Abstract
Helicobacter pylori (H. pylori) infection is commonly treated using antibiotics and proton pump inhibitors; however, drug resistance and adverse effects continue to reduce treatment effectiveness. In this context, the present study aimed to explore the Ayurvedic formulation Kaidaryadi Kashayam, traditionally indicated for gastrointestinal ailments, including H. pylori infection, as a potential source of phytochemicals with multitarget regulatory activity. Initially, the medicinal plants were authenticated through DNA barcoding. Subsequently, the phytochemicals identified from Gas Chromatography-Mass Spectrometry (GC-MS) analysis, along with those retrieved through literature mining, were subjected to virtual screening against 18 selected H. pylori targets using molecular docking. Out of 671 screened compounds, 25 phytochemicals exhibited interactions with multiple targets, and among these, five compounds, proanthocyanidin, phytomelin, drieline, riboflavin, and (2E,4E)-15-(1,3-benzodioxol-5-yl)-N-(2-methylpropyl) pentadeca-2,4-dienamide, displayed docking scores greater than the respective mean values. Notably, riboflavin demonstrated affinity toward ten targets, and prediction efficacy (PE) analysis revealed its highest total score (1,470) among all compounds. The binding stability of riboflavin with the target protein exhibiting the highest docking score (112) was further validated through a 100 ns molecular dynamics simulation. Collectively, these findings highlight the potential of Kaidaryadi Kashayam-derived phytochemicals in modulating multiple pathways of H. pylori pathogenesis, with riboflavin emerging as a particularly promising lead candidate for further experimental validation.
Introduction
Helicobacter pylori (H. pylori) is a Gram-negative and microaerophilic bacterium that colonizes in more than half of the world’s population, inducing gastro-duodenal diseases and a wide variety of non-gastrointestinal disorders. 1 Achieving complete disease eradication remains one of the most significant challenges in the field of gastroenterology. Drug resistance and the adverse effects of existing therapies represent major limitations in the management of H. pylori infection. Studies from the Indian population have reported resistance rates to first-line therapy drugs ranging from about 32.8% to as high as 77.65%, 2 which is relatively high compared to developed countries. 3 Furthermore, the discomfort and unpleasant experiences associated with antibiotic-related adverse effects often reduce patient compliance, thereby compromising overall therapeutic outcomes. 4 As an alternative, natural product-derived therapeutics have gained preference owing to their favorable pharmacological attributes. Their broad spectrum of therapeutic actions and multitarget regulatory effects offer distinct advantages over conventional synthetic drugs. In recent years, interest in natural products as lead candidates has been renewed, particularly in addressing antimicrobial resistance. Historically, natural compounds and their derivatives have made substantial contributions to drug discovery and development, especially in the treatment of chronic and infectious diseases. 5 Recent trends in drug discovery indicate that research institutions and pharmaceutical industries are increasingly focusing on natural products and their derivatives, owing to their superior biological activities and comparatively fewer side effects than synthetic counterparts.
In Ayurveda, several formulations have been traditionally recognized for their effectiveness in managing gastrointestinal disorders. The Ayurvedic system emphasizes a holistic approach, aiming to restore and maintain the homeostasis of the gut microbiome. Research evidence suggests that many traditionally used medicinal plants serve as rich sources of pharmacologically active compounds. Therefore, medicinal plants and formulations indicated for gastric ailments can be scientifically evaluated against H. pylori. Ayurveda prescribes several formulations aimed at improving gut health, among which Kaidaryadi Kashayam is specifically recommended for managing gastric disorders such as gastritis, gastric ulcers, and related conditions. Kaidaryadi Kashayam is formulated with five medicinal plants: Zingiber officinale, Murraya koenigii, Terminalia chebula, Trichosanthes dioica, and Piper longum. In addition to their traditional applications, these plants have demonstrated a wide range of therapeutic effects, including significant gastroprotective activity, as supported by scientific studies. The botanical characteristics and validated medicinal properties of these plants are summarized in Supplementary Table S1.6–10
Phytochemical research suggests that solvent-specific extracts and individual bioactive constituents of these medicinal plants exhibit significant efficacy in gastrointestinal disorders. 11 Therefore, the therapeutic potential of these formulations, as well as their constituent plants, can be evaluated against H. pylori. Moreover, their phytochemicals may be screened against disease-related targets to elucidate their regulatory mechanisms. However, despite their remarkable therapeutic promise, natural products encounter multiple challenges in drug discovery, including difficulties in standardization, compound isolation, high-throughput screening, structural optimization, and comprehensive safety assessment. These complexities have limited their systematic utilization in drug development. Bioactive compounds identified with promising pharmacological activities require deeper assessments, particularly to evaluate their pharmacokinetic profiles. Since the molecular mechanisms and biological actions of these phytochemicals are often difficult to interpret, integrating multidisciplinary approaches, such as in silico techniques, becomes essential. This paradigm shift has facilitated the broad implementation of computer-aided drug discovery (CADD), thereby accelerating and streamlining various stages of drug development within pharmaceutical research and industry.12,13 Using in silico methodologies, novel drug-like compounds can be identified by evaluating molecular interactions between plant-derived phytochemicals and disease-specific targets. This approach facilitates the discovery of multitarget regulatory candidates in a time- and cost-effective manner, thereby strengthening the development of new therapeutics against H. pylori. In the present study, computational strategies were employed to assess the multitarget regulatory potential of phytochemicals from the medicinal plants of Kaidaryadi Kashayam, an Ayurvedic formulation traditionally known for its protective effects against gastric disorders, including H. pylori-mediated inflammation.
Initially, the plants included in the formulation were authenticated, and the identified phytochemicals were virtually screened against selected therapeutic targets of H. pylori, with their molecular interactions evaluated in detail. Based on the docking scores, an interactome was constructed to illustrate the multitarget interactions between phytochemicals and specific protein targets. Furthermore, the predictive efficacy of these phytochemicals was assessed using their docking scores, and the binding stability of the most promising compound was further examined against its highest-scoring targets through molecular dynamics (MD) simulations.
Materials and Methods
Plant Authentication Using DNA Barcoding
The medicinal plants included in the formulation were collected from different regions of India and authenticated to the species level using DNA barcoding. The rbcL gene segment was amplified and sequenced for accurate species identification. Fresh leaf samples from five selected plants were collected and submitted for DNA sequencing. The universal primers of forward (RBCL-AF (ATGTCACCACAAACAGAGACTAAAGC) and reverse (RBCL-724R (TCGCATGTACCTGCAGTAGC) were used for barcoding. DNA isolation was performed using the NucleoSpin→ Plant II Kit. The quality of the isolated DNA was assessed using agarose gel electrophoresis, and the bands were visualized under a UV transilluminator (Genei). Images were captured with a Gel Documentation System (Bio-Rad). Sanger sequencing was conducted on a PCR thermal cycler (GeneAmp PCR System 9700, Applied Biosystems) using the BigDye Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems, USA), based on the manufacturer’s protocol. Sequence quality was evaluated with Sequence Scanner Software v1 (Applied Biosystems). Sequence alignment and editing were performed using Geneious Pro v5.1. The sequences were assembled, and the consensus sequence for each plant was identified. To identify related species, these sequences were aligned with the existing sequences using the Basic Local Alignment Search Tool (BLAST) (
Phytochemical Identification
Literature Analysis
A comprehensive literature survey was performed to retrieve information on phytochemicals previously reported from the medicinal plants present in Kaidaryadi Kashayam. Data were obtained from the PubMed database (
GC-MS Analysis
The plant parts used were selected according to their traditional indications documented in classical Ayurvedic texts, and the details are provided in Supplementary Table S2. The collected plant samples were washed with distilled water and shade-dried at room temperature. Methanol was used as the solvent. Crushed samples weighing 25 g were subjected to Soxhlet extraction with 250 ml of methanol for 24 hours, as per the procedure outlined in reference. 14 The resulting extracts were filtered through Whatman No. 1 filter paper and concentrated under reduced pressure using a rotary evaporator. The extracts were then freeze-dried in a lyophilizer and stored in sterile, pre-weighed screw-cap bottles at 4ºC. The extracts were analyzed using GC-MS (Gas Chromatography-Mass Spectrometry) with a Shimadzu QP2020 model and an SH-Rxi-5Sil MS column. The oven temperature was initially set to 60°C for 8 minutes, and 1.0 µl of the sample was injected. Helium gas (99.99% purity) was used as both the carrier and eluent, with a flow rate of 1 ml/min. The injector temperature was maintained at 250°C, and the split ratio was set to 10 throughout. Ionization was performed using 70 eV, and mass spectra were recorded in the range of 10–20 m/z for 8 minutes. As compounds eluted from the chromatographic column, they were ionized and fragmented in the electron ionization detector, producing charged ions with distinct masses. The resulting m/z ratios were calibrated and matched against the NIST 17 Library for compound identification.
Target Identification
A comprehensive literature assessment was conducted to retrieve molecular targets associated with H. pylori from PubMed and DrugBank databases using the keyword “H. pylori + molecular targets.” Both host-associated and H. pylori-specific targets were identified, and only experimentally validated targets were shortlisted for further investigation.
Target and Ligand Preparation
The crystallographic structure files of selected targets having a resolution less than 2.5 Å were downloaded from the Protein Data Bank (PDB) (
Molecular Docking
Molecular docking was performed to predict the binding modes and affinities of phytochemicals at the target protein active sites. The library of identified compounds was docked against selected H. pylori targets. Binding site coordinates were extracted from PDB site annotations and defined for docking. A high-throughput, site-directed docking algorithm, LibDock, was employed to prioritize compounds based on their docking scores. LibDock rapidly screens large ligand libraries against rigid receptor structures, offering computational efficiency suitable for multitarget studies. The algorithm aligns ligand conformations within the binding site by identifying polar and apolar interaction hotspots. The number of hotspots was set to 100, with a docking tolerance of 0.25, while remaining parameters were maintained at default settings, allowing up to 255 ligand conformations.
Network Pharmacology Analysis
To identify the most effective plants and phytochemicals against the selected disease targets, a network pharmacology approach was applied. A plant- phytochemical- target interaction network was constructed using Cytoscape (
PE Analysis
The prediction efficacy (PE) of the top-ranked molecules was calculated independently to evaluate their overall multitarget regulatory potential across the selected targets. PE was determined by summing the docking scores of ligand–target complexes with docking scores higher than the corresponding mean docking score thresholds across the docking dataset, using the following equation. 17
Where P is the prediction efficacy, L is the ligand, S is the docking score, and TL is the target-ligand complex.
MD Simulation
MD simulations were performed on the top-ranked ligand that exhibited the highest docking score to assess its binding stability with the target protein. All simulations were conducted using GROMACS 2023 with the CHARMM36 force field for the protein and Swiss Param-generated parameters for the ligand and reference compound. The receptor structure was preprocessed using UCSF Chimera’s DockPrep tool to remove water molecules, add hydrogens, and assign appropriate charges, and was saved as REC.pdb. The protein-ligand complex was solvated in a triclinic box with TIP3P water molecules, maintaining a 1.0 nm buffer from the complex. The system was neutralized and ionized to a 0.1 M NaCl concentration.
Energy minimization was carried out using the steepest descent algorithm until the maximum force fell below 1,000 kJ/mol/nm. Equilibration was performed in two phases: a 100 ps NVT ensemble at 300 K using the V-rescale thermostat, followed by a 100 ps NPT ensemble at 1 bar pressure controlled by the Parrinello–Rahman barostat. Position restraints were applied to heavy atoms during equilibration. The production MD simulation was run for 100 ns with a 2 fs integration time step, employing periodic boundary conditions and Particle Mesh Ewald (PME) for long-range electrostatics. Trajectory analyses involved calculating the root mean square deviation (RMSD) to evaluate overall structural stability and the root mean square fluctuation (RMSF) to assess residue-level flexibility throughout the simulation period.
Lipinski Rule of Filtering and ADMET Prediction
Understanding the pharmacological properties of lead candidates at the early stage of drug discovery can significantly reduce the likelihood of failure in subsequent clinical trials. Therefore, we employed computational predictive analyses to assess the pharmacological characteristics of promising candidates following docking studies. Drug-likeness was evaluated using the Lipinski filter protocol in DS, considering parameters such as hydrogen bond donors (HBD), hydrogen bond acceptors (HBA), molecular weight (MW, Da), and the octanol- water partition coefficient (AlogP). According to Lipinski’s rule, an orally active drug should have HBD ≤ 5, HBA ≤ 10, MW ≤ 500 Da, and AlogP ≤ 5.
Next, the pharmacokinetic profiling was carried out using the “ADMET descriptors” module of DS, a comprehensive computational tool that predicts key properties from molecular structures. The evaluated parameters included intestinal absorption, aqueous solubility, blood–brain barrier permeability, plasma protein binding, cytochrome P4502D6 inhibition, and hepatotoxicity.
Results
Plant Authentication
The annotated DNA sequences of medicinal plants of Kaidaryadi Kashayam were submitted to the NCBI database. The GenBank accession numbers for all the submitted sequences of plants are listed in Table 1.
GenBank Accession Numbers for the Medicinal Plants of Kaidaryadi Kashayam.
Phytochemical Identification
The GC-MS chromatograms of the five medicinal plants included in the formulation are shown in Figure 1, and the identified compounds along with their names, retention times (RT), peak areas, and peak heights are listed in Supplementary Table S3. Peaks exhibiting potential overlap were carefully evaluated, and only those with high match scores and clear spectral resolution were considered for further analysis to ensure accuracy and reliability. The phytochemicals identified through literature mining are provided in Supplementary Table S4. The total number of compounds identified through literature mining and GC-MS analysis is summarized in Supplementary Table S5.
GC-MS Chromatogram of Medicinal Plants of Kaidaryadi Kashayam. The Phytochemicals Present in the Methanol Extract Were Identified Using the GC-MS Method. The Compounds Detected Were Represented as Peaks. The X-axis Represents Retention Time (RT), and the Y-axis Represents the Relative Abundance of the Compounds.
Target Identification
The details of molecular targets of H. pylori are listed in Table 2.
List of Molecular Targets of H. pylori Based on Literature Analysis.
Molecular Docking
Molecular docking was performed in DS to identify phytochemicals interacting with the selected H. pylori targets. A total of 671 compounds, after removal of 93 duplicates, were docked against 18 target proteins. For each target, the mean LibDock score was used as the threshold. Forty-seven compounds did not generate valid docking poses with any of the selected targets. Table 3 summarizes the docking scores of phytochemicals whose LibDock scores exceeded the mean docking score calculated individually for each target protein. Only multitarget ligand–target interactions satisfying this target-specific threshold criterion are presented in the table.
Molecular Docking Parameters of the Phytochemicals of Medicinal Plants of Kaidaryadi Kashayam That Interact with Multiple Targets and Have Docking Scores Higher Than the Mean Docking Score for Each Target.
Docking results revealed that riboflavin, identified in Trichosanthes dioica and Murraya koenigii, exhibited high-affinity interactions with 10 targets, making it the top candidate. This was followed by phytomelin, from Murraya koenigii, which showed strong affinity toward four targets. The 2D interaction profiles of riboflavin with its corresponding targets are presented in Figure 2.
The 2D Interaction Image of Riboflavin Against Selected Targets of H. pylori. The Ball-shaped Structures Represent Interacting Amino Acids of the Target Protein. The Nature of Interaction Is Represented as Colored Lines as Indicated Below (Hydrogen Bonds: Conventional Hydrogen Bond, Pi–Lone Pair; Hydrophobic Bonds: Alkyl Bond; Other Bonds: Pi–Cation [Electrostatic] and Unfavourable Bond [Steric/Electrostatic Clash]).
Network Pharmacology Analysis
A plant–phytochemical–target interaction network was constructed to elucidate the multitarget effects of Kaidaryadi Kashayam against selected H. pylori proteins. Based on the docking outcomes of 671 phytocompounds against 18 targets, the five top-scoring phytochemicals from each of the five plants were incorporated into the network (Figure 3). The network comprised 48 nodes (5 plants, 18 targets, and 25 phytochemicals) and 172 edges, where edges denote interactions and nodes represent plants (blue), phytochemicals (green), and targets (orange). Degree centrality was calculated using the CytoNCA plugin in Cytoscape.
Interaction Network Between Phytochemicals of Medicinal Plants of Kaidaryadi Kashayam and Selected Targets of H. pylori. The network was constructed using the five highest-scoring phytochemicals from each medicinal plant based on docking analysis against selected H. pylori targets. The Blue Color Represents Medicinal Plants (Tri; Trichosanthus dioica; Zin; Zingiber officinale; Ter; Terminalia chebula; Pip; Piper longum; Mur; Murraya koenigii), the Orange Color Represents Molecular Targets, and the Green Color Represents the Phytochemicals.
Degree centrality values for each plant, along with the corresponding number of active phytochemicals and interacting targets, are presented in Table 4a, while degree centrality for individual phytochemicals is shown in Table 4b. The results indicate that Zingiber officinale exhibits the highest degree centrality, suggesting the strongest multitarget regulatory potential among the evaluated plants. From the results, it is evident that the plant, Zingiber officinalis, has the highest number of degrees and phytochemicals interacting with targets. Among the phytochemicals, riboflavin (PC ID 493570), present in two plants of Kaidaryadi Kashayam, exhibited the highest degree centrality, interacting with 10 targets, followed by phytomelin, which interacted with 9 targets.
The Degree Centrality of Medicinal Plants of Kaidaryadi Kashayam and Phytochemicals of the Medicinal Plants of Kaidaryadi Kashayam.
PE Calculation
To assess the therapeutic potential of the most active phytochemicals in the selected formulation, PE was calculated by summing the docking scores of each compound across all targets. The mean docking score of all phytochemicals was used as a threshold to identify compounds with superior binding affinity. The PE values for phytochemicals of Kaidaryadi Kashayam are presented in Table 5. Results indicated that riboflavin (PC ID 493570) exhibited the highest PE, based on cumulative docking scores against the selected H. pylori targets.
Prediction Efficacy of Top-scored Phytochemicals of Kaidaryadi Kashayam Based on the Docking with 18 Targets.
MD Simulation
Based on the overall in silico predictions, riboflavin emerged as a promising candidate due to its high affinity toward multiple molecular targets of H. pylori. Therefore, riboflavin was selected for further evaluation of its binding stability with β-lactam-inducible penicillin-binding protein (PBP), the target to which it exhibited the highest docking score. Amoxicillin, a β-lactam antibiotic known to inhibit PBP, was used as the reference control. The RMSD and RMSF profiles for PBP bound with riboflavin and amoxicillin over a 100-ns simulation period are illustrated in Figure 4a and 4b, respectively.
RMSF Plot During 100 ns Molecular Dynamics Simulation of PBP-riboflavin (red) and PBP-amoxicillin (black) Complexes.
The MD results, as reflected in RMSD and RMSF patterns, indicate that riboflavin forms a stable and energetically favorable interaction with PBP, exhibiting lower structural deviation and residue-level fluctuation compared to the reference drug.
Lipinski and ADMET
Riboflavin was further assessed using Lipinski’s rule of five and ADMET prediction, and the outcomes are summarized in Table 6. The compound satisfied all Lipinski parameters, suggesting good oral drug-likeness. ADMET evaluation indicated favorable pharmacological characteristics, including good solubility, absence of hepatotoxicity, no cytochrome P4502D6 inhibition, minimal plasma protein binding, and no penetration of the blood–brain barrier. However, riboflavin was predicted to exhibit poor intestinal absorption.
Lipinski and ADMET Parameters of Riboflavin.
Discussion
In the present study, the individual medicinal plants were collected and authenticated using the DNA barcoding method. Later, the phytochemicals of the methanolic fractions of the formulation were identified using GC-MS analysis. The compound “mesitylene” was found commonly in three medicinal plants of Kaidaryadi Kashayam (Murraya koenigii, Trichosanthus dioica, and Piper longum). The compounds, “Benzene, 1-ethyl-2-methyl” for Zingiber officinalis, “Decane” in Murraya koenigii, “3,5-dimethyl” in Trichosanthus dioica, and “2,4-Decadienamide, N-isobutyl-, (E, E)” for Piper longum, were observed highest yield based on the area in the chromatogram. In addition to the phytochemicals identified through GC-MS analysis, previously reported compounds from these plants, irrespective of extraction solvent, were collected through literature mining. This led to the compilation of a library of 671 small molecules, which were subsequently subjected to virtual screening against selected molecular targets of H. pylori.
A total of 17 H. pylori-specific targets and 1 host-associated target were selected for virtual screening of the identified phytochemicals from the medicinal plants of the formulation. Molecular docking revealed that several compounds exhibited favorable binding conformations with multiple targets. Among them, riboflavin, identified from Trichosanthes dioica and Murraya koenigii, showed high-affinity interactions with ten targets (PBP, Ure, nth, aroQ, fldA, fabL, CAT, aroK, fabZ and Cagα ATPase). The formation of multiple conventional hydrogen bonds within these target-ligand complexes indicate favorable binding interactions and supports the potential structural stability of riboflavin within the respective active sites. Notably, Cagα ATPase plays a critical role in H. pylori virulence, as it functions as an essential energy-providing component of the Type IV secretion system. This ATPase drives the assembly and operation of the secretion machinery, which is responsible for the translocation of virulence factors, including CagA, into host cells, thereby contributing to bacterial pathogenicity. 18 The targets PBP, Ure, nth, aroQ, fldA, fabL, CAT, and aroK are well documented for their essential roles in H. pylori colonization, survival, and pathogenesis within the host system. 19 Therefore, the interaction of riboflavin with these key proteins may indicate its potential protective effect against H. pylori-mediated infections. Moreover, riboflavin (vitamin B2) is an essential micronutrient known for its antimicrobial properties. Previous studies have demonstrated its efficacy against multidrug-resistant strains of Pseudomonas aeruginosa, Staphylococcus aureus, and Staphylococcus epidermidis. 20 Additionally, riboflavin treatment has been shown to downregulate polA and dnaB mRNA expression in H. pylori in a dose-dependent manner. 21 Correlation analyses further revealed significantly reduced riboflavin levels in gastric carcinoma tissues infected with H. pylori when compared to normal samples, highlighting its potential contribution to gastroprotection. 22 The findings of this study, together with previously reported evidence, strongly suggest that riboflavin exerts protective effects against H. pylori infection and its associated gastric complications. Accordingly, it may be inferred that the medicinal plants in Kaidaryadi Kashayam that are rich in riboflavin could contribute to its protective effects against H. pylori-mediated gastric inflammation.
While dietary intake of riboflavin primarily supports normal physiological and metabolic requirements, higher doses are believed to confer antibacterial activity. Riboflavin-induced antimicrobial effects have been attributed to multiple mechanisms, including damage to microbial membranes and DNA via photodynamically activated reactive oxygen species (ROS), enhancement of innate immune response by activating macrophages, monocytes, and neutrophils, improved pathogen recognition, and suppression of pro-inflammatory mediators. Thus, the pharmacological action of riboflavin is context-dependent, exhibiting dual roles depending on physiological conditions and dosage. 23
Another compound, phytomelin (commonly known as rutin), demonstrated strong affinity toward four selected targets, NAT2, yrpC, clpX, and NADS. Its documented antibacterial properties highlight its potential as a promising alternative in the context of rising antibiotic resistance. Rutin has been shown to disrupt bacterial cell membranes, resulting in leakage of essential intracellular components and ultimately causing cell death. 24 Furthermore, several studies have reported its effectiveness against both Gram-positive and Gram-negative bacteria, including H. pylori. 25
The compound, proanthocyanidin identified in this study showed interaction with two prominent H. pylori targets, fabZ and PDF1. Proanthocyanidin has gained considerable attention as a potential therapeutic agent against H. pylori, supported by multiple preclinical and clinical investigations. A double-blind, randomized, placebo-controlled trial involving 522 H. pylori–positive adults demonstrated significant improvement following proanthocyanidin treatment. 26 In addition to its anti-H. pylori activity, proanthocyanidin has been shown to mitigate NSAID-induced gastric injury.
Moreover, several studies have evaluated its influence on gastrointestinal hormone regulation and motility. For example, in a study involving rats fed a cafeteria diet, reduced enteroendocrine cell density and decreased circulating levels of active glucagon-like peptide-1 (GLP-1) were observed, whereas administration of grape seed–derived proanthocyanidin prevented these alterations. 27 Collectively, these findings reinforce the potential of proanthocyanidin as an anti-H. pylori candidate, consistent with the observations of the present study.
As multiple phytochemicals from the formulation exhibited binding affinity toward key H. pylori targets, their therapeutic potential was further evaluated by calculating the efficacy score, derived by summing the docking scores of each compound across all targets. Riboflavin (PubChem ID: 493570) showed the highest efficacy score, followed by Drieline (PC ID: 319409105). The therapeutic relevance of these compounds in gastroprotection and H. pylori-mediated inflammation has been discussed above.
To evaluate the binding stability of riboflavin, identified as the most potent compound based on efficacy score and target interactions, MD simulations were conducted against PBP, the protein for which it exhibited the highest docking affinity. The RMSD analysis indicated that both the riboflavin-PBP and reference amoxicillin-PBP complexes remained stable throughout the simulation. Amoxicillin exhibited a maximum deviation of approximately 1.5 Å between 53 and 56 ns. In the case of riboflavin, the ligand-bound target demonstrated an initial increase during the early equilibration phase (5–10 ns), reaching approximately 2.2 Å, which corresponds to structural relaxation from the starting minimized conformation. Following equilibration, the system attained a stable conformational state, and RMSD remained minimal without any progressive drift throughout the 100 ns simulation. The post-equilibration deviation of riboflavin relative to the stabilized conformational ensemble was negligible (maximum deviation ≈0.05 Å), indicating strong binding stability and persistent retention of the ligand within the active site. These results confirm the conformational stability of the protein-ligand complex under physiological simulation conditions.
The RMSF profiles of both systems demonstrated comparable fluctuation patterns. The riboflavin-bound PBP showed a maximum fluctuation of approximately 2.6 Å near residue 270, while the amoxicillin-bound PBP exhibited a peak fluctuation of about 2.3 Å around residue 110. These limited fluctuations in the protein backbone suggest stable protein-ligand interactions in both complexes, further supported by the favorable thermodynamic parameters observed during the simulation.
ADMET and Lipinski profiling of riboflavin provided key insights into its drug-like characteristics. Riboflavin satisfied all components of Lipinski’s rule of five, indicating compliance with basic physicochemical criteria required for oral drug candidates. This suggests that riboflavin possesses favorable molecular properties to be considered a potential lead compound. ADMET predictions further revealed desirable pharmacokinetic attributes, including good solubility, absence of hepatotoxicity, lack of CYP2D6 inhibition, and minimal plasma protein binding. These features reduce the risk of drug–drug interactions and toxicity, which are common contributors to late-stage drug development failures. Additionally, the absence of blood–brain barrier penetration aligns with riboflavin’s role as a systemic rather than CNS-active agent. However, the prediction of poor intestinal absorption represents a substantial limitation. Riboflavin is known to exhibit saturable gastrointestinal absorption, which is consistent with the computational findings. This may affect its overall bioavailability and therapeutic effectiveness. Therefore, formulation-based optimization—such as nanoparticle systems, prodrug strategies, or co-administration with absorption enhancers—may be required to overcome this drawback.
Overall, these results highlight riboflavin’s favorable safety and drug-likeness profile, while identifying absorption efficiency as a critical parameter requiring improvement for its advancement as a promising therapeutic agent.
The overall findings of the present study indicate that the phytochemicals present in the medicinal plants of the selected formulation exhibit promising activity against multiple molecular targets of H. pylori. Based on experimental outcomes, it is evident that these plant-derived molecules possess the ability to simultaneously regulate several key pathways associated with H. pylori pathogenesis, unlike conventional antibiotics that primarily act on a single target.
Given the current challenges posed by limited drug efficacy and escalating antimicrobial resistance, the results highlight new opportunities to explore traditionally important medicinal plants and their formulations as potential sources of multitarget lead compounds. As Kaidaryadi Kashayam contains medicinal plants whose phytochemicals have demonstrated strong in silico performance, these findings warrant further investigation to evaluate its therapeutic efficacy against H. pylori infection through experimental and clinical validation.
The identified compounds may be taken forward for experimental validation to establish their potential as natural therapeutic agents against H. pylori. Further in vitro and in vivo studies are required to substantiate the computational predictions before progressing toward clinical evaluation.
Limitations and Future Directions
Although the present study rigorously examined riboflavin as a potential candidate against H. pylori using a bioinformatics-driven approach, future research must focus on experimental validation through appropriate in vitro and in vivo studies. Even if riboflavin is a well-established essential vitamin with a long history of safe use in food and pharmaceutical applications, and its safety profile has been extensively documented in the scientific literature, 28 its toxicity profile should be reassessed when intended for antimicrobial applications, as such effects may require comparatively higher doses than normal nutritional supplementation.
Conclusion
The findings of this study highlight the regulatory potential of selected phytochemicals from a traditional Ayurvedic formulation against key molecular targets of H. pylori. Several identified compounds, specifically riboflavin, exhibited strong affinity toward multiple targets, including those associated with drug resistance, one of the major hurdles in effective H. pylori eradication. Thus, these phytochemicals may offer valuable prospects in overcoming resistance-related challenges. Moreover, their presence within the formulation underscores its potential relevance in disease management. By integrating traditional knowledge with an in silico drug discovery approach, this study identified promising lead molecules with potential therapeutic effects against H. pylori. Such multidisciplinary strategies, employing computational predictive tools, can significantly accelerate translational research by identifying drug candidates of natural origin in a time- and cost-efficient manner.
Supplemental Material
Supplemental material for this article is available online.
Footnotes
Acknowledgements
We would like to thank the Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to be University), Mangalore, India.
Authors’ 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 agreed to be accountable for all aspects of the work. All the authors are eligible to be authors as per the International Committee of Medical Journal Editors (ICMJE) requirements/guidelines.
Consent to Participate
Not applicable.
Consent for Publication
Not applicable.
Data Availability Statement
All the data generated and analyzed during the study are included in the article and its supplementary file.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Ethical Approval
This study does not involve experiments on animals or human subjects.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Informed Consent
Not applicable.
Use of Artificial Intelligence-assisted Tools
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
Supplementary Material
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