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Abstract

Blumea lanceolaria (Roxb.) is a medicinal shrub traditionally used to treat infections, inflammation and gastric ulcers. This study investigated its antimicrobial and anti-ulcer potential. Antimicrobial phytochemicals were extracted and evaluated using disc diffusion and broth dilution methods against Pseudomonas aeruginosa, Proteus mirabilis, Enterobacter aerogenes and Escherichia coli. Bioactive compounds were characterised by LC-HRMS profiling, and their anti-ulcer potential was further examined through molecular docking studies against the human gastric proton pump. Sulfuric acid extracts showed the strongest antibacterial activity, with inhibition zones ranging from 8.9 to 14.5 mm. Acid neutralising capacity assays indicated that phosphate buffer leaf extracts had significant activity (280 mEq/g) compared to a standard antacid, suggesting potential anti-ulcer effects. LC-HRMS profiling identified 87 peaks, out of which 30 major bioactive compounds were followed by molecular docking against the human gastric proton pump (PDB ID: 3PGL). N₂-Aristololactam-I-guanine and estrone showed high binding affinities (−9.3 and −8.6 kcal/mol) and favourable ADME properties, highlighting their potential as anti-ulcer drug candidates.

Keywords

Antimicrobial phytochemicals Acid Neutralising Capacity Peptic Ulcer Multidrug Resistance

Introduction

A significant worldwide health concern is the sharp increase in multidrug-resistant (MDR) bacterial infections, which calls for the creation of alternative treatment approaches in addition to traditional antibiotics.^1,2 Among developing techniques, antimicrobial phytochemicals (APs) along with antimicrobial peptides (AMPs) have attracted great attention due to their broad-spectrum activity, fast mode of action, and lower likelihood of resistance formation.³ Plants are regarded as a viable source of antimicrobial compounds because they generate structurally varied bioactive phytochemicals that are essential to their defence against microbial diseases.^4–6 Plant-derived APs and AMPs can be divided into many groups according to their chemical structure, functional groups, and biosynthetic classes. These groups frequently exhibit a variety of structural traits and biological activities that are similar to those of other naturally occurring antimicrobial substances.^7–13 Thus, studies on various plant species have resulted in the development of tailored AMPs extraction methods from APs that consider the unique characteristics of plant tissues.¹⁴ AMPs are small molecules with molecular weights ranging from 2 to 10 kDa. They are usually positively charged, amphiphilic, and exhibit a basic pH, which contributes to their antimicrobial activity.^{11,12,15–17} These phytochemicals, along with peptides, can be isolated from the stems, roots, seeds, flowers and leaves of plants.^12,18

Blumea lanceolaria (Roxb.) is a medicinal plant widely used in traditional medicine to treat infections, inflammation and gastric problems. Despite its extensive use, it remains underexplored for bioactive peptides.^19–21 Peptic ulcer disease (PUD) continues to be a major health issue, especially in developing areas, with current treatments often causing side effects, recurrence, and resistance.²² Therefore, this study evaluates the extraction methods of AP-rich fractions from B. lanceolaria to develop a dual antimicrobial and anti-ulcer framework. The study also highlights potential bioactive compounds for therapeutic application and connects the traditional use of plants towards targeted drug discovery for MDR infections and peptic ulcers.

Material and Methods

Collection, Identification and Extract Preparation of Plant Sample

Leaves of B. lanceolaria were gathered from Debargaon village in Kokrajhar district, Assam, India (26°24′16.1964″ N, 90°16′23.1672″ E). The plant was identified and confirmed at the Department of Botany, Bodoland University. Mature, fully expanded, healthy leaves were selected, thoroughly washed with distilled water and oven-dried for 5 days. Once dried, the leaves were ground into a fine powder and kept in airtight containers for extraction.

To prepare the aqueous extract, 10 g of the leaf powder was blended with 100 mL of distilled water and heated in a water bath at 60°C for 3 hours, stirring intermittently.²³ The mixture was filtered through Whatman No. 1 filter paper and then lyophilised.

For the methanolic extract, 10 g of leaf powder was soaked in 100 mL of methanol and kept at room temperature for 3–4 days, with occasional stirring.²⁴ The mixture was filtered through Whatman No. 1 paper, and the filtrate was concentrated by evaporating the solvent. The dried extracts were stored at −20°C until needed.

Extraction of APs

Multiple extraction solvents were used to maximise the recovery of APs from plant leaves by leveraging differences in solubility, polarity, and pH sensitivity. Given that APs from plants exist in various forms, no single solvent can efficiently extract all bioactive fractions. Acidic solvents, including acetic acid (1 M) and sulfuric acid (50 mM), are utilised to break down cellular structures and promote the release of bioactive substances while reducing deterioration. Under weakly buffered conditions, polar APs can be extracted with the use of sodium acetate buffer (50 mM). Water-soluble phytochemicals are extracted while retaining their structural integrity using phosphate buffer (PB) (20 mM, pH 7.2, 0.1 M NaCl). Terpenoids and other lipophilic phytoconstituents that may contribute to antibacterial activity are extracted using dichloromethane (DCM), a non-polar solvent.^16,25–27 To minimise enzymatic degradation and improve extraction efficiency, all extractions were carried out at 4°C with constant stirring. Comprehensive profiling of the plant material’s polar and non-polar APs was made possible by this combined solvent technique.

Syrup Preparation

Simple syrup was prepared by dissolving 66.7 g of sucrose in 1 L of water, heated with occasional stirring until fully dissolved. 50 g of B. lanceolaria leaf powder was boiled with 400 mL of water until the volume reduced to one-fourth. After cooling, the mixture was filtered to obtain the herbal syrup. One part of the decoction was mixed with five parts of simple syrup (1:5).^28–30

Protein Quantification

The protein content of various chemical extracts used was determined using the Lowry assay method. This involved preparing an alkaline copper solution (Reagent C) by mixing 50 mL of 2% sodium carbonate in 0.1 N sodium hydroxide (Reagent A) with 1 mL of 0.5% copper sulfate in 1% potassium sodium tartrate (Reagent B). A diluted Folin’s reagent (Reagent D) was made by combining Folin-Ciocalteau reagent with an equal volume of 0.1 N NaOH. A standard curve was created using bovine serum albumin (BSA) with concentrations from 40 to 200 µg (Figure 1). The samples and standards were treated with 5 mL of Reagent C, incubated for 10 minutes, and then 0.5 mL of Reagent D was added. After 30 minutes of incubation in the dark, the absorbance was measured at 660 nm, and the protein concentration was calculated using the standard curve.^31,32

Figure 1.

Standard Curve for Protein Estimation.

Microbial Strains

Pseudomonas aeruginosa (MTCC 1688), Escherichia coli (MTCC 443), Enterobacter aerogenes (MTCC 2822), and Proteus mirabilis (MTCC 1439) were obtained from Microbial Type Culture Collection (MTCC), Chandigarh, India.

Antimicrobial Activity Tests

Disc Diffusion Method

The antimicrobial activity of the extracts was determined using the disc diffusion method.³³ Microbial cultures were swabbed on nutrient agar plates, and discs of 6 mm diameter were placed on each plate. 10 µL of the plant extracts and syrup was added to the discs, which were incubated at 37°C for 24 hours. The development of the zone was noticed, and its diameter was measured. The experiment was repeated three times to confirm the accuracy of the result. A positive control (standard commercial Ciprofloxacin) and a negative control (sterile distilled water) were taken along with the different extracts. The standard Ciprofloxacin 5 µg antibiotic disc was tested against P. aeruginosa, E. coli, E. aerogenes, and P. mirabilis.

Broth Dilution Method

The antimicrobial activity of B. lanceolaria extracts was verified using the modified broth dilution method.³⁴ Glassware and media were sterilised by autoclaving at 121°C for 15 minutes. Nutrient Agar (2.3 g) and Nutrient Broth (8 g) were prepared and sterilised in 1 L of distilled water. E. coli, P. mirabilis, P. aeruginosa, and E. aerogenes were incubated at 37°C for 24 hours. A loopful of each culture was suspended in sterile normal saline to create a uniform inoculum. Extracts were prepared at concentrations of 100, 50, 25, 12.5, and 6.25 mg/mL, with Ciprofloxacin (1 mg/mL) as the positive control and distilled water as the negative control. Different extract concentrations were added to the Nutrient Broth and inoculated with 0.1 mL of bacterial suspension. After incubation at 37°C for 24 hours, antimicrobial activity was assessed by turbidity, and the lowest concentration with no visible growth was recorded as the Minimum Inhibitory Concentration (MIC).

Acid Neutralising Capacity

The acid neutralising capacity (ANC) per gram of antacid was determined by dividing the moles of HCl neutralised by the grams of extract. The ANC of plant extracts at concentrations of 100 mg/mL and herbal syrup was compared to a standard antacid by mixing each extract and syrup with water, adding 30 mL of 1N HCl, stirring, and titrating the excess HCl with 0.5 N sodium hydroxide, with neutralisation calculated as^35,36

(V_{1} \times N_{1}) - (V_{2} \times N_{2}) / W e i g h t o f t h e s a m p l e (g)

where,

V₁ = Volume of HCl

N₁ = Normality of HCl

V₂ = Volume of NaOH

N₂ = Normality of NaOH

ANC per gram of antacid = moles of HCl neutralised/grams of sample.

LC-HRMS Analysis

The liquid chromatography-high resolution mass spectrometry (LC-HRMS) analysis was performed using a Waters Alliance 2695 HPLC system coupled to a MassLynx 4.1 software-controlled mass spectrometer. Separation was achieved on an ACCUCORE C18 column (150×4.6mm, 2.6µm particle size) at a flow rate of 1.0mL/min, following a 40-minute gradient. The mobile phases consisted of 5mM ammonium acetate in 5% acetonitrile/water (A) and acetonitrile (B), with B increasing from 5% to 80% over 32 minutes, then returning to initial conditions. A 10µL injection volume was used, with the autosampler kept at 20°C. Detection was performed in both positive (ES+) and negative (ES−) electrospray ionisation modes, scanning from 100 to 750m/z in enhanced mode. The desolvation temperature was set to 350°C, with gas flows of 650L/hr (desolvation) and 50L/hr (cone gas). The Waters 2998 diode array detector monitored absorbance between 200–450nm, including channels at 220, 240, 280, 350, and 410nm, sampling at 20 points/sec. Data processing involved spike removal and smoothing.

In Silico Studies

The absorption, distribution, metabolism, and excretion (ADME) and toxicity study of the compounds was carried out using the SwissADME server (https://www.swissadme.ch) to predict the pharmacokinetic profiles of the compounds.³⁷

Target Protein Structure Preparation

The 3D structure of the human gastric proton pump (PDB ID: 3PGL) was obtained from the Protein Data Bank (PDB) website. To prepare the structure for further analysis, the BIOVIA Discovery Studio Visualiser was employed to eliminate water molecules, heteroatoms, and other solvent-related entities from the model. Subsequently, AutoDock Tools (ADT) version 1.5.7 was used to prepare the receptor protein and to remove any bound ligands. Hydrogens were added to the structure, along with Kollman charges for the polar atoms and Gasteiger charges for all atoms. The system also involved detecting flexible torsions, and adjustments were made to the number of torsions as necessary. Both polar and non-polar hydrogens were merged appropriately. Finally, the docking input file, formatted as a PDBQT file, was generated using ADTs. Importantly, the chosen protein was docked without any prior relaxation, treating it as a rigid model structure throughout the docking process.

Ligand Structure Preparation

The ligands for this docking study were 30 bioactive compounds selected from LC-HRMS analysis of B. lanceolaria leaves. Structures were downloaded from the PUBCHEM database for 3D optimisation. Using Open Babel 3.1.1, SDF files containing all hydrogens were converted to PDB format. For ligands not found in PUBCHEM, 3D structures were created with Marvin Chemaxon using canonical SMILES. Gasteiger charges were added, non-polar hydrogens were merged, and aromatic carbons were prepared for docking in ADT, allowing for torsional flexibility and a wide range of conformational options.

Active Site and Grid Generation

A grid box for blind docking of the gastric proton pump was created with dimensions of 60, 62, and 76 along the X, Y, and Z axes. Standard docking reporting uses: Centre: X = 19.6373, Y = 10.904, Z = 4.837.

Molecular Docking

The AutoDock Vina tool was used to predict binding poses between 30 selected phytochemicals and the gastric proton pump. The docking procedure employed a local search global optimiser and the Fletcher Goldfarb-Shanno (BFGS) method for optimisation, serving as a positive control. With a docking exhaustiveness of 8, the software generated nine protein-ligand complexes, which were ranked by binding affinity.

Analysis and Visualisation of Docking Simulation Results

The conformation with the lowest binding affinity was chosen for further study after ranking the docking postures. The BIOVIA Discovery Studio Visualiser was used to display the binding poses, orientation, interacting residues, and bond details.

Drug Likeness and ADME Analysis

The pharmacokinetic profiles of the top binding affinity drugs were predicted using the Swiss ADME predictor. Ligand screening considered physicochemical properties, such as lipophilicity and water solubility, along with pharmacokinetics based on the Lipinski, Veber, Egan, and Muegge rules. Medicinal chemistry was also evaluated for lead likeness compliance.

Result and Discussion

Protein Quantification

The protein content of various B. lanceolaria extracts is shown in Table 1 and Figure 2. The acetic acid extract exhibited the highest protein concentration at 284.846 µg/mL, corresponding to 56.969 mg/g of the sample, closely followed by the methanol extract, which had a concentration of 140.643 µg/mL (56.257 mg/g). The aqueous extract demonstrated moderate protein content with a concentration of 72.557 µg/mL (29.023 mg/g), while the sulfuric acid extract yielded 126.093 µg/mL (25.219 mg/g). Lower protein yields were recorded for sodium acetate (15.252 µg/mL; 6.101 mg/g), DCM (65.107 µg/mL; 6.511 mg/g), and PB extracts (29.252 µg/mL; 11.701 mg/g). Overall, acidic and polar solvents, particularly acetic acid and methanol, proved to be more effective in extracting proteinaceous components from B. lanceolaria compared to the less polar solvents. A similar finding was made by Ben Brahim et al. (2022), where proteins were detected in all leaf and root extracts of Anthyllis sericea and Astragalus armatus, with significant variations observed among the solvents used. Specifically, acetic acid extraction produced a higher protein content compared to sodium acetate.¹⁶

Table 1.

Protein Content of All the Blumea lanceolaria Extracts.

SI No	Sample Name	Conc. of Protein (µg/mL)	Conc. of Protein Per Gram of Sample (mg/g)
1	BL aqueous extract	72.557	29.023
2	BL methanol extract	140.643	56.257
3	BL sulfuric acid extract	126.093	25.219
4	BL sodium acetate extract	15.252	6.101
5	BL DCM extract	65.107	6.511
6	BL PB extract	29.252	11.701
7	BL acetic acid extract	284.846	56.969

Note: BL = Blumea lanceolaria.

Figure 2.

Protein Content of Various Blumea lanceolaria Extracts.

Antimicrobial Activity

The antimicrobial activity of various B. lanceolaria extracts and syrup against P. aeruginosa, E. coli, E. aerogenes and P. mirabilis was assessed using disc diffusion and broth dilution methods. The sulfuric acid extract showed the highest antibacterial efficacy, with zones of inhibition (ZOI) of 9.1 mm (P. aeruginosa), 11.5 mm (E. coli), 8.9 mm (E. aerogenes), and 14.5 mm (P. mirabilis) (Table 2). The syrup exhibited moderate inhibition (9.5 mm for E. coli and 8.5 mm for P. mirabilis) (Table 2 and Figure 3). In the broth dilution assay, the MIC was the lowest effective concentration after 24 hours at 37°C, as shown in Table 3. The aqueous extract and syrup inhibited E. coli and P. mirabilis at 100 mg/mL but were ineffective against P. aeruginosa and E. aerogenes. The methanol extract worked against E. coli, E. aerogenes, and P. mirabilis at 100 mg/mL. The sulfuric acid extract was the most potent, with MIC values of 50 mg/mL against E. coli and P. mirabilis, and 100 mg/mL against P. aeruginosa and E. aerogenes. The DCM extract inhibited P. mirabilis at 50 mg/mL and was effective against the other strains at 100 mg/mL. Overall, the sulfuric acid extract demonstrated the strongest antibacterial activity, having the largest ZOI and the lowest MIC.

Table 2.

Antimicrobial Activity of the Various Extracts and Syrup of Blumea lanceolaria.

SI No	Sample Name	ZOI of Different Microbes (mm)
SI No	Sample Name	Pseudomonas aeruginosa	Escherichia coli	Enterobacter aerogenes	Proteus mirabilis
1	BL aqueous extract	–	5.5 ± 0.5	–	7 ± 0.28
2	BL methanol extract	–	6 ± 0.5	5.9 ± 0.05	9 ± 0.35
3	BL sulfuric acid extract	9.1 ± 0.21	11.5 ± 1.06	8.9 ± 0.06	14.5 ± 2.12
4	BL sodium acetate extract	–		–	–
5	BL DCM extract	7.9 ± 0.15	9.5 ± 0.7	8 ± 0.05	14.5 ± 0.7
6	BL PB extract	–		–	–
7	BL acetic acid extract	7 ± 0.35	6.5 ± 0.71	7 ± 0.15	10.5 ± 2.12
9	Ciprofloxacin 5 µg	15 ± 0.15	16.7 ± 0.42	20.3 ± 0.57	13 ± 0.05
10	BL syrup	–	9.5 ± 0.7	–	8.5± 0.71

Note: The values are the average of three replicates and are expressed as mean ± SD, BL = Blumea lanceolaria.

Figure 3.

The Antimicrobial Activity of the Various Extracts of Blumea lanceolaria Against (A) Pseudomonas aeruginosa, (B) Escherichia coli, (C) Enterobacter aerogenes and (D). Proteus mirabilis.

Table 3.

MIC Determination of Various Extracts.

SI No	Sample Name	MIC
SI No	Sample Name		100 mg/mL	50 mg/mL	25 mg/mL	12.5 mg/mL	6.25 mg/mL
1	BL aqueous extract	Pseudomonas aeruginosa	NA
		Escherichia coli	–	+	+	+	+
		Enterobacter aerogenes	NA
		Proteus mirabilis	–	+	+	+	+
2	BL methanol extract	Pseudomonas aeruginosa	NA
		Escherichia coli	–	+	+	+	+
		Enterobacter aerogenes	–	+	+	+	+
		Proteus mirabilis	–	+	+	+	+
3	BL sulfuric acid extract	Pseudomonas aeruginosa	–	+	+	+	+
		Escherichia coli	–	–	+	+	+
		Enterobacter aerogenes	–	+	+	+	+
		Proteus mirabilis	–	–	+	+	+
4	BL DCM extract	Pseudomonas aeruginosa	–	+	+	+	+
		Escherichia coli	–	+	+	+	+
		Enterobacter aerogenes	–	+	+	+	+
		Proteus mirabilis	–	–	+	+	+
5	BL acetic acid extract	Pseudomonas aeruginosa	–	+	+	+	+
		Escherichia coli	–	+	+	+	+
		Enterobacter aerogenes	–	+	+	+	+
		Proteus mirabilis	–	+	+	+	+
6	BL syrup	Pseudomonas aeruginosa	NA
		Escherichia coli	–	+	+	+	+
		Enterobacter aerogenes	NA
		Proteus mirabilis	–	+	+	+	+

Note: BL = Blumea lanceolaria, + = Turbidity, – = No turbidity.

Other studies done on leaf extracts of A. sericea, obtained using acetic acid and sodium acetate, demonstrated broad-spectrum activity against both gram-positive (Staphylococcus aureus, Bacillus subtilis, B. pumilus) and gram-negative (E. coli, Salmonella enterica) bacteria, with inhibition zones ranging from 9 to 22.5 mm, indicating a strong antibacterial efficacy.¹⁶

Acid Neutralising Capacity

The ANC of B. lanceolaria extracts revealed significant antacid potential, with most extracts showing activity comparable to or higher than the commercial standard (262.0 mEq/g) presented in Table 4. Among the extracts, the PB extract exhibited the highest ANC (280 mEq/g), followed closely by sulfuric acid and sodium acetate extracts (264 mEq/g each), aqueous extract (261.2 mEq/g), and acetic acid extract (256.0 mEq/g), all of which were nearly equivalent or superior to the marketed antacid. The B. lanceolaria syrup (246.0 mEq/g) also showed moderate efficacy. At the same time, the methanol (233.2 mEq/g) and DCM (160.0 mEq/g) extracts were less effective, suggesting that polar phytoconstituents contribute more significantly to the antacid effect than non-polar ones.

Table 4.

ANC of Blumea lanceolaria Extracts.

SI No	Sample Name	Concentration (mg/mL)	Vol. of NaOH Consumed (mL)	ANC/gram of antacid
1	BL aqueous extract	100	7.76 ± 0.12	261.2
2	BL methanol extract	100	13.36 ± 0.06	233.2
3	BL sulfuric acid extract	100	7.2 ± 0.12	264.0
4	BL sodium acetate extract	100	7.2 ± 0.12	264.0
5	BL DCM extract	100	28 ± 0.05	160.0
6	BL PB extract	100	4 ± 0.06	280.0
7	BL acetic acid extract	100	8.8 ± 0.05	256.0
8	Antacid	100	7.6 ± 0.15	262.0
9	BL syrup		10.8 ± 0.06	246.0

Note: *The values are the average of three replicates and are expressed as mean ± SD, BL = Blumea lanceolaria.

Studies tested Anogeissus latifolia Roxb. for its ANC at doses from 100 to 1500 mg. They found that 1500 mg was more effective than 500 mg of aluminium hydroxide.³⁸ Another study showed that the aqueous extract of Ficus thonningii with a pH of 8.32 and an ANC of 7.4 mEq, exceeding the FDA’s minimum of 5 mEq, indicates its potential as a natural antacid.³⁹ Overall, these findings suggest that B. lanceolaria could be a promising natural alternative to antacids.

Liquid Chromatography-high Resolution Mass Spectrometry

LC-HRMS analysis of the BLM (B. lanceolaria methanolic extract) identified a complex chromatographic profile with retention times from 1.5 to 15 minutes and m/z values ranging from 100 to over 1,000. A total of 87 peaks were detected in positive ionisation mode, most of which showed appropriate signal-to-noise ratios (S/N > 10) and a Gaussian distribution. The analysis revealed diverse metabolites, including amino acids, heterocyclic compounds, organosulfur compounds, flavonoids, and drug-like molecules. Tentative identification was performed by comparing mass values with reference databases. 30 high-intensity metabolites were selected as major components based on their area, height, and spectral quality, as summarised in Table 5.

Table 5.

Major Peaks Detected in BLM Fraction by LC-HRMS.

Sl. No	Compound Name	RT (min)	m/z	Height	Area	Class
1	Theanine	14.62583	175.1097	141117.2	1378083	Other/miscellaneous
2	Mepirizole	11.17838	235.1209	133018.5	1089688	Other/miscellaneous
3	O2-Methyl-Thymine	2.440317	100.0298	832947.1	8292414	Other/miscellaneous
4	2-Hydroxyquinoline	8.4136	144.0434	294057.9	2928735	Heterocyclic aromatic compound
5	Diallyl Sulfide	1.6894	136.9417	172478.1	1706944	Organosulfur compound
6	Benzamide	7.833333	122.055	183195.2	1710287	Amine/nitrogen-containing compound
7	N-Methyl-L-Glutamate	1.552867	162.0829	299903.8	2854785	Other/miscellaneous
8	Normianserin	14.62583	251.1503	622719.1	5901358	Other/miscellaneous
9	Desloratadine	24.7974	311.1312	291973.2	4378550	Other/miscellaneous
10	Bicuculline	11.21252	368.116	494023.3	4428895	Other/miscellaneous
11	2-Mercaptobenzimidazole	19.91643	149.0184	2153028	3.29E+07	Benzene derivative
12	NCGC00180357-02_C15H20O2_2(4ah)-Naphthalenone, 5,6,7,8-Tetrahydro-6-Hydroxy-4a,5-Dimethyl-3-(1-Methylethenyl)-, (4ar,5R,6R)-	14.65997	215.1418	398923.8	3866436	Other/miscellaneous
13	(4S,5Z,6S)-4-(2-Methoxy-2-Oxoethyl)-5-[2-[(E)-3-Phenylprop-2-Enoyl]Oxyethylidene]-6-[(2S,3R,4S,5S,6R)-3,4,5-Trihydroxy-6-(Hydroxymethyl)Oxan-2-Yl]Oxy-4H-Pyran-3-Carboxylic Acid	14.62583	233.1837	669455.8	6461163	Organic acid/amino acid derivative
14	4-Hydroxyquinoline	1.552867	146.0562	291348.8	2386729	Heterocyclic aromatic compound
15	Estriol	11.21252	271.1686	116470.9	957382.4	Flavonoid/steroid
16	2-Hydroxybenzonitrile	1.552867	118.0296	517518	4749417	Benzene derivative
17	Tobramycin	11.21252	466.2532	110975.1	1010156	Other/miscellaneous
18	3’,4’-Dimethoxy-7-Hydroxyflavone	24.72913	311.0932	262697.3	3727687	Flavonoid/steroid
19	6-Methylisoquinoline	1.552867	144.0813	138378.6	1134354	Heterocyclic aromatic compound
20	Estrone	11.17838	253.2015	154627.3	1573895	Flavonoid/steroid
21	N₂-Aristololactam-I-Guanine	25.34353	250.0488	126257.4	1264824	Amine/nitrogen-containing compound
22	8-2,6-Dimethylaniline-Guanine	1.723533	234.893	630785.9	7686444	Amine/nitrogen-containing compound
23	Isophorone	14.62583	139.1063	159544.3	1586814	Other/miscellaneous
24	Levamisole Hydrochloride (Ergamisol)	20.01882	205.0765	158211.3	2399696	Other/miscellaneous
25	Cyclohexylamine; LC-Tdda; CE40	2.406183	100.1057	291017	2384012	Amine/nitrogen-containing compound
26	Valine	1.518733	118.1056	286320.9	3141054	Other/miscellaneous
27	4-Guanidinobutyric Acid	1.518733	146.0941	306187.8	3256943	Organic acid/amino acid derivative
28	Homovanillic Acid	1.587	180.9966	164553.8	1581221	Organic acid/amino acid derivative
29	N-Alpha-Acetyl-L-Asparagine	14.5917	175.0718	109966.1	900842.8	Other/miscellaneous
30	Tryptophanamide	1.6894	159.0066	202150.3	2528295	Amine/nitrogen-containing compound

Molecular Docking

The inhibitory potential of certain phytocompounds against the target protein 3PGL, which is linked to the pathophysiology of peptic ulcers, was assessed using molecular docking analysis. With docking scores of −9.3 kcal/mol and −8.6 kcal/mol, respectively, N₂-Aristololactam-I-guanine (N2-Aristololactam-I-guanine | C22H14N6O5 | CID 169449418 - PubChem) and Estrone (Estrone | C18H22O2 | CID 5870 - PubChem) showed the greatest binding affinities among the 30 ligands evaluated using AutoDock Vina (Table 6). Strong binding potential of both compounds is shown by docking scores below −7.0 kcal/mol, which are often regarded as suggestive of positive ligand-protein interactions. Using Chimera 1.17.1 and BIOVIA Discovery Studio visualizer software, the interaction between the complex of the 3PGL and both compounds was examined (Figure 4). Numerous stabilising interactions, including conventional hydrogen bonds, π-anion, π-donor hydrogen bonds, π-π T-shaped interactions, and metal-acceptor coordination involving mg²⁺, were produced by N₂-Aristololactam-I-guanine. In docking studies of ulcer-related proteins, important interaction residues, including ASP, GLU, HIS, TYR, and ASN, are commonly identified. These residues are linked to improved binding stability and an anticipated inhibitory effect.^39,40 The current findings are relevant since quinazolinone derivatives and other small-molecule inhibitors that target enzymes linked to stomach ulcers have been shown to have similar binding energies (≤ −9.0 kcal/mol).⁴⁰ Additionally, estrone showed stable binding through hydrophobic interactions, such as π-alkyl contacts with aromatic residues and π-π stacking, as well as hydrogen bonding. Similar binding energies (−7.0 to −9.0 kcal/mol) have been reported in previous docking investigations on steroidal and plant-derived drugs that target Helicobacter pylori and ulcer-related proteins, suggesting physiologically significant interactions.^41,42 Overall, the docking data point to estrone and N₂-Aristololactam-I-guanine as possible 3PGL inhibitors.

Table 6.

Docking Scores of 30 Ligands and Their Interactions with the 3PGL Protein.

Sl. No	Compound Name	Binding Affinity (kcal/mol)	Molecular Weight (g/mol)
1	N₂-Aristololactam-I-guanine	–9.3	442.4
2	Estrone	–8.6	270.4
3	Estriol	–8.3	288.4
4	(4S,5Z,6S)-4-(2-methoxy-2-oxoethyl)-5-[2-[(E)-3-phenylprop-2-enoyl]oxyethylidene]-6-[(2S,3R,4S,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]oxy-4H-pyran-3-carboxylic acid	–8.1	550.5
5	3’,4’-Dimethoxy-7-hydroxyflavone	–7.9	298.29
6	Tobramycin	–7.5	467.52
7	8-2,6-Dimethylaniline-guanine	–7.5	270.29
8	Normianserin	–7.4	254.36
9	Bicuculline	–7.1	367.36
10	NCGC00180357-02_C15H20O2_2(4aH)-Naphthalenone, 5,6,7,8-tetrahydro-6-hydroxy-4a,5-dimethyl-3-(1-methylethenyl)-, (4aR,5R,6R)-	–7.0	232.32
11	Homovanillic acid	–6.8	182.17
12	Tryptophanamide	–6.8	203.24
13	Desloratadine	–6.6	310.83
14	N-Alpha-Acetyl-L-Asparagine	–6.4	174.15
15	2-Hydroxyquinoline	–6.3	145.16
16	N-Methyl-L-Glutamate	–6.1	161.16
17	4-Hydroxyquinoline	–6.1	145.16
18	6-methylisoquinoline	–6.1	143.19
19	Mepirizole	–6.0	234.25
20	Levamisole Hydrochloride (Ergamisol)	–6.0	240.75
21	2-Mercaptobenzimidazole	–5.4	150.20
22	Benzamide	–5.3	121.14
23	4-Guanidinobutyric acid	–5.7	145.16
24	Theanine	–5.7	174.20
25	2-Hydroxybenzonitrile	–5.7	119.12
26	Isophorone	–5.7	138.21
27	Valine	–5.0	117.15
28	O2-Methyl-thymine	–4.9	256.24
29	Cyclohexylamine	–4.3	99.17
30	Diallyl Sulfide	–3.4	114.21

Figure 4.

Molecular Docking Analysis (A) Complex 3PGL and N2-Aristololactam-I-guanine, (B) 2D Depiction of the Molecular Docking Interaction Between 3PGL and N₂-Aristololactam-I-guanine, (C) Complex 3PGL and Estrone and (D) 2D Depiction of the Molecular Docking Interaction Between 3PGL and Estrone.

Swiss ADME Analysis

Compounds with the highest scores were selected for ADME analysis and presented in Table 6. The Swiss ADME tool was utilised to evaluate the pharmacokinetic properties of these compounds. Out of 30 ligands, 10 had favourable docking scores. Both compounds with high docking scores satisfy drug likeness criteria (Table 7). N₂-Aristololactam-I-guanine showed high intestinal absorption, good bioavailability, and non-permeability of the blood-brain barrier. With a bioavailability score of 0.55. Additional research is needed to confirm its toxicology, pharmacology, and experimental bioavailability.

Table 7.

Swiss ADME Screening of Selected Bioactive Compounds for Drug Likeness.

ADME Parameter
	N₂-Aristololactam-I-guanine	Estrone
Physicochemical Properties
Formula	C22H14N6O5	C18H22O2
Molecular weight	442.38 g/mol	270.37 g/mol
Number heavy atoms	33	20
Num. arom. heavy atoms	25	6
Fraction Csp3	0.09	0.61
Num. rotatable bonds	2	0
Num. H-bond acceptors	8	2
Num. H-bond donors	4	1
Molar refractivity	118.81	80.06
TPSA	150.50 Å²	37.30 Å²
Lipophilicity
Log P_o/w (iLOGP)	1.42	2.40
Log P_o/w (XLOGP3)	3.04	3.13
Log P_o/w (WLOGP)	2.55	3.82
Log P_o/w (MLOGP)	1.27	3.44
Log P_o/w (SILICOS-IT)	4.37	3.84
Consensus Log P_o/w	2.53	3.33
Water solubility
Log S (ESOL)	–4.93	–3.71
Solubility	5.24e-03 mg/mL; 1.18e-05 mol/L	5.27e-02 mg/mL; 1.95e-04 mol/L
Class	Moderately soluble	Soluble
Log S (Ali)	–5.87	–3.58
Solubility	6.02e-04 mg/mL; 1.36e-06 mol/L	7.07e-02 mg/mL; 2.62e-04 mol/L
Class	Moderately soluble	Soluble
Pharmacokinetics
GI absorption	Low	High
BBB permeant	No	Yes
P-gp substrate	No	Yes
CYP1A2 inhibitor	Yes	No
CYP2C19 inhibitor	Yes	No
CYP2C9 inhibitor	No	No
CYP2D6 inhibitor	No	Yes
CYP3A4 inhibitor	No	No
Log K_p (skin permeation)	–6.84 cm/s	–5.73 cm/s
Druglikeness
Lipinski	Yes, 1 violation: NorO>10	Yes, 0 violations
Ghose	Yes	Yes
Veber	No, 1 violation: TPSA>140	Yes
Egan	No, 1 violation: TPSA>131.6	Yes
Muegge	No, 1 violation: TPSA>150	Yes
Bioavailability score	0.55	0.55
Medicinal chemistry
PAINS	0 alert	0 alert
Brenk	1 alert: polycyclic_aromatic_hydrocarbon_3	0 alert
Leadlikeness	No, 1 violation: MW>350	Yes
Synthetic accessibility	3.50	3.27

Conclusion

The sulfuric acid extract of B. lanceolaria leaf demonstrated strong antibacterial activity against gram-negative bacteria, representing the first study of AMPs in this plant and indicating its anti-ulcerogenic potential. In silico studies revealed N₂-Aristololactam-I-guanine and estrone as potential candidates for the treatment of peptic ulcer. These findings enhance understanding of natural interventions for MDR and peptic ulcers, supporting future research on effective treatments.

Footnotes

Acknowledgements

The authors kindly acknowledge the financial support as a studentship to Mr Shubam Sinha from the Department of Biotechnology (DBT), Government of India. Also, we would like to express our gratitude to the Department of Biotechnology, Government of India, Sponsored Bioinformatics Infrastructure Facility, Bodoland University and DST-FIST, Bodoland University, for providing the required resources and technical support and the Central Instrumental Facility, Assam Downtown University, for allowing us to utilise their instrumentation facility.

Author’s Contribution

All authors made substantial contributions to conception and design, acquisition of data or analysis and interpretation of data; took part in drafting the article or revising it critically for important intellectual content; agreed to submit to the current journal; gave final approval of the version to be published; and agree to be accountable for all aspects of the work. All the authors are eligible to be an author as per the International Committee of Medical Journal Editors (ICMJE) requirements/guidelines.

Consent for Participate

Not applicable.

Consent to Publication

Not applicable.

Data Availability

All the data is available with the authors and shall be provided upon request.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Ethics Approvals

This work does not contain any studies involving human and animal subjects.

Funding

The authors disclosed receipt of the following financial support for the research, authorship and/or publication of this article: The first and second authors, Shubam Sinha and Pallavi Rabha, respectively, received financial support in the form of a PG-Studentship stipend from the Department of Biotechnology (DBT), Government of India, during the course of this research work. No specific funding was received for the research, authorship or publication of this article.

Informed Consent

Not applicable.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of the publisher, the editors and the reviewers. This journal remains neutral with regard to jurisdictional claims in published institutional affiliation.

Use of Artificial Intelligence-assisted Technology

The authors declare that they have not used artificial intelligence (AI)-tools for writing and editing of the manuscript, and no images were manipulated using AI.

References

Wisplinghoff

, Bischoff

, Tallent

, . Nosocomial bloodstream infections in US hospitals: Analysis of 24,179 cases from a prospective nationwide surveillance study. Clin Infect Dis, 2004; 39(3): 309–317. DOI: 10.1086/421946.

Zhu

, Tse

, Weller

, . The future of antibiotics begins with discovering new combinations. Ann N Y Acad Sci, 2021; 1496(1): 82–96. DOI: 10.1111/nyas.14649.

Bourlioux

. De quelles alternatives notre arsenal thérapeutique anti-infectieux dispose-t-il face aux bactéries multirésistantes? Ann Pharm Fr, 2013; 71(3): 150–158. DOI: 10.1016/j.pharma.2013.02.005.

Cowan

. Plant products as antimicrobial agents. Clin Microbiol Rev, 1999; 12(4): 564–582. DOI: 10.1128/CMR.12.4.564.

Dhama

, Karthik

, Khandia

, . Medicinal and therapeutic potential of herbs and plant metabolites/extracts countering viral pathogens—Current knowledge and future prospects. Curr Drug Metab, 2018; 19(3): 236–263. DOI: 10.2174/1389200219666180129145252.

Yan

, Yuan

, Jiang

, . Plant antifungal proteins and their applications in agriculture. Appl Microbiol Biotechnol, 2015; 99(12): 4961–4981. DOI: 10.1007/s00253-015-6654-6.

Bulet

, Hetru

, Dimarcq

, . Antimicrobial peptides in insects; structure and function. Dev Comp Immunol, 1999; 23(4–5): 329–344. DOI: 10.1016/S0145-305X(99)00015-4.

Oliveira

Carvalho A

and Gomes

. Plant defensins—Prospects for the biological functions and biotechnological properties. Peptides, 2009; 30(5): 1007–1020. DOI: 10.1016/j.peptides.2009.01.018.

Zasloff

. Antimicrobial peptides of multicellular organisms. Nature, 2002; 415(6870): 389–395. DOI: 10.1038/415389a.

10.

Reddy

KVR

, Yedery

and Aranha

Antimicrobial peptides: Premises and promises. Int J Antimicrob Agents, 2004; 24(6): 536–547. DOI: 10.1016/j.ijantimicag.2004.09.005.

11.

Tam

, Wang

, Wong

, . Antimicrobial peptides from plants. Pharmaceuticals (Basel), 2015; 8(4): 711–757. DOI: 10.3390/ph8040711.

12.

Tang

, Prodhan

, Biswas

, . Antimicrobial peptides from different plant sources: Isolation, characterisation and purification. Phytochemistry, 2018; 154: 94–105. DOI: 10.1016/j.phytochem.2018.07.002.

13.

Thevissen

, Kristensen

, Thomma

BPHJ

, . Therapeutic potential of antifungal plant and insect defensins. Drug Discov Today, 2007; 12(21–22): 966–971. DOI: 10.1016/j.drudis.2007.07.016.

14.

Zou

, Tan

, Shinali

, . Plant antimicrobial peptides: Classification, production, mode of action, applications and challenges. Food Funct, 2023; 14(12): 5492–5515. DOI: 10.1039/D3FO01119D.

15.

Barashkova

and Rogozhin

. Isolation of antimicrobial peptides from different plant sources: Does a general extraction method exist? Plant Methods, 2020; 16(1): 143. DOI: 10.1186/s13007-020-00687-1.

16.

Ben

Brahim R

, Ellouzi

, Fouzai

, . Optimized chemical extraction methods of antimicrobial peptides from roots and leaves of extremophilic plants. Antibiotics (Basel), 2022; 11(10): 1302. DOI: 10.3390/antibiotics11101302.

17.

Pelegrini

and Franco

. Plant γ-thionins: Novel insights on the mechanism of action of a multifunctional class of defense proteins. Int J Biochem Cell Biol, 2005; 37(11): 2239–2253. DOI: 10.1016/j.biocel.2005.06.011.

18.

Huan

, Kong

, Mou

, . Antimicrobial peptides: Classification, design, application and research progress. Front Microbiol, 2020; 11: 582779. DOI: 10.3389/fmicb.2020.582779.

19.

Joshi

. GC–MS analysis of volatile organic constituents of traditionally used medicinal plants from Western Ghats of India. J Mex Chem Soc, 2020; 64(2): 74–82. DOI: 10.29356/jmcs.v64i2.1093.

20.

Wiart

. Medicinal plants of Asia and the Pacific. Boca Raton: CRC Press, 2006. DOI: 10.1201/9781420006803.

21.

Rai

and Lalramnghinglova

Ethnomedicinal plant resources of Mizoram, India. Ethnobot Leafl, 2010; 2010(3): 1–6.

22.

Javed

and Das

. Preparation, standardization and in vitro antimicrobial efficacy of Gairikadya malahara. Int J Ayurveda Res, 2022; 3(2): 136–141. DOI: 10.4103/ijar.ijar_17_22.

23.

Edeoga

, Okwu

and Mbaebie

. Phytochemical constituents of some Nigerian medicinal plants. Afr J Biotechnol, 2005; 4(7): 685–688. DOI: 10.5897/AJB2005.000-3127.

24.

Brahma

and Baruah

Phytochemical constituents and antioxidant activity of Glochidion sphaerogynum bark. Plant Sci Today, 2023; 10(2): 98–105. DOI: 10.14719/pst.2019.

25.

Atindehou

, Lagnika

, Guérold

, . Isolation of antibacterial agents from Chromolaena odorata. Adv Microbiol, 2013; 3(1): 115–121. DOI: 10.4236/aim.2013.31018.

26.

Fujimura

, Minami

, Watanabe

, . Novel antimicrobial peptides from buckwheat seeds. Biosci Biotechnol Biochem, 2003; 67(8): 1636–1642. DOI: 10.1271/bbb.67.1636.

27.

Zhang

and Lewis

. Fabatins: New antimicrobial plant peptides. FEMS Microbiol Lett, 1997; 149(1): 59–64. DOI: 10.1111/j.1574-6968.1997.tb10308.x.

28.

Khory

. Principles and practice of ayurvedic medicine. New Delhi: Biotech Books, 2004.

29.

Indian Pharmacopoeia Commission. Indian Pharmacopoeia. Ghaziabad: IPC, 2007.

30.

Sagar

, Khan

, Ahmed

, . Scientific standard validation and HPTLC fingerprinting of Jawarish-e-Usquf. J Sci Res Chem, 2023; 8(4): 1–13. DOI: 10.32628/IJSRCH.

31.

Lowry

, Rosebrough

, Farr

, . Protein measurement with the Folin phenol reagent. J Biol Chem, 1951; 193(1): 265–275.

32.

Sapan

, Lundblad

and Price

. Colorimetric protein assay techniques. Biotechnol Appl Biochem, 1999; 29(2): 99–108. DOI: 10.1111/j.1470-8744.1999.tb00538.x.

33.

Biemer

. Antimicrobial susceptibility testing by the Kirby–Bauer method. Ann Clin Lab Sci, 1973; 3(2): 135–140.

34.

Noval

, Yuwindry

and Syahrina

Phytochemical screening and antimicrobial activity of bundung plants extract by dilution method. J Surya Med, 2019; 5(1): 143–154. DOI: 10.33084/jsm.v5i1.954.

35.

Kalva

and Sulthana

Exploring fruit remedies for ulcer treatment: An in vitro analysis. Asian J Pharm Res Dev, 2025; 13(2): 21–25. DOI: 10.22270/ajprd.v13i2.1534.

36.

Kumar

, Verma

, Kaur

, . In vitro antiulcer activity of Crocus sativus petal extract. J Med Bot, 2020; 4: 6–8. DOI: 10.25081/jmb.2020.v4.6225.

37.

Daina

, Michielin

and Zoete

. SwissADME: A free web tool to evaluate pharmacokinetics and drug-likeness. Sci Rep, 2017; 7(1): 42717. DOI: 10.1038/srep42717.

38.

Singhal

, Giri

and Kumar

Investigation of in vitro antioxidant and anti-ulcer activity of Anogeissus latifolia Roxb (dhava). NeuroQuantology, 2022; 20(11): 5680–5686. DOI: 10.14704/NQ.2022.20.11.NQ66568.

39.

Uku

, Fokunang

, Grace

, . Phytochemical screening and antiulcer activity of Ficus thonningii (Moraceae) aqueous fruits extract in Wistar rats. Asian J Res Med Pharm Sci, 2020; 9(1): 41–59. DOI: 10.9734/AJRIMPS/2020/v9i130145.

40.

Baba

, Uzairu

, Shallangwa

, . Molecular docking and quantitative structure-activity relationship study of anti-ulcer activity of quinazolinone derivatives. J King Saud Univ Sci, 2020; 32(1): 657–666. DOI: 10.1016/j.jksus.2018.10.003.

41.

Dawood

, Fatima

, Mumtaz

, . Molecular docking studies of sesquiterpenoids against Helicobacter pylori peptide deformylase. Br J Pharm Res, 2016; 10: 1–7. DOI: 10.9734/BJPR/2016/23792.

42.

Agarwal

, Bajpai

and Gupta

. A quantitative structure–activity relationship and molecular modeling study on heteroaryl- and heterocyclyl-substituted imidazo[1,2-a]pyridine derivatives acting as acid pump antagonists. Biochem Res Int, 2013; 2013: 141469. DOI: 10.1155/2013/141469.

Chemical Extraction of Antimicrobial Phytochemicals from Blumea lanceolaria Leaves and Their Anti-ulcer Potential: In Vitro and In Silico Analysis

Abstract

Keywords

Introduction

Material and Methods

Collection, Identification and Extract Preparation of Plant Sample

Extraction of APs

Syrup Preparation

Protein Quantification

Standard Curve for Protein Estimation.

Microbial Strains

Antimicrobial Activity Tests

Disc Diffusion Method

Broth Dilution Method

Acid Neutralising Capacity

LC-HRMS Analysis

In Silico Studies

Target Protein Structure Preparation

Ligand Structure Preparation

Active Site and Grid Generation

Molecular Docking

Analysis and Visualisation of Docking Simulation Results

Drug Likeness and ADME Analysis

Result and Discussion

Protein Quantification

Protein Content of Various Blumea lanceolaria Extracts.

Antimicrobial Activity

The Antimicrobial Activity of the Various Extracts of Blumea lanceolaria Against (A) Pseudomonas aeruginosa, (B) Escherichia coli, (C) Enterobacter aerogenes and (D). Proteus mirabilis.

Acid Neutralising Capacity

Liquid Chromatography-high Resolution Mass Spectrometry

Molecular Docking

Molecular Docking Analysis (A) Complex 3PGL and N2-Aristololactam-I-guanine, (B) 2D Depiction of the Molecular Docking Interaction Between 3PGL and N2-Aristololactam-I-guanine, (C) Complex 3PGL and Estrone and (D) 2D Depiction of the Molecular Docking Interaction Between 3PGL and Estrone.

Swiss ADME Analysis

Conclusion

Footnotes

Acknowledgements

Author’s Contribution

Consent for Participate

Consent to Publication

Data Availability

Declaration of Conflicting Interests

Ethics Approvals

Funding

Informed Consent

Publisher’s Note

Use of Artificial Intelligence-assisted Technology

References

Molecular Docking Analysis (A) Complex 3PGL and N2-Aristololactam-I-guanine, (B) 2D Depiction of the Molecular Docking Interaction Between 3PGL and N₂-Aristololactam-I-guanine, (C) Complex 3PGL and Estrone and (D) 2D Depiction of the Molecular Docking Interaction Between 3PGL and Estrone.