounds and related microRNAs in cancer therapy. Phytother Res 35:1176–1186. https://doi.org/10.1002/ptr.6883 Additional Declarations No competing interests reported. Supplementary Files GraphicalAbstract.jpg Cite Share Download PDF Status: Published Journal Publication published 26 Nov, 2025 Read the published version in In Silico Pharmacology → Version 1 posted Editorial decision: Revision requested 12 Jul, 2025 Reviews received at journal 11 Jul, 2025 Reviewers agreed at journal 29 Jun, 2025 Reviewers invited by journal 29 Jun, 2025 Editor assigned by journal 02 Jun, 2025 Submission checks completed at journal 02 Jun, 2025 First submitted to journal 31 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6789028","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":479073169,"identity":"7ddc46ca-b92a-4e7f-a652-c5daa9c64f93","order_by":0,"name":"Kavi Malar Surendran","email":"","orcid":"","institution":"Nirmala College for Women (Autonomous)","correspondingAuthor":false,"prefix":"","firstName":"Kavi","middleName":"Malar","lastName":"Surendran","suffix":""},{"id":479073170,"identity":"96041a05-d2c0-41cb-81a1-890d12974828","order_by":1,"name":"Saradha 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University)","correspondingAuthor":false,"prefix":"","firstName":"Sugandhi","middleName":"","lastName":"Pugazhendhi","suffix":""}],"badges":[],"createdAt":"2025-05-31 06:23:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6789028/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6789028/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s40203-025-00487-2","type":"published","date":"2025-11-26T15:56:52+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":85842684,"identity":"fad3573c-c211-43aa-99f5-f9544514e68a","added_by":"auto","created_at":"2025-07-02 09:23:09","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":957999,"visible":true,"origin":"","legend":"\u003cp\u003eActive Site Predictions of Target Protein 1L6J for Wound\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6789028/v1/bdfc4be69fd5902697612f8d.jpg"},{"id":85842653,"identity":"0ee71f2c-335f-45b5-8b34-563ebb9ae625","added_by":"auto","created_at":"2025-07-02 09:23:08","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1081891,"visible":true,"origin":"","legend":"\u003cp\u003e3D and 2D interactions of wound healing compounds from \u003cem\u003eE. viscosus\u003c/em\u003e methanolic extract (GC-MS) with the target receptor\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6789028/v1/5f536d30aaa7be24fae6dfcc.jpg"},{"id":85842672,"identity":"1597f6a6-c821-4e27-b25b-589c4c9fb69e","added_by":"auto","created_at":"2025-07-02 09:23:08","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1119784,"visible":true,"origin":"","legend":"\u003cp\u003e3D and 2D interactions of wound healing compounds from \u003cem\u003eE. viscosus\u003c/em\u003e methanolic extract (GC-MS) with the target receptor\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6789028/v1/1a2d9225da4d8077ba48e1e1.jpg"},{"id":85842692,"identity":"aef421ed-6a8b-4f28-8122-f755fd1f73f0","added_by":"auto","created_at":"2025-07-02 09:23:09","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1012189,"visible":true,"origin":"","legend":"\u003cp\u003e3D and 2D interactions of wound healing compounds from \u003cem\u003eE. viscosus\u003c/em\u003e essential oil extract (GC-MS) with the target receptor\u003c/p\u003e","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6789028/v1/3506d613d25362aaa6b538a9.jpg"},{"id":85842689,"identity":"7540aa2a-9d3e-42e5-889f-4dae6aa7d105","added_by":"auto","created_at":"2025-07-02 09:23:09","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1002023,"visible":true,"origin":"","legend":"\u003cp\u003e3D and 2D interactions of wound healing compounds from \u003cem\u003eE. viscosus\u003c/em\u003e essential oil extract (GC-MS) with the target receptor\u003c/p\u003e","description":"","filename":"Fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6789028/v1/74fae996c7cab22e5ad792b7.jpg"},{"id":97178292,"identity":"33e8da42-0939-4b27-a328-4fbe7ea70e49","added_by":"auto","created_at":"2025-12-01 16:07:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6612644,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6789028/v1/966c2765-da7c-43bb-bb35-cf808cf4779e.pdf"},{"id":85842669,"identity":"7b9581c0-cdfb-49a2-8453-da15e8d9eacc","added_by":"auto","created_at":"2025-07-02 09:23:08","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":508862,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6789028/v1/a3c952d407e77ad028fc43d7.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eInsilico Pharmacological Profiling of Endostemon Viscosus Bioactive Compounds Targeting MMP-9 for Wound Healing\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePlant-derived bioactive compounds have garnered significant attention in the field of therapeutic research due to their diverse biological activities and potential medicinal applications (Zou et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These natural substances, extracted from various plant sources, exhibit a wide range of beneficial effects, including anti-inflammatory, antioxidant, antimicrobial, and neuroprotective properties (Gangwar et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The growing interest in these compounds stems from their systemic pleiotropic effects, minimal side effects, and low toxicity, making them attractive candidates for natural therapeutic agents against various disease conditions. One area of particular interest is the potential application of plant-derived bioactive compounds in wound healing. The wound healing process involves complex interactions between various cellular and molecular components, including matrix metalloproteinases (MMPs). Among these, MMP-9 plays a crucial role in tissue remodeling and wound closure. However, excessive activation of MMP-9 can impede the healing process, especially in chronic wounds (Zhou et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Lan et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Therefore, the inhibition of MMP-9 has emerged as a promising strategy to enhance wound healing by reducing excessive tissue breakdown, decreasing inflammation, and restoring the balance between MMPs and their inhibitors. Recent studies have highlighted the potential of natural compounds in inhibiting MMP-9 activity. For instance, flavonoid-rich fractions from plants such as Glycyrrhiza glabra and Sophora japonica have demonstrated wound healing potential, as evidenced by molecular docking studies of their major constituents with wound healing-related proteins (Aly et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These findings suggest that \u003cem\u003ein silico\u003c/em\u003e pharmacological profiling of bioactive compounds from medicinal plants could be a viable approach for identifying potential MMP-9 inhibitors for wound-healing applications. In this context, the present study focuses on \u003cem\u003eEndostemon viscosus\u003c/em\u003e, a plant species with potential medicinal properties. Despite the lack of specific information regarding this plant, the study aims to explore its phytochemical composition and evaluate the potential of its bioactive compounds as MMP-9 inhibitors for wound healing applications. The research employs a comprehensive approach, combining GC-MS analysis of methanolic and oil extracts, molecular docking studies, and ADMET property evaluations to assess the pharmacokinetic behaviour and drug-likeness of the identified compounds. By integrating these analytical approaches, this study seeks to provide a thorough understanding of the phytochemical composition, potential biological activities, and safety profile of \u003cem\u003eEndostemon viscosus\u003c/em\u003e. The findings may contribute to the development of novel therapeutic agents and inform future investigations of the medicinal properties of this plant species, potentially advancing the field of natural product-based wound healing therapies.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eTarget protein Preparation\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eMMP-9\u003c/h2\u003e \u003cp\u003eThe crystallographic three-dimensional structure of human matrix metalloproteinase 9 (MMP-9), identified by PDB ID 1L6J, was sourced from the Protein Data Bank (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.rcsb.org/\u003c/span\u003e\u003cspan address=\"http://www.rcsb.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The protein structure was elucidated and experimentally validated using X-ray diffraction at a resolution of 2.5 \u0026Aring;. Subsequently, the three-dimensional structure was processed using Biovia Studio, where ligands, co-ligands, heteroatoms, and water molecules were removed to create an appropriate environment for docking (Kundu et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Further optimization of the protein structure was conducted using AutoDock Tools (PyRx), which involved the addition of charges, energy minimization, and conversion to the PDBQT format. These optimized structures were then used for subsequent analyses.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eActive site prediction and grid generations\u003c/h3\u003e\n\u003cp\u003eActive site prediction and grid generation require a precise assessment of the active site during docking. Potential binding sites for amino acid residues associated with the target protein were identified using CASTp. (2018), web service (Computed Atlas for Surface Topography of Proteins).\u003c/p\u003e\n\u003ch3\u003eLigand preparation and retrieval\u003c/h3\u003e\n\u003cp\u003eLigand preparation and retrieval involved selecting the top six compounds from the methanolic extract and six compounds from the essential oil out of 37 and 27 compounds identified by GC-MS, respectively (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The three-dimensional chemical structures were downloaded in SDF format from the PubChem database of the National Center for Biotechnology Information, 2021. The methanolic extract ligands included Avenanthramide B (Pubchem CID: 10087955), 3-Amino-1-phenyl-2-pyrazolin-5-one (Pubchem CID: 77794), (4,6-Diamino-1,3,5-triazin-2-yl) cyanamide (Pubchem CID: 592015), Heptanoic acid, 4-methoxyphenyl ester (Pubchem CID: 579908), 3-Fluoro-5-trifluoromethylbenzoic acid, 2-nitro-5-fluorophenylester (Pubchem CID: 91730956), and 3,4-Dihydroisoquinoline,1-[3-methoxybenzyl]-6-methoxy (Pubchem CID: 624494). The essential oil ligands comprised (1R,4R)-1-methyl-4-(6-Methylhept-5-en-2-yl) cyclohex-2-enol (Pubchem CID: 13213649), caryophyllene oxide (Pubchem CID: 1742210), 3-Cyclohexen-1-ol, 4-methyl-1-(1-methylethyl)- (R) (Pubchem CID: 5325830), 1-Isopropyl-4,7-dimethyl-1,2,3,5,6,8a-hexahydronaphthalene (Pubchem CID: 10233), d-limonene (Pubchem CID: 440917), and methyleugenol (Pubchem CID: 7127).\u003c/p\u003e\n\u003ch3\u003eMolecular docking of MMP-9\u003c/h3\u003e\n\u003cp\u003eAuto Dock Vina (PyRx software version 0.8) was employed to conduct molecular docking between the prepared receptor and ligands (Dallakyan and Olson \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Utilizing default parameters, the macromolecule (1L6J) was docked against the top five ligands derived from the methanolic and essential oil extracts, with default settings applied. During the docking phase, the ligands were considered flexible, whereas the protein was treated as rigid. A grid parameter configuration file was developed using the binding amino acids analyzed from CASTp. Upon completion of the separate protein-ligand docking and retrieval of the PDBQT output files, binding affinities (kcal/mol) were recorded in a CSV file. It was concluded that the ligand exhibiting the strongest interaction possessed the highest negative binding energy.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eVisualization and post docking analysis of MMP-9\u003c/h2\u003e \u003cp\u003eThe three-dimensional and two-dimensional interactions of the docked complexes were visualized and analyzed using the Biovia Discovery Studio Visualizer version 24.1.0.23298 (BIOVIA, Dassault Systemes, 2019). Various receptor-ligand interactions, including hydrogen bonding and hydrophobic interactions, were evaluated.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePharmacokinetic properties analysis of MMP-9\u003c/h3\u003e\n\u003cp\u003eThe Swiss ADME web server, a freely accessible tool introduced in 2017, SwissADME. (2017) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.swissadme.ch/\u003c/span\u003e\u003cspan address=\"http://www.swissadme.ch/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was employed to evaluate the ADME profile of each selected compound. This evaluation encompassed drug-likeness (as per Lipinski's rule of five), solubility profile, lipophilicity, pharmacokinetic properties, medicinal chemistry, and gastrointestinal absorption profile (GIT).\u003c/p\u003e\n\u003ch3\u003eToxicology properties prediction of MMP-9\u003c/h3\u003e\n\u003cp\u003ePrior to the initiation of clinical studies, it is imperative to evaluate the safety profiles of these compounds. The use of in silico toxicity profile prediction offers advantages in terms of speed, accuracy, and accessibility, leading to significant savings in time, cost, and effort. The admetSAR1 (2012), a web-based tool available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://lmmd.ecust.edu.cn/admetsar1\u003c/span\u003e\u003cspan address=\"http://lmmd.ecust.edu.cn/admetsar1\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, which is both user-friendly and cost-free, was employed to analyze the toxicity profiles and potential adverse effects of the selected four compounds. This server provides predictions on carcinogenicity, acute oral toxicity, rat acute toxicity (LD50), biodegradation, and the inhibition of human ether-a-go-go-related genes.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eActive site prediction and grid generation of MMP-9\u003c/h2\u003e \u003cp\u003eCASTp analysis has delineated the functional binding regions of MMP-9, identifying critical active site residues: 34, 35, 36, 38, 39, 44, 47, 48, 51, 52, 92, 94\u0026ndash;98, 182, 184\u0026ndash;187, 209, 213, 215, 216, 232, 233, 242, 334, 338, 366\u0026ndash;368, 370, 371, 387\u0026ndash;393, 423\u0026ndash;425 in Chain A, as illustrated in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A grid box was configured to encompass these binding sites for the subsequent docking analysis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePredicted actives for target protein (1L6J) for wound healing activity.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS.No\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSurface area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVolume\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSite Residues\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e841.248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1233.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChain A\u003c/p\u003e \u003cp\u003e34,35,36,38,39,44,47,48,51,52,92,94,95,96,97,98,182,184,185,186,187,209,213,215,216,232,233,242,334,338,366,367,368,370,371,387,388,389,390,391,392,393,423,424,425\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMolecular docking\u003c/h2\u003e \u003cp\u003eThe evaluation of bioactive compounds from \u003cem\u003eE. viscosus\u003c/em\u003e has focused on assessing their potential as drug candidates. This study examined 37 compounds from the methanolic extract and 27 from the essential oil extract, applying Lipinski's Rule of Five and ADME analysis to determine their drug-likeness. This screening process is crucial in early-stage drug discovery as it helps identify compounds with favorable physicochemical properties that are likely to be orally active in humans. The analysis revealed that 14 compounds from the essential oil extract and 10 compounds from the methanolic extract met these criteria, suggesting their potential for further investigation as drug candidates.\u003c/p\u003e \u003cp\u003eFollowing the initial screening, the selected compounds underwent molecular docking studies against the 1L6J protein (Chain A) using PyRx software. This computational approach aims to predict the binding affinity and interaction modes between compounds and the target protein. The results of these docking studies, presented in Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, provide insights into the potential effectiveness of these compounds as inhibitors or modulators of target proteins. Furthermore, Tables\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e offer a comprehensive list of compounds that not only exhibit drug-like properties but also demonstrate strong binding energies (below \u0026minus;\u0026thinsp;7 kcal/mol) in their interactions with the protein. This information is valuable for prioritizing compounds for further experimental validation and optimization of the drug discovery pipelines.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGC-MS identified phyto constituents from methanolic extract of \u003cem\u003eE. viscosus\u003c/em\u003e based on Lipinski\u0026rsquo;s rule and ADME properties for wound healing\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS.No\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompound Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLipinski\u0026rsquo;s Rule of 5 (Ro5) violation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eADME based exclusion\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,4-Dihydroisoquinoline,1-[3-methoxybenzyl]-6-methoxy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u003cb\u003e-\u003c/b\u003eMethoxyheptnophene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeptanoic acid, 4-methoxyphenyl ester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003cb\u003e-\u003c/b\u003eFluoro-5-trifluoromethylbenzoic acid, 2-nitro-5-fluorophenylester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAvenanthramide B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003cb\u003e-\u003c/b\u003eAmino-1-phenyl-2-pyrazolin-5-one\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1-Methyl-1H-imidazole-4-carboxylic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(4,6\u003cb\u003e-\u003c/b\u003eDiamino-1,3,5-triazin-2-yl) cyanamide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2-Furancarbodithioic acid, ethyl ester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThiophene, 3-methyl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (Low HBA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003elow solubility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMethyl acetoxyacetate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (Low MW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRapid Metabolism\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBenzene, 1,2,3-trimethyl-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High Log P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLow Bioavailability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMethoxyacetaldehyde diethyl acetal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High Log P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor Absorption\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCyclopentanecarboxylic acid, 1-(2-ethyl-1-oxobutoxy)-2-oxo-, ethyl ester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High MW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor Solubility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1-Nonene, 4,6,8-trimethyl-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High Log P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor Permeability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5-[4-(Carboxyadamanthyl-3)-phenyl]-10,15,20-triphenyl-21H,23H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High MW, Log P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor Absorption\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBenzene,1-methyl-4(1,2,2-trimethylcyclopentyl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High Log P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLow Metabolism\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCycloocta-1,3,6-triene,2,3,5,5,8,8-hexamethyl-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High MW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor Absorption\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2H-1-benzopyran-2-one, 3,4-dihydro-4,4,6-trimethyl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High Log P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLow Bioavailability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTridecene,5-propyl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High Log P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor Absorption\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeptadecane,3-methyl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High Log P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLow Metabolism\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecane,5-propyl-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High Log P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor Permeability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeptacosane\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High MW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLow Solubility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePentadecanoic acid, 14-methyl-, methyl ester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High Log P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor Absorption\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhthalic acid, cis-hex-3-enyl,octadecyl ester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High MW, Log P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor Bioavailability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3-Penten-2-one\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High Log P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRapid Metabolism\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,4-Diamino-6-cyanamino-1,3,5-triazine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High MW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor Absorption\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEicosane, 1-iodo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High MW, Log P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor Solubility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCaprolactone oxime, (NB)-O-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High MW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor Metabolism\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNonane, 5-methyl-5-propyl-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1-Butyl-1-methyl-1,2,3,4-tetrahydroisoquinoline 2-(dimethylamino)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High Log P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLow Permeability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,4-bi-4H-pyran,2,2,6,6-tetrakis(1,1-dimethylethyl)-4,4-dimethyl-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High MW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor Absorption\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,2,4,4-Tetrahydroxybenzophenone, tetrakis(tert-butyldimethylsilyl) ether\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High MW, Log P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLow Bioavailability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhthalic acid, 4-nitrophenyl 2-propyl ester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High LogP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor Solubility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhenyl 4-[(Trimethylsilyl)amino] benzoate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High MW, Log P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor Absorption\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePerfluorobutyramide, N-allyl-N-(hept-2-yl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High Log P),\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor Permeability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI-Leucine, n-pentafluorobenzoyl-,pentadecyl ester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (High MW, Log P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor Absorption\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003eHBA\u0026minus;Hydrogen Bond Acceptor, MW: molecular Weight, LogP\u0026minus; logarithm of the partition coefficient (P) Octanol\u0026minus;Water purification Coefficient, ADME\u0026minus; Absorption, Distribution, Metabolism and Excretion, Ro5\u0026minus;Lipinski\u0026rsquo;s rule of five\u003c/sup\u003e.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGC-MS identified phytoconstituents from essential oil of \u003cem\u003eE. viscosus\u003c/em\u003e based on Lipinski\u0026rsquo;s rule and ADME properties for wound healing\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS.No\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompound Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLipinski\u0026rsquo;s Rule of 5 (Ro5) violation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eADME based exclusion\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3-Carene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeta-Phellandrene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD-Limonene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eγ-Terpinene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLinalool\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3-Cyclohexen-1-ol, 4-methyl-1-(1-methylethyl)-,(R)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eα-Cubebene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (LogP\u0026thinsp;\u0026gt;\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003elow aqueous solubility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMethyleugenol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBicyclo[5.2.0]nonane, 2-methylene-4,8,8-trimethyl-4-vinyl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (LogP\u0026thinsp;\u0026gt;\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ehigh hydrophobicity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,4,7-Cycloundecatriene, 1,5,9,9-tetramethyl-,z,z,z\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (LogP\u0026thinsp;\u0026gt;\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003elow permrability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1R,2S,6S,7S,8S)-8-Isopropyl-1-methyl-3-methylenetricyclo[4.4.0.02,7] decane-rel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1-Isopropyl-4,7-dimethyl-1,2,3,5,6,8a-hexahydronaphthalene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNerolidol 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCaryophyllene oxide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1R,4R)-1-methyl-4-(6-Methylhept-5-en-2-yl)cyclohex-2-enol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eαR-Turmerone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTetradecanoic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIsopimara-9(11),15-diene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (LogP\u0026thinsp;\u0026gt;\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ehigh hydrophobicity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1-Napthalenepropanol, α-ethenyldecahydro-α,5,5,8a-tetramethyl-2-methylene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (LogP\u0026thinsp;\u0026gt;\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003elow water solubility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(4as,10aS)-7Isopropyl-1,1,4a-trimethyl-1,2,3,4a,5,6,9,10,10a-decahydrophenanthrene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (LogP\u0026thinsp;\u0026gt;\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ehigh hydrophobicity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhenanthrene, 1,2,3,4,4a,9,10,10a-octahydro-1,1,4a-trimethyl-7-(1-methylethyl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (LogP\u0026thinsp;\u0026gt;\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003epoor permeability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrans-Kaur-16-ene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (LogP\u0026thinsp;\u0026gt;\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003elow metabolic stability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1-Naphthalenepropanol, α-ethenyldecahydro-[1α(R),2β,4aβ,8aα]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (LogP\u0026thinsp;\u0026gt;\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003elow absorption\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKaur-16-ene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (LogP\u0026thinsp;\u0026gt;\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ehigh lipophilicity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(2S,4aR,5S,8aR)-5-((S)-3-hydroxy-3-methylpent-4-methylenedecahydronaphthalen-2-ol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1-Phenanthrenemethanol, 1,2,3,4,4a,9,10,10a-octahydro-(1α,4aα,10aβ)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (LogP\u0026thinsp;\u0026gt;\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003epoor permeability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeneicosane\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (LogP\u0026thinsp;\u0026gt;\u0026thinsp;5), high MW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eextremely poor solubility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003eMW \u0026minus; molecular Weight, LogP\u0026minus; logarithm of the partition coefficient (P) Octanol\u0026minus;Water purification coefficient; ADME \u0026minus; absorption, distribution, metabolism and Excretion, Ro5\u0026minus;Lipinski\u0026rsquo;s rule of five\u003c/sup\u003e.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBinding affinity and hydrogen bond interactions of GC-MS identified bioactive compounds from methanolic extract of \u003cem\u003eE.viscosus\u003c/em\u003e for wound healing\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS.No\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGCMS compounds\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBinding affinity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo. of H bonds\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eH bonds\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHydrophobic interactions\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10087955\u003c/p\u003e \u003cp\u003eAvenanthramide B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMET 422, ARG 422, PRO 415, ALA 417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLEU 397, LEU 418, VAL 398, MET 422, ALA 417\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77794\u003c/p\u003e \u003cp\u003e3-Amino-1-phenyl-2-pyrazolin-5-one\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eARG 424, PRO 430, GLU 416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVAL 398, MET 422, ALA417, LEU 397, LEU 418\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e592015\u003c/p\u003e \u003cp\u003e(4,6-Diamino-1,3,5-triazin-2-yl) cyanamide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eARG 424, TYR 420, ALA 417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMET 422,\u003c/p\u003e \u003cp\u003eLEU418, ALA 417, LEU 397, PHE 425, LEU 188, VAL 398, CYS 99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e579908\u003c/p\u003e \u003cp\u003eHeptanoic acid, 4-methoxyphenyl ester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHIS 401, ARG 424\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLEU 418, LEU 397, MET 422, VAL 398, LEU 188, CYC 99, ALA 189\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e91730956\u003c/p\u003e \u003cp\u003e3-Fluoro-5-trifluoromethylbenzoic acid, 2-nitro-5-fluorophenylester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTYR 52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLEU 187, LEU 39,\u003c/p\u003e \u003cp\u003eLEU 44, MET 94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e624494\u003c/p\u003e \u003cp\u003e3,4-Dihydroisoquinoline,1-[3-methoxybenzyl]-6-methoxy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTYR 52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLEU 44,\u003c/p\u003e \u003cp\u003eLEU 187, MET 94, LEU 39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBinding affinity and hydrogen bond interactions of GC-MS identified bioactive compounds from essential oil of \u003cem\u003eE.viscosus\u003c/em\u003e for wound healing\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS.No\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGCMS compounds\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBinding affinity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo. of H bonds\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInteractions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHydrophobic interactions\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13213649\u003c/p\u003e \u003cp\u003e(1R,4R)-1-methyl-4-(6-Methylhept-5-en-2-yl)cyclohex-2-enol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVan der Waals, alkyl, pi-alkyl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVAL 398,\u003c/p\u003e \u003cp\u003eLEU 188,\u003c/p\u003e \u003cp\u003eCYS99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1742210\u003c/p\u003e \u003cp\u003eCaryophyllene oxide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVan der Waals, carbon hydrogen bond, alkyl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMET 94,\u003c/p\u003e \u003cp\u003eLEU 187,\u003c/p\u003e \u003cp\u003eLEU 39,\u003c/p\u003e \u003cp\u003eLEU 44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5325830\u003c/p\u003e \u003cp\u003e3-Cyclohexen-1-ol, 4-methyl-1-(1-methylethyl)-,(R)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMET 94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eALA 417,\u003c/p\u003e \u003cp\u003eLEU 188,\u003c/p\u003e \u003cp\u003eVAL 398,\u003c/p\u003e \u003cp\u003eLEU 397,\u003c/p\u003e \u003cp\u003eMET 422,\u003c/p\u003e \u003cp\u003eLEU 188\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10233\u003c/p\u003e \u003cp\u003e1-Isopropyl-4,7-dimethyl-1,2,3,5,6,8a-hexahydronaphthalene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVan der Waals, alkyl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLEU 39,\u003c/p\u003e \u003cp\u003eMET 94,\u003c/p\u003e \u003cp\u003eLEU 187,\u003c/p\u003e \u003cp\u003eLEU 44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e440917\u003c/p\u003e \u003cp\u003eD-Limonene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVan der Waals, alkyl, pi-alkyl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLEU 418,\u003c/p\u003e \u003cp\u003eALA 417,\u003c/p\u003e \u003cp\u003eMET 422,\u003c/p\u003e \u003cp\u003eLEU 397,\u003c/p\u003e \u003cp\u003eVAL 398,\u003c/p\u003e \u003cp\u003eLEU188,\u003c/p\u003e \u003cp\u003eCYS 99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7127\u003c/p\u003e \u003cp\u003eMethyleugenol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVan der Waals, pi-alkyl,\u003c/p\u003e \u003cp\u003ealkyl, carbon hydrogen bond,\u003c/p\u003e \u003cp\u003epi-pi stacked,\u003c/p\u003e \u003cp\u003epi-sigma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eALA 417,\u003c/p\u003e \u003cp\u003eMET 422,\u003c/p\u003e \u003cp\u003eLEU 418,\u003c/p\u003e \u003cp\u003eLEU 397, LEU188,\u003c/p\u003e \u003cp\u003eVAL-398,\u003c/p\u003e \u003cp\u003eCYC-99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe in silico analysis revealed significant binding affinities for compounds from both the methanolic extract and essential oil of \u003cem\u003eE. viscosus\u003c/em\u003e. In the methanolic extract, 3-fluoro-5-trifluoromethylbenzoic acid demonstrated the highest binding affinity (-8.0 kcal/mol), interacting with TYR 52. Other compounds, such as 3-Amino-1-phenyl-2-pyrazolin-5-one, Avenanthramide B, and 4-methoxyphenyl ester of hexanoic acid, exhibited strong binding affinities and formed hydrogen bonds with key residues. These interactions, along with hydrophobic interactions involving residues like MET 422, ARG 422, and TYR 420, contribute to the stability of the ligand-protein complexes.\u003c/p\u003e \u003cp\u003eThe essential oil compounds also showed notable binding affinities, with (1R, 4R) 6-Methylhept-5-en-2-yl-1-methyl-4-Cyclohex-2-enol exhibiting the highest at -7.7 kcal/mol. This compound interacted with VAL 398, LEU 188, and CYS 99 through various non-covalent interactions. Other compounds, including Caryophyllene oxide, D-Limonene, and Methyleugenol, primarily engaged in hydrophobic interactions with minimal hydrogen bonding. This suggests that the wound-healing potential of \u003cem\u003eE. viscosus\u003c/em\u003e essential oil is predominantly based on hydrophobic interactions rather than hydrogen bonds, providing insight into the mechanism of action for these compounds.\u003c/p\u003e \u003cp\u003eThe molecular docking analysis revealed intricate interactions between the bioactive compounds from both the methanolic extract and essential oils of \u003cem\u003eE. viscosus\u003c/em\u003e with the target protein. Figures\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e demonstrate that compounds from the methanolic extract effectively occupied the binding pockets of the protein, engaging in multiple types of molecular interactions. These interactions include hydrogen bonding, which provides specificity and directionality to the binding, van der Waals forces that contribute to the overall stability of the complex, and hydrophobic interactions that play a crucial role in the binding affinity. Similarly, Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e illustrate that compounds from essential oils also occupied the binding pockets, participating in the same types of molecular interactions.\u003c/p\u003e \u003cp\u003eHowever, a notable difference was observed between the two extracts. The bioactive compounds from the methanolic extract of \u003cem\u003eE. viscosus\u003c/em\u003e exhibited a higher number of hydrogen bonds and stronger binding potential compared to those from essential oils. This enhanced binding profile suggests that the methanolic extract compounds may have a more pronounced effect on the target protein, potentially leading to more efficient modulation of its activity. These findings provide molecular-level support for the role of \u003cem\u003eE. viscosus\u003c/em\u003e compounds, particularly those from the methanolic extract, in wound healing mechanisms. The stronger interactions observed with the methanolic extract compounds indicate their potential superiority in influencing the biological processes involved in wound repair, although further experimental validation would be necessary to confirm this hypothesis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eADME (Absorption, Distribution, Metabolism, Excretion) properties of MMP-9\u003c/h2\u003e \u003cp\u003eThe methanolic extract and essential oil components of \u003cem\u003eE. viscosus\u003c/em\u003e exhibited promising characteristics for wound healing applications, as demonstrated by in silico pharmacokinetics and drug-likeness analyses (Tables\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The methanolic substances showed high gastrointestinal absorption (GI), with only one compound (3,4-Dihydroisoquinoline,1-[3-methoxybenzyl]-6-methoxy) capable of crossing the blood-brain barrier. These substances also inhibited key CYP enzymes (CYP2C9, CYP2D6, CYP1A2, CYP2C19, and CYP3A4) but were not substrates of P-glycoprotein. While meeting Lipinski's Rule of Five criteria for drug-likeness, some compounds presented Brenk alerts due to structural concerns.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eIn-Silico\u003c/em\u003e pharmacokinetics and drug-likeness of bioactive compounds from \u003cem\u003eE.viscosus\u003c/em\u003e methanolic extract for wound healing activity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAvenanthramide B\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3-Amino-1-phenyl-2-pyrazolin-5-one\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(4,6-Diamino-1,3,5-triazin-2-yl) cyanamide\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHeptanoic acid, 4-methoxyphenyl ester\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3-Fluoro-5-trifluoromethylbenzoic acid, 2-nitro-5-fluorophenylester\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,4-Dihydroisoquinoline,1-[3-methoxybenzyl]-6-methoxy\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysiochemical properties\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMW (Da) g/mol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e329.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e151.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e236.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e347.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e281.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH-bond donors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH-bond acceptors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRotable bonds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLipophilicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConsensus Logp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWater solubility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLog S (ESOL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-3.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLog S (Ali)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-5.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-3.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePharmacokinetics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGI absoorption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBbb permeant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-gp substrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCYP enzymes inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCYP2C9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCYP2D6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCYP1A2,\u003c/p\u003e \u003cp\u003eCYP2C19,\u003c/p\u003e \u003cp\u003eCyp2C9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCYP1A2,\u003c/p\u003e \u003cp\u003eCYP2C19,\u003c/p\u003e \u003cp\u003eCYP3A4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDrug likeness\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLipinski\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0V\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedicinal chemistry\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAINS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 alert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 alert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 alert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 alert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 alert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 alert\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrenks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 alerts: Hydroquinone, Michael acceptor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 alert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 alerts: cyanate aminonitrile thiocyanate, enamine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 alert: phenol ester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 alerts: nitro group, oxygen nitrogen single bond, phenol ester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 alert\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003eMW (Da)- Molecular Weight (Daltons), 0 V- 0 violations, Consensus LogP- Consensus Partition Coefficient (LogP), Log S (ESOL)- Logarithm of Water Solubility predicted by the ESOL model, Log S (Ali)Logarithm of Water Solubility predicted by Ali model, GI absorption \u0026ndash; Gastrointestinal Absorption (High/Low\u003cb\u003e)\u003c/b\u003e, BBB permeant \u0026ndash; Blood-Brain Barrier Permeability (Yes/No), P-gp substrate \u0026ndash; Substrate of P-glycoprotein, related to drug efflux, PAINS \u0026ndash; Pan-Assay Interference Compounds (alerts for potential false positives), CYP enzyme inhibitor \u0026ndash; Cytochrome P450 Enzyme Inhibition\u003c/sup\u003e.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eIn-Silico\u003c/em\u003e pharmacokinetics and drug-likeness of bioactive compounds from \u003cem\u003eE.viscosus\u003c/em\u003e essential oil for wound healing activity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1R,4R)-1-methyl-4-(6-Methylhept-5-en-2-yl) cyclohex-2-enol\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCaryophyllene oxide\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3-Cyclohexen-1-ol, 4-methyl-1-(1-methylethyl)-,(R)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1-Isopropyl-4,7-dimethyl-1,2,3,5,6,8a-hexahydronaphthalene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eD-Limonene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMethyl eugenol\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysiochemical properties\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMW (Da) g/mol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e222.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e220.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e154.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e204.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e136.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e178.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH-bond donors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH-bond acceptors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRotable bonds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLipophilicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConsensus Logp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLog S (ESOL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-2.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLog S (Ali)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-2.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePharmacokinetics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGI absoorption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBbb permeant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-gp substrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCYP enzymes inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCYP2C9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCYP2C9, CYP2C19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCYP2C9, CYP2C19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCYP2C9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCYP1A2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDrug likeness\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLipinski\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes; 1 violation: MLOGP\u0026thinsp;\u0026gt;\u0026thinsp;4.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0V\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedicinal chemistry\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAINS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 alert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 alert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 alert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 alert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 alert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 alert\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrenks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 alert:\u003c/p\u003e \u003cp\u003eIsolated alkene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 alerts: Three-membered heterocycle, isolated_alkene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 alert: isolated alkene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 alert: isolated alkene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 alert: isolated alkene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 alert: isolated alkene\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003eMW (Da)- Molecular Weight (Daltons), Consensus LogP- Consensus Partition Coefficient (LogP), Log S (ESOL)- Logarithm of Water Solubility predicted by the ESOL model, Log S (Ali)Logarithm of Water Solubility predicted by Ali model, GI absorption \u0026ndash; Gastrointestinal Absorption (High/Lsow\u003cb\u003e)\u003c/b\u003e, BBB permeant \u0026ndash; Blood-Brain Barrier Permeability (Yes/No), P-gp substrate \u0026ndash; Substrate of P-glycoprotein, related to drug efflux, PAINS \u0026ndash; Pan-Assay Interference Compounds (alerts for potential false positives), CYP enzyme inhibitor \u0026ndash; Cytochrome P450 Enzyme Inhibition\u003c/sup\u003e.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe essential oil compounds similarly displayed favorable properties, with most exhibiting high gastrointestinal absorption except for d-limonene. All but one compound (1-Isopropyl-4,7-dimethyl-1,2,3,5,6,8a-hexahydronaphthalene) (Lipinski violation MLOGP\u0026thinsp;\u0026gt;\u0026thinsp;4.15)showed blood-brain barrier permeability. Several essential oil compounds inhibited specific CYP enzymes (specifically CYP2C9, CYP2C19, and CYP1A2), but none were P-glycoprotein substrates. Although no PAINS alerts were detected, some structures presented Brenk alerts due to solitary alkenes and three-membered heterocycles. Overall, both the methanolic extract and essential oil components of \u003cem\u003eE. viscosus\u003c/em\u003e demonstrated favorable pharmacokinetic and drug-likeness properties, suggesting their potential for wound healing applications.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eToxicology properties of MMP-9\u003c/h2\u003e \u003cp\u003eThe methanolic extract and essential oil of \u003cem\u003eE. viscosus\u003c/em\u003e have garnered attention for their wound-healing and antioxidant properties. To further assess their potential therapeutic applications, the bioactive compounds derived from these sources were subjected to carcinogenicity and acute oral toxicity evaluations using ADMESAR 1. The results, presented in Tables\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e and \u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e, provide valuable insights into the safety profile of these compounds. All evaluated compounds were classified as Class III in terms of wound healing activities, indicating moderate toxicity. This classification suggests that while these compounds may have some level of toxicity, they do not pose significant toxicological concerns, which is promising for their potential use in therapeutic applications.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eToxicity Profile of Bioactive Compounds from Methanolic Extract of \u003cem\u003eEndostemon viscosus\u003c/em\u003e for Wound Healing Activity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS.No\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompounds\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCarcinogenicity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAcute oral toxicity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAvenanthramide B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIII-Moderate toxicity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3-Amino-1-phenyl-2-pyrazolin-5-one\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIII-Moderate toxicity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(4,6-Diamino-1,3,5-triazin-2-yl) cyanamide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIII-Moderate toxicity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeptanoic acid, 4-methoxyphenyl ester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIII-Moderate toxicity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3-Fluoro-5-trifluoromethylbenzoic acid, 2-nitro-5-fluorophenylester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIII-Moderate toxicity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,4-Dihydroisoquinoline,1-[3-methoxybenzyl]-6-methoxy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIII-Moderate toxicity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eToxicity Profile of Bioactive Compounds from Methanolic Extract of \u003cem\u003eEndostemon viscosus\u003c/em\u003e for Wound Healing Activity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS.No\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompounds\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCarcinogenicity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAcute oral toxicity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1R,4R)-1-methyl-4-(6-Methylhept-5-en-2-yl) cyclohex-2-enol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIII-Moderate toxicity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCaryophyllene oxide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIII-Moderate toxicity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3-Cyclohexen-1-ol, 4-methyl-1-(1-methylethyl)-,(R)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIII-Moderate toxicity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1-Isopropyl-4,7-dimethyl-1,2,3,5,6,8a-hexahydronaphthalene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIII-Moderate toxicity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD-Limonene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIII-Moderate toxicity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMethyl eugenol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIII-Moderate toxicity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFurthermore, the evaluation revealed that none of the bioactive compounds exhibited carcinogenic properties, which is a crucial finding for their potential use in medical treatments. The majority of these compounds were found to be generally non-carcinogenic, further supporting their safety profile. The moderate levels of oral toxicity observed in these bioactive compounds from \u003cem\u003eE. viscosus\u003c/em\u003e suggest that they may be suitable candidates for therapeutic applications. This combination of wound healing and antioxidant properties, coupled with a favorable toxicity profile, opens up possibilities for developing new treatments or enhancing existing ones using these natural compounds. However, further research and clinical trials would be necessary to fully establish their efficacy and safety for specific medical applications.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe findings of this study highlight the potential of \u003cem\u003eE.viscosus\u003c/em\u003e extract as a source of bioactive compounds with therapeutic applications. Through computational methods, researchers have identified compounds that meet drug-likeness criteria and exhibit promising binding affinities to the 1L6J protein. The analysis revealed that both methanolic and essential oil extracts contained compounds capable of interacting with the target protein through various non-covalent interactions, including hydrogen bonding, van der Waals forces, and hydrophobic interactions (Wang et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Notably, the methanolic extract compounds demonstrated a higher number of hydrogen bonds and stronger binding potential than the essential oil-derived compounds, aligning with the understanding that hydrogen bonding significantly contributes to protein-ligand complex stability (Schiebel et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study is part of a broader trend in utilizing computational methods to screen plant-derived compounds for drug discovery. Similar studies have been conducted on various plant species including Gymnema sylvestre (Nganso Ditchou et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), Pleurotus ostreatus (Effiong et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), Wedelia trilobata (Gowtham et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Teucrium polium (Noumi et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and Caulerpa racemosa (Tassakka et al. 2023). These studies typically involve extracting compounds from plant materials, identifying them through techniques such as GC-MS or HPLC, conducting in silico molecular docking to predict binding affinities, and assessing drug-likeness properties through ADMET predictions. The consistent identification of promising compounds across these studies underscores the potential of plant-derived bioactive molecules for drug discovery and development.\u003c/p\u003e \u003cp\u003eThe in silico analyses conducted to assess the pharmacokinetic profiles and drug-likeness of the identified compounds provided crucial insights into their potential as therapeutic agents. These analyses focused on the absorption, distribution, metabolism, and excretion (ADME) properties, as well as the potential interactions with key enzymes and transporters. The results indicated that many compounds from various plant extracts, including Moringa oleifera seed extract and \u003cem\u003eE. viscosus\u003c/em\u003e methanolic extract, demonstrated good drug-likeness according to Lipinski's Rule of Five and Veber's rules (Shady et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This suggests that these compounds possess favorable physicochemical properties for oral bioavailability and drug development.\u003c/p\u003e \u003cp\u003eEssential oil compounds, in particular, show promising characteristics, such as high gastrointestinal (GI) absorption and blood-brain barrier (BBB) permeability. Studies on essential oils from plants such as Satureja kitaibelii and Ptychotis verticillata revealed the presence of compounds such as p-cymene, limonene, geraniol, carvacrol, and borneol (Nikolova et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2025\u003c/span\u003e;Taibi et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Similarly, compounds from guava essential oil exhibit good drug-likeness (Mandal et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, it is important to note that many of these compounds also showed potential inhibition of cytochrome P450 (CYP) enzymes, which could lead to drug-drug interactions. This highlights the need for a comprehensive evaluation of both the beneficial properties and potential risks when considering natural compounds for medicinal use, as exemplified by the study of antidiabetic flavonoids (Bitew et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe safety and efficacy of \u003cem\u003eE. viscosus\u003c/em\u003e for wound healing and antioxidant applications have been established along with a broader trend in phytochemical research. Methanolic extracts and essential oils derived from various plants have shown significant potential in these therapeutic areas (Ramasamy et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The bioactive compounds present in these extracts, including terpenoids, phenolics, and flavonoids, are primarily responsible for their medicinal properties (Bouyahya et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These compounds often exhibit synergistic effects, which enhance their overall therapeutic potential.\u003c/p\u003e \u003cp\u003eThe growing interest in plant-derived bioactive compounds stems from their promising therapeutic potential coupled with relatively low toxicity profiles. These characteristics make them attractive candidates for the development of new pharmaceutical products and natural remedies. The antioxidant properties of these compounds play a crucial role in wound healing by neutralizing free radicals and reducing oxidative stress in the damaged tissues. Additionally, many plant extracts possess antimicrobial properties that can prevent infections and promote faster wound closure. As research in this field progresses, more plant-derived compounds will likely be identified and characterized for potential applications in wound healing, antioxidant therapies, and other medical applications.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study confirmed the therapeutic potential of \u003cem\u003eEndostemon viscosus\u003c/em\u003e bioactive compounds, particularly those from the methanolic extract, in targeting MMP-9 for wound healing. The methanolic compounds exhibited strong binding interactions and hydrogen bonding, supporting their stability and efficacy. The ADME analysis demonstrated favorable pharmacokinetics, and toxicity assessments indicated moderate safety with no carcinogenic risk. These findings suggest that \u003cem\u003eE. viscosus\u003c/em\u003e could serve as a natural source of bioactive agents for wound-healing applications, encouraging further experimental validation through in vitro and in vivo studies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cb\u003eConflict of Interest declaration\u003c/b\u003e: None\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding Statement:\u003c/h2\u003e \u003cp\u003eNone\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthor contributions: KMS and SM conceived the idea; KMS experimented; KMS analyzed the data; KMS, SM, and SP wrote the manuscript; KMS, SM, and SP edited the manuscript, and all authors approved the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAly SH, Elissawy AM, Mahmoud AMA, El-Tokhy FS, Mageed SSA, Almahli H, Al-Rashood ST, Binjubair FA, Hassab MAE, Eldehna WM, Singab AE-NB (2023) Synergistic Effect of Sophora japonica and Glycyrrhiza glabra Flavonoid-Rich Fractions on Wound Healing: In Vivo and Molecular Docking Studies. 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Phytother Res 35:1176\u0026ndash;1186. https://doi.org/10.1002/ptr.6883\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"in-silico-pharmacology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"insp","sideBox":"Learn more about [In Silico Pharmacology](https://link.springer.com/journal/40203)","snPcode":"40203","submissionUrl":"https://submission.nature.com/new-submission/40203/3","title":"In Silico Pharmacology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"MMP-9, E.viscosus. essential oil, methanolic extract, Molecular docking, ADMET, wound healing","lastPublishedDoi":"10.21203/rs.3.rs-6789028/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6789028/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePlants have been valuable sources of bioactive compounds with therapeutic potential. The exploration of phytochemicals in plant extracts and essential oils has gained attention due to their biological activities and medicinal properties. This study investigated the phytochemicals in methanolic extracts and essential oils by analyzing molecular docking and toxicological profiles of their bioactive and pharmacokinetic properties. Molecular docking using AutoDock Vina, integrated within PyRx version 0.8, was employed to dock the chemicals into MMP-9 protein 1L6J. Among these, the highest-scoring compounds underwent pharmacokinetics, receptor-ligand interactions, and binding affinity analysis after identification by GC-MS analysis. To prepare the grid boxes for docking, the active sites of MMP-9 were predicted using CASTp. The findings revealed that several active ingredients in the methanolic extract, particularly 3-fluoro-5-trifluoromethylbenzoic acid, exhibited significant affinity for MMP-9 and strong interactions, including hydrogen bonding with the key residue TYR 52. Conversely, most interactions formed by the essential oil compounds were hydrophobic. In addition to their biological activity, ADME prediction indicated that both the methanol extract and essential oil possessed adequate drug-likeness characteristics, such as high gastrointestinal absorbability and low permeability through the blood-brain barrier. Based on the toxicological predictions using AdmetSAR 1, the compounds were moderately toxic (class III); however, there were no indications of carcinogenic risk. The observed characteristics of bioactive chemicals derived from \u003cem\u003eE. viscosus\u003c/em\u003e support their potential application in wound healing, suggesting that these compounds have favorable pharmacokinetic and safety profiles and exhibit a high MMP-9 inhibitory capacity.\u003c/p\u003e","manuscriptTitle":"Insilico Pharmacological Profiling of Endostemon Viscosus Bioactive Compounds Targeting MMP-9 for Wound Healing","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-02 09:23:03","doi":"10.21203/rs.3.rs-6789028/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-12T23:18:14+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-12T01:42:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"68933386375504896968357451253168363405","date":"2025-06-29T23:23:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-29T22:30:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-03T02:24:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-03T02:23:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"In Silico Pharmacology","date":"2025-05-31T06:18:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"in-silico-pharmacology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"insp","sideBox":"Learn more about [In Silico Pharmacology](https://link.springer.com/journal/40203)","snPcode":"40203","submissionUrl":"https://submission.nature.com/new-submission/40203/3","title":"In Silico Pharmacology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"7bbebe16-c73f-477d-84eb-08215e760dd3","owner":[],"postedDate":"July 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-01T16:00:36+00:00","versionOfRecord":{"articleIdentity":"rs-6789028","link":"https://doi.org/10.1007/s40203-025-00487-2","journal":{"identity":"in-silico-pharmacology","isVorOnly":false,"title":"In Silico Pharmacology"},"publishedOn":"2025-11-26 15:56:52","publishedOnDateReadable":"November 26th, 2025"},"versionCreatedAt":"2025-07-02 09:23:03","video":"","vorDoi":"10.1007/s40203-025-00487-2","vorDoiUrl":"https://doi.org/10.1007/s40203-025-00487-2","workflowStages":[]},"version":"v1","identity":"rs-6789028","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6789028","identity":"rs-6789028","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}