Integrating network pharmacology and in vivo study to explore the anti-Alzheimer’s potential of Bergenia ligulata and Nelumbo nucifera

Abstract

Amyloid plaque buildup, tau protein tangles, oxidative stress, and neuronal death are the hallmarks of Alzheimer’s disease (AD). Using network pharmacology, molecular docking, and in vivo experiments, this study investigated the neuroprotective potential of Bergenia ligulata (BL) and Nelumbo nucifera (NN) against aluminum chloride (AlCl₃)-induced AD. Network pharmacology focused on important biomarker proteins like acetylcholinesterase (AChE), BCL2, and caspase-3 to identify 74 bioactive targets linked to AD. The evaluation of ligand–protein interactions was done using molecular docking. Male Wistar rats were exposed to AlCl₃ to cause AD-like pathology in vivo, and a combination treatment of BL and NN at varying doses was provided. Apoptosis markers (BCL2, caspase-3), biochemical investigations (AChE activity, oxidative stress markers—GSH, SOD, catalase, and lipid peroxidation), behavioral evaluations (elevated plus maze, conditioned avoidance test), and histopathological analyses were investigated. The combination of BL and NN demonstrated substantial neuroprotection in a dose-dependent manner. Reduced AChE levels point out improved cholinergic activity. Oxidative stress indicators showed improvement, with lower levels of malondialdehyde and higher anti-oxidant levels of GSH, SOD, and catalase. Apoptotic markers showed an increase in BCL2 expression and a decrease in caspase-3, suggesting anti-apoptotic effects. Reduced neuronal degeneration in the cortex and hippocampal regions was confirmed by histopathology of the brain. The synergistic potential of BL and NN demonstrated potent neuroprotective effects by modulating AChE activity, reducing oxidative stress, increasing anti-oxidant levels, and inhibiting apoptosis. These findings highlighted the potential of BL and NN as a new therapeutic approach for the AD.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-025-04274-w.

Introduction

Progressive memory loss and cognitive dysfunctions are hallmarks of Alzheimer’s disease (AD; Jahn 2013). Amyloid plaques, tau protein tangles, oxidative stress, mitochondrial dysfunction, and neuroinflammation contribute to Alzheimer’s disease pathology (Butterfield and Halliwell 2019). Mitochondrial dysfunction plays a crucial role in AD pathology by impairing energy metabolism and increasing oxidative stress, making it a potential therapeutic target (Rai et al. 2020). There is currently no known cure for AD, and present treatments merely control symptoms and modestly enhance quality of life. Cholinesterase inhibitors, such as donepezil, rivastigmine, galantamine, and aricept, are currently the most often used medications in the treatment of AD (Hampel and Mesulam 2018). AD is complex and can be effectively managed with multifunctional medicinal plants containing multiple bioactives that modulate several proteins to attain homeostasis (Khanal et al. 2021). Traditional medicinal plants have shown promise in AD management by modulating multiple targets involved in disease progression (Tripathi et al. 2024). Metal is an element that substantially influences human health and disease. Iron’s redox properties intensify as the disease advances, significantly contributing to its deleterious impacts on AD (Castellani and Moreira 2012). Copper levels in the brains of AD patients are significantly increased, which has been associated with oxidative stress and neuropathology (Hung and Bush 2010). Aluminum’s neurotoxic potential was investigated experimentally in 1965; it caused the formation of neurofibrillary tangles in rabbits, which resembled the symptoms of AD (Colomina and Peris-Sampedro 2017). In addition to metal toxicity, hormonal factors such as androgen deprivation therapy have also been linked to an increased risk of AD, further highlighting the multifactorial nature of the disease (Singh et al. 2024).

Across cultures, medicinal plants have been used to heal various diseases since millennials (Dwivedi et al. 2021). The botanical sources contain anti-oxidant, anti-inflammatory, and neuroprotective phytochemicals like alkaloids, flavonoids, terpenoids, and polyphenols (Dwivedi et al. 2023). These biologically active substances might decrease β-amyloid plaques, neurofibrillary tangles, oxidative stress, and neuroinflammation in AD (Tamagno et al. 2021). One such medicinal plant, Bergenia ligulata, is known to possess numerous pharmacological effects, such as anti-inflammatory, immunomodulatory, and anti-oxidant potential (Salimo et al. 2023). A similar genus plant, Bergenia ciliata, showed neuroprotective potential in treating sporadic AD induced by the intracerebroventricular streptozotocin model (Barai et al. 2018). In addition, numerous reports describe bergenin, a potential bioactive of B. ciliata, to possess anti-inflammatory, anti-oxidant, and antidiabetic properties (Barai et al. 2018). The effects of rhizome extracts from Bergenia ciliata on rats with AD restored cholinergic function, decreased oxidative stress, and enhanced learning and memory. This implies that Bergenia ciliata has therapeutic potential in AD with dose levels of 125, 250 and 500 mg/kg per day (Barai et al. 2018). Nelumbo nucifera, an aquatic perennial plant commonly known as lotus, is used in traditional medicine as a spleen tonic and cough suppressor (Paudel and Panth 2015). The seeds of N. nucifera are used to treat a wide range of ailments, including hypertension, high fevers accompanied by restlessness, neurological disorders, and sleeplessness (Haritha et al. 2021). It has been reported to have anti-proliferative, anti-inflammatory, hepatoprotective, anti-fibrotic, antidepressant, free radical scavenging qualities, immunomodulatory, and antiviral potential (Sheikh 2014). In a pentobarbital-induced sleep model, Nelumbo nucifera extract treatment reduced sleep latency and increased sleep duration with dose of 160 mg/kg. (Jo et al. 2021).

Computational pharmacology has gained great precedence in identifying the potential of bioactives against a disease (Bhattacharya et al. 2024). Network pharmacology (NP) is a cutting-edge technique employed to uncover potential therapeutic medicines and gain insights into the therapeutic processes beneath intricate disorders (Wu et al. 2018). NP is crucial for developing herbal medicines as therapeutic agents because it targets many sites in signaling pathways (Patil et al. 2022). NP examines drug–target interactions, drug–drug interactions, and the effects of prospective medicines on biological pathways and networks (Dwivedi and Shastry 2023a). Network pharmacology analyzes biological pathways and networks to disclose drug action mechanisms, identify therapeutic targets, forecast side effects, and aid drug discovery and development. Instead of confirming individual targets, network pharmacology investigates disease-causing networks and identifies ligands that can affect numerous treatment targets (Yuan et al. 2017). Natural products are receiving more attention from a therapeutic standpoint than modern synthetic drugs because of their lower toxicity, negligible adverse effects, low cost, and accessibility. Active phytoconstituents from plants have shown promise in treating diseases, such as diabetes, hypertension, Alzheimer’s, and Parkinson’s (Açar et al. 2023; Şahin et al. 2023). Further, molecular docking provides insights into the binding potential of small molecules to a target of interest. This, in addition, provides the interaction stability of the bioactive (small molecule) against a target (Khanal et al. 2023). Moreover, quantifying the identified hub genes in an animal model serves as a confirmation of the computational work performed. Integrating various approaches like network pharmacology, gene ontology analysis, and molecular docking with in vitro and in vivo protocols can potentially help deduce the potential proteins involved in the amelioration of the disease. Hence, in the present study, we aimed to integrate various in silico tools with experimental pharmacology to decode the possible mechanism of Bergenia ligulata and Nelumbo nucifera against AD.

Materials and methods

Computational pharmacology

Identification of targets

The DisGeNet database (https://www.disgenet.org; Piñero et al. 2015) was used to identify the targets involved in the pathogenesis of AD using the keyword “Alzheimer’s disease” with disease id “C0002395”. The phytoconstituents for Bergenia ligulata rhizomes and Nelumbo nucifera embryos were retrieved from IMPPAT: Indian Medicinal Plants, Phytochemistry And Therapeutics (https://cb.imsc.res.in/imppat/; Mohanraj et al. 2018) and Chemical Entities of Biological Interest (ChEBI; https://www.ebi.ac.uk/chebi/; Degtyarenko et al. 2008). The targets for identified bioactives from Bergenia ligulata rhizomes and Nelumbo nucifera embryos were identified from the DIGEP-Pred (http://www.way2drug.com/ge) database considering targets possessing pharmacological activity greater than 0.5.

Network and gene ontology analysis

The targets from AD were matched with the proteins known to be regulated by bioactives from Bergenia ligulata rhizomes and Nelumbo nucifera embryos. The common targets were subjected to STRING ver. 11.5 (https://string-db.org/) to retrieve protein–protein interaction, KEGG pathway, and gene ontology analysis. Moreover, KEGG pathway analysis was utilized to identify pathways regulated by the bioactives, which were further integrated into Cytoscape ver. 3.9.0 to acquire pathway-protein interaction. The network analysis was performed on the basis of “edge count,” “node degree distribution,” and “betweenness by degree,” where parameters like eccentricity, neighborhood connectivity, in-degree distribution, and out-degree distribution were analyzed. The gene ontology of bioactive-modulated proteins was retrieved from STRING, which comprises cellular component (CC), molecular function (MF), and biological process (BP).

Molecular docking

Molecular docking was performed on the hub genes identified via network analysis along with potential proteins involved in inflammation and repair of neurons along with acetylcholinesterase (BCL2, CASP3, and AChE). The structure of proteins was modeled/retrieved from protein databank i.e., NOS2 (PDB ID: 3E7G), CTNNB1 (PDB ID: 1QZ7), CASP8 (PDB ID: 1QTN), TNFRSF1A (PDB ID: 1EXT), GAPDH (PDB ID: 1U8F), AChE (PDB ID: 4BDT), CASP3 (PDB ID: 1NME), and BCL2 (modeled).

Preparation of proteins

The UniProt database (https://www.uniprot.org/; UniProt Consortium 2008) was utilized to query the structures of hub genes. The targets were then queried in the Protein Data Bank (RCSB; https://www.rcsb.org/); the targets not available were modeled using SWISS-MODEL (https://swissmodel.expasy.org) by subjecting the known FASTA sequence. The proteins were assessed for heteroatoms, and heteroatoms present were removed using the Discovery Studio Visualizer (BOVIA Discovery Studio Visualizer; https://discover.3ds.com/discovery-studio-visualizer-download). Further, energy was minimized for all the proteins using the MMFF94 force field.

Preparation of ligand

The 3D structures of phytoconstituents for Bergenia ligulata rhizomes and Nelumbo nucifera embryos were retrieved from the PubChem database in.sdf. The structure data file was converted to.pdb via Discovery Studio Visualizer 2019. The energy of the ligand was minimized and converted into.pdbqt format before subjecting it to docking.

Protein–ligand docking

Docking was performed using AutoDock Vina on the PyRx platform to assess the binding affinity of the bioactives against the hub genes. Molecular docking was performed to assess various binding parameters like binding energy, docking interactions, and their distances. The top binding complexes were analyzed in Discovery Studio Visualizer 2019 (Dwivedi and Shastry 2023b).

Experimental pharmacology

Plant authentication and extraction

Bergenia ligulata rhizomes and Nelumbo nucifera embryos hydroalcoholic extract (60:40 ratio) were procured and authenticated from Nutan Ayurvedic Research Centre, Anand. (PCL002 and PCL003).

In vivo assessment of anti-Alzheimer’s potential of Bergenia ligulata and Nelumbo nucifera

Procurement of animals and experimental study design

A total of 46 male Wistar rats were freshly procured from the CCSEA-registered facility and acclimatized for 1 week at the animal house facility of the institute. The Institutional Animal Ethics Committee of the institute approved protocol and the after procurement of the animals were done (Approval No.: RPCP/IAEC/2022-23/R2). Polypropylene cages with corn cob beds accommodated six animals each. The animals were housed in a room having a 12-h light–dark cycle. The room maintained a temperature of 25 + 2 °C and a humidity range of 30–70%. All the animals had free access to fresh animal feed and water. The animals were divided into six groups, with 8 animals in each group, except the normal group with 6 animals (Table 1). We used oral ingestion of aluminum chloride (100 mg/kg) to induce AD for 28 days. The normal group was fed with normal chow and water. After 28 days, the behavioral tests were performed on all animals. From day 33 to day 61, the standard drug donepezil was administered in the standard group. Similarly, the treatment groups received a mixture of both plant extracts orally at three different doses. Bergenia ligulata (125 mg/kg) and Nelumbo nucifera (50 mg/kg) were mixed in BN treatment 1 (low dose); Bergenia ligulata (250 mg/kg) and Nelumbo nucifera (100 mg/kg) were mixed in BN treatment 2 (medium dose); and Bergenia ligulata (500 mg/kg) and Nelumbo nucifera (100 mg/kg) were mixed in BN treatment 3 (high dose). Behavioral tests were performed on all animals upon completion of treatment. On completion of the study period, all animals were sacrificed, and the brains were removed for evaluating various parameters.

Table 1.

The grouping of animals used for treatment with Bergenia ligulata and Nelumbo nucifera

Group	No. of animals	Administration
Group 1: Normal	6	Normal Saline treatment with ad libitum food and water
Group 2: Disease Control	8	Alzheimer’s induction with AlCl3 (100 mg/kg)
Group 3: Standard Drug	8	AlCl3 (100 mg/kg) + Donepezil (10 mg/kg) treatment
Group 4: Treatment 1 (Low Dose)	8	AlCl3 (100 mg/kg) + Combination treatment of Bergenia ligulata (125 mg/kg) and Nelumbo nucifera (50 mg/kg)
Group 5: Treatment 2 (Medium Dose)	8	AlCl3 (100 mg/kg) + Combination treatment of Bergenia ligulata (250 mg/kg) and Nelumbo nucifera (100 mg/kg)
Group 6: Treatment 3 (High Dose)	8	AlCl3 (100 mg/kg) + Combination treatment of Bergenia ligulata (500 mg/kg) and Nelumbo nucifera (150 mg/kg)

Evaluation of neurobehavioral parameters

Assessment of anxiety, memory and spatial learning using elevated plus maze (EPM)

The EPM test, utilized to assess anxiety levels, memory, and spatial learning in test animals, involves a plus-shaped maze apparatus. It contains two open arms (50 cm × 10 cm) opposite to each other, with two closed walls of 40 cm in height. The maze is elevated 50 cm from the ground and includes a central square connecting the open arms. Wistar rats were evaluated for memory acquisition at the end of the study. The rats were observed for five minutes as they moved from the open arm to the close arm and back to their original place. The number of entries and the time taken for each transition were recorded. Less-anxious animals were easily located with open arms, while highly anxious animals were predicted to spend less time doing so.

Assessment of associative memory using conditioned avoidance test

Two compartments of similar size, one of which is dark, make up the equipment used for the conditioned avoidance test (CAT). A door connects the two chambers, allowing rats to go from one side to the other freely. The CAT was used to evaluate associative memory, which comprises two phases: training and test. When the rat entered the dark chamber with all four paws, it was removed from the light compartment for training purposes. The time taken for the rat to transition from the light compartment to the dark chamber during the test session was measured as latency. The animals were observed for a total of five minutes.

AChE Estimation in brain homogenate

Ingkaninan et al. 2000 described the approach that was used to determine AChE inhibition with galantamine as a reference. A 96-well microplate was used to combine different doses of the extracts with 50 mM Tris–HCl buffer (pH 8.00), 3 mM DTNB (in the buffer), 0.2 U/mL AChI, and other components. The combinations were left to incubate at 25 °C for 15 min. The microplate was then incubated at room temperature for 5 min after adding 15 mM AChI. A spectrophotometric recording of AChI hydrolysis was made by reacting DTNB with thiocholine to produce a yellow 5-thio-2-nitrobenzoate anion; the absorbance at 412 nm was measured using a 96-well microplate reader. From the graph of the percentage inhibition against extract concentrations, we were able to compute the inhibitory concentrations of 50% of AChE values (IC₅₀).

$$\text{Inhibition}\left(\%\right)=\left[\frac{A0-A1}{A0}\right]\times 100$$

where A0: absorbance of control; A1: Absorbance of extract.

Antioxidant biomarkers in rat brain homogenate

Measurement of malondialdehyde

The assay combination included 0.2 mL of brain PMS (10% w/v), 20% acetic acid (pH 3.5), 1.5 mL of TBA (0.8%), and 0.2 mL of SDS (8.1%), diluted to 5 mL with purified water. The mixture was heated in an oil bath at 100 °C for 60 min. After cooling, 5 mL of a 15:1 combination of n-butanol and pyridine was added followed by vigorous mixing. After centrifugation at 4000 rpm for 10 min, the organic layer was extracted and its absorbance was measured at 532 nm. MDA concentration is given as nM/g (Okhawa et al. 1979).

Superoxide dismutase

To 0.1 mL of brain homogenate (10% w/v), 1.2 mL of sodium pyrophosphate buffer (0.052 M, pH 8.3), 0.1 mL of phenazonium methosulfate (186 M), 0.3 mL of NBT (300 M), and 0.2 mL of NADH (780 M) were added. After 90 s of incubation at 30 °C, the reaction was halted with 0.1 mL of glacial acetic acid. The mixture was briskly mixed, agitated with 4 mL of n-butanol, then centrifuged at 4000 × g for 10 min. The absorbance of the organic layer was measured at 560 nm. The control was produced with 0.1 mL of distilled water instead of homogenate (Kakkar et al. 1984).

Glutathione peroxidase

The assay combination included 0.2 mL of brain homogenate (10% w/v), 0.2 mL of EDTA (0.8 mM), 0.1 mL of sodium azide (10 mM), 0.1 mL of 4 mM reduced glutathione (GSH), 0.1 mL of H₂O₂ (30 mM), and 0.4 mL of pH 7.0 phosphate buffer. After incubating at 37 °C for 10 min, the tubes were maintained at room temperature. Then, 0.5 mL of 10% trichloroacetic acid (TCA) was added and centrifuged at 3000 × g for 10 min. The supernatant was then mixed with 0.1 mL of 0.04% DTNB solution. The optical density was recorded at 420 nm against a blank (Mohandas et al. 1984).

Catalase

The assay combination included 0.1 mL of brain homogenate (10% w/v) and 1.9 mL of phosphate buffer (0.05 M, pH 7). 1 mL of freshly produced 30 mM H₂O₂ was added to the mixture and the absorbance was measured at 240 nm every 30 s for 3 min. To make a control, 0.1 mL of distilled water was used instead of the homogenate. Enzyme activity is defined as the concentration needed to prevent a 50% change in absorbance in a control sample within one minute. Catalase activity was measured as nM of H₂O₂ metabolized/min per mg protein (Johansson and Borg 1988).

Apoptotic biomarkers in rat brain homogenate

Caspase-3 activity

An ELISA method was used to measure caspase-3 activity in accordance with a predetermined methodology. 100 µL of prepared standards and samples were first added to each well. The plate was then sealed and incubated for 60 min at 37 °C. The plate was aspirated without being cleaned, 100 µL of the biotinylated solution of the active CASP3 antibody was added to each well. The plate was then sealed and incubated for an additional 60 min at 37 °C. Following the removal of the surplus buffer by tapping the plate upside down on absorbent paper, 100 µL of the working streptavidin: HRP conjugate solution was added to each well. The dish was thoroughly mixed, sealed, and incubated at 37 °C for 30 min. Once more, excess buffer was eliminated by tapping the plate upside down on absorbent paper. Further, 100 µL of TMB substrate was pipetted into each well. After that, the plate was incubated for 10 min at 37 °C without being shaken to prevent background interference. It was anticipated that positive wells would turn bluish in color. Following the incubation period, each well received 100 µL of stop solution, which turned the wells from blue to yellow. A microplate reader was used to measure absorbance at 450 nm within 10 to 15 min of administering the stop solution. (Krishgen CASP3 ELISA (KLR1648)).

BCL2 activity

For each empty well, 50 µL of standard diluent was dispensed. Then, 50 µL of prepared standards were dispensed into the standard well. To prepare the sample wells, 40 µL of samples and then 10 µL of biotinylated BNIP3 antibody were added to the designated wells. It is important to note that the standard and the blank wells should not be treated with this antibody. Later, 50 µL of streptavidin: HRP conjugate substrate was added to all wells and ensured full mixing. The plate was closed tightly and placed in an incubator at a temperature of 37 °C for 60 min. Following incubation, the plate was inverted and pressed against absorbent paper to remove excess buffer. Proceeded to wash the plate four times with diluted Wash Buffer (1X), ensuring that any liquid collected outside the wells is removed. Next, 100 µL of TMB substrate was introduced into each well and allowed to incubate at a temperature of 37 °C for 10 min, ensuring no shaking occurs. Positive wells are expected to exhibit a blue color. At last, 100 µL of stop solution was added into each well, resulting in a color transition from blue to yellow. After adding the stop solution, a microplate reader was used to measure the absorbance at 450 nm. (Krishgen BCL2 ELISA (KLR1880)).

Histopathology of rat brain

The hippocampus and the cortex of control and treated rats were excised, sliced into small sections, and fixed in Bouin’s fixative solution for 24 h. The pieces were then paraffinized and sectioned to 4–6 mm thickness. The sections were stained with hematoxylin and eosin before being captured using a high-resolution camera in the light microscope.

Results

Computational pharmacology

Network analysis

A total of 74 targets were identified to be present in the plant’s Bergenia ligulata rhizomes and Nelumbo nucifera embryos, from which Bergenia ligulata has 72.3% and Nelumbo nucifera has 69.11% of the identified targets to be involved in the pathogenesis of AD i.e., 51 targets combined (Fig. 1). Network analysis revealed 73 nodes to be present in the network, with 443 edges possessing an average node degree of 12.1 and an average local clustering coefficient of 0.58 (Fig. 2). Further, a bioactive–pathway–protein interaction was constructed using Cytoscape, which revealed 1,3-diphenylurea to possess the highest edge betweenness of 1527.29 with IFNG. Similarly, 1,3-diphenylurea possessed the highest betweenness centrality of 0.11, myricetin 3-O-β-D-glucopyranoside possessed the highest closeness centrality of 0.37, myristic acid possessed the highest degree of 26, and 24-methylene-24-dihydroparkeol possessed the highest neighborhood connectivity of 16.75. The ‘Pathways in cancer (hsa05200)’ was identified to possess the highest degree of 12. However, ‘Alzheimer disease (hsa05010)’ possessed a degree of 5, betweenness centrality of 0.005, closeness centrality of 0.28, eccentricity of 7, and neighborhood connectivity of 14.4. Further, molecular docking was performed on the hub genes identified to be linked with AD pathway (Fig. 3, Supp. Table T1, Supp. File 1).

Fig. 1.

The overlap between known targets linked to Alzheimer’s disease (AD) and molecular targets found in Nelumbo nucifera (NN) and Bergenia ligulata (BL) is depicted by the Venn diagram in (a). It emphasizes the different goals particular to every plant, the shared targets between Nelumbo nucifera and Bergenia ligulata, and the targets from any or both plants that cross with AD-related targets, therefore highlighting their possible therapeutic significance. Showing unique and common targets across the three sets, the Venn diagram in (b) offers a relative picture of targets identified from Nelumbo nucifera, Bergenia ligulata, and Alzheimer’s disease. It provides information on the extent of interaction between AD-associated targets and plant-derived molecular targets, therefore guiding their potential function in neuroprotection or disease modification

Fig. 2.

Target proteins for Bergenia ligulata and Nelumbo nucifera based on protein–protein interaction (PPI) network against Alzheimer’s disease. The network was built to show the interactions among possible target proteins, hence stressing important hubs and links. While edges show interactions, nodes are proteins; different colors illustrate different kinds of interactions including empirically found interactions, database-derived interactions, and predicted interactions. High connection central nodes could be quite important for the therapeutic action against Alzheimer’s disease

Fig. 3.

The protein–pathway–phytoconstituent network of targets against Alzheimer’s disease that was discovered in Nelumbo nucifera embryos and Bergenia ligulata rhizomes. The network’s edge color intensity (low to high: blue to green to brown) indicates the strength of the interactions between the proteins (circles), phytoconstituents (diamonds), and routes (hexagons)

Gene ontology analysis

The data for GO terms i.e., cellular components (CC), molecular function (MF), and biological process (BP) were retrieved from the STRING database. GO analysis identified 16 CC in which ‘extracellular space (GO:0005615)’ scored the lowest false discovery rate of 1.68E-12 via the modulation of 34 observed genes i.e., TNFRSF1A, HMOX1, TIMP1, MMP2, PLAT, CCL2, IFNG, CAT, MMP7, PRDX1, FLT1, MMP3, PRL, GH1, KLK3, CLU, TAC1, CD86, PRDX6, RAC1, IL6R, PLAU, PRDX4, KRT18, GAPDH, CD14, ADIPOQ, CHEK1, PRKCA, CD36, FKBP5, VIM, CCL4, and CTNNB1 against 3247 background genes at a strength of 0.62. Similarly, 36 MFs were identified in which ‘Protein binding (GO:0005515)’ scored the lowest false discovery rate of 4.51E-08 via the modulation of 42 observed genes i.e., TNFRSF1A, HMOX1, TIMP1, MMP2, PLAT, CCL2, IFNG, NR3C1, CAT, PRDX1, FLT1, PRL, GH1, CLU, TAC1, PGR, NOS2, CYP1A2, PRDX6, ESR2, RAC1, CASP8, GYPA, ABCG1, IL6R, AR, ABCA1, TP73, PRDX4, KRT18, GAPDH, NFE2L2, PPARA, ADIPOQ, CHEK1, PRKCA, CD36, FKBP5, VIM, CCL4, CTNNB1, and CYP3A4 against 7242 background genes at a strength of 0.36. Moreover, 459 BPs were identified where ‘Response to chemical (GO:0042221)’ scored the lowest false discovery rate of 1.03E-21 via the modulation of 45 observed genes i.e., TNFRSF1A, HMOX1, TIMP1, MMP2, PLAT, CCL2, CYP27B1, IFNG, NR3C1, CAT, PRDX1, FLT1, MMP3, GH1, CLU, TAC1, PGR, NOS2, CD86, CYP1A2, PRDX6, ESR2, RAC1, CASP8, ABCG1, IL6R, ATG5, PLAU, AR, ABCA1, TP73, PRDX4, KRT18, GAPDH, NFE2L2, CD14, PPARA, ADIPOQ, CHEK1, PRKCA, CD36, VIM, CCL4, CTNNB1, and CYP3A4 against 4010 background gene count with a strength of 0.65 (Supp. Tables T2–T4). The GO of the top 5 CC, MF, and BP has been represented in the form of a chord diagram (Fig. 4).

Fig. 4.

Gene ontology (GO) classification of target genes identified from Bergenia ligulata rhizomes and Nelumbo nucifera embryos. The GO terms are categorized into three major domains: Biological Process (red), Molecular Function (green), and Cellular Component (blue). The x-axis represents the gene count associated with each GO term, while the y-axis lists the specific GO terms

Molecular docking

Table 2 presented the binding energies (in kcal/mol) for a range of phytoconstituents derived from Nelumbo nucifera (NN) and Bergenia ligulata (BL) in relation to targets associated with Alzheimer’s disease. Binding energy serves as an indicator of the interaction strength between these phytochemicals and their respective target proteins, with lower (more negative) values signifying more robust interactions. Notably, compounds, such as Cycloartenol ( – 11.1 kcal/mol) and Liriodenine ( – 11.5 kcal/mol), demonstrate a significant binding affinity across multiple targets. Several phytoconstituents, including anonaine, calendol, and isoliensinine, exhibit binding energies comparable to established Alzheimer’s treatments such as Donepezil ( – 9.5 kcal/mol). Conversely, compounds like 1-triacontanol and linoleic acid reveal higher binding energies, indicating relatively weaker interactions with Alzheimer’s disease targets (Table 2).

Table 2.

The binding energies of the phytoconstituents identified from Nelumbo nucifera (NN) and Bergenia ligulata (BL) with targets for Alzheimer’s disease Binding energy

[Where, *Standard drug; A: NOS2; B: CASP8; C: TNFRSF1A; D: CTNNB1; E: GAPDH; F: BCL2; G: AChE; H: CASP3; Standard for NOS2: Dexamethasone; CASP8: Oleandrin; TNFRSF1A: Cyclophosphamide; CTNNB1: Dexamethasone; GAPDH: Tamoxifen; BCL2: Paclitaxel; AChE: Donepezil; CASP3: Paclitaxel]

Molecular docking was performed with all the identified bioactives with 8 targets i.e., NOS2 (PDB ID: 3E7G), CTNNB1 (PDB ID: 1QZ7), CASP8 (PDB ID: 1QTN), TNFRSF1A (PDB ID: 1EXT), GAPDH (PDB ID: 1U8F), AChE (PDB ID: 4BDT), CASP3 (PDB ID: 1NME), and BCL2 (modeled) (Supp. file 2). The docking with NOS2 revealed cycloartenol to possess the highest binding affinity of  – 11.1 kcal/mol with 1 hydrogen bond interaction with TRP463, 8 π–π bond interactions with residues CYS200, PHE369, TRP194, LEU209, and 13 van der Waal interaction with residues GLY371, TYR489, PRO350, ASN370, ILE201, GLU377, MET374, PRO467, PRO466, VAL465, ARG381, ARG199, VAL352. The docking with CASP8 revealed β-amyrin to possess the highest binding affinity of  – 8.1 kcal/mol with 2 hydrogen bond interactions with residues GLU335, GLN339 and 1 π–π bond interaction with TYR293. The CASP8–calendol possessed the second highest binding affinity with ARG258, 2 π–π bond interactions with residue LYS253. The TNFRSF1A–isoliensinine complex possessed the highest binding affinity with 5 hydrogen bond interactions with residues THR135, ASN148, ASN116, ASN 134, 2 pi bond interactions with HIS105, PHE115, and 7 van der Waal interactions with GLN133, LYS132, TYR103, GLU147, LEU145, VAL136, CYS137. Docking analysis with CTNNB1–fucosterol revealed to possess the highest binding affinity of  – 8.3 kcal/mol with 1 Hydrogen bond interaction with ASP299 & ARG342 and 6 π–π bond interactions with LYS292, ILE296, ALA295, LYS335, PHE253. The docking interaction with GAPDH revealed a complex with taraxasterol to possess the highest binding affinity of  – 9.2 kcal/mol with no potential interaction. However, cynaroside displayed a binding affinity of  – 8.7 kcal/mol with 7 hydrogen bond interactions with ASN239, ALA238, ASN316, GLU317, CYS152, THR153, ARG234, and 8 π–π bond interactions with residues ALA183, ARG13, THR182, ILE14, and CYS152. The docking interaction of CASP3 revealed calendol–CASP3 complex to possess the highest binding affinity with 1 hydrogen bond with THR140 and π–π interaction with ILE160. Similarly, the docking interaction with AChE revealed liriodenine–AChE complex to possess the highest binding affinity of  – 11.5 kcal/mol with 8 π–π interactions with residues LEU289, TYR72, TRP286, and TYR341. The docking interaction of bioactives with BCL2 revealed taraxasterol–BCL2 complex to possess the highest binding affinity of  – 9.1 kcal/mol with 3 hydrogen bond interactions with residues SER5 and GLU55 (Fig. 5; Supp. Tables T5–T12).

Fig. 5.

a 3D and b 2D interaction of 1. NOS2-Cycloartenol, 2. CASP8-Beta amyrin, 3. TNFRSF1A-Isoliensinine, 4. CTNNB1-Fucosterol, 5. GAPDH-Cynaroside, 6. BCL2-Taraxasterol, 7. AChE-Liriodenine, and 8. CASP3-Calendol

Anti-Alzheimer activity of Bergenia ligulata and Nelumbo nucifera

Assessment of body weight

The body weight of all the animals was measured at the time when they were included in the study, then at the time when induction was completed, and daily during the treatment. There was no significant difference observed in the change in body weight between the groups. All the animals were seen to have improved body weight from the time of treatment (Supp. Fig. S1).

Evaluation of neurobehavioral parameters

Assessment of anxiety, memory, and spatial learning using elevated plus maze (EPM)

Transfer delay was assessed in an elevated plus maze. In the elevated plus maze test, AlCl₃-treated rats had a substantially longer retention transfer latency (TL) than the normal rats. TL was lower with donepezil treatment compared with AlCl₃-treated rats. Retention transfer latency was reduced significantly by a low dose of BN treatment, while a highly significant reduction in TL with BN medium and high-dose treatment was observed compared to AlCl₃-treated rats. It was observed that the high dose of BN had a positive effect, which was similar to donepezil-treated rats. So, a high dose of BN treatment proved its neuroprotective potential in AlCl₃-induced neurotoxicity in rats. AlCl₃-treated rats showed decreased time spent in open arms and increased time spent in closed arms as compared to the normal rats. The donepezil-treated rats spent more time in the open arms and less time in the closed arms, which was opposite to that of AlCl₃-treated rats. The low dose of BN treatment showed a slight increase in the time spent in the open arm and a slight decrease in the time spent in the closed arm, while the medium and the high doses of BN treatment showed significantly increased time spent in the open arm and decreased time spent in the closed arm. The high dose of BN treatment showed similar results compared to the donepezil treatment. Overall, a high dose of BN treatment improved neurobehavioral parameters significantly (Fig. 6).

Fig. 6.

a Assessment of initial and retention latency utilizing the Elevated Plus Maze (EPM). Initial latency denotes the duration required for the subject to first enter the open arm during the initial trial, whereas retention latency reflects the time spent in the second trial to evaluate memory retention. and b Comparison of the duration spent in the open arms relative to the closed arms of the Elevated Plus Maze (EPM). Prolonged duration in the open arms signifies diminished anxiety-like behavior, whereas a preference for the closed arms denotes elevated anxiety, where, NC Normal Control, DC Disease Control, STD Standard treatment, BN-Low BN treatment at a low dose, BN-Med BN treatment at medium dose, BN-High BN treatment at a high dose, ITL Initial transfer latency, RTL Retention transfer latency, OA Time spent in open arm, and CA Time spent in closed arm. All the data are presented in mean ± SEM

Conditioned avoidance test

Word.

Estimation of acetylcholinesterase (AChE) levels

Combination treatment of BN showed a dose-dependent reduction in AChE levels, which proves its neuroprotective potential by improving direct AChE levels in brain tissue as compared to disease control (Fig. 7). Donepezil-treated rats reduced AChE levels significantly as compared to only AlCl₃-treated rats. The AChE level of a high dose of BN was found to be similar to that of donepezil treatment (Fig. 8).

Fig. 7.

a Measurement of initial and retention latency in a conditioned avoidance task and b Comparison of time spent in the light chamber versus the dark chamber, NC Normal Control, DC Disease Control, STD Standard treatment, BN-Low BN treatment at a low dose, BN-Med BN treatment at medium dose, BN-High BN treatment at a high dose, IL Initial latency, RL Retention latency, TL Time spent in light chamber, and TD Time spent in dark chamber. All the data are presented in mean ± SEM

Fig. 8.

The acetylcholine esterase (AchE) levels in rat brain. The effect of distinct therapies on the AchE levels (nM/gm of tissue) across different groups. NC Normal Control, DC Disease Control, STD Standard treatment, BN-Low BN treatment at a low dose, BN-Med BN treatment at medium dose, BN-High BN treatment at a high dose. The following indicate statistical significance: *p < 0.05 vs. NC; #p < 0.05 vs. DC; (single filled circle)p < 0.05 vs. STD; ⋆p < 0.05 vs. DC. All the data are presented in mean ± SEM

Measurement of antioxidants in rat brain homogenate

The MDA level in the normal control group was low. MDA levels were increased in the AlCl₃-treated rats. Combination therapy of BN showed a significant reduction in MDA levels dose-dependently, indicating plants’ anti-oxidant properties. Standard therapy, donepezil, lowered MDA levels as compared to AlCl₃-treated rats. High doses of extract exhibited an impressively positive effect as compared to donepezil treatment. In the current investigation, SOD levels were low in disease group animals due to oxidative stress. In normal rats, SOD level was high. Standard treatment with donepezil increases the level of SOD which is almost similar to the normal group. Combination treatment of BN showed a significant increment in SOD level, which shows a reduction in oxidative stress due to treatment. High doses of extract showed similar levels of SOD as the standard treatment. The catalase levels were low in disease group animals due to oxidative stress. In normal rats, the catalase level was high. The standard treatment donepezil increased the level catalase which is almost similar to normal group. Combination treatment of BN showed a significant increment in catalase level, which shows reduce in oxidative stress due to treatment. High doses of extract showed similar levels of catalase as the standard treatment. The GSH levels were low in the disease group animals due to oxidative stress. In normal rats, GSH level was high. Standard treatment with donepezil increased the levels of GSH, which was similar to the normal group. Combination treatment of BN showed a significant increase in GSH level, which shows reduce in oxidative stress due to treatment. High doses showed almost similar levels to the standard treatment (Fig. 9).

Fig. 9.

Oxidative stress and anti-oxidant levels measured in rat brain homogenate (a) Malondialdehyde (MDA), (b) Superoxide dismutase (SOD), (c) Catalase, and (d) Glutathione (GSH). The differences among the means of each group were analyzed using one-way ANOVA followed by Turkey’s multiple comparison test for post hoc analysis. *p < 0.001 as compared to normal, #p < 0.001 as compared to DC, (single filled circle)p < 0.005, (double filled circle)p < 0.001 as compared to STD, and ⋆p < 0.001 as compared to BN-Low. All the data are presented in mean ± SEM

Estimation of BCL2 and CASP3

BCL2 is an anti-apoptotic marker. The results displayed the BCL2 levels were significantly reduced in AlCl₃-treated rats as compared to normal rats. Here BN treatment showed significant improvement in BCL2 levels in the rat brain dose-dependently as compared to AlCl₃-treated rats. Donepezil significantly improved BCL2 level as compared to AlCl₃ treatment. Caspase-3 plays an important role in apoptosis. The results displayed that caspase-3 levels were significantly increased in AlCl₃-treated rats as compared to normal rats. Here, BN treatment showed a highly significant reduction in caspase-3 levels in the rat brain dose-dependently as compared to AlCl₃-treated rats. Donepezil also significantly reduced caspase-3 level as compared to AlCl₃ treatment (Fig. 10).

Fig. 10.

Effect of different treatments on (a) BCL2 and (b) CASP3 levels in rat brain in experimental groups. The differences among the means of each group were analyzed using one-way ANOVA followed by Turkey’s multiple comparison test for post hoc analysis. *p < 0.001 as compared to normal, #p < 0.001 as compared to DC, (single filled circle)p < 0.001 as compared to STD, and ⋆p < 0.001 as compared to BN-Low. All the data are presented in mean ± SEM

Histopathology of rat brain

The figure demonstrated the neurotoxic impact of AlCl₃ in the histopathology of rat brains with significant neuronal cell loss, glial cell scattering, and evidence of edema with inflammation in the cerebral cortex. The BN treatment showed significant reversal (dose-dependently) in neuronal cell loss, glial scattering, and improvement in edema in the cerebral cortex as compared to AlCl₃-treated rat brain histopathology. Donepezil treatment showed significant improvement in neuronal cell loss, glial scattering, and edema in the cerebral cortex as compared to the AlCl₃ treatment alone. The histopathological features of a high dose of BN treatment showed similar changes as that of donepezil (Fig. 11).

Fig. 11.

The histopathological analysis of rat brain at 20 × for (a) Normal control, (b) AlCl3-treated Disease control, (c) Standard (donepezil) treatment (d) BN-Low, (e) BN-Medium and (f) BN-High dose levels

Discussion

Network pharmacology (NP) has emerged as a valuable tool for elucidating complex therapeutic mechanisms and identifying potential drug candidates (Wu et al. 2018). By analyzing drug–target interactions and biological pathways, NP aids in the discovery of novel therapeutic agents, especially from natural sources (Patil et al. 2022; Yuan et al. 2017). Phytoconstituents from medicinal plants offer promising candidates for AD therapy, with experimental evidence supporting their neuroprotective effects (Açar et al. 2023, Şahin et al. 2023). The network analysis revealed oleic acid, myristic acid, and palmitic acid to possess the highest degree which indicates these phytoconstituents to be majorly involved against AD. Further, molecular docking with the hub proteins and phytoconstituents displayed stable complex with a better binding affinity than the respective standards, this indicates the stability of the complexes.

Aluminum (Al) is a potent cholinotoxin that has the potential to disrupt the BBB and cause changes in cholinergic transmission. Al’s capacity for neurotoxin production significantly boosts AChE activity (Zatta et al. 2002). Al is a strong neurotoxin, and its accumulation in the brain tissues is linked to dementia and cognitive decline. Al also interferes with cholinergic neurotransmission, which enhances the activity of AChE and increases the breakdown of acetylcholine in the brain (Lin et al. 2015). According to reports, Al can react with the AChE’s peripheral sites, alter its secondary structure, and ultimately increase its activity (Kakkar and Kaur 2011). AChE inhibition is a crucially advantageous approach in the treatment of AD. AChE inhibitors increase acetylcholine availability by preventing its breakdown, which aids in treating AD symptoms by improving cholinergic transmission in the brain (Wilkinson et al. 2004; Scheltens et al. 2016). This study displayed that the level of AChE was significantly raised in AlCl₃-treated rats. The standard drug donepezil belongs to the class of acetylcholinesterase inhibitors, which decreased the level of AChE in AlCl₃-induced rats. Our treatment with a plant combination of Bergenia ligulata and Nelumbo nucifera significantly reduced the level of AChE. The high dose of this treatment showed a remarkable effect on the AChE level. It is known that acetylcholinesterase levels are inversely proportional to acetylcholine, resulting in increased acetylcholine in the brain by our test agent which will ultimately improve the learning and memory as part of cognition. Hence, this indicates the neuroprotective potential of BN treatment in AlCl₃-induced neurotoxicity targeting cholinergic hypothesis in AD. A study conducted on Sprague Dawley with AlCl₃ induction displayed a significant increase in the AChE levels; a similar trend has been observed in the present study (Liu et al. 2020). A study reported that induction with AlCl₃ increased the AChE levels, which were further reversed by treatment with onion, indicating improved neuroprotection (Chen et al. 2021). A similar study on Wistar rats reported the reversal of AlCl₃-induced increase in AChE levels upon treatment with syringic acid (Zhao et al. 2020). Recent studies have shown that bioactives, such as indole-3 carbinol and diindolylmethane, effectively mitigate β-amyloid-induced neurotoxicity and inhibit AChE activity, supporting the therapeutic potential of natural compounds in AD (Ramakrishna et al. 2024). In one study, molecular docking of the phytoconstituents with AChE revealed a better interaction of multiple bioactive compared to the standard donepezil; this aligns with the results obtained via quantification of AChE via ELISA. One such study where inhibitors targeting AChE with additional anti-oxidant properties, such as biphenyl-3-oxo-1,2,4-triazine derivatives, have been shown to enhance learning and memory, reinforcing the therapeutic potential of multifunctional compounds in AD (Tripathi et al. 2019).

As a member of the apoptosis regulator protein family known as BCL2, it is crucial for controlling cell death in both pathological and normal circumstances. The intrinsic route depends on the equilibrium of pro- and anti-apoptotic BCL2 family signals. These family proteins have anti-apoptotic properties and support cell survival via BCL2 (Callens et al. 2021). In the current investigation, combination treatment with BN decreased BCL2 activity in the brain and proved its anti-apoptotic activity. Similarly, the docking of identified phytoconstituents with BCL2 possessed similar binding affinity as of the standards paclitaxel and donepezil. The molecular docking results mimic the results observed in BCL2 quantification. The change in BCL2 activity in the brain is a sign that apoptosis is progressing, which results in Al-induced oxidative cellular stress (Shanesazzade et al. 2018). Additionally, after AlCl₃ treatment, it has increased cytochrome c and Apaf-1 activity, which indicates that mitochondrial-mediated apoptosis was involved, which is linked with AlCl₃-associated reactive oxygen species to form and calcium ions to build up, which releases cytochrome c from the mitochondria and into the cytoplasm; there, it binds to Apaf-1, a different cytoplasmic factor, which when combined with dATP forms an oligomeric apoptosome complex (Alsharif et al. 2023). In the current study, it was seen that the level of BCL2 was reduced in Al-treated rat brain homogenate. The donepezil-treated rats showed an increase in the level of BCL2 compared with the disease control group. The combination treatment showed a rise in the level of BCL2 as compared to disease control rats dose-dependently. The high dose of combination treatment increased BCL2 significantly as compared to the other treatments. With BN treatment, the incremental level of BCL2 proved its role in reducing the rate of apoptosis. A study conducted by Samuel Bolaji Mesole et al. (2020) reported that aluminum chloride causes a reduction in the level of BCL2 in Wistar rats, which supports our study (Mesole et al. 2020). In the apoptotic cascade, activated caspase-3 executes cell apoptosis and is regarded as a key signal throughout the neurodegenerative process. According to several studies, treatment with Al causes a noticeably higher level of active caspase-3 protein production (Chen et al. 2020). Recently, it has been hypothesized that the activation of caspase-3 is crucial for synaptic plasticity. Caspase-3 activation appears to be engaged in numerous regulatory processes, spanning from natural neuronal death to non-apoptotic activities. Studies have reported that Al-exposed animal models might avoid neurodegeneration and cognitive impairment by specifically knocking down the caspase-3 gene using RNA interference (RNAi) (Park et al. 2020). The results of the present investigation showed that the disease group receiving AlCl₃ treatment had elevated caspase-3 levels; treatment reduced the level of caspase-3 in AlCl₃-induced neurotoxicity. Compared to the disease control group, the therapy of BN-treated groups showed a significant reduction in Caspase-3 levels. In comparison to the other groups, the high dosage of BN treatment had a significant effect on Caspase-3 levels as compared to disease control rats. The BN treatment lowered caspase-3 levels dose-dependently, which reduced the rate of apoptosis in rat brains; this proves BN treatment to be neuroprotective. The molecular docking with caspase-3 revealed the phytoconstituents possess significantly stable interaction as compared to the standard. Aluminum poisoning causes oxidative damage and disrupts the brain’s anti-oxidant defense mechanism, leading to neuronal impairment (Parekh et al. 2013). Endogenous antioxidants are formed by living cells and act as a buffer for accumulated free radicals and a line of defense against oxidative damage. CAT and GSH are the two most prevalent endogenous antioxidants. When there are more free radicals present, the cells neutralize them by creating antioxidants; this is known as oxidative stress (MA 2013). MDA levels are critical biomarkers of oxidative stress as ROS damages and degrades membranes; MDA builds up through lipid peroxidation (Busch and Binder 2017). Al accelerates the LPO and raises the formation of free radicals, which ultimately leads to oxidative stress with neurotoxicity. Free radical levels that are too high and anti-oxidant status that is too low put the brain at risk for oxidative stress and brain toxicity. In the present investigation, it was shown that AlCl₃ decreased the level of SOD, GSH, and catalase and raised the level of MDA, which represented the rise in oxidative stress in rat brains. The combination treatment showed a significant effect on oxidative stress levels. The treatment improved the level of SOD, GSH, and catalase and reduced the level of MDA. In recent study where, integration of AChE inhibition with anti-oxidant properties has been demonstrated in phenyl benzoxazole derivatives, highlighting the importance of dual-function therapeutic agents in AD management (Srivastava et al. 2019), may align with our results.

The histopathology of brain tissue was developed in all the groups. Rats’ brains from the AlCl₃-treated group exhibited considerable neuronal cell loss, glial scarring, and signs of continuing inflammation. The brain tissue of the low dose of BN treatment observed slight improvement in the cerebral cortex region. However, large doses and medium doses of BN efficiently reversed brain tissue damage in the cerebral cortex to a degree that was comparable to the normal and donepezil-treated rat. So, this suggests that a high-dose combination treatment showed remarkable neuroprotection in rat cerebral cortex and hippocampus histopathology by reversing neuronal cell loss and glial scattering. However, pathways and proteins identified need to be assessed via more rigid protocols to define the exact mechanism by which BN combination ameliorates AD; this is the future scope of this study.

Conclusion

The current study concludes that the combination of Bergenia ligulata and Nelumbo nucifera (BN) possesses neuroprotective potential. AlCl₃-induced neurotoxicity clearly developed symptoms associated with the rat model of AD. AlCl₃ decreased the level of acetylcholine, induced oxidative stress, and increased apoptosis in the rat brain, which lead to neuronal cell damage and death. The combination treatment of BN showed a potential neuroprotective effect in brain tissue by inhibiting caspase-3 activation and increasing BCL2 levels. It increased the level of acetylcholine by inhibiting AChE and proved its role in the cholinergic hypothesis of AD pathogenesis. BN treatment also reduced oxidative stress levels by improving the levels of GSH, SOD, and catalase and decreasing the level of MDA. Histopathology of the hypothalamus and the cerebral cortex clearly revealed neuroprotection in various regions of the rat brain by the BN combination and reversed AlCl₃-induced damage. The integration of network pharmacology, molecular docking, and in vivo studies represented an innovative approach to exploring the therapeutic potential of BN in AD. The current study proved that the neuroprotective and synergistic effects of BN were therapeutically significant in the AlCl₃-induced AD model. By leveraging computational and experimental techniques, this study provides novel insights into the therapeutic mechanisms of Bergenia ligulata and Nelumbo nucifera in AD. BL and NN hold promise as an adjunct therapy for AD. However, challenges include formulation optimization, bioavailability enhancement, and regulatory approvals for clinical use.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

2D

2-Dimensional

3D

3-Dimensional

AChE

Acetylcholinesterase

AD

Alzheimer’s disease

BL

Bergenia ligulata

BN

Bergenia ligulata & Nelumbo nucifera

BP

Biological Process

CAT

Conditioned Avoidance Test

CC

Cellular component

CCSEA

Committee for Control and Supervision of Experiments on Animals

ChEBI

Chemical Entities of Biological Interest

DTNB

5,5′-Dithiobis-(2-nitrobenzoic acid

EDTA

Ethylenediaminetetraacetic acid

ELISA

Enzyme-linked immunosorbent assay

EPM

Elevated plus maze

GO

Gene Ontology

GSH

Glutathione

HRP

Horseradish peroxidase

KEGG

Kyoto Encyclopedia of Genes and Genomes

MDA

Malondialdehyde

NBT

Nitroblue tetrazolium test

NN

Nelumbo nucifera

NP

Network pharmacology

MF

Molecular Function

RCSB

Research Collaboratory for Structural Bioinformatics

SOD

Superoxide Dismutase

TBA

Thiobarbituric acid

TCA

Trichloroacetic acid

TMB

3,3′,5,5′-Tetramethylbenzidine

TL

Transfer latency

Funding

This research received funding for research work from Ramanbhai Patel College of Pharmacy, Charotar University of Science and Technology, Changa, India.

Data availability statement

The data were presented in the manuscript along with supplementary data.

Declarations

Conflict of interest

There is no conflict of interests between authors.

Ethical statement

This work has been approved by the Institutional Animal Ethics Committee of the institute under the CCSEA guidelines, India with approval number RPCP/IAEC/2022-23/R2.