Pharmacological and Molecular Docking studies of Allium ampeloprasum L.

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Deepti Teotia, Anjali Malik, Vijai Malik This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7126283/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: To investigate the bioactive compounds present in the leaf extract of Allium ampeloprasum and evaluate its antioxidant and antibacterial potential using experimental and computational methods. Methods: The phytochemical composition of the leaf extract was analyzed using Gas Chromatography-Mass Spectrometry (GC-MS). Antioxidant activity was determined using the DPPH radical scavenging assay, while the Antibacterial activity was tested against four bacterial strains ( Pseudomonas aeruginosa , Staphylococcus aureus , Escherichia coli , and Bacillus subtilis ) using the well diffusion method. Molecular docking was conducted to assess the binding affinities of identified compounds with bacterial DNA gyrase, followed by Molecular Dynamics (MD) simulations, MM-PBSA (Molecular Mechanics Poisson–Boltzmann Surface Area) and PCA (Principle component analysis) to evaluate complex stability. Results: The leaf extract of A. ampeloprasum showed the strong antioxidant activity, with DPPH radical scavenging reaching up to 87.3% at 500 µg/mL, attributed to its phenolic and flavonoid content. The highest antibacterial activity was against Bacillus subtilis (10 mm inhibition zone at 1000 µL/mL), followed by Escherichia coli and Staphylococcus aureus (7 mm each at 1000 µL/mL concentration). GC-MS analysis revealed several bioactive compounds, among which gamma-sitosterol exhibited the strongest binding affinity to DNA gyrase (-7.1 kcal/mol), comparable to ciprofloxacin. MD simulation and MM-PBSA and Principle component analysis confirmed the stability of the gamma-sitosterol–DNA gyrase complex. Conclusion: The leaf extract of A. ampeloprasum possesses strong antibacterial and antioxidant properties due to the presence of valuable natural compounds. In India, this plant is not commonly cultivated and remains underutilized, despite offering numerous health benefits. Currently, A. ampeloprasum is being grown as a commercial crop in the Uttarakhand hills, Manipur, and Kashmir. Since it is growing well in the study area, it can be recommended to farmers for food value addition and for use in functional food development. This may also be important for selecting superior Allium genotypes with enhanced bioactive properties. While Allium sativum L. and Allium cepa L. are commonly grown species across India, the introduction of A. ampeloprasum in new regions could provide access to natural medicines and offer farmers new income opportunities through the cultivation of medicinal plants. Computational Biology Drug Discovery, Design, & Development Allium ampeloprasum Antibacterial activity Antioxidant activity GC-MS analysis Molecular Docking MD Simulation MM-PBSA PCA Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction In recent years, medicinal plants have gained significant attention as natural sources of antibacterial compounds. These natural alternatives not only help combat antibiotic resistance but also minimize the side effects associated with chemical antibiotics (Tavakkoli et al., 2015). Genus Allium includes more than 1,089 accepted species (POWO, 2021) among them garlic ( Allium sativum ), onion ( Allium cepa ), leeks ( Allium ampeloprasum var. porrum ), chives ( Allium schoenoprasum ), and shallots ( Allium ascalonicum ) are the most utilized and studied edible species (Poojary et al., 2017). The genus Allium has long been recognized for its ethno pharmacological significance, owing to its diverse medicinal properties and widespread traditional use across different cultures (Teotia et al., 2024). Allium species offer a wide array of health benefits, including antiviral, antibacterial, antifungal, antidiabetic, anticancer, antiplatelet, antispasmodic, antiseptic, anthelmintic, antithrombotic, antiasthmatic, carminative, antioxidant, anti-inflammatory, antihypertensive, hypoglycemic, hypotensive, lithontriptic, and hypocholesterolemic effects (Najeebullah et al., 2021). Garlic, a widely studied member of the Allium genus, exhibits potent antimicrobial properties due to presence of bioactive compounds, including allicin, vinyldithiin, ajoene, and diallyl polysulfides (Muhsin et al., 2015). Recent studies have shown an association between reduced risk and incidence of breast cancer with the consumption of certain Allium species, especially Allium sativum and Allium ampeloprasum (Pourzand et al., 2016). Allium ampeloprasum L. (Amaryllidaceae) is a monocotyledonous plant which is commonly known as broadleaf wild leek. This is a unique species, single-pod garlic which is highly valued for its medicinal properties (Dey & Khaled, 2015). Native to the Mediterranean region—including Southern Europe, North Africa, and Western Asia, it has been introduced to other parts of the world, such as North and South America and Australia, and is cultivated in various regions of Asia, including India (Guhabakshi et al., 1999). A. ampeloprasum possesses a range of pharmacological properties, including antitoxic, antioxidative, immunostimulatory, and anti-inflammatory effects due to the presence of many sulphur containing bio-active constituents which include: dimethyl disulphide, methyl propenyl disulphide, propyl propenyl disulphide, dimethyl trisulfide, methyl propyl trisulfide, methyl propenyl trisulfide, S-methyl cysteine sulfoxide, S-propyl cysteine sulfoxide, S-propenyl cysteine sulfoxide and N-(γ-glutamyl)-S-(E-1-propenyl) cysteine (Dey & Khaled, 2015). A. ampeloprasum is recognized as a valuable source of dietary fiber, zinc, polyunsaturated fatty acids particularly linoleic acid as well as a range of lipophilic and hydrophilic bioactive compounds exhibiting significant antioxidant activity (Devi et al., 2014). Gas Chromatography-Mass Spectrometry (GC-MS) is a crucial analytical technique for characterizing the complex chemical composition of plant extracts. This method allows for the identification and quantification of a broad spectrum of bioactive compounds, providing a detailed chemical profile of the plant (Jain et al., 2024). DNA gyrase, a type II topoisomerase, is a key enzyme that has been used as a target in molecular docking studies. This enzyme introduces negative supercoils into DNA using ATP hydrolysis and is essential for bacterial survival, while being absent in higher eukaryotes (Reece & Maxwell, 1991). This make it an attractive target for antibacterial drug development. Fluoroquinolones, such as ciprofloxacin, are well-established gyrase inhibitors and are frequently used as positive controls in various in vitro studies (Richards et al. 1998). Several in vitro and in vivo studies have been conducted to evaluate the antimicrobial potential of Allium spp. such as the methanol extracts of Allium were tested against a set of Gram-positive ( Staphylococcus aureus, Staphylococcus feacalis, Bacillus cereus, Enterococcus feacium and Bacillus subtilis ) and Gram-negative ( Escherichia coli, Pseudomonas aeruginosa and Enterobacter feacalis ) bacterial strains (Dziri et al., 2012). Bareemizadeh et al. (2014) demonstrated that ethyl acetate extracts of A. ampeloprasum exhibited strong antimicrobial activity against Klebsiella pneumoniae and Shigella flexneri at a concentration of 250 µg/mL, likely due to its pinene and phenol content. Caputo et al. (2022) reported that extracts from the aerial parts of A. ampeloprasum significantly inhibited the adhesion of P. aeruginosa (95.78%) and S. aureus (85.01%). Conversely, Añides et al. (2021) found that while A. ampeloprasum extracts did not inhibit P. aeruginosa and B. subtilis , they exhibited strong antibacterial effects against E. coli , K. pneumoniae , S. typhimurium , and S. aureus . The authors did not find antimicrobial activity with in-silico validation of A. ampeloprasum extract against Bacillus subtilis, Escherichia coli , Pseudomonas aeruginosa and Staphylococcus aureus . Therefore, the aim of the present study was to investigate the bioactive compounds present in the leaf extract of A. ampeloprasum and evaluate their antibacterial potential through well diffusion assay and antioxidant activity, molecular docking, molecular dynamics simulations and MMPBSA studies with a focus on identifying potential plant-derived inhibitors of bacterial DNA gyrase. Material and Methods 1. Collection of Plant material Plant sapling of A. ampeloprasum were collected from Bhowali station Nanital (Uttrakhand) and grown in Botanical garden of CCSU, Meerut, Uttar Pradesh (India) in the month of October 2023. Leaves of plant were harvested in month of July 2024 for experimental purpose. 1.1. Preparation of Plant extract Samples were ground and then 2.5 gm of samples were taken and mixed with 25 ml of solvent (Absolute Methanol). Sample mixtures were incubated on a rocker shaker for 24 hours. The extracts were filter with Whatman filter 1. Then extracts were completely dried in the oven at 40°C. Extracts were collected in micro centrifuge tube and stored at 4°C. Further dilution is done by using distilled water. Five concentration of plant extracts were used for antibacterial assay i.e., 50 (µg/well), 125 (µg/well), 250 (µg/well), 500 (µg/well) and 1000 (µg/well). 1.2. Percentage yield Percentage yield (PY) of the concentration crude extract was estimated using the formula given below: Yield % = weight of crude plant extract x 100/ weight of powdered plant material 1.3. GC-MS analysis The extracted plant samples were analyzed using Gas Chromatography-Mass Spectrometry (GC-MS) to identify and measure their chemical constituents. A high-resolution instrument with a fused silica capillary column, specifically the SH-Rxi-5Sil MS column (5% biphenyl and 95% dimethyl polysiloxane), measuring 30 meters in length, 0.25 mm in inner diameter, and with a 0.25 μm film thickness was employed. The analysis was conducted at a temperature range of 320-350°C. Helium (He) was used as the mobile phase, flowing at 1.0 ml/min. The gas chromatography process started at 50°C and increased to 300°C at a rate of 5°C/min. A 1 microliter injection volume was used. Samples dissolved in methanol, were analyzed within a mass-to-charge ratio (m/z) range of 50-650. The results were compared using an integrated chemical library search program that identified individual compounds based on their retention times and mass spectra. Peak integration and area normalization quantified the relative abundance of each compound in the sample. 1.4. Total Phenolic Content (TPC) TPC was estimated using Folin-Ciocalteu Colorimetric method of Aiyegroro & Okoh, (2010) with slight modification. 2.5 mL of freshly synthesized Folin-ciocalteu reagent (10%) was poured into test tube containing 1 mL of plant extract. 2 mL Na 2 CO 3 (2%) was then added to the test tube and kept under the dark conditions for 30 minutes. Absorbance was noted at 765 nm using UV-Vis Spectrophotometer (Shimadzu-80228), Japan. Gallic acid (1mg/mL) was used as standard and five concentrations (20-100 μg/mL) were used for preparing standard curve. 1mL solvent along with 2.5 mL Folin-Ciocalteu reagent and 2mL Na 2 CO 3 solutions was used as blank. Experiment were performed in triplicates and TPC was calculated using the calibration curve (y=0.0119x + 0.2346, R 2 =0.998). TPC in plant extracts was calculated by the formula given below and expressed in mg Gallic Acid Equivalent (GAE)/gm T = C x V/M Here, T = Total Phenol Content mg/gm GAE C = Concentration of Gallic Acid obtained from the calibration curve in mg V= Volume of plant extract in mL M = Weight of plant extract in gm 1.5. Total Flavonoid Content (TFC) TFC was estimated using Aluminium Chloride Colorimetric method used by Aiyegroro & Okoh, (2010) with minor modifications. 0.3mL aluminium chloride (10%) and 0.3mL potassium acetate (1M) were poured in a test tube containing 1 mL of plant extract. 3mL of methanol and 3.5mL of distilled water was taken and then added to the test tube. This was kept under dark conditions for 30 minutes. Absorbance of the solution was noted at 417 nm. Quercetin (1mg/mL) was considered as reference compound and standard curve was prepared using five concentrations (20-100 μg/mL). All the experiment was performed in triplicates and the mean value was used for further calculations. The calibration curve (y=0.0188x+0.1532, R 2 +0.9993) was used to calculate the TFC of the plant extracts. TFC of the plant extract was calculated using the formula given below. TFC was expressed in mg/gm of Quercetin equivalent (mg QE/g). T + C x V/M Here, T = Total Flavonoid Content mg/gm Quercetin Equivalent (QE) C = Concentration of Quercetin obtained from the calibration curve in mg V= Volume of plant extract in mL M = Weight of plant extract in gm 1.6. Antioxidant Activity Each sample was dissolved in 95% methanol to make a concentration of 1 mg/ml and then diluted to prepare the series concentrations for antioxidant assays. 1.6.1. DPPH Assay The free radical scavenging activity of the fractions was measured in vitro by 2,2 - diphenyl-1-picrylhydrazyl (DPPH) assay according to the method described as Brand-Williams et. al., (1995). A 0.1 mM DPPH solution was prepared in methanol. Plant samples at five varying concentrations (20-100 μg/mL) were mixed with the DPPH solution in a 1:1 ratio and incubated in the dark for 20–30 minutes. Absorbance was measured at 517 nm using a spectrophotometer. DPPH mixed in methanol solvent was taken as control. Ascorbic acid was used as standard. Lower absorbance indicates higher activity. IC50 values can be determined for comparative analysis. Antioxidant activity was calculated as % inhibition of DPPH using the formula: % Inhibition = (Abc – Abs)/ Abc x 100 Here, Abc is Absorbance of Control Abs is Absorbance of Sample (Standard / plant extract) 1.6.2. IC 50 value IC 50 is the concentration of the plant extract/standard required to scavenging 50% of the free radicals. This value is inversely related to the antioxidant capacity as lower the IC 50 values higher is the antioxidant capability and vice-versa. The value was calculated using the formula y = mx+b; which was obtained by plotting the graph between the concentration and % inhibition recorded in the DPPH assay. 2. Antimicrobial studies Antimicrobial efficacy for the plant extracts was assessed using four aforementioned bacterial strains. Well diffusion assay was used to determine the zone of inhibition (ZOI) of the plant extract (Bauer et al., 1966). 2.1. Bacterial Strains Bacterial strains used in the present investigation were Bacillus subtilis (MTCC-2057), Escherichia coli (MTCC-41), Pseudomonas aeruginosa (MTCC-2453) and Staphylococcus aureus (MTCC-96) were obtained from Microbial Type Culture Collection and Gene Bank (MTCC), Institute of Microbial Technology Chandigarh. 2.2. Bacterial culture Bacterial strains were cultured in nutrient agar procured from Hi-media. About 28 gm of nutrient agar powder was mixed in 1000 mL distilled water followed by autoclaving for 20 minutes at 121 o C and 15 psi pressure. A loopful of lyophilized bacteria (powdered form) was streaked on the solid and sterilized nutrient agar plates. Streaked bacterial plates were incubated for 24 hours in B.O.D incubater shaker at 37 o C for 24 hours. For experimental studies, the turbidity of bacterial cultures was checked and calibrated to standard i.e., 0.5 McFarland (1.5x 10 8 CFU/mL). 2.3. Well diffusion assay To assess the antibacterial potential of the plant extracts, well diffusion assay was carried out (Bauer et al., 1996). About 28 gm of nutrient agar was mixed in 1000 mL distilled water and kept in autoclave at 121 o C for 20 minutes. 25 mL of sterilized nutrient agar media was poured in aseptic petri plates. 100 µL of calibrated bacterial culture (1.5x 10 8 CFU/mL) was evenly spread over the solidified media. 10 µL of plant extract with five different concentrations 50 (µg/mL), 125 (µg/mL), 250 (µg/mL), 500 (µg/mL) and 1000 (µg/mL) were loaded in wells and name them A, B, C, D & E respectively. Ciprofloxacin (0.1mg/mL) was used as positive control and loaded with it labelled as F. Prepared petri plates were then incubated in B.O.D at 37 o C for 24 hours. The ZOI obtained was measured using antibacterial scale, Himedia. The experiments were performed in triplicates and the mean value of ZOI was recorded. 3. Detailed Methodology of Molecular Docking 3.1 Library generation and protein retrieval The 3D structure of ligands isolated from methanolic extract of A. ampeloprasum leaves were downloaded from PubChem database (https://pubchem.ncbi.nlm.nih.gov) in an SDF file format. It is then converted into PDBQT format by using Open Babel GUI (O’Boyle et al., 2011). The 3D protein structure of the target enzyme DNA Gyrase with PDB ID 6fju was downloaded from protein data bank i.e.., RCSB PDB (https://www.rcsb.org/) in PDB (Protein Databank) format. It was converted into PDBQT format by Autodock 4.2. (Morris et al., 2009). The protein subjected to energy minimization and optimization with the help of SPDBV, to make it stable. Now, this protein was used for performing the molecular docking process by using Autodock Vina (Morris et al., 2009). 3.2. Molecular Docking studies The molecular docking studies of all the identified compounds and proteins were performed with AutoDock Vina (Morris et al., 2009). Receptor active site dimensions were set at -31.684 x 8.021 x -4.598 XYZ coordinates for 6fju with 0.375 grid spacing for each atom type. The box dimension was kept as 40 A 0 x 40 A 0 x 40 A 0 (Aliye et al., 2021). Ten confirmations were obtained for each docking experiment, each with a corresponding binding affinity expressed in kcal/mol. For further studies, the ligand-binding position with the lowest binding energy was selected. In our investigation, the phytochemicals that have strong interactions with target enzymes were further examined. 3.3. Visualization of Ligand-Protein interaction The best possible 2D structures between ligand and protein were analyzed using Discovery Studio Visualizer for different interactions such as conventional H Bond, Vander wall interactions, Carbon H Bond, Pi-Alkyl, Pi-Sulphur, Pi-Sigma, Pi-Anion and Alkyl are visualized (Design et al., 2014). 3.4. Molecular Dynamics simulation To assess the dynamic properties of the ligand-protein complexes, MD simulations were conducted. The Charmm36-feb 2021.ff force field was utilized in all simulations using GROMACS 2020.1-1 version. The ligand topology files were created using the CGenFF server (Vanommeslaeghe et al., 2010). Protein complexes that had been created were solved in a cubic box, and enough ions were added to keep the system neutral. The steepest descent approach was used to minimize the system's energy with a convergence threshold of less than 1000 kJ/mol/nm in order to remove any steric collisions among atoms. Equilibration was carried out in two stages. The solvent and ions were kept unrestrained in the NVT ensemble for 100ns in the first phase, while the restraint weight from the protein and protein-ligand complexes was gradually reduced in the NPT ensemble for 100ns in the second phase. The LINCS algorithm was used to keep all hydrogen bonds constrained. Utilizing Berendsen's temperature and Parrinello-Rahman pressure coupling, the temperature and pressure of the system were kept at 300 K and 1 atm respectively (Berendsen et al.,1984). The conformational dynamics and stability of protein–ligand complexes were analyzed using GROMACS and Python 3.8 by monitoring backbone RMSD, ligand RMSD, complex RMSD, RMSF, radius of gyration (Rg), and solvent-accessible surface area (SASA). 3.5. MMPBSA free energy calculation MMPBSA was used to calculate the binding energy and the energy contribution per residue. In MMPBSA, the nonpolar component (ΔGnpsolv) was computed using a linear connection to the solvent accessible surface area (SASA), whereas the polar percentage of solvation energy (ΔGpsolv) was evaluated by solving the Poisson-Boltzmann equation. In this study, different parts of the binding free energy of complexes were estimated using the gmmpbsa module of GROMACS (Kumara et al., 2014). The 100ns of the trajectory were used in the analysis. 3.6. Principal Component Analysis Principal Component Analysis (PCA) was carried out using the Galaxy server (Sloggett et al., 2013) to investigate the dynamic behavior of protein-ligand complexes. Protein conformation plays a critical role in maintaining the structural integrity required for effective binding. The covariance matrix generated during the simulation was utilized to analyze the large-scale motions within the enzyme-ligand systems. PCA is a widely accepted approach for identifying key conformational changes and assessing the flexibility of biomolecular structures. This computational strategy enabled a wide-range evaluation of the structural dynamics and energetic profiles of the protein-ligand interactions that offer valuable insights into the therapeutic potential of A. ampeloprasum phytochemicals. Results 4.1. Percentage yield The percentage yield of methanolic leaf extract from A. ampeloprasum was determined through an extraction process. A total of 2500 gm of powdered leaf material was used, yielding 367 mg of extract with 14.68%, recovery percentage. 4.2. GC-MS analysis The methanol extracts of A. ampeloprasum, overall 23 different compounds were identified (table 1) along with their retention time and m/z value. The GC-MS chromatogram which shows peak 1 with an m/z value of 43.00, corresponding to 2- Pentanol, acetate, while peak 2, with an m/z value of 57.00, 2-(Isobutoxymethyl)oxirane. peak 3, 4, 5 and 6 with m/z 73.00, 73.00, 73.00, and 68.05 respectively, reveal the presence of Dodecanoic acid, methyl ester, Dodecanoic acid, methyl ester, Methyl tetradecanoate and Neophytadiene which are fatty acid compounds. Peak 7, 8, 9 with an m/z value 43.05, 81.05 and 81.05 are shown the presence of compound 2-Pentadecanone, 6,10,14-trimethyl- and Neophytadiene. Peak 10 and 11 with an m/z value 74.00, 73.00 indicates the compound is Hexadenoic acid, methyl ester and n-Hexadecanoic acid. Peak 12,13 and 14 with m/z value 67.00, 55.05 and 55.05 are 9,12-Octadecadienoic acid (Z,Z)-, methyl ester, 9-Octadecenoic acid, methyl ester, (E)-and 9-Octadecenoic acid (Z)-, methyl ester respectively. Peak 15 with an m/z value 71.05 is phytol, and peak 16 with an m/z value is 74.00 is Methyl stearate. Peak 17, 18, 19 with m/z value 57.00 is Hexatriacontane, Tetracosane and Tetracontane. Peak 20 with m/z value 97.10 represents octacosanol. Peak 21 with an m/z value 147.10 is beta-Sitosterol acetate, and peak 22 with an m/z value 165.00 is alpha.-Tocopherol-.beta.-D-mannoside. Peak 23, 24 and 25 with an m/z value 57.05, 239.15, 43.05 represents compounds Phytyl stearate, 16-Hentriacontanone and gamma-Sitosterol respectively. The GC-MS chromatogram of different peaks corresponding to their respective compounds are given in fig.1, table 1. Table 1. List of Bioactive Compounds Identified through GC-MS analysis from methanolic leaf extract of A. ampeloprasum S.N Compound Name Formula MW RT Peak area Class Reported activity References 1 2-Pentanol, acetate C7H14O2 130.18 2.53 1 Carboxylic acid ester Not found 2 2-(Isobutoxymethyl)oxirane C7H14O2 130.18 12.997 9.09 Glycidyl ether Not found 3 Dodecanoic acid, methyl ester C13H26O2 214.34 13.695 0.54 Fatty acid ester Antimicrobial Reddy et al., 2018 4 Dodecanoic acid, methyl ester C13H26O2 214.34 13.752 3.64 Fatty acid ester Antimicrobial Reddy et al., 2018 5 Methyl tetradecanoate C15H30O2 242.4 16.071 3.02 Fatty acid ester Anticancer Ukwubile et al., 2019 6 Neophytadiene C20H38 278.52 17.261 6.91 Diterpenes anti-inflammatory, anti-microbial, antioxidant Akter et al., 2024 7 2-Pentadecanone, 6,10,14-trimethyl- C18H36O 268.48 17.335 0.5 Fatty acid Antimicrobial Amos-Tautua et al., 2020 8 Neophytadiene C20H38 278.52 17.516 2.48 Diterpenes anti-inflammatory, anti-microbial, antioxidant Akter et al., 2024 9 Neophytadiene C20H38 278.52 17.705 3.69 Diterpenes anti-inflammatory, anti-microbial, antioxidant Akter et al., 2024 10 Hexadecanoic acid, methyl ester C17H34O2 270.45 18.163 20.2 Fatty acid ester Antioxidant, anticancer, antidiabetic, nephroprotective, anti-inflammatory, and antibacterial Akter et al., 2024 11 n-Hexadecanoic acid C16H32O2 256.42 18.538 2.17 Fatty acid Anti-inflammatory antimicrobial, antioxidant, anticancer Antitumor & Hypocholesterolemic Akter et al., 2024 12 9,12-Octadecadienoic acid (Z,Z)-, methyl ester C19H34O2 294.47 19.781 3.43 Fatty acid ester Antioxidant, antimicrobial, and anti-inflammatory Akter et al., 2024 13 9-Octadecenoic acid, methyl ester, (E)- C19H36O2 296.49 19.837 14.9 Fatty acid ester Antimicrobial, Antifungal, Antioxidant Akkoyunlu et al., 2022 14 9-Octadecenoic acid (Z)-, methyl ester C19H36O2 296.49 19.905 0.68 Fatty acid ester Antimicrobial, Antifungal, Antioxidant Akkoyunlu et al., 2022 15 Phytol C20H40O 296.53 19.939 0.84 Diterpene alcohol Antioxidant, antidiabetic, anticancer, anti-inflammatory, antitumor, chemoprotective, antimicrobial, antiprotozoal, histamine release inhibitor, and antimicrobial Akter et al., 2024 16 Methyl stearate C19H38O2 298.5 20.078 3.19 Fatty acid methyl ester Anti-inflammatory, antidiarrheal, cytotoxic, antiproliferative, and antioxidant Akter et al., 2024 17 Hexatriacontane C36H74 506.97 24.718 1.32 Hydrocarbon Antibacterial, Antiviral, Antioxidant Aadesariya et al., 2018 18 Tetracosane C24H50 338.65 26.116 0.56 Hydrocarbon Antimicrobial, Antifungal, Antioxidant Akkoyunlu et al., 2022 19 Tetracontane C40H82 563.08 27.425 0.83 Hydrocarbon Antifungal Pavirhra et al., 2020 20 Octacosanol C28H58O 410.76 27.48 0.87 Fatty acid alcohol anticancer activity, hypocholesterolemic agent, anticoagulant activity Umoh et al., 2025 21 .beta.-Sitosterol acetate C31H52O2 456.74 27.514 1.26 Triterpenoid Antimicrobial Nweze et al., 2019 22 alpha.-Tocopherol-.beta.-D-mannoside C35H60O7 592.85 27.665 0.61 Vitamin E Antidiabetic, Antioxidant Chike-Ekwughe et al., 2023 23 Phytyl stearate C38H74O2 562.99 27.769 0.98 Fatty acid ester Not found 24 16-Hentriacontanone C31H62O 450.82 28.63 11.87 dialkyl ketone Antimicrobial Shanker et al., 2005 25 gamma-sitosterol C29H50O 414.71 29.032 5.42 Phytosterol Antidiabetic (Increase insulin secretion and inhibit glucogenesis) Akter et al., 2024 4.3. Total Phenolic Content A standard calibration curve was constructed using gallic acid as the reference phenolic compound (fig. 2A). The absorbance values obtained from the plant extract were then compared against this standard curve to determine the phenolic concentration. The TPC of the A. ampeloprasum extract was found to be 15.45 ± 0.51 mg gallic acid equivalents (GAE) per gram of extract (fig. D). These results indicate a moderate presence of phenolic compounds, which are known to contribute to the antioxidant properties of plant-based extracts. 4.4. Total Flavonoid Content Quantification of TFC was performed using the aluminum chloride colorimetric method. A standard calibration curve was generated using quercetin as the reference flavonoid compound, as shown in fig. 2 B. The absorbance values of the plant extract were measured and compared to this standard curve to estimate the flavonoid concentration. The TFC of the A. ampeloprasum extract was determined to be 21.71 ± 0.51 mg quercetin equivalents (QE) per gram of extract, as illustrated in fig. 2 D. The relatively high flavonoid content suggests the potential of A. ampeloprasum as a natural source of antioxidant compounds. 4.5. DPPH Assay The antioxidant potential of the sample was assessed using the DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging assay across a concentration range of 10 to 100 µg/mL. The percentage radical scavenging activity (%RSA) demonstrated a clear concentration-dependent increase, rising from 50.74% at 10 µg/mL to 93.70% at 100 µg/mL, indicating strong antioxidant potential. The regression equation obtained from the plotted data was y = 0.4466x + 49.334 with an R² value of 0.9829. This linearity confirms the reliability of the experimental results (Figure 3C). To quantify the effectiveness of the sample, the IC₅₀ value (the concentration required to scavenge 50% of DPPH radicals) was calculated using the following interpolation formula: IC50 = C1+(%RSA2−%RSA150−%RSA1) × (C2−C1) Where: C₁ = 10 µg/mL (concentration at %RSA₁ = 50.74) C₂ = 20 µg/mL (concentration at %RSA₂ = 60.19) This low IC₅₀ value of 9.22 µg/mL indicates that the sample possesses potent free radical scavenging ability, consistent with previously reported results (Kumar et al., 2014). 4.6. Antibacterial studies Well diffusion assay The antibacterial efficacy of A. ampeloprasum leaf extracts was assessed using five different concentrations (1000 µL/mL, 500 µL/mL, 250 µL/mL, 125 µL/mL, and 50 µL/mL) through the well diffusion assay. The study targeted four bacterial strains, including two Gram-positive ( Bacillus subtilis and Staphylococcus aureus ) and two Gram-negative bacteria ( Escherichia coli and Pseudomonas aeruginosa ). The zones of inhibition (ZOI) were obtained for each bacterial strain at the various extract concentrations table 2. The concentration-dependent antibacterial activity and the differential susceptibility of the bacterial strains to the extracts are given in fig, 3. Graphical representation of ZOI obtained with A. ampeloprasum extracts with positive control (ciprofloxacin) against four bacterial strains are presented in fig, 4. The highest zone of inhibition (ZOI) was observed against B. subtilis across all tested concentrations. The recorded ZOI values were as follows: 10 ± 0.34 mm at 1000 µL/mL, 8 ± 0.44 mm at 500 µL/mL, 7 ± 0.37 mm at 250 µL/mL, 7 ± 0.43 mm at 125 µL/mL, and 7 ± 0.15 mm at 50 µL/mL. In contrast, S. aureus exhibited minimal inhibition, with a ZOI of 6 ± 0.64 mm observed only at the highest concentration of 1000 µL/well. P. aeruginosa showed consistent ZOI values of 6 ± 0.33 mm across the concentrations of 1000, 500, and 250 µL/mL. Similarly, E. coli demonstrated its maximum ZOI of 7 ± 0.05 mm at 1000 µL/mL, with similar inhibition levels of 6 ± 0.04 mm at both 500 and 250 µL/mL. Table 2 . Zone of Inhibition (mm) obtained against four different bacterial strains Amount (µg/well) S. aureus P. aeruginosa E. coli B. subtilis PC 30 27.33 28.66 28.66 0 0 0 0 0 50 0 0 0 5.5 ±0.66 125 6 ± 0.56 6 ± 0.064 5 ± 0.16 6.2 ± 0.15 250 6.33± 0.64 7 ± 0.77 5 ± 0.47 6.7 ±0.64 500 7.33 ± 0.399 7.33 ± 0.21 5.55 ± 0.33 7. 0 ± 0.11 1000 7.33 ± 0.322 8 ± 0.54 7.44 ± 0.26 10 ± 0.55 4.7. In silico Docking Studies The GC–MS analysis revealed that A. ampeloprasum leaf methanolic extracts contained 21 different bioactive compounds. However, 3D structure of 9-Octadecenoic acid methyl ester (E)-, 9-Octadecenoic acid (Z)-methyl ester, Methyl sterate, Hexatriacontane, Tetracosane, Tetracontane, Octacosanol, beta-sitosterol are not avaliabe on Pubchem (Kim et al., 2016). All the available compounds with their Compound ID, Canonical smiles and 3D structure represents in table 3. These identified compounds were subjected to molecular docking studies against DNA Gyrase by using Autodock vina (Morris et al., 2009). Out of twenty-one GC-MS identified compounds, only four compounds namely 2-Pentadecanone, 6, 10, 14-trimethyl-, gamma-sitosterol, Neophytadiene and Phytol shows binding interaction with DNA gyrase. The compound gamma-sitosterol formed highest binding energy i.e., -7.1 kcal/mol out of selected compounds with one conventional H bond against DNA gyrase at ASP 73. Binding interactions of all interacted compounds of A. ampeloprasum with interacting amino acid were analysed using Discovery Studio Vizualizer (Design et al., 2014) (fig. 5a & 5b, table 4). The different bonding interactions of ligand and protein residues are hydrogen, hydrophobic (alkyl), hydrophobic (pi-alkyl), pi-lone pair (table 3). Table 4 . Docking of DNA gyrase with compounds identified through GC-MS analysis Compound name Type of H Bond Binding Energy with alpha amylase Number of H bonds involved in bonding Amino acid involved in H bond Ciprofloxin Conventional H-Bond, Alkyl, Pi-Alkyl, Pi-Anion -7.1 2 Asn 46, Thr 165 2-Pentadecanone, 6,10,14-trimethyl- Alkyl Bond -4.9 Gamma-sitosterol Conventional H-Bond, Alkyl Bond -7.1 1 Asp 73 Neophytadiene Alkyl -5.6 Phytol Conventional H-Bond, Alkyl Bond -5.1 1 Val 167 5. Molecular Dynamic Simulation 5.1. Root Mean Square Deviation (RMSD) Analysis The Root Mean Square Deviation (RMSD) is a crucial parameter for quantifying the extent of conformational changes in proteins during molecular dynamics (MD) simulations. In this study, the RMSD of the Cα atoms from their initial structures was calculated to evaluate the stability of the protein-ligand complexes. The time-dependent RMSD of the backbone atoms of DNA gyrase in both free and ligand-bound states was observed to range between 0.2nm to 0.25nm, the plateau is remaining stabilize from 0 to 100 ns throughout the simulation. The range of ciprofloxacin (standard antibacterial drug) and gamma-sitosterol are overlapping during whole simulation. This indicates a high degree of stability with DNA gyrase in its ligand-bound conformations. It has been observed that the RMSD values for all systems remained below 0.3 nm throughout the simulation period (fig. 6A) with minimal deviation of the enzyme from its starting conformation indicates the stability of complex. Furthermore, the binding of phytomolecules did not induce significant conformational changes in the protein backbone. This affirms the structural stability of DNA gyrase protein in the presence of ligands. 5.2. Flexibility and Dynamics Analysis Using Root Mean Square Fluctuation (RMSF) The flexibility and dynamics of the system were assessed through RMSF analysis. The majority of the enzyme residues exhibited RMSF values ranging from 0.2 to 0.5 nm (fig.6 B). This value indicates minimal fluctuations. This observation suggests that the positional stability of the amino acid residues remains largely unaffected by the binding of the phytochemical to the active site of enzyme DNA gyrase. Consequently, it can be concluded that the ligand-protein interaction does not significantly alter the overall dynamics of the protein. 5.3. Radius of Gyration Analysis (Rg) The radius of gyration (Rg) serves as a measure of protein compactness, with lower Rg values indicating greater stability. Since ligand binding can potentially induce protein unfolding, the variation in Rg was analyzed throughout the simulation for all cases. For the unbound state of DNA gyrase (control), the Rg values were centered around ~1.6 nm. Similarly, Rg values ranging from ~1.58 to 1.62 nm were observed with ligand bound state phytomolecules i.e., ciprofloxacin, gama-sitosterol and phytol (fig.6C). These results indicate that the binding of the phytomolecules does not affect the structural integrity or compactness of DNA gyrase. 5.4 Solvent Accessible Surface Area (SASA) Analysis Hydrophobic interactions between non-polar amino acids play an important role in stabilizing globular proteins by shielding these residues within hydrophobic cores from the aqueous environment. The solvent-accessible surface area (SASA) provides a theoretical measure of changes in protein accessibility to solvent, reflecting the contribution of free energy of solvation for each atom in the system, including water, and the polar and non-polar amino acids of the protein. In the case of unbound DNA gyrase (control), SASA profile peaked at approximately ~95-98 nm². Upon binding with ligands, the SASA values shifted to a range of ~95–105nm² (fig.6 D). Since the observed SASA values show minimal deviation compared to the control, it can be inferred that the binding of these compounds does not disrupt protein folding or alter the structural integrity of protein. 5.5. Hydrogen Bond Analysis The hydrogen bond interactions between DNA gyrase and the bioactive metabolites were evaluated using the hydrogen bond module of GROMACS. The distribution of hydrogen bonds was monitored throughout the 100 ns simulation, with the maximum hydrogen bond distances ranging from 0.25 to 0.35 nm. The hydrogen bond distribution graph (fig.6 F) indicated that hydrogen bond formation initiated at a distance of 0.25 nm between the hydrogen bond donor and acceptor, with the maximum distribution observed at a distance of 0.30 nm. These findings highlight the stability and optimal geometry of hydrogen bond interactions (fig.6 E) in the ligand-receptor complex. The average values of different parameters of molecular dynamics simulation are given in table 5. Table 5: The average values of different parameters of molecular dynamics simulation Sr. no. Control (DNA gyrase) Ciprofloxacin Gamma-sitosterol Phytol 1 Backbone RMSD 0.128 ± 0.0313 0.126±0.036 0.189±0.021 0.972±0.030 2 Complex RMSD - 0.620±0.0661 0.273±0.035 0.340±0.030 3 Ligand RMSD - 0.079±0.018 0.082±0.017 0.070±0.015 4 Radius of Gyration 1.586±0.180 1.592±0.177 1.581±0.173 1.584±0.172 5 SASA 133.438±4.394 134.850±3.887 133.236±2.737 135.263±3.025 6 RMSF 0.125±0.101 0.128±0.098 0.119±0.072 0.125±0.092 5. Binding Free Energy Analysis The binding free energy (ΔGbind) of the ligand-protein complexes was calculated using Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) analysis. This provides insights into the binding potential of the ligands. The MMPBSA results confirmed that all tested molecules viz. ciprofloxacin, gamma-sitosterol and phytol are successfully bind to the active site of target protein to form stable complexes. The variation in ΔGbind values was primarily influenced by the van der waals interaction component (ΔEvdw) and the polar solvation free energy component (ΔGpsolv), which played significant roles in lowering the binding free energy. Additional energy components, including electrostatic energy (ΔEEL), polar solvation energy (ΔGpsolv), and nonpolar solvation energy (ΔGnpsolv), also contributed to the overall binding free energy of the enzyme-ligand complexes. The detailed MMPBSA results for all ligands are given in fig. 7 and table 6. Table 6: Free energy depiction of protein ligand-complex (KJ/mol) through MMPBSA analysis S.N Compound ∆E VDWAALS ∆E EL ∆E PB ∆E NPOLAR ∆G GAS ∆G SOLV ∆Total 1 Ciprofloxacin -31.39±3.32 -24.00±2.3 33.21±1.9 -2.99±0.06 -55.40±3.5 30.21±2.09 -25.128±2.61 2 Gamma-sitosterol -37.12±3.16 -13.74±2.461 30.21±2.67 -3.73±0.071 -50.86±2.88 26.48±2.64 -24.38±1.11 3 Phytol -29.33±1.84 -26.875±1.60 30.912±4.15 -3.347±0.12 -56.20±2.052 27.56±1.66 -28.64±3.05 6. Principal Component Analysis (PCA) Principal component analysis was utilized to investigate the conformational dynamics of the protein upon binding with ciprofloxacin, gamma-sitosterol, and phytol, highlighting the dominant collective motions during molecular dynamics (MD) simulations. The PCA scatter plots in figures 8 A, 8 B, and 8 C represent the distribution of conformations along the principal components PC1, PC2, and PC3 for each complex. The color gradient from red to blue reflects decreasing rigidity and increasing atomic mobility, with red indicating the least fluctuation, white intermediate, and blue the most dynamic regions. For the ciprofloxacin-bound complex, PC1 accounted for 18.01% of the total motion, followed by PC2 and PC3, each contributing 8.39%. In the gamma-sitosterol-bound system, PC1 exhibited higher motion at 23.91%, with PC2 and PC3 contributing 8.62% and 6.8%, respectively. The phytol-bound protein showed the most dominant motion in PC1 at 47.37%, while PC2 and PC3 contributed 9% and 5.38%, respectively. The eigenvalue graphs for all complexes demonstrated a steep decline in variance after the first few eigenvectors. This confirms that the majority of the motion was captured by the top five principal components. This indicates that ciprofloxacin and gamma-sitosterol induce moderate dynamic fluctuations, whereas phytol binding results in pronounced conformational changes along PC1, indicating more significant structural rearrangements. In contrast, the minimal variability in PC3 across all systems reflects a relatively stable and compact protein-ligand complex in that principal component space. Discussion The growing concern of antimicrobial resistance has renewed interest in natural bioresources as alternative or complementary therapies. Within this context, species of the Allium genus have consistently demonstrated significant bioactive potential, particularly due to their rich reservoir of secondary metabolites. Our findings align with numerous prior reports, which highlight the strong antibacterial and antioxidant efficacy of Allium ampeloprasum extracts. Specifically, the methanol extract showed notable zones of inhibition against both gram-positive and gram-negative bacteria, including Bacillus subtilis , Escherichia coli , and Pseudomonas aeruginosa . These outcomes validate the findings of Dziri et al. (2012) and Bareemizadeh et al. (2014), who reported similar efficacy of Allium extracts. This implies that differences in bacterial susceptibility may result from variations in extraction solvents, phytochemical composition, or bacterial strain types. Interestingly, the inconsistency in antibacterial response across studies, such as the lack of effect on P. aeruginosa and B. subtilis reported by Añides et al. (2021) highlights the complex nature of plant-based bioactivity. Nevertheless, our findings support that A. ampeloprasum extract possesses clear antibacterial effects, particularly against B. subtilis (10 ± 0.34 mm), and also retains moderate activity against E. coli and P. aeruginosa . This supports the hypothesis that phenolic and flavonoid compounds are instrumental in disrupting microbial integrity and function. Beyond antimicrobial properties, A. ampeloprasum displayed exceptional antioxidant potential. The extract's low IC₅₀ value (0.193 µg/mL) and high DPPH radical scavenging efficiency suggest strong electron-donating capacity. These effects are consistent with findings by Caputo et al. (2022) who reported up to 87.3% DPPH inhibition in methanolic extracts. The total phenolic (TPC: 11.45 ± 0.51 mg GAE/g) and flavonoid content (TFC: 21.71 ± 0.51 mg QE/g) further confirm that antioxidant and antimicrobial activities are largely driven by these secondary metabolites, which function by scavenging reactive oxygen species (ROS) and potentially disrupting bacterial membranes and metabolic pathways. Complementing our experimental results, in silico docking and molecular dynamics simulations offered deeper insight into the mechanism of action at the molecular level. Gamma-sitosterol, a major phytosterol present in Allium species, displayed strong affinity for DNA gyrase, the same enzymatic target as ciprofloxacin. With a binding energy of –7.1 kcal/mol and a hydrogen bond formed at ASP 73, gamma-sitosterol mimicked ciprofloxacin’s interaction profile. Moreover, MD simulation parameters—including RMSD, RMSF, SASA, and radius of gyration—validated the structural stability of the gamma-sitosterol–enzyme complex, indicating its potential to inhibit bacterial DNA replication. However, a crucial discrepancy lies in the pharmacokinetic profile of these compounds. Ciprofloxacin boasts high systemic bioavailability, rapid absorption, and renal excretion, making it a potent and predictable therapeutic agent. Gamma-sitosterol, in contrast is hindered by poor aqueous solubility and limited intestinal absorption though its lipophilic nature enables effective interactions at membrane-rich sites. While its clinical application may currently be limited, gamma-sitosterol’s binding behavior presents an exciting opportunity for chemical optimization and drug development aimed at enhancing solubility and systemic availability. Altogether, this integrated approach combining traditional microbiological assays, phytochemical profiling, and computational modelling demonstrates the therapeutic promise of A. ampeloprasum as a natural reservoir of potent antimicrobial and antioxidant agents. The strong correlation between in vitro activity and in silico predictions not only validates the biological relevance of gamma-sitosterol but also paves the way for novel phytochemical-based drug discovery targeting bacterial DNA replication pathways. Given the growing resistance to existing antibiotics, such compounds offer a valuable starting point for the development of next-generation therapeutics derived from plant-based sources. Conclusion This study establishes Allium ampeloprasum leaf extract as a potent natural source of antioxidant and antibacterial agents. Phytochemical analysis revealed notable levels of phenolics (TPC: 11.45 ± 0.51 mg GAE/g) and high flavonoids (TFC: 21.71 ± 0.51 mg QE/g), supporting its strong antioxidant activity, evidenced by a concentration-dependent DPPH scavenging effect (50.74%–93.70%) and a low IC₅₀ value of 9.22 µg/mL (R² = 0.9829). Antibacterial evaluation showed selective activity, with Bacillus subtilis being most sensitive (10 ± 0.34 mm), followed by E. coli and P. aeruginosa , while S. aureus showed minimal response. Molecular docking and MD simulation confirmed stable interactions of key compounds like gamma-sitosterol and phytol with bacterial targets, particularly DNA gyrase, with binding affinities comparable to ciprofloxacin. These findings indicate promising therapeutic potential and justify further in vitro and in vivo investigations of unreported constituents such as 2-Pentanol acetate and Phytyl stearate. Despite its medicinal value, A. ampeloprasum remains underutilized in India. It is currently cultivated in parts of Uttarakhand, Manipur, and Kashmir. Given its adaptability and bioactive richness, it should be promoted for cultivation in new regions to enhance dietary value, develop functional foods, and support phytopharmaceutical innovation. This approach may also help identify superior genotypes for medicinal plant-based agriculture and rural income generation. Declarations 9. Acknowledgement The authors gratefully acknowledge the Department of Botany and Department of Microbiology, Chaudhary Charan Singh University, Meerut, for providing essential research facilities. Special thanks to Dr. K.M. Rai, ICAR-NBPGR Regional Station, Bhowali (Nainital, Uttarakhand), for supplying Allium saplings. 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Meerut","correspondingAuthor":false,"prefix":"","firstName":"Anjali","middleName":"","lastName":"Malik","suffix":""},{"id":485506575,"identity":"1e4c4240-de7f-4cb5-af8a-c6520fc0f5ef","order_by":2,"name":"Vijai Malik","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDklEQVRIie2RPWrDMBiGJQzK8iVeHSjtFQwF4cE4B+kiIXCW9gQNRK4hXXyVrpodBM0S6tUlS0UukNGFDpVDhoZitWOhejR94n149YOQx/MXCRCzC10QwMX+o0vtFi7q3yhAICjjcZX3inQrJwDBaBUB0cfJqcQbZA7mNoMJrFdRBE329KhtyyK9GVQ0EhFXAsi4KJM42Qm15VZ5zu/kgDItEbNKACTERctgJ2htFSy1SxEdV8tekVFNXgRtjFsJA5TbFt0f7GEqSZ3R9oeWXkm42thHXpfXuBKMtraFOe5Cwq14fVf3l1fV3OxRl81oMzdvh0U6qNgfYWcjPybZ99wXRvXZOHOGPR6P51/yCUORXmNsTUiVAAAAAElFTkSuQmCC","orcid":"","institution":"Chaudhary Charan Singh University, Meerut","correspondingAuthor":true,"prefix":"","firstName":"Vijai","middleName":"","lastName":"Malik","suffix":""}],"badges":[],"createdAt":"2025-07-15 05:03:24","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7126283/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7126283/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86833951,"identity":"7fefbe52-dce9-4980-a0c5-f334e168073f","added_by":"auto","created_at":"2025-07-16 06:47:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":224747,"visible":true,"origin":"","legend":"\u003cp\u003eGC-MS Chromatogram of methanolic extract of the leaves of \u003cem\u003eA. ampeloprasum\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7126283/v1/73e02652d80b31d2ecc3ebd7.png"},{"id":86832925,"identity":"9f1afd96-f55d-4d20-9581-e718babad2b8","added_by":"auto","created_at":"2025-07-16 06:31:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":65014,"visible":true,"origin":"","legend":"\u003cp\u003eA) Standard curve TPC, B) Standard curve TFC, C) Standard curve DPPH assay D) Graphical representation of Total Flavonoid Content (TFC), Total Phenolic Content (TPC) and IC\u003csub\u003e50\u003c/sub\u003e value of \u003cem\u003eA. ampeloprasum\u003c/em\u003e leaf extract\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7126283/v1/30a4654f309a917b835825d9.png"},{"id":86833961,"identity":"d23dc773-e6d9-47e9-ba7c-3ede51222732","added_by":"auto","created_at":"2025-07-16 06:47:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1037430,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eZOI obtained with \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eA. ampeloprasum\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e leaf extract against four different bacterial strains\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7126283/v1/d381e8e5ac9b919b416f33f4.png"},{"id":86833732,"identity":"ddccb053-7226-48eb-94f3-da0dc13b780a","added_by":"auto","created_at":"2025-07-16 06:39:34","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":15195,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical representation of ZOI obtained with \u003cem\u003eA. ampeloprasum\u003c/em\u003e extracts and positive control against four bacterial strains\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7126283/v1/c9ec950bec8f2be2e771c593.png"},{"id":86833966,"identity":"447f2d9d-4053-43f8-8ccb-133c21b3dc25","added_by":"auto","created_at":"2025-07-16 06:47:33","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":382587,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e. Docking interaction compounds identified through GC-MS analysis against DNA gyrase\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb\u003c/strong\u003e. Docking interaction compounds identified through GC-MS analysis against DNA gyrase\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7126283/v1/bfc9701f98a26c45df5edc65.png"},{"id":86833697,"identity":"46aa061b-d032-4ee2-997d-5b7a19974880","added_by":"auto","created_at":"2025-07-16 06:39:31","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":273018,"visible":true,"origin":"","legend":"\u003cp\u003ePlot of MD simulation between protein DNA gyrase (control) and ligands are (ciprofloxacin, gamma-sitosterol and phytol). (A) RMSD (B) RMSF (C) Radius of gyration (D) SASA (E) H-bond distribution (F) H bond number.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7126283/v1/96b6193d27c8d316aaae4043.png"},{"id":86832929,"identity":"866e6a0b-4fc8-4bd4-91ac-2b21808b7615","added_by":"auto","created_at":"2025-07-16 06:31:31","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":86390,"visible":true,"origin":"","legend":"\u003cp\u003eDiagrammatic representation of protein–ligand complexes through MM-PBSA analysis\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7126283/v1/318001c1ccc463d64e5a1179.png"},{"id":86833956,"identity":"c7780e9e-9b00-45c8-a1d6-a53a3e3d5ce2","added_by":"auto","created_at":"2025-07-16 06:47:31","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":354331,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ea. Ciprofloxacin\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb. Gamma sitosterol\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec. Phytol\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7126283/v1/d24f95ce61f343dcf6ba4d89.png"},{"id":87467372,"identity":"1deefccf-f339-4a53-911f-5695dde10e03","added_by":"auto","created_at":"2025-07-24 08:08:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3860455,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7126283/v1/6b7f0924-3475-4bc5-8562-bcb10a39e393.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003ePharmacological and Molecular Docking studies of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eAllium ampeloprasum \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eL.\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn recent years, medicinal plants have gained significant attention as natural sources of antibacterial compounds. These natural alternatives not only help combat antibiotic resistance but also minimize the side effects associated with chemical antibiotics (Tavakkoli et al., 2015).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGenus\u003cem\u003e\u0026nbsp;Allium\u003c/em\u003e includes more than 1,089 accepted species (POWO, 2021) among them garlic (\u003cem\u003eAllium sativum\u003c/em\u003e), onion (\u003cem\u003eAllium cepa\u003c/em\u003e), leeks (\u003cem\u003eAllium ampeloprasum\u003c/em\u003e var. \u003cem\u003eporrum\u003c/em\u003e), chives (\u003cem\u003eAllium schoenoprasum\u003c/em\u003e), and shallots (\u003cem\u003eAllium ascalonicum\u003c/em\u003e) are the most utilized and studied\u0026nbsp;edible species\u0026nbsp;(Poojary et al., 2017).\u0026nbsp;The genus \u003cem\u003eAllium\u003c/em\u003e has long been recognized for its ethno pharmacological significance, owing to its diverse medicinal properties and widespread traditional use across different cultures (Teotia et al., 2024). \u003cem\u003eAllium\u003c/em\u003e species offer a wide array of health benefits, including antiviral, antibacterial, antifungal, antidiabetic, anticancer, antiplatelet, antispasmodic, antiseptic, anthelmintic, antithrombotic, antiasthmatic, carminative, antioxidant, anti-inflammatory, antihypertensive, hypoglycemic, hypotensive, lithontriptic, and hypocholesterolemic effects (Najeebullah et al., 2021). Garlic, a widely studied member of the \u003cem\u003eAllium\u003c/em\u003e genus, exhibits potent antimicrobial properties due to presence of bioactive compounds, including allicin, vinyldithiin, ajoene, and diallyl polysulfides (Muhsin et al., 2015). Recent studies have shown an association between reduced risk and incidence of breast cancer with the consumption of certain \u003cem\u003eAllium\u003c/em\u003e species, especially \u003cem\u003eAllium sativum\u003c/em\u003e and \u003cem\u003eAllium\u003c/em\u003e \u003cem\u003eampeloprasum\u003c/em\u003e (Pourzand et al., 2016).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAllium ampeloprasum\u003c/em\u003e L. (Amaryllidaceae) is a monocotyledonous plant which is commonly known as broadleaf wild leek. This is a unique species, single-pod garlic which is highly valued for its medicinal properties (Dey \u0026amp; Khaled, 2015). Native to the Mediterranean region—including Southern Europe, North Africa, and Western Asia, it has been introduced to other parts of the world, such as North and South America and Australia, and is cultivated in various regions of Asia, including India (Guhabakshi et al., 1999). \u003cem\u003eA. ampeloprasum\u003c/em\u003e possesses a range of pharmacological properties, including antitoxic, antioxidative, immunostimulatory, and anti-inflammatory effects\u0026nbsp;due to the presence of many sulphur containing bio-active constituents which include: dimethyl disulphide, methyl propenyl disulphide, propyl propenyl disulphide, dimethyl trisulfide, methyl propyl trisulfide, methyl propenyl trisulfide, S-methyl cysteine sulfoxide, S-propyl cysteine sulfoxide, S-propenyl cysteine sulfoxide and N-(γ-glutamyl)-S-(E-1-propenyl) cysteine (Dey \u0026amp; Khaled, 2015). \u003cem\u003eA. ampeloprasum\u003c/em\u003e is recognized as a valuable source of dietary fiber, zinc, polyunsaturated fatty acids particularly linoleic acid as well as a range of lipophilic and hydrophilic bioactive compounds exhibiting significant antioxidant activity (Devi et al., 2014).\u003c/p\u003e\n\u003cp\u003eGas Chromatography-Mass Spectrometry (GC-MS) is a crucial analytical technique for characterizing the complex chemical composition of plant extracts. This method allows for the identification and quantification of a broad spectrum of bioactive compounds, providing a detailed chemical profile of the plant (Jain et al., 2024).\u003c/p\u003e\n\u003cp\u003eDNA gyrase, a type II topoisomerase, is a key enzyme that has been used as a target in molecular docking studies. This enzyme introduces negative supercoils into DNA using ATP hydrolysis and is essential for bacterial survival, while being absent in higher eukaryotes (Reece \u0026amp; Maxwell, 1991). This make it an attractive target for antibacterial drug development. Fluoroquinolones, such as ciprofloxacin, are well-established gyrase inhibitors and are frequently used as positive controls in various \u003cem\u003ein vitro\u003c/em\u003e studies (Richards et al. 1998).\u003c/p\u003e\n\u003cp\u003eSeveral \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e studies have been conducted to evaluate the antimicrobial potential of \u003cem\u003eAllium\u0026nbsp;\u003c/em\u003espp. such as the methanol extracts of \u003cem\u003eAllium\u003c/em\u003e were tested against a set of Gram-positive (\u003cem\u003eStaphylococcus aureus, Staphylococcus feacalis, Bacillus cereus, Enterococcus feacium and Bacillus subtilis\u003c/em\u003e) and Gram-negative (\u003cem\u003eEscherichia coli, Pseudomonas aeruginosa\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;Enterobacter feacalis\u003c/em\u003e) bacterial strains (Dziri et al., 2012). Bareemizadeh et al. (2014) demonstrated that ethyl acetate extracts of \u003cem\u003eA. ampeloprasum\u003c/em\u003e exhibited strong antimicrobial activity against \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e and \u003cem\u003eShigella flexneri\u003c/em\u003e at a concentration of 250 µg/mL, likely due to its pinene and phenol content. Caputo et al. (2022) reported that extracts from the aerial parts of \u003cem\u003eA. ampeloprasum\u003c/em\u003e significantly inhibited the adhesion of \u003cem\u003eP. aeruginosa\u003c/em\u003e (95.78%) and \u003cem\u003eS. aureus\u003c/em\u003e (85.01%). Conversely, Añides et al. (2021) found that while \u003cem\u003eA. ampeloprasum\u003c/em\u003e extracts did not inhibit \u003cem\u003eP. aeruginosa\u003c/em\u003e and \u003cem\u003eB. subtilis\u003c/em\u003e, they exhibited strong antibacterial effects against \u003cem\u003eE. coli\u003c/em\u003e, \u003cem\u003eK. pneumoniae\u003c/em\u003e, \u003cem\u003eS. typhimurium\u003c/em\u003e, and \u003cem\u003eS. aureus\u003c/em\u003e. The authors did not find antimicrobial activity with in-silico validation of \u003cem\u003eA. ampeloprasum\u003c/em\u003e extract against\u0026nbsp;\u003cem\u003eBacillus subtilis,\u003c/em\u003e \u003cem\u003eEscherichia coli\u003c/em\u003e, \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e and \u003cem\u003eStaphylococcus aureus\u003c/em\u003e.\u0026nbsp;Therefore,\u0026nbsp;the aim of the present study was to investigate the bioactive compounds present in the leaf extract of \u003cem\u003eA. ampeloprasum\u003c/em\u003e and evaluate their antibacterial potential through well diffusion assay and antioxidant activity, molecular docking, molecular dynamics simulations and MMPBSA studies with a focus on identifying potential plant-derived inhibitors of bacterial DNA gyrase.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003e\u003cstrong\u003e1. Collection of Plant material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlant sapling of \u003cem\u003eA. ampeloprasum\u003c/em\u003e were collected from Bhowali station Nanital (Uttrakhand) and grown in Botanical garden of CCSU, Meerut, Uttar Pradesh (India) in the month of October 2023. Leaves of plant were harvested in month of July 2024 for experimental purpose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.1. \u003c/strong\u003e\u003cstrong\u003ePreparation of Plant extract\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSamples were ground and then 2.5 gm of samples were taken and mixed with 25 ml of solvent (Absolute Methanol). Sample mixtures were incubated on a rocker shaker for 24 hours. The extracts were filter with Whatman filter 1. Then extracts were completely dried in the oven at 40°C. Extracts were collected in micro centrifuge tube and stored at 4°C. Further dilution is done by using distilled water. Five concentration of plant extracts were used for antibacterial assay i.e., 50 (µg/well), 125 (µg/well), 250 (µg/well), 500 (µg/well) and 1000 (µg/well).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.2. Percentage yield\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePercentage yield (PY) of the concentration crude extract was estimated using the formula given below: \u003c/p\u003e\n\u003cp\u003eYield % = weight of crude plant extract x 100/ weight of powdered plant material\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.3. GC-MS analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe extracted plant samples were analyzed using Gas Chromatography-Mass Spectrometry (GC-MS) to identify and measure their chemical constituents. A high-resolution instrument with a fused silica capillary column, specifically the SH-Rxi-5Sil MS column (5% biphenyl and 95% dimethyl polysiloxane), measuring 30 meters in length, 0.25 mm in inner diameter, and with a 0.25 μm film thickness was employed. The analysis was conducted at a temperature range of 320-350°C. Helium (He) was used as the mobile phase, flowing at 1.0 ml/min. The gas chromatography process started at 50°C and increased to 300°C at a rate of 5°C/min. A 1 microliter injection volume was used. Samples dissolved in methanol, were analyzed within a mass-to-charge ratio (m/z) range of 50-650. The results were compared using an integrated chemical library search program that identified individual compounds based on their retention times and mass spectra. Peak integration and area normalization quantified the relative abundance of each compound in the sample.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.4. Total Phenolic Content (TPC)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTPC was estimated using Folin-Ciocalteu Colorimetric method of Aiyegroro \u0026amp; Okoh, (2010) with slight modification. 2.5 mL of freshly synthesized Folin-ciocalteu reagent (10%) was poured into test tube containing 1 mL of plant extract. 2 mL Na\u003csub\u003e2\u003c/sub\u003eCO\u003csub\u003e3\u003c/sub\u003e (2%) was then added to the test tube and kept under the dark conditions for 30 minutes. Absorbance was noted at 765 nm using UV-Vis Spectrophotometer (Shimadzu-80228), Japan.\u003c/p\u003e\n\u003cp\u003eGallic acid (1mg/mL) was used as standard and five concentrations (20-100 μg/mL) were used for preparing standard curve. 1mL solvent along with 2.5 mL Folin-Ciocalteu reagent and 2mL Na\u003csub\u003e2\u003c/sub\u003eCO\u003csub\u003e3 \u003c/sub\u003esolutions was used as blank. Experiment were performed in triplicates and TPC was calculated using the calibration curve (y=0.0119x + 0.2346, R\u003csup\u003e2\u003c/sup\u003e =0.998).\u003c/p\u003e\n\u003cp\u003eTPC in plant extracts was calculated by the formula given below and expressed in mg Gallic Acid Equivalent (GAE)/gm\u003c/p\u003e\n\u003cp\u003eT = C x V/M\u003c/p\u003e\n\u003cp\u003eHere, \u003c/p\u003e\n\u003cp\u003eT = Total Phenol Content mg/gm GAE\u003c/p\u003e\n\u003cp\u003eC = Concentration of Gallic Acid obtained from the calibration curve in mg\u003c/p\u003e\n\u003cp\u003eV= Volume of plant extract in mL\u003c/p\u003e\n\u003cp\u003eM = Weight of plant extract in gm \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.5. Total Flavonoid Content (TFC)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTFC was estimated using Aluminium Chloride Colorimetric method used by Aiyegroro \u0026amp; Okoh, (2010) with minor modifications. 0.3mL aluminium chloride (10%) and 0.3mL potassium acetate (1M) were poured in a test tube containing 1 mL of plant extract. 3mL of methanol and 3.5mL of distilled water was taken and then added to the test tube. This was kept under dark conditions for 30 minutes. Absorbance of the solution was noted at 417 nm. \u003c/p\u003e\n\u003cp\u003eQuercetin (1mg/mL) was considered as reference compound and standard curve was prepared using five concentrations (20-100 μg/mL). All the experiment was performed in triplicates and the mean value was used for further calculations. The calibration curve (y=0.0188x+0.1532, R\u003csup\u003e2\u003c/sup\u003e+0.9993) was used to calculate the TFC of the plant extracts.\u003c/p\u003e\n\u003cp\u003eTFC of the plant extract was calculated using the formula given below. TFC was expressed in mg/gm of Quercetin equivalent (mg QE/g).\u003c/p\u003e\n\u003cp\u003eT + C x V/M\u003c/p\u003e\n\u003cp\u003eHere, \u003c/p\u003e\n\u003cp\u003eT = Total Flavonoid Content mg/gm Quercetin Equivalent (QE)\u003c/p\u003e\n\u003cp\u003eC = Concentration of Quercetin obtained from the calibration curve in mg\u003c/p\u003e\n\u003cp\u003eV= Volume of plant extract in mL\u003c/p\u003e\n\u003cp\u003eM = Weight of plant extract in gm \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.6. Antioxidant Activity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEach sample was dissolved in 95% methanol to make a concentration of 1 mg/ml and then diluted to prepare the series concentrations for antioxidant assays. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.6.1. DPPH Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe free radical scavenging activity of the fractions was measured in vitro by 2,2 - diphenyl-1-picrylhydrazyl (DPPH) assay according to the method described as Brand-Williams et. al., (1995). A 0.1 mM DPPH solution was prepared in methanol. Plant samples at five varying concentrations (20-100 μg/mL) were mixed with the DPPH solution in a 1:1 ratio and incubated in the dark for 20–30 minutes. Absorbance was measured at 517 nm using a spectrophotometer. DPPH mixed in methanol solvent was taken as control. Ascorbic acid was used as standard. Lower absorbance indicates higher activity. IC50 values can be determined for comparative analysis. Antioxidant activity was calculated as % inhibition of DPPH using the formula:\u003c/p\u003e\n\u003cp\u003e% Inhibition = (Abc – Abs)/ Abc x 100\u003c/p\u003e\n\u003cp\u003eHere,\u003c/p\u003e\n\u003cp\u003eAbc is Absorbance of Control\u003c/p\u003e\n\u003cp\u003eAbs is Absorbance of Sample (Standard / plant extract)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.6.2. IC\u003csub\u003e50 \u003c/sub\u003e value\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIC\u003csub\u003e50\u003c/sub\u003e is the concentration of the plant extract/standard required to scavenging 50% of the free radicals. This value is inversely related to the antioxidant capacity as lower the IC\u003csub\u003e50 \u003c/sub\u003evalues higher is the antioxidant capability and vice-versa. The value was calculated using the formula \u003cstrong\u003ey = mx+b; \u003c/strong\u003ewhich was obtained by plotting the graph between the concentration and % inhibition recorded in the DPPH assay.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. Antimicrobial studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAntimicrobial efficacy for the plant extracts was assessed using four aforementioned bacterial strains. Well diffusion assay was used to determine the zone of inhibition (ZOI) of the plant extract (Bauer et al., 1966).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1. Bacterial Strains\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBacterial strains used in the present investigation were \u003cem\u003eBacillus subtilis\u003c/em\u003e (MTCC-2057), \u003cem\u003eEscherichia coli\u003c/em\u003e (MTCC-41), \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (MTCC-2453) and \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (MTCC-96) were obtained from Microbial Type Culture Collection and Gene Bank (MTCC), Institute of Microbial Technology Chandigarh.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2. Bacterial culture\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBacterial strains were cultured in nutrient agar procured from Hi-media. About 28 gm of nutrient agar powder was mixed in 1000 mL distilled water followed by autoclaving for 20 minutes at 121\u003csup\u003eo \u003c/sup\u003eC and 15 psi pressure. A loopful of lyophilized bacteria (powdered form) was streaked on the solid and sterilized nutrient agar plates. Streaked bacterial plates were incubated for 24 hours in B.O.D incubater shaker at 37\u003csup\u003eo\u003c/sup\u003e C for 24 hours. For experimental studies, the turbidity of bacterial cultures was checked and calibrated to standard i.e., 0.5 McFarland (1.5x 10\u003csup\u003e8 \u003c/sup\u003eCFU/mL).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3. Well diffusion assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess the antibacterial potential of the plant extracts, well diffusion assay was carried out (Bauer et al., 1996). About 28 gm of nutrient agar was mixed in 1000 mL distilled water and kept in autoclave at 121\u003csup\u003eo\u003c/sup\u003e C for 20 minutes. 25 mL of sterilized nutrient agar media was poured in aseptic petri plates. 100 µL of calibrated bacterial culture (1.5x 10\u003csup\u003e8 \u003c/sup\u003eCFU/mL) was evenly spread over the solidified media. 10 µL of plant extract with five different concentrations 50 (µg/mL), 125 (µg/mL), 250 (µg/mL), 500 (µg/mL) and 1000 (µg/mL) were loaded in wells and name them A, B, C, D \u0026amp; E respectively. Ciprofloxacin (0.1mg/mL) was used as positive control and loaded with it labelled as F. Prepared petri plates were then incubated in B.O.D at 37\u003csup\u003eo\u003c/sup\u003e C for 24 hours. The ZOI obtained was measured using antibacterial scale, Himedia. The experiments were performed in triplicates and the mean value of ZOI was recorded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. Detailed Methodology of Molecular Docking \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1 Library generation and protein retrieval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 3D structure of ligands isolated from methanolic extract of \u003cem\u003eA. ampeloprasum\u003c/em\u003e leaves were downloaded from PubChem database (https://pubchem.ncbi.nlm.nih.gov) in an SDF file format. It is then converted into PDBQT format by using Open Babel GUI (O’Boyle et al., 2011). The 3D protein structure of the target enzyme DNA Gyrase with PDB ID 6fju was downloaded from protein data bank i.e.., RCSB PDB (https://www.rcsb.org/) in PDB (Protein Databank) format. It was converted into PDBQT format by Autodock 4.2. (Morris et al., 2009). The protein subjected to energy minimization and optimization with the help of SPDBV, to make it stable. Now, this protein was used for performing the molecular docking process by using Autodock Vina (Morris et al., 2009).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2. Molecular Docking studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe molecular docking studies of all the identified compounds and proteins were performed with AutoDock Vina (Morris et al., 2009). Receptor active site dimensions were set at -31.684 x 8.021 x -4.598 XYZ coordinates for 6fju with 0.375 grid spacing for each atom type. The box dimension was kept as 40 A\u003csup\u003e0\u003c/sup\u003e x 40 A\u003csup\u003e0\u003c/sup\u003e x 40 A\u003csup\u003e0\u003c/sup\u003e (Aliye et al., 2021). Ten confirmations were obtained for each docking experiment, each with a corresponding binding affinity expressed in kcal/mol. For further studies, the ligand-binding position with the lowest binding energy was selected. In our investigation, the phytochemicals that have strong interactions with target enzymes were further examined.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3. Visualization of Ligand-Protein interaction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe best possible 2D structures between ligand and protein were analyzed using Discovery Studio Visualizer for different interactions such as conventional H Bond, Vander wall interactions, Carbon H Bond, Pi-Alkyl, Pi-Sulphur, Pi-Sigma, Pi-Anion and Alkyl are visualized (Design et al., 2014). \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4. Molecular Dynamics simulation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess the dynamic properties of the ligand-protein complexes, MD simulations were conducted. The Charmm36-feb 2021.ff force field was utilized in all simulations using GROMACS 2020.1-1 version. The ligand topology files were created using the CGenFF server (Vanommeslaeghe et al., 2010). Protein complexes that had been created were solved in a cubic box, and enough ions were added to keep the system neutral. The steepest descent approach was used to minimize the system's energy with a convergence threshold of less than 1000 kJ/mol/nm in order to remove any steric collisions among atoms. Equilibration was carried out in two stages. The solvent and ions were kept unrestrained in the NVT ensemble for 100ns in the first phase, while the restraint weight from the protein and protein-ligand complexes was gradually reduced in the NPT ensemble for 100ns in the second phase. The LINCS algorithm was used to keep all hydrogen bonds constrained. Utilizing Berendsen's temperature and Parrinello-Rahman pressure coupling, the temperature and pressure of the system were kept at 300 K and 1 atm respectively (Berendsen et al.,1984). The conformational dynamics and stability of protein–ligand complexes were analyzed using GROMACS and Python 3.8 by monitoring backbone RMSD, ligand RMSD, complex RMSD, RMSF, radius of gyration (Rg), and solvent-accessible surface area (SASA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5.\u003c/strong\u003e \u003cstrong\u003eMMPBSA free energy calculation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMMPBSA was used to calculate the binding energy and the energy contribution per residue. In MMPBSA, the nonpolar component (ΔGnpsolv) was computed using a linear connection to the solvent accessible surface area (SASA), whereas the polar percentage of solvation energy (ΔGpsolv) was evaluated by solving the Poisson-Boltzmann equation. In this study, different parts of the binding free energy of complexes were estimated using the gmmpbsa module of GROMACS (Kumara et al., 2014). The 100ns of the trajectory were used in the analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6.\u003c/strong\u003e \u003cstrong\u003ePrincipal Component Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrincipal Component Analysis (PCA) was carried out using the Galaxy server (Sloggett et al., 2013) to investigate the dynamic behavior of protein-ligand complexes. Protein conformation plays a critical role in maintaining the structural integrity required for effective binding. The covariance matrix generated during the simulation was utilized to analyze the large-scale motions within the enzyme-ligand systems. PCA is a widely accepted approach for identifying key conformational changes and assessing the flexibility of biomolecular structures. This computational strategy enabled a wide-range evaluation of the structural dynamics and energetic profiles of the protein-ligand interactions that offer valuable insights into the therapeutic potential of \u003cem\u003eA. ampeloprasum\u003c/em\u003e phytochemicals.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e4.1. Percentage yield\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe percentage yield of methanolic leaf extract from \u003cem\u003eA. ampeloprasum\u003c/em\u003e was determined through an extraction process. A total of 2500 gm of powdered leaf material was used, yielding 367 mg of extract with 14.68%, recovery percentage.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.2. GC-MS analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe methanol extracts of \u003cem\u003eA. ampeloprasum,\u003c/em\u003e overall 23 different compounds were identified (table 1) along with their retention time and m/z value. The GC-MS chromatogram which shows peak 1 with an m/z value of 43.00, corresponding to 2- Pentanol, acetate, while peak 2, with an m/z value of 57.00, 2-(Isobutoxymethyl)oxirane. peak 3, 4, 5 and 6 with m/z 73.00, 73.00, 73.00, and 68.05 respectively, reveal the presence of Dodecanoic acid, methyl ester, Dodecanoic acid, methyl ester, Methyl tetradecanoate and Neophytadiene which are fatty acid compounds. Peak 7, 8, 9 with an m/z value 43.05, 81.05 and 81.05 are shown the presence of compound 2-Pentadecanone, 6,10,14-trimethyl- and Neophytadiene. Peak 10 and 11 with an m/z value 74.00, 73.00 indicates the compound is Hexadenoic acid, methyl ester and n-Hexadecanoic acid. Peak 12,13 and 14 with m/z value 67.00, 55.05 and 55.05 are 9,12-Octadecadienoic acid (Z,Z)-, methyl ester, 9-Octadecenoic acid, methyl ester, (E)-and 9-Octadecenoic acid (Z)-, methyl ester respectively. Peak 15 with an m/z value 71.05 is phytol, and peak 16 with an m/z value is 74.00 is Methyl stearate. Peak 17, 18, 19 with m/z value 57.00 is Hexatriacontane, Tetracosane and Tetracontane. Peak 20 with m/z value 97.10 represents octacosanol. Peak 21 with an m/z value 147.10 is beta-Sitosterol acetate, and peak 22 with an m/z value 165.00 is alpha.-Tocopherol-.beta.-D-mannoside. Peak 23, 24 and 25 with an m/z \u0026nbsp;value 57.05, 239.15, 43.05 represents compounds Phytyl stearate, 16-Hentriacontanone and gamma-Sitosterol respectively. The GC-MS chromatogram of different peaks corresponding to their respective compounds are given in fig.1, table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. List of Bioactive Compounds Identified through GC-MS analysis from methanolic leaf extract of \u003cem\u003eA. ampeloprasum\u003c/em\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"987\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS.N\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCompound Name\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFormula\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeak area\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClass\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReported activity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReferences\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e2-Pentanol, acetate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC7H14O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e130.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e2.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eCarboxylic acid ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eNot found\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e2-(Isobutoxymethyl)oxirane\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC7H14O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e130.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e12.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e9.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eGlycidyl ether\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eNot found\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eDodecanoic acid, methyl ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC13H26O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e214.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e13.695\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eFatty acid ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAntimicrobial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eReddy et al., 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eDodecanoic acid, methyl ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC13H26O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e214.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e13.752\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e3.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eFatty acid ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAntimicrobial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eReddy et al., 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eMethyl tetradecanoate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC15H30O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e242.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e16.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e3.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eFatty acid ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAnticancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 105px;\"\u003e\n \u003cp\u003eUkwubile et al., 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eNeophytadiene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC20H38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e278.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e17.261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e6.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eDiterpenes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eanti-inflammatory, anti-microbial, antioxidant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eAkter et al., 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e2-Pentadecanone, 6,10,14-trimethyl-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC18H36O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e268.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e17.335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eFatty acid\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAntimicrobial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eAmos-Tautua et al., 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eNeophytadiene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC20H38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e278.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e17.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e2.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eDiterpenes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eanti-inflammatory, anti-microbial, antioxidant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eAkter et al., 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eNeophytadiene\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC20H38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e278.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e17.705\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e3.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eDiterpenes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eanti-inflammatory, anti-microbial, antioxidant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eAkter et al., 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eHexadecanoic acid, methyl ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC17H34O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e270.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e18.163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e20.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eFatty acid ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAntioxidant, anticancer, antidiabetic, nephroprotective, anti-inflammatory, and antibacterial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eAkter et al., 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003en-Hexadecanoic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC16H32O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e256.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e18.538\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eFatty acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAnti-inflammatory antimicrobial, antioxidant, anticancer Antitumor \u0026amp; Hypocholesterolemic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eAkter et al., 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e9,12-Octadecadienoic acid (Z,Z)-, methyl ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC19H34O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e294.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e19.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e3.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eFatty acid ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAntioxidant, antimicrobial, and anti-inflammatory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eAkter et al., 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e9-Octadecenoic acid, methyl ester, (E)-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC19H36O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e296.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e19.837\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e14.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eFatty acid ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAntimicrobial, Antifungal, Antioxidant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eAkkoyunlu et al., 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e9-Octadecenoic acid (Z)-, methyl ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC19H36O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e296.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e19.905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eFatty acid ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAntimicrobial, Antifungal, Antioxidant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eAkkoyunlu et al., 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003ePhytol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC20H40O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e296.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e19.939\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eDiterpene alcohol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAntioxidant, antidiabetic, anticancer, anti-inflammatory, antitumor, chemoprotective, antimicrobial, antiprotozoal, histamine release inhibitor, and antimicrobial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eAkter et al., 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eMethyl stearate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC19H38O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e298.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e20.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eFatty acid methyl ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAnti-inflammatory, antidiarrheal, cytotoxic, antiproliferative, and antioxidant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eAkter et al., 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eHexatriacontane\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC36H74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e506.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e24.718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eHydrocarbon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAntibacterial, Antiviral, Antioxidant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eAadesariya et al., 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eTetracosane\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC24H50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e338.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e26.116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eHydrocarbon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAntimicrobial, Antifungal, Antioxidant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eAkkoyunlu et al., 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eTetracontane\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC40H82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e563.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e27.425\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eHydrocarbon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAntifungal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003ePavirhra et al., 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eOctacosanol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC28H58O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e410.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e27.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eFatty acid alcohol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eanticancer activity, hypocholesterolemic agent, anticoagulant activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eUmoh et al., 2025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e.beta.-Sitosterol acetate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC31H52O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e456.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e27.514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eTriterpenoid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAntimicrobial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eNweze et al., 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003ealpha.-Tocopherol-.beta.-D-mannoside\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC35H60O7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e592.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e27.665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eVitamin E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAntidiabetic, Antioxidant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eChike-Ekwughe et al., 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003ePhytyl stearate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC38H74O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e562.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e27.769\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eFatty acid ester\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eNot found\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e16-Hentriacontanone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC31H62O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e450.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e28.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e11.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;dialkyl ketone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAntimicrobial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eShanker et al., 2005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003egamma-sitosterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eC29H50O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e414.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e29.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 59px;\"\u003e\n \u003cp\u003e5.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003ePhytosterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 178px;\"\u003e\n \u003cp\u003eAntidiabetic (Increase insulin secretion and inhibit glucogenesis)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003eAkter et al., 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e4.3. Total Phenolic Content\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA standard calibration curve was constructed using gallic acid as the reference phenolic compound (fig. 2A). The absorbance values obtained from the plant extract were then compared against this standard curve to determine the phenolic concentration. The TPC of the \u003cem\u003eA. ampeloprasum\u003c/em\u003e extract was found to be 15.45 \u0026plusmn; 0.51 mg gallic acid equivalents (GAE) per gram of extract (fig. D). These results indicate a moderate presence of phenolic compounds, which are known to contribute to the antioxidant properties of plant-based extracts.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.4. Total Flavonoid Content\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eQuantification of TFC was performed using the aluminum chloride colorimetric method. A standard calibration curve was generated using quercetin as the reference flavonoid compound, as shown in fig. 2 B. The absorbance values of the plant extract were measured and compared to this standard curve to estimate the flavonoid concentration. The TFC of the \u003cem\u003eA. ampeloprasum\u003c/em\u003e extract was determined to be 21.71 \u0026plusmn; 0.51 mg quercetin equivalents (QE) per gram of extract, as illustrated in fig. 2 D. The relatively high flavonoid content suggests the potential of \u003cem\u003eA. ampeloprasum\u003c/em\u003e as a natural source of antioxidant compounds.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.5. DPPH Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe antioxidant potential of the sample was assessed using the DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging assay across a concentration range of 10 to 100 \u0026micro;g/mL. The percentage radical scavenging activity (%RSA) demonstrated a clear concentration-dependent increase, rising from 50.74% at 10 \u0026micro;g/mL to 93.70% at 100 \u0026micro;g/mL, indicating strong antioxidant potential. The regression equation obtained from the plotted data was y = 0.4466x + 49.334 with an R\u0026sup2; value of 0.9829. This linearity confirms the reliability of the experimental results (Figure 3C). To quantify the effectiveness of the sample, the IC₅₀ value (the concentration required to scavenge 50% of DPPH radicals) was calculated using the following interpolation formula:\u003c/p\u003e\n\u003cp\u003eIC50 = C1+(%RSA2\u0026minus;%RSA150\u0026minus;%RSA1) \u0026times; (C2\u0026minus;C1)\u003c/p\u003e\n\u003cp\u003eWhere:\u003c/p\u003e\n\u003cp\u003eC₁ = 10 \u0026micro;g/mL (concentration at %RSA₁ = 50.74)\u003c/p\u003e\n\u003cp\u003eC₂ = 20 \u0026micro;g/mL (concentration at %RSA₂ = 60.19)\u003c/p\u003e\n\u003cp\u003eThis low IC₅₀ value of 9.22 \u0026micro;g/mL indicates that the sample possesses potent free radical scavenging ability, consistent with previously reported results (Kumar et al., 2014).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.6. Antibacterial studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWell diffusion assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe antibacterial efficacy of \u003cem\u003eA. ampeloprasum\u003c/em\u003e leaf extracts was assessed using five different concentrations (1000 \u0026micro;L/mL, 500 \u0026micro;L/mL, 250 \u0026micro;L/mL, 125 \u0026micro;L/mL, and 50 \u0026micro;L/mL) through the well diffusion assay. The study targeted four bacterial strains, including two Gram-positive (\u003cem\u003eBacillus subtilis\u003c/em\u003e and \u003cem\u003eStaphylococcus aureus\u003c/em\u003e) and two Gram-negative bacteria (\u003cem\u003eEscherichia coli\u003c/em\u003e and \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e). The zones of inhibition (ZOI) were obtained for each bacterial strain at the various extract concentrations table 2. The concentration-dependent antibacterial activity and the differential susceptibility of the bacterial strains to the extracts are given in fig, 3. Graphical representation of ZOI obtained with \u003cem\u003eA. ampeloprasum\u003c/em\u003e extracts with positive control (ciprofloxacin) against four bacterial strains are presented in fig, 4.\u003c/p\u003e\n\u003cp\u003eThe highest zone of inhibition (ZOI) was observed against \u003cem\u003eB. subtilis\u003c/em\u003e across all tested concentrations. The recorded ZOI values were as follows: 10 \u0026plusmn; 0.34 mm at 1000 \u0026micro;L/mL, 8 \u0026plusmn; 0.44 mm at 500 \u0026micro;L/mL, 7 \u0026plusmn; 0.37 mm at 250 \u0026micro;L/mL, 7 \u0026plusmn; 0.43 mm at 125 \u0026micro;L/mL, and 7 \u0026plusmn; 0.15 mm at 50 \u0026micro;L/mL. In contrast, \u003cem\u003eS. aureus\u003c/em\u003e exhibited minimal inhibition, with a ZOI of 6 \u0026plusmn; 0.64 mm observed only at the highest concentration of 1000 \u0026micro;L/well. \u003cem\u003eP. aeruginosa\u003c/em\u003e showed consistent ZOI values of 6 \u0026plusmn; 0.33 mm across the concentrations of 1000, 500, and 250 \u0026micro;L/mL. Similarly, \u003cem\u003eE. coli\u003c/em\u003e demonstrated its maximum ZOI of 7 \u0026plusmn; 0.05 mm at 1000 \u0026micro;L/mL, with similar inhibition levels of 6 \u0026plusmn; 0.04 mm at both 500 and 250 \u0026micro;L/mL.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e.\u003cem\u003e\u0026nbsp;\u003c/em\u003eZone of Inhibition (mm) obtained against four different bacterial strains\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"566\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmount (\u0026micro;g/well)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eS. aureus\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP. aeruginosa\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eE. coli\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eB. subtilis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e27.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e28.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e28.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e50\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e5.5 \u0026plusmn;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e125\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e6 \u0026plusmn; 0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e6 \u0026plusmn; 0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e5 \u0026plusmn; 0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e6.2 \u0026plusmn; 0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e250\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e6.33\u0026plusmn; 0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e7 \u0026plusmn; 0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e5 \u0026plusmn; 0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e6.7 \u0026plusmn;0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e500\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e7.33 \u0026plusmn; 0.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e7.33 \u0026plusmn; 0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e5.55 \u0026plusmn; 0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e7. 0 \u0026plusmn; 0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e7.33 \u0026plusmn; 0.322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e8 \u0026plusmn; 0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e7.44 \u0026plusmn; 0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e10 \u0026plusmn; 0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e4.7. \u0026nbsp;In silico Docking Studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe GC\u0026ndash;MS analysis revealed that \u003cem\u003eA. ampeloprasum\u003c/em\u003e leaf methanolic extracts contained 21 different bioactive compounds. However, 3D structure of 9-Octadecenoic acid methyl ester (E)-, 9-Octadecenoic acid (Z)-methyl ester, Methyl sterate, Hexatriacontane, Tetracosane, Tetracontane, Octacosanol, beta-sitosterol are not avaliabe on Pubchem (Kim et al., 2016). All the available compounds with their Compound ID, Canonical smiles and 3D structure represents in table 3. These identified compounds were subjected to molecular docking studies against DNA Gyrase by using Autodock vina (Morris et al., 2009). Out of twenty-one GC-MS identified compounds, only four compounds namely 2-Pentadecanone, 6, 10, 14-trimethyl-, gamma-sitosterol, Neophytadiene and Phytol shows binding interaction with DNA gyrase. The compound gamma-sitosterol formed highest binding energy i.e., -7.1 kcal/mol out of selected compounds with one conventional H bond against DNA gyrase at ASP 73. Binding interactions of all interacted compounds of \u003cem\u003eA. ampeloprasum\u003c/em\u003e with interacting amino acid were analysed using Discovery Studio Vizualizer (Design et al., 2014) (fig. 5a \u0026amp; 5b, table 4). The different bonding interactions of ligand and protein residues are hydrogen, hydrophobic (alkyl), hydrophobic (pi-alkyl), pi-lone pair (table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e.\u0026nbsp;Docking of DNA gyrase with compounds identified through GC-MS analysis\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"548\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCompound name\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of H Bond\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBinding Energy with alpha amylase\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of H bonds involved in bonding\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmino acid involved in H bond\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eCiprofloxin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eConventional H-Bond, Alkyl, Pi-Alkyl, Pi-Anion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e-7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eAsn 46, Thr 165\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e2-Pentadecanone, 6,10,14-trimethyl-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eAlkyl Bond\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e-4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eGamma-sitosterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eConventional H-Bond, Alkyl Bond\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e-7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eAsp 73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eNeophytadiene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eAlkyl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e-5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003ePhytol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eConventional H-Bond, Alkyl Bond\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e-5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eVal 167\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch3\u003e5. Molecular Dynamic Simulation\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003e5.1. Root Mean Square Deviation (RMSD) Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Root Mean Square Deviation (RMSD) is a crucial parameter for quantifying the extent of conformational changes in proteins during molecular dynamics (MD) simulations. In this study, the RMSD of the C\u0026alpha; atoms from their initial structures was calculated to evaluate the stability of the protein-ligand complexes. The time-dependent RMSD of the backbone atoms of DNA gyrase in both free and ligand-bound states was observed to range between 0.2nm to 0.25nm, the plateau is remaining stabilize from 0 to 100 ns throughout the simulation. \u0026nbsp;The range of ciprofloxacin (standard antibacterial drug) and gamma-sitosterol are overlapping during whole simulation. This indicates a high degree of stability with DNA gyrase in its ligand-bound conformations. It has been observed that the RMSD values for all systems remained below 0.3 nm throughout the simulation period (fig. 6A) with minimal deviation of the enzyme from its starting conformation indicates the stability of complex. Furthermore, the binding of phytomolecules did not induce significant conformational changes in the protein backbone. This affirms the structural stability of DNA gyrase protein in the presence of ligands.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.2.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eFlexibility and Dynamics Analysis Using\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eRoot Mean Square Fluctuation (RMSF)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe flexibility and dynamics of the system were assessed through RMSF analysis. The majority of the enzyme residues exhibited RMSF values ranging from 0.2 to 0.5 nm (fig.6 B). This value indicates minimal fluctuations. This observation suggests that the positional stability of the amino acid residues remains largely unaffected by the binding of the phytochemical to the active site of enzyme DNA gyrase. Consequently, it can be concluded that the ligand-protein interaction does not significantly alter the overall dynamics of the protein.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.3.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eRadius of Gyration Analysis\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(Rg)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe radius of gyration (Rg) serves as a measure of protein compactness, with lower Rg values indicating greater stability. Since ligand binding can potentially induce protein unfolding, the variation in Rg was analyzed throughout the simulation for all cases. For the unbound state of DNA gyrase (control), the Rg values were centered around ~1.6 nm. Similarly, Rg values ranging from ~1.58 to 1.62 nm were observed with ligand bound state phytomolecules i.e., ciprofloxacin, gama-sitosterol and phytol (fig.6C). These results indicate that the binding of the phytomolecules does not affect the structural integrity or compactness of DNA gyrase.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.4\u003c/strong\u003e \u003cstrong\u003eSolvent Accessible Surface Area (SASA) Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHydrophobic interactions between non-polar amino acids play an important role in stabilizing globular proteins by shielding these residues within hydrophobic cores from the aqueous environment. The solvent-accessible surface area (SASA) provides a theoretical measure of changes in protein accessibility to solvent, reflecting the contribution of free energy of solvation for each atom in the system, including water, and the polar and non-polar amino acids of the protein. In the case of unbound DNA gyrase (control), SASA profile peaked at approximately ~95-98 nm\u0026sup2;. Upon binding with ligands, the SASA values shifted to a range of ~95\u0026ndash;105nm\u0026sup2; (fig.6 D). Since the observed SASA values show minimal deviation compared to the control, it can be inferred that the binding of these compounds does not disrupt protein folding or alter the structural integrity of protein.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.5.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eHydrogen Bond Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe hydrogen bond interactions between DNA gyrase and the bioactive metabolites were evaluated using the hydrogen bond module of GROMACS. The distribution of hydrogen bonds was monitored throughout the 100 ns simulation, with the maximum hydrogen bond distances ranging from 0.25 to 0.35 nm. The hydrogen bond distribution graph (fig.6 F) indicated that hydrogen bond formation initiated at a distance of 0.25 nm between the hydrogen bond donor and acceptor, with the maximum distribution observed at a distance of 0.30 nm. These findings highlight the stability and optimal geometry of hydrogen bond interactions (fig.6 E) in the ligand-receptor complex. The average values of different parameters of molecular dynamics simulation are given in table 5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eThe average values of different parameters of molecular dynamics simulation\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"688\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSr. no.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl (DNA gyrase)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCiprofloxacin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGamma-sitosterol\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhytol\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBackbone RMSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e0.128 \u0026plusmn; 0.0313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e0.126\u0026plusmn;0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e0.189\u0026plusmn;0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.972\u0026plusmn;0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComplex RMSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e0.620\u0026plusmn;0.0661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e0.273\u0026plusmn;0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.340\u0026plusmn;0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLigand RMSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e0.079\u0026plusmn;0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e0.082\u0026plusmn;0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.070\u0026plusmn;0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRadius of Gyration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e1.586\u0026plusmn;0.180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1.592\u0026plusmn;0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e1.581\u0026plusmn;0.173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1.584\u0026plusmn;0.172\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSASA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e133.438\u0026plusmn;4.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e134.850\u0026plusmn;3.887\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e133.236\u0026plusmn;2.737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e135.263\u0026plusmn;3.025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e0.125\u0026plusmn;0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e0.128\u0026plusmn;0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e0.119\u0026plusmn;0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.125\u0026plusmn;0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e5.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eBinding Free Energy Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe binding free energy (\u0026Delta;Gbind) of the ligand-protein complexes was calculated using Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) analysis. This provides insights into the binding potential of the ligands. The MMPBSA results confirmed that all tested molecules viz. ciprofloxacin, gamma-sitosterol and phytol are successfully bind to the active site of target protein to form stable complexes. The variation in \u0026Delta;Gbind values was primarily influenced by the van der waals interaction component (\u0026Delta;Evdw) and the polar solvation free energy component (\u0026Delta;Gpsolv), which played significant roles in lowering the binding free energy. Additional energy components, including electrostatic energy (\u0026Delta;EEL), polar solvation energy (\u0026Delta;Gpsolv), and nonpolar solvation energy (\u0026Delta;Gnpsolv), also contributed to the overall binding free energy of the enzyme-ligand complexes. The detailed MMPBSA results for all ligands are given in fig. 7 and table 6.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eFree energy depiction of protein ligand-complex (KJ/mol) through MMPBSA analysis\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"751\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003eS.N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eCompound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e∆E\u003csub\u003eVDWAALS\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e∆E\u003csub\u003eEL\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e∆E\u003csub\u003ePB\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e∆E\u003csub\u003eNPOLAR\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e∆G\u003csub\u003eGAS\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e∆G\u003csub\u003eSOLV\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e∆Total\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eCiprofloxacin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e-31.39\u0026plusmn;3.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e-24.00\u0026plusmn;2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e33.21\u0026plusmn;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e-2.99\u0026plusmn;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e-55.40\u0026plusmn;3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e30.21\u0026plusmn;2.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e-25.128\u0026plusmn;2.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eGamma-sitosterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e-37.12\u0026plusmn;3.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e-13.74\u0026plusmn;2.461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e30.21\u0026plusmn;2.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e-3.73\u0026plusmn;0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e-50.86\u0026plusmn;2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e26.48\u0026plusmn;2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e-24.38\u0026plusmn;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 37px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003ePhytol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e-29.33\u0026plusmn;1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e-26.875\u0026plusmn;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e30.912\u0026plusmn;4.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e-3.347\u0026plusmn;0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e-56.20\u0026plusmn;2.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e27.56\u0026plusmn;1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e-28.64\u0026plusmn;3.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e6. Principal Component Analysis (PCA)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrincipal component analysis was utilized to investigate the conformational dynamics of the protein upon binding with ciprofloxacin, gamma-sitosterol, and phytol, highlighting the dominant collective motions during molecular dynamics (MD) simulations. The PCA scatter plots in figures 8 A, 8 B, and 8 C represent the distribution of conformations along the principal components PC1, PC2, and PC3 for each complex. The color gradient from red to blue reflects decreasing rigidity and increasing atomic mobility, with red indicating the least fluctuation, white intermediate, and blue the most dynamic regions. For the ciprofloxacin-bound complex, PC1 accounted for 18.01% of the total motion, followed by PC2 and PC3, each contributing 8.39%. In the gamma-sitosterol-bound system, PC1 exhibited higher motion at 23.91%, with PC2 and PC3 contributing 8.62% and 6.8%, respectively. The phytol-bound protein showed the most dominant motion in PC1 at 47.37%, while PC2 and PC3 contributed 9% and 5.38%, respectively. The eigenvalue graphs for all complexes demonstrated a steep decline in variance after the first few eigenvectors. This confirms that the majority of the motion was captured by the top five principal components. This indicates that ciprofloxacin and gamma-sitosterol induce moderate dynamic fluctuations, whereas phytol binding results in pronounced conformational changes along PC1, indicating more significant structural rearrangements. In contrast, the minimal variability in PC3 across all systems reflects a relatively stable and compact protein-ligand complex in that principal component space.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe growing concern of antimicrobial resistance has renewed interest in natural bioresources as alternative or complementary therapies. Within this context, species of the \u003cem\u003eAllium\u003c/em\u003e genus have consistently demonstrated significant bioactive potential, particularly due to their rich reservoir of secondary metabolites. Our findings align with numerous prior reports, which highlight the strong antibacterial and antioxidant efficacy of \u003cem\u003eAllium ampeloprasum\u003c/em\u003e extracts. Specifically, the methanol extract showed notable zones of inhibition against both gram-positive and gram-negative bacteria, including \u003cem\u003eBacillus subtilis\u003c/em\u003e, \u003cem\u003eEscherichia coli\u003c/em\u003e, and \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e. These outcomes validate the findings of Dziri et al. (2012) and Bareemizadeh et al. (2014), who reported similar efficacy of \u003cem\u003eAllium\u003c/em\u003e extracts. This implies that differences in bacterial susceptibility may result from variations in extraction solvents, phytochemical composition, or bacterial strain types.\u003c/p\u003e\n\u003cp\u003eInterestingly, the inconsistency in antibacterial response across studies, such as the lack of effect on \u003cem\u003eP. aeruginosa\u003c/em\u003e and \u003cem\u003eB. subtilis\u003c/em\u003e reported by A\u0026ntilde;ides et al. (2021) highlights the complex nature of plant-based bioactivity. Nevertheless, our findings support that \u003cem\u003eA. ampeloprasum\u003c/em\u003e extract possesses clear antibacterial effects, particularly against \u003cem\u003eB. subtilis\u003c/em\u003e (10 \u0026plusmn; 0.34 mm), and also retains moderate activity against \u003cem\u003eE. coli\u003c/em\u003e and \u003cem\u003eP. aeruginosa\u003c/em\u003e. This supports the hypothesis that phenolic and flavonoid compounds are instrumental in disrupting microbial integrity and function.\u003c/p\u003e\n\u003cp\u003eBeyond antimicrobial properties, \u003cem\u003eA. ampeloprasum\u003c/em\u003e displayed exceptional antioxidant potential. The extract\u0026apos;s low IC₅₀ value (0.193 \u0026micro;g/mL) and high DPPH radical scavenging efficiency suggest strong electron-donating capacity. These effects are consistent with findings by Caputo et al. (2022) who reported up to 87.3% DPPH inhibition in methanolic extracts. The total phenolic (TPC: 11.45 \u0026plusmn; 0.51 mg GAE/g) and flavonoid content (TFC: 21.71 \u0026plusmn; 0.51 mg QE/g) further confirm that antioxidant and antimicrobial activities are largely driven by these secondary metabolites, which function by scavenging reactive oxygen species (ROS) and potentially disrupting bacterial membranes and metabolic pathways. Complementing our experimental results, in silico docking and molecular dynamics simulations offered deeper insight into the mechanism of action at the molecular level. Gamma-sitosterol, a major phytosterol present in \u003cem\u003eAllium\u003c/em\u003e species, displayed strong affinity for DNA gyrase, the same enzymatic target as ciprofloxacin. With a binding energy of \u0026ndash;7.1 kcal/mol and a hydrogen bond formed at ASP 73, gamma-sitosterol mimicked ciprofloxacin\u0026rsquo;s interaction profile. Moreover, MD simulation parameters\u0026mdash;including RMSD, RMSF, SASA, and radius of gyration\u0026mdash;validated the structural stability of the gamma-sitosterol\u0026ndash;enzyme complex, indicating its potential to inhibit bacterial DNA replication.\u003c/p\u003e\n\u003cp\u003eHowever, a crucial discrepancy lies in the pharmacokinetic profile of these compounds. Ciprofloxacin boasts high systemic bioavailability, rapid absorption, and renal excretion, making it a potent and predictable therapeutic agent. Gamma-sitosterol, in contrast is hindered by poor aqueous solubility and limited intestinal absorption though its lipophilic nature enables effective interactions at membrane-rich sites. While its clinical application may currently be limited, gamma-sitosterol\u0026rsquo;s binding behavior presents an exciting opportunity for chemical optimization and drug development aimed at enhancing solubility and systemic availability.\u003c/p\u003e\n\u003cp\u003eAltogether, this integrated approach combining traditional microbiological assays, phytochemical profiling, and computational modelling demonstrates the therapeutic promise of \u003cem\u003eA. ampeloprasum\u003c/em\u003e as a natural reservoir of potent antimicrobial and antioxidant agents. The strong correlation between in vitro activity and in silico predictions not only validates the biological relevance of gamma-sitosterol but also paves the way for novel phytochemical-based drug discovery targeting bacterial DNA replication pathways. Given the growing resistance to existing antibiotics, such compounds offer a valuable starting point for the development of next-generation therapeutics derived from plant-based sources.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study establishes \u003cem\u003eAllium ampeloprasum\u003c/em\u003e leaf extract as a potent natural source of antioxidant and antibacterial agents. Phytochemical analysis revealed notable levels of phenolics (TPC: 11.45 ± 0.51 mg GAE/g) and high flavonoids (TFC: 21.71 ± 0.51 mg QE/g), supporting its strong antioxidant activity, evidenced by a concentration-dependent DPPH scavenging effect (50.74%–93.70%) and a low IC₅₀ value of 9.22 µg/mL (R² = 0.9829). Antibacterial evaluation showed selective activity, with \u003cem\u003eBacillus subtilis\u003c/em\u003e being most sensitive (10 ± 0.34 mm), followed by \u003cem\u003eE. coli\u003c/em\u003e and \u003cem\u003eP. aeruginosa\u003c/em\u003e, while \u003cem\u003eS. aureus\u003c/em\u003e showed minimal response. Molecular docking and MD simulation confirmed stable interactions of key compounds like gamma-sitosterol and phytol with bacterial targets, particularly DNA gyrase, with binding affinities comparable to ciprofloxacin. These findings indicate promising therapeutic potential and justify further in vitro and in vivo investigations of unreported constituents such as 2-Pentanol acetate and Phytyl stearate. Despite its medicinal value, \u003cem\u003eA. ampeloprasum\u003c/em\u003e remains underutilized in India. It is currently cultivated in parts of Uttarakhand, Manipur, and Kashmir. Given its adaptability and bioactive richness, it should be promoted for cultivation in new regions to enhance dietary value, develop functional foods, and support phytopharmaceutical innovation. This approach may also help identify superior genotypes for medicinal plant-based agriculture and rural income generation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e9.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors gratefully acknowledge the Department of Botany and Department of Microbiology, Chaudhary Charan Singh University, Meerut, for providing essential research facilities. Special thanks to Dr. K.M. Rai, ICAR-NBPGR Regional Station, Bhowali (Nainital, Uttarakhand), for supplying \u003cem\u003eAllium\u003c/em\u003e saplings. The study was financially supported by the Council of Scientific and Industrial Research (CSIR), New Delhi.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAadesariya, M. K., Ram, V. R., \u0026amp; Dave, P. N. (2018). Phytochemical analysis of leaves extract of \u003cem\u003eAbutilon pannosum\u003c/em\u003e in n-butanol for its bioactive components through gas chromatography-mass spectrometry (GC-MS). \u003cem\u003ePhytochemical Analysis, 8\u003c/em\u003e(9).\u003c/li\u003e\n\u003cli\u003eAiyegroro OA, Okoh AI. Preliminary phytochemical screening and in vitro antioxidant activities of aqueous extract of Helichrysum longifolium DC. BMC compl. And. Alt. Med., (2010), 10:21.\u003c/li\u003e\n\u003cli\u003eAkkoyunlu, A., \u0026amp; Dulger, G. (2022). Chemical composition and in vitro antimicrobial, antioxidant, and antiproliferative studies of the \u003cem\u003eLamium galeobdolon\u003c/em\u003e L. 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CHARMM general force field: A force field for drug‐like molecules compatible with the CHARMM all‐atom additive biological force fields. \u003cem\u003eJournal of computational chemistry\u003c/em\u003e, \u003cem\u003e31\u003c/em\u003e(4), 671-690.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Chaudhary Charan Singh University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Allium ampeloprasum, Antibacterial activity, Antioxidant activity, GC-MS analysis, Molecular Docking, MD Simulation, MM-PBSA, PCA","lastPublishedDoi":"10.21203/rs.3.rs-7126283/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7126283/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e\u003cbr\u003e\nTo investigate the bioactive compounds present in the leaf extract of \u003cem\u003eAllium ampeloprasum\u003c/em\u003e and evaluate its antioxidant and antibacterial potential using experimental and computational methods.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003cbr\u003e\nThe phytochemical composition of the leaf extract was analyzed using Gas Chromatography-Mass Spectrometry (GC-MS). Antioxidant activity was determined using the DPPH radical scavenging assay, while the Antibacterial activity was tested against four bacterial strains (\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e, \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, \u003cem\u003eEscherichia coli\u003c/em\u003e, and \u003cem\u003eBacillus subtilis\u003c/em\u003e) using the well diffusion method. Molecular docking was conducted to assess the binding affinities of identified compounds with bacterial DNA gyrase, followed by Molecular Dynamics (MD) simulations, MM-PBSA (Molecular Mechanics Poisson–Boltzmann Surface Area) and PCA (Principle component analysis) to evaluate complex stability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003cbr\u003e\nThe leaf extract of \u003cem\u003eA. ampeloprasum\u003c/em\u003e showed the strong antioxidant activity, with DPPH radical scavenging reaching up to 87.3% at 500 µg/mL, attributed to its phenolic and flavonoid content. The highest antibacterial activity was against \u003cem\u003eBacillus subtilis\u003c/em\u003e (10 mm inhibition zone at 1000 µL/mL), followed by \u003cem\u003eEscherichia coli\u003c/em\u003e and \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (7 mm each at 1000 µL/mL concentration). GC-MS analysis revealed several bioactive compounds, among which gamma-sitosterol exhibited the strongest binding affinity to DNA gyrase (-7.1 kcal/mol), comparable to ciprofloxacin. MD simulation and MM-PBSA and Principle component analysis confirmed the stability of the gamma-sitosterol–DNA gyrase complex.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003cbr\u003e\n The leaf extract of \u003cem\u003eA. ampeloprasum\u003c/em\u003e possesses strong antibacterial and antioxidant properties due to the presence of valuable natural compounds. In India, this plant is not commonly cultivated and remains underutilized, despite offering numerous health benefits. Currently, \u003cem\u003eA. ampeloprasum\u003c/em\u003e is being grown as a commercial crop in the Uttarakhand hills, Manipur, and Kashmir. Since it is growing well in the study area, it can be recommended to farmers for food value addition and for use in functional food development. This may also be important for selecting superior \u003cem\u003eAllium\u003c/em\u003e genotypes with enhanced bioactive properties. While \u003cem\u003eAllium sativum\u003c/em\u003e L. and \u003cem\u003eAllium cepa\u003c/em\u003e L. are commonly grown species across India, the introduction of \u003cem\u003eA. ampeloprasum\u003c/em\u003e in new regions could provide access to natural medicines and offer farmers new income opportunities through the cultivation of medicinal plants.\u003c/p\u003e","manuscriptTitle":"Pharmacological and Molecular Docking studies of Allium ampeloprasum L.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-16 06:31:26","doi":"10.21203/rs.3.rs-7126283/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dce9b6e9-5ff3-4f87-9adb-107a70a4e871","owner":[],"postedDate":"July 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":51538379,"name":"Computational Biology"},{"id":51538380,"name":"Drug Discovery, Design, \u0026 Development"}],"tags":[],"updatedAt":"2025-07-16T06:31:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-16 06:31:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7126283","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7126283","identity":"rs-7126283","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}