Gold chloride (HAuCl₄) was obtained from Sigma-Aldrich (St. Louis, MO, United States). Bakuchiol was procured from Cayman Chemical Company. DCFH-DA (2′,7′-dichlorodihydrofluorescein diacetate), and DAPI (4′,6-diamidino-2-phenylindole) were obtained from Sigma (St. Louis, MO, United States). Fetal bovine serum (FBS), Dulbecco’s modified Eagle’s medium (DMEM), 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyl tetrazolium bromide (MTT), Müeller Hinton (MH) broth, agar, and tryptone soy broth (TSB) were obtained from HiMedia (Mumbai, India). All other solvents and chemicals used were of analytical grade and were purchased from HiMedia Limited (Mumbai, Maharashtra, India).

Information derived from protein-protein interaction (PPI) networks is indispensable for understanding cellular functions and biological processes. Numerous studies have demonstrated that proteins in close proximity to one another in a constructed PPI network frequently exhibit shared characteristics (Lee et al., 2004; Wurmbach et al., 2007; Wu et al., 2009). It can be deduced from numerous investigations that proteins within the subnetwork linking genes are likely to exhibit similar biological functions (Ideker and Sharan, 2008; Miryala et al., 2018). The present study used the STRING database, a widely recognized online repository of protein interactions, to construct a PPI network that incorporated both direct (physical) and indirect (functional) associations (Table 1). To determine which nodes in a network are essential, topological characteristics are crucial. The primary goals of topological property analysis include biological network analysis, pharmacological activity mechanisms, and protein identification. The PPI network in the Cytoscape tool was used to determine the topological aspects of the network using a Network Analyzer (Supplementary Figure 1). Network Analyzer using the Simple Interaction Format (.sif) in Cytoscape. The top five weighted genes (CD44, EPHA3, EFGR, PTGER3, and TP53) are shown in Table 1. One technique for identifying objects that can efficiently send data across a network is closeness centrality (CC). An excellent way to find objects that can transport data across a network is through closeness centrality (CC). A node’s proximity centrality determines the average distance between nodes. Our selection of the top five nearby genes for each protein was based on the criterion of high closeness scores, which indicates greater proximity to one another than to any other node in the network (Supplementary Figure 1). Network Analyzer using the Simple Interaction Format (.sif) in Cytoscape. The top five weighted genes (CD44, EPHA3, EFGR, PTGER3, and TP53).

Molecular docking was performed to identify the best bakuchiol target. To validate the 25 shortlisted targets based on closeness centrality, the optimal target proteins were identified using AutoDock Vina 4.1. There are nine distinct docked postures for protein-ligand complexes produced by the versatile molecular docking tool AutoDock Vina (Trott and Olson, 2010). The initial posture with the highest binding affinity for each protein was selected from nine stances. After the docking process was completed, the best target proteins were selected based on their binding affinities. A more thorough revision docking procedure was performed for the best suited proteins. To determine the protein that would work best for bakuchiol in targeting lung cancer, a molecular docking study was conducted. Based on the docking data, GNAI3 had the highest binding energy of −7.5 kcal/mol. In contrast, PTGER3 had the second-highest binding energy of −6.9 kcal/mol, indicating that GNAI3 is the best target protein for bakuchiol Table 2 (Supplementary Tables 1–5).

The present study aimed to explore the expression of GNAI3 and PTGER3 genes through the utilization of gene chip data in a TNM plot analyzer. Our findings, derived from extensive analysis, indicated that these genes were prominently expressed in lung tissue, with p-values of 2.21e-04 and 9.71e-16. Subsequently, we carried out a comparative analysis of these genes in normal, tumor, and metastatic tissues, which indicated a substantial decrease in their expression in metastatic tissues compared with that in tumor tissues. The p-values for these genes were 8.34e-04 and 4.51e-16, respectively (Supplementary Figure 7).

In this study, Bakuchiol GNPs were synthesized using a biologically mediated method, with bakuchiol serving as both reducing and capping agent. Gold nanoparticles (GNPs) exhibit a characteristic reddish hue when suspended in aqueous solutions, which results from the excitation of surface plasmon vibrations (Wang et al., 2009). GNPs formation was confirmed through a color transformation from white to pink after approximately 24 h of incubation.

The antibacterial effectiveness of a nanomaterial primarily relies on two key factors: the size of its particles and alterations made to its surface. Smaller particles exhibit heightened biological and chemical activities owing to their larger surface areas relative to their volumes. This increased surface area enhances the interaction between nanoparticles (NPs) and microorganisms, amplifying their efficacy (Brayner et al., 2006; Muthukumar et al., 2016). Bak-GNPs exhibit robust antibacterial activity against both Gram-positive and Gram-negative pathogenic bacterial strains.

The synthesized Bak-GNPs, pure bakuchiol (Bak), and negative control (PBS) were added to the wells of MH agar plates. The experiments were conducted in triplicate and the agar plates were incubated overnight at 37°C. The diameter of the inhibitory zone was determined (Figure 2). In the following experiment, it was noted that pure bakuchiol (Bak) and Bak-GNPs diffused into the agar and strongly suppressed bacterial growth (Table 3).

The minimum inhibitory concentration (MIC₅₀) values for pure bakuchiol and bak-GNPs against Escherichia coli, Klebsiella pneumoniae, Bacillus subtilis, and Staphylococcus aureus were quantified. Notably, Bak-GNPs displayed superior antibacterial efficacy, with lower MIC₅₀ values than those of pure bakuchiol. Specifically, MIC₅₀ values were determined as follows: 5.47 μg/mL (Bak-GNPs) vs. 9.93 μg/mL (Bak) for Escherichia coli; 8.94 μg/mL (Bak-GNPs) vs. 11.40 μg/mL (Bak) for Klebsiella pneumoniae; 6.11 μg/mL (Bak-GNPs) vs. 10.59 μg/mL (Bak) for Bacillus subtilis; and 7.51 μg/mL (Bak-GNPs) vs. 12.12 μg/mL (Bak) for Staphylococcus aureus (Figure 3). These results highlight the enhanced antibacterial potential of the Bak-GNPs (Khan et al., 2015). Escherichia coli and Bacillus subtilis exhibited superior antibacterial effects among the tested bacterial strains compared with the other two strains. Bak-GNPs demonstrated heightened effectiveness against bacteria at the lowest nanoparticle concentration. The variations in antibacterial performance observed across different bacterial species can be attributed to disparities in their cell wall compositions. According to a study by Kim et al. (2007), the interaction between bacteria and metallic GNPs involves binding to active sites on the cell membrane, thereby hindering cell cycle functions (Muthukumar et al., 2016). The antibacterial activity of Bak-GNPs demonstrated in our study offers a promising potential for the development of new antimicrobial agents. The efficacy of Bak-GNPs against various bacterial strains suggests that they could be utilized in designing novel antibacterial treatments, particularly for combating resistant strains that are not effectively addressed by current antibiotics. This aspect of our study could have significant implications for public health and the development of advanced therapeutic strategies.

This study investigated the anticancer potential of Bak-GNPs compared to that of pure Bak in lung (A549) and liver (HepG2) cancer cells. The results revealed that Bak-GNPs exhibited significantly greater anticancer activity than pure Bak. The inhibitory effect on cell growth increased with higher concentrations of Bak-GNPs and pure Bak. The IC₅₀ values for Bak-GNPs and pure Bak on lung cancer cells were 11.19 and 23.80 μg/mL and liver cancer were 6.6 μg/mL and 18.62 μg/mL respectively, as shown in Figures 4A, B. This suggests that Bak-GNPs are more potent in inhibiting the viability of A549 and HepG2 cells.

To assess the effects of Bak-GNPs on A549 and HepG2 cells, various concentrations of Bak-GNPs were used. The viability of A549 cells declined rapidly within the concentration range of 1.56–100 μg/mL, ultimately resulting in an IC₅₀ value of 11.19 μg/mL. The high selectivity of GNPs for cancer cells, as opposed to normal cells, highlights their potential as targeted therapeutic agents (Soliman et al., 2020). The effect of various concentrations of Bak-GNPs on the A549 lung carcinoma cell line and human primary osteoblast cells was evaluated using the MTT assay. The IC₅₀ values of the synthesized Bak-GNPs was determined for lung cancer cells to be 11.19 μg/mL and for liver cancer cell to be 11.19 μg/mL. Consequently, a concentration of 6.6 μg/mL was chosen for subsequent experiments. Notably, no signs of toxicity were observed in human primary osteoblasts (Zhang et al., 2019).

Morphological changes in A549 and HepG2 Cells were examined after treatment with Bak-GNPs and Bak, respectively, at their respective IC₅₀ concentrations. Control cells remained largely unchanged, whereas treated cells displayed detachment from the well surface, with some retaining intact plasma membranes, indicating the initiation of apoptosis. Pure Bak-treated cells exhibited signs of apoptosis but at significantly higher concentrations than those required for Bak-GNPs to induce apoptosis in lung cancer cells (Figure 5). This suggests that Bak-GNPs may induce apoptosis more effectively than pure Bak at lower concentrations.

ROS generation in A549 and HepG2 cells was assessed using DCFH-DA as the marker. Bak-GNP-treated A549 cells HepG2 Cells exhibited higher fluorescence levels than those in the control group, indicating increased ROS production. Pure Bak-treated cells also showed intense fluorescence; however, Bak-GNP-treated cells displayed even more intense fluorescence and disrupted morphological structures. This suggests that Bak-GNPs may induce oxidative stress and apoptosis through excessive generation of ROS, potentially contributing to their anticancer effects (Figure 6).

To investigate the internalization of Bak-GNPs and their interaction with nuclear material, we used the fluorescent dye 4′, 6-diamidino-2-phenylindole (DAPI). A549 and HepG2 cancer cells were incubated for 48 h at 37°C, during which time they were exposed to Bak-GNPs at the IC₅₀. The cells were stained with DAPI. Our microscopic analysis revealed striking differences in the nuclear morphology of A549 and HepG2 cells treated with Bak-GNPs compared with untreated cells. Notably, Bak-GNP-treated cells exhibited robust apoptotic effects, which were characterized by densely compacted chromatin and nuclei displaying consolidated dark blue fluorescence. This observation indicates significant changes in the structure and condensation of chromatin within the nucleus. The observed alterations in nuclear morphology and chromatin condensation suggested that Bak-GNPs may induce apoptosis in A549 cells. One possible mechanism for this apoptotic effect is an increase in cell membrane permeability (Iram et al., 2019). This may have allowed Bak-GNPs to enter the cells more effectively and interact with their nuclear material, ultimately leading to apoptosis. Such changes in membrane permeability can disrupt normal cell function and trigger programmed cell death (Figure 7).

To substantiate our findings, we conducted experiments in triplicates to ensure the reliability of our results. In summary, our investigation of the internalization of Bak-GNPs and their subsequent interaction with nuclear material, using DAPI staining, revealed substantial apoptotic effects in A549 and HepG2 cells. These effects are characterized by distinct changes in nuclear morphology, such as chromatin condensation, and are likely facilitated by an increase in cell membrane permeability (Syed et al., 2023).

Despite significant advances in cancer treatment, cancer management remains a formidable challenge. Although important milestones have been achieved in cancer therapy, the survival rate of patients with lung cancer remains disappointingly low. Patients with lung cancer are typically treated with cisplatin and other chemotherapeutic agents. However, these treatments resulted in a survival rate of approximately 20%–26% (Klastersky et al., 1989). Therefore, there is a pressing need to find an effective medication with minimal or no side effects for treating lung cancer. Nanomedicine represents a promising approach for cancer treatment (Peer et al., 2020). However, the conventional chemical synthesis of nanoparticles results in the production of toxic compounds, which can further exacerbate the condition of cancer patients. Consequently, in this study, we opted for a biological method to synthesize gold nanoparticles using bakuchiol, isolated from the seed of the Chinese tree Psoralea corylifolia. The cytotoxic effect of gold nanoparticles stems from their active physicochemical interactions with the functional groups of intracellular proteins, nitrogen bases, and phosphate groups within DNA. In a previous study by Sangiliyandi (2010) highlighted that nanoparticles with anticancer properties can inhibit the activities of abnormally expressed signaling proteins, such as Akt and Ras. Additionally, they can affect cytokine-based therapies, DNA- or protein-based vaccines targeting specific tumor markers, and tyrosine kinase inhibitors, all of which consistently demonstrate antitumor effects (Martins et al., 2010). This study observed anticancer activity, where the synthesized gold nanoparticles showed dose-dependent inhibition of lung and liver cells. However, some approved chemotherapeutic agents have side effects and are expensive. Thus, there is a critical need to develop alternative medicines to treat this serious disease. The discovery of synthesized gold nanoparticles aims to meet the demand for new treatments. Our findings on the anticancer properties of Bak-GNPs reveal their potential as effective agents for cancer therapy. The observed cytotoxicity against cancer cell lines indicated that Bak-GNPs may be used to enhance targeted cancer treatment approaches, potentially leading to new therapies with improved specificity and reduced side effects compared to conventional treatments.