Computational examination to reveal Kaempferol as the most potent active compound from Euphorbia hirta against breast cancer by targeting AKT1 and ERα

ABSTRACT

Breast cancer belongs to diseases with the highest mortality rates. Euphorbia hirta is an herbal plant with various pharmacological properties and is predicted to have good anti-breast cancer properties. This current study analyzed a potent compound from E. hirta as an anti-breast cancer candidate and predicted its mechanism. The Bioactive compounds in E. hirta were screened for drug-likeness, toxicity, membrane permeability, and bioactivity. Protein target prediction utilized four databases, followed by functional annotation analysis. Molecular docking employed AutoDock Vina, and molecular dynamic simulation used Yet Another Scientific Artificial Reality Application with parameters reflecting human cell physiology. Kaempferol was the potent compound in E. hirta that passed the screening and was predicted to have better anti-breast cancer activity than that of other compounds. Kaempferol targets AKT1 and ERα, the proteins correlating with breast cancer progression. The molecular docking results showed that Kaempferol bound to inhibitor sites on both AKT1 and ERα. In addition, Molecular dynamic analysis showed that the interaction between Kaempferol with AKT1 and ERα was stable, as seen from the RMSD, RMSF, hydrogen bonding, and MM/PBSA binding energy values. Therefore, Kaempferol was a bioactive compound from E. hirta with promising anti-breast cancer activities by targeting the AKT1 and ERα.

KEYWORDS:

• AKT1
• anticancer
• Euphorbia hirta
• ERα
• Kaempferol

Introduction

Breast cancer ranks first in global cancer occurrence, with approximately 2.26 million documented cases annually, constituting 11.7% of the total reported cancer cases and 24.5% of cancers diagnosed in women [1]. In 2023, solely within the United States, it is estimated that there will be 1,958,310 new cancer cases and 609,820 cancer-related deaths [2]. It is estimated that one in eight women worldwide will be diagnosed with breast cancer [3]. The highest mortality rate is in low-income countries because it has various medical limitations [4]. Breast cancer occurs due to the dysregulation of pathways related to cell proliferation and cell survival [5].

The PI3K/Akt and Estrogen Receptor (ER) signaling pathways are commonly dysregulated in breast cancer cells [6,7]. The PI3K/Akt signaling pathway relates to the induction of proliferation and survival of tumor cells [8]. This pathway is activated when receptor tyrosine kinases, such as IGF1R, EGFR, HER2, and HER3, bind to their ligands. The activated RTK phosphorylates PI3K, then PI3K activates the AKT1 protein. AKT1 activates the signaling cascade, resulting in the expression of genes related to cell growth and proliferation [7]. In breast cancer, the PI3K/Akt pathway experiences overactivity due to the overexpression of proteins and mutations in the pathway [9]. Mutations in the AKT1 are frequently found in patients with breast cancer. This mutation causes AKT1 to be overactivated, upregulating the PI3K/Akt signaling pathway [10]. The ER signaling pathway also contributes to breast cancer progression. ERα and ERβ are involved in the ER signaling pathway, but only ERα plays a role in cancer cell progression. ERα is activated after binding to estrogen and then translocates to the nucleus to become a transcription factor for proliferation and metastasis-related genes [11]. In most breast cancer cases, ERα is overexpressed, thus triggering the proliferation and metastasis of tumor cells [12]. Inhibition of PI3K/Akt and ER signaling pathways is an accurate strategy to inhibit breast cancer progression.

Euphorbia hirta is an herb with a high potential for anti-breast cancer. E. hirta is a plant of the Euphorbiaceae family. It spread to several countries in Asia and Australia [13]. Previous research stated that crude extract of E. hirta has good anticancer activity in the lungs, liver, and leukemia through in vitro studies [14–16]. The activity of the E. hirta extract is influenced by the bioactive compounds contained therein. Previous studies have stated that Guava contains compounds with good pharmacological activity, such as rutin, quercetin, Kaempferol, etc [13]. However, no studies have revealed which compounds in E. hirta have the highest anticancer activity. Identifying which compounds in E. hirta have the best anti-breast cancer properties will be useful for drug development. In the present study, an in-silico study was performed to screen the bioactive compound of E. hirta that has the most potential as an anti-breast cancer with a predictable mechanism.

Method

Data mining of compounds contained in Euphorbia hirta

The compounds contained in E. hirta were retrieved from previous studies [17,18]. Canonical SMILES of compounds contained in E. hirta were obtained from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/).

Screening for drug-likeness, toxicity, membrane permeability, and bioactivity

Drug-likeness screening was conducted using the SWISS ADME web server (http://www.swissadme.ch/index.php) with the parameters used, namely Lipinski, Veber, and Egan [19]. Compounds passing the drug-likeness screening were followed by toxicity screening using the ProTox web server (https://tox-new.charite.de/protox_II/) to select nontoxic compounds for humans [20]. Membrane permeability screening was performed using the PerMM web server (https://permm.phar.umich.edu/) to select compounds that could easily pass through the lipid bilayer [21]. Compounds that passed the above screenings were continued for bioactivity screening using the PASS Online webserver (http://www.way2drug.com/passonline/) [22]. The parameters used were related to breast cancer progression.

Target protein determination

The direct protein targets of Kaempferol compounds were determined using the SWISS Target Prediction (http://www.swisstargetprediction.ch/), STITCH (http://stitch.embl.de/), and CTD (http://ctdbase.org) databases [23–25]. The selected target proteins were related to breast cancer progression according to the cBioportal database (https://www.cbioportal.org/). Indirect protein targets were determined using the STRING database (https://string-db.org/). Target protein visualization was performed using Cytoscape 3.7.2 software.

Functional annotation

Functional annotation was performed to group target proteins based on their role in the cell. Functional annotation analysis was performed using the DAVID web server (Database for Annotation, Visualization, and Integrated Discovery) (https://david.ncifcrf.gov/) [26]. The databases used were Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG pathway). GO would group proteins into three domains: Biological Process, Cellular Component, and Molecular Function. The KEGG pathway will classify target proteins based on their role in human cellular pathways.

Ligand preparation

The 3D structure of Kaempferol was obtained from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). The inhibitors for each protein were retrieved from the protein pdb file. All ligands were prepared by minimizing the conformational energy using the Open babel plugin integrated into the PyRx 8.0 software [27].

Protein preparation

The 3D structures of the AKT1 (PDB ID: 6hhf) and ERα (PDB ID: 3ert) proteins were obtained from the RCSB PDB database (https://www.rcsb.org/). The proteins were prepared by removing water molecules and contaminant ligands using the Biovia Discovery Studio 2019 software (Dassault Systèmes Biovia, San Diego, California, USA).

Molecular docking

Specific docking was performed on the active sites of AKT1 and ERα proteins using the AutoDock Vina tools integrated with PyRx 8.0 [28–30]. The grid coordinates for specific docking are in Table 1. The docking result with the lowest binding affinity value was selected. Docking results were visualized using the Discovery Studio Visualizer 2019 to analyze the binding pose and chemical interaction.

Table 1. Grid coordinate for specific docking.

				Grid coordinate (Å)
Protein	PDB ID	Active site	Ref.	Center	Dimention
Akt1	6hhf	Trp80, Ile84, Glu85, Leu210, Leu264, Lys268, Val270, Tyr272, Arg273, Asp292	[26]	X: 5.0233, Y: 5.3081 Z: 14.1707	X: 17.6221 Y: 22.8262 Z: 25.5946
ERa	3ert	Glu353, Leu387, Met388, Met343, Leu346, Thr347, Arg394, Asp351, Leu428, Ile424, Met421, Leu525	[27]	X: 30.3707, Y: 0.4633 Z: 27.7685	X: 26.889 Y: 18.3735 Z: 20.6289

Molecular dynamic simulation and binding energy evaluation

Molecular dynamics simulations were conducted using Yet Another Scientific Artificial Reality Application version 19.12.14 software with the AMBER14 force field [31]. Conditions in the system were regulated according to the human’s physiological conditions, such as temperature 310K, pH 7.4, salt content 0.9%, and pressure 1 bar. The simulation lasted for 100 ns with autosave every 25 ps. The Root-Mean-Square Deviation (RMSD) values and the number of protein hydrogen bonds were analyzed using the md_analyze macro program. The Root-Mean-Square-Fluctuation (RMSF) was analyzed using the md_analyzeres macro program. The binding free energy of the protein and ligand complexes was evaluated using the Molecular Mechanics Poisson – Boltzmann Surface Area (MM/PBSA) method with 0.65 kJ/mol/Ų surface tension and omitting the entropy term [32]. The binding free energy was calculated every 24 ps after equilibrium. The binding pose of the ligand was also evaluated every 20 ns after equilibrium.

Result

Screening based on drug-likeness, toxicity, membrane permeability, and bioactivity

This screening identified the compounds with the best anti-breast cancer activity. Drug-likeness screening showed that ten compounds had no violation in the Lipinski, Veber, and Egan parameters. Therefore, these ten compounds passed the drug-likeness selection (Figure 1a). The ten compounds underwent toxicity screening to identify nontoxic compounds for the human body. The screening results identified five nontoxic compounds for humans: epicatechin, chrysin, syringic acid, Kaempferol, and quercitol (Figure 1b). The five compounds continued to the selection based on membrane permeability. The results showed that all compounds could penetrate the plasma membrane (Figure 2a,b). The five compounds were continued for bioactivity screening. The results of the bioactivity screening showed that Kaempferol had a high Pa value for almost all bioactivity parameters (Figure 2c). Therefore, it is predicted that Kaempferol has the best anticancer activity in E. hirta. The two-dimensional structure of Kaempferol can be seen in Figure 2d.

Figure 1. Drug-likeness and toxicity screening. a) drug-likeness screening using Lipinski, Veber, and Egan rules. b) toxicity examination based on LD50 and the probability of inducing toxicity.

Figure 2. Screening of membrane permeability and bioactivity. a) simulation of the chrysin, epicatechin, Kaempferol, quercitol, and syringic acid penetrating the lipid bilayer. b) the energy transfer value of the six compounds penetrating the phospholipid membrane. c) bioactivity screening. d) the 2D structure of the Kaempferol.

Target protein prediction and functional annotation

Based on three databases, the direct targets of Kaempferol were ABCC1, AHR, CYP1B1, MMP2, ALOX12, ESR2, ESR1, CDK1, and AKT1 (Figure 3a). The nine proteins’ relation to patients’ breast cancer progression were analyzed using cBioportal. The analysis showed that AKT1 and ESR1(ERα) proteins were most altered in patients with breast cancer (Figure 3b). The proteins interacting with AKT1 and ERα can be seen in Figure 3c. Functional annotation analysis showed that all Kaempferol’s direct and indirect target proteins were involved in PI3K-Akt, FoXo, and JAK-STAT signaling pathways, including other pathways related to cancer cell growth. According to the GO database, the target proteins are involved in biological processes related to proliferation and cell survival (Figure 3d).

Figure 3. Prediction of protein targets and functional annotation. a) prediction of the direct target of the Kaempferol in the nine protein targets. b) analysis of target proteins with cBioportal found AKT1 and ERα proteins to be involved in breast cancer progression. c) proteins interacting with AKT1 and ERα proteins. d) functional annotation of target proteins.

Interaction between Kaempferol and AKT1 and ERα

Molecular docking results showed that Kaempferol bound to AKT1 and ERα at the same site as an inhibitor with a low binding affinity value. The interaction between Kaempferol and AKT1 resulted in a binding affinity value of −9.2 kcal/mol. Kaempferol bound to AKT1 by forming three hydrogen bonds and four hydrophobic interactions. The interaction of Kaempferol on AKT1 protein residues had similarities with the interaction of inhibitors with AKT1, namely Ser205, Trp80, Leu264, and Val270 (Figure 4a and Table 2). The interaction between Kaempferol and ERα had a binding affinity value of −8.2 kcal/mol. Kaempferol interacted with ERα by forming one hydrogen bond and seven hydrophobic interactions. Kaempferol bound to ERα at the same residue as inhibitors Leu387, Ile424, Met421, Leu346, Ala350, Leu387, Met388, and Leu525 (Figure 4b and Table 2). The docking results predicted that Kaempferol could be a competitive inhibitor of AKT1 and ERα proteins. Next, the stability of the interaction between Kaempferol and AKT1 and ERα was analyzed by MD simulation.

Figure 4. 3D and 2D visualization of protein-ligand interactions. a) interaction between AKT1-inhibitor and AKT1-Kaempferol. b) interaction between ERα-inhibitor and ERα-Kaempferol.

Table 2. Chemical interaction between Akt1 and ERα with the ligands.

Protein	Ligand	Binding Affinity (kcal/mol)	Position of Chemical interaction
			Hydrogen bond	Hyrophobic interaction
Akt1	Kaempferol	−9.2	Thr211, Ser205, Tyr263	Trp80, Leu210, Leu264, Val270
	Inhibitor	−13	Ser205, Cys296, Val271, Tyr272, Gly294	Val270, Trp80, Leu264, Lys268
ERα	Kaemferol	−8.2	Leu387	Ile424, Met421, Leu346, Ala350, Leu387, Met388, Leu525
	Inhibitor	−9.4	Thr347	Met388, Leu391, Met421, Ile424, Leu428, Leu346, Leu387, Leu391, Met421, Leu525, Ala350, Leu525

The underscore represents the same binding site with the inhibitor.

The stability of the interaction between Kaempferol and AKT1 and ERα

MD simulation was used to analyze the stability of protein structure and the stability of protein-ligand interactions. After interacting with Kaempferol, the RMSD backbone parameter analyzed the structural stability of the AKT1 and ERα proteins, the number of hydrogen bonds, and the RMSF value. The RMSD ligand movement and binding energy analyzed the stability of the interaction between AKT1 and ERα with Kaempferol. The simulation results showed that the RMSD backbone value of the AKT1-Kaempferol complex is below 3Å (Figure 5a). The number of AKT1 hydrogen bonds interacting with Kaempferol was similar to that of AKT1 interacting with inhibitors (Figure 5c). The RMSF values of AKT1 were also mostly below 3Å (Figure 5e). The simulation results indicate that the structure of AKT1 binding to Kaempferol is stable during the simulation. The RMSD ligand movement represents the movement of the ligand during the simulation. The simulation showed that the RMSD ligand movement value at 60–100 ns had minimal fluctuations (Figure 5b). This indicated stable Kaempferol binding to AKT1 from the 60th ns. The MM/PBSA binding energy represents the stability of protein-ligand interactions. The AKT1-Kaempferol complex had a low binding energy value (Table 3) and was stable until the end of the simulation (Figure 5d). This showed that the AKT1-Kaempferol interaction was stable for 100 ns.

Figure 5. Simulation of the molecular dynamics of the interaction between AKT1 and the ligand. a) RMSD backbone proteins. b) RMSD ligand movement. c) number of hydrogen bonds of the AKT1 protein. d) MM/PBSA binding energy values of the AKT1-inhibitor and AKT1-Kaempferol complexes. e) RMSF values of AKT1-inhibitor and AKT1-Kaempferol complexes.

Table 3. Calculations on the binding free energy of the complexes.

Protein	Ligand	Δ Energy (kJ/mol)
		Binding	Potential Receptor	Solvation Receptor	Potential Ligand	Solvation Ligand	Potential Complex	Solvation Complex
AKT1	Inhibitor	−236.969 ± 158.563	−289.755 ± 25.228	−43.627 ± 10.917	−21459.801 ± 687.185	−29111.451 ± 764.751	−22097.040 ± 701.134	−29044.563 ± 765.081
	Kaempferol	−137.111 ± 241.042	−334.324 ± 17.902	−177.556 ± 14.526	−20898.934 ± 577.465	−29637.799 ± 677.017	−21372.924 ± 575.333	−29812.799 ± 645.086
ERα	Inhibitor	−43.102 ± 56.472	265.604 ± 24.024	−214.935 ± 24.072	−10799.681 ± 474.933	−18691.253 ± 696.206	−11060.442 ± 492.295	−18422.924 ± 710.610
	Kaempferol	−26.539 ± 30.234	−345.145 ± 15.204	−224.433 ± 20.488	−10771.844 ± 477.166	−18780.577 ± 671.473	−11380.812 ± 478.393	−18714.648 ± 670.126

The values were presented in mean ± standard deviation.

The simulation results on the ERα-Kaempferol complex also showed good stability. The RMSD backbone value was below 3Å and had minimal fluctuation (Figure 6a). The number of hydrogen bonds in the ERα-Kaempferol complex was similar to that of the ERα-inhibitor (Figure 6c). The RMSF values were also mostly below 3Å, indicating that most of the amino acids moved slightly during the simulation (Figure 6e). The RMSD value of the ligand movement of the ERα complex had minimal fluctuations from 4 ns until the end of the simulation (Figure 6b). The ERα-Kaempferol complex had a more stable MM/PBSA binding energy than the ERα-inhibitor complex (Figure 6d). The simulation results showed that the interaction between ERα and Kaempferol is stable.

Figure 6. Simulation of the molecular dynamics of the interaction between ERα and ligands. a) RMSD backbone proteins. b) RMSD ligand movement. c) number of hydrogen bonds of the Akt1 protein. d) MM/PBSA binding energy value of ERα-inhibitor and ERα-Kaempferol complexes. e) RMSF values of ERα-inhibitor and ERα-Kaempferol complexes.

Changes of Kaempferol binding pose seen from hydrogen bond position

MD simulation also analyzed the position of Kaempferol’s hydrogen bonds in proteins. During the simulation, there was a change in the position of the hydrogen bond in the interaction between Kaempferol and AKT1. At 0 ns, Kaempferol formed three hydrogen bonds with Thr211, Ser205, and Thr263. At the 25th, 50, 70, and 100 ns times, the positions of the hydrogen bonds were alternated. At 50 ns, Kaempferol did not form hydrogen bonds with AKT1, resulting in a high binding energy value. At 75 and 100 ns, Kaempferol formed hydrogen bonds with Lys268 again (Figure 7a). Changes in hydrogen bond positions also occurred in Kaempferol and Erα interactions. At 0 ns, Kaempferol only formed hydrogen bonds with Leu387. At 5 to 100 ns, Kaempferol formed more hydrogen bonds, namely in Glu419 and Glu353, so the binding energy value was stable (Figure 7b).

Figure 7. Changes in the pose of Kaempferol during the simulation change the number and position of hydrogen bonds. a) AKT1-Kaempferol, b) ERα-Kaempferol.

Discussion

E. hirta contains pharmacologically important bioactive compounds. This study will predict only which candidate compounds had the highest anti-breast cancer potential. The bioactive compounds from E. hirta were screened with drug-likeness parameters, toxicity, membrane permeability, and bioactivity to obtain compounds with the most potent anti-breast cancer activity. The screening results showed that the compound in E. hirta with the most potential as an anticancer agent was Kaempferol.

Kaempferol (3,5,7-trihydroxy-2-(4′-hydroxyphenyl)-4 H-chrome-4-one; Figure 1d) is a flavonoid with high antioxidant activity [33]. Kaempferol has a 3-OH in the aromatic ring and a 5,7-dihydroxy group in ring A. It has relatively large three-ring planar and hydrophobic aromatic systems and a double bond between C2–C3 in ring C. This structure allows Kaempferol to have a high affinity for the lipid bilayer [34]. The structure of Kaempferol has two intramolecular hydrogen bonds, which add to the stability of the structure. Kaempferol has a high polarity, allowing it to bind strongly to proteins [35]. The structure of Kaempferol causes the compound to have various pharmacological activities. Kaempferol can significantly inhibit Nitric Oxide (NO) production and tumor necrosis factor-alpha (TNF-α) expression in LPS-stimulated RAW cells [36]. Kaempferol also has high antiproliferative activity in HepG2, CT26, and B16F1 cells and can inhibit NO release [37]. This compound can inhibit the PI3K/Akt pathway in liver and lung cancer [38]. This study states that Kaempferol has a high potential as an AKT1 and ERα inhibitor.

Kaempferol is predicted to have good anticancer activity. The drug-likeness analysis stated that Kaempferol had no violation in the Lipinski, Veber, and Egan parameters. Compounds passing the drug-likeness analysis have drug-like characteristics: Dissolve easily in the blood, penetrate cell membranes, and are easily metabolized and transported [39]. Kaempferol is also nontoxic to humans, as seen from the results of the toxicity analysis using ProTox. ProTox II uses the QSAR principle in analyzing the test compounds’ toxicity, so it can be said that the Kaempferol does not have a structural resemblance to the toxic compounds found previously [20]. Kaempferol can also penetrate the plasma membrane easily based on membrane permeability analysis with perMM (Figure 1a,b). The permeability of the membrane of a compound is affected by the transfer of energy. Energy transfer is the energy required to pass through the plasma membrane; the energy transfer value will change according to the position of the compound in the lipid bilayer [21]. Hydrophobic molecules have the highest energy transfer values in the middle and lowest of the ends of the lipid bilayer. Hydrophobic molecules have the lowest energy transfer in the middle and the highest at the edges [40]. In addition, based on the PASS Online bioactivity analysis, Kaempferol has good anti-breast cancer activity. PASS Online predicts the bioactivity of a query compound with the QSAR principle with a minimum Pa (Probable to be active) value of more than 0.3, which means it has a certain bioactivity. High values of Pa mean a high possibility of certain bioactivity of a compound [22].

Kaempferol could stably bind to AKT1 and ERα proteins based on molecular docking and dynamics. Kaempferol binds to AKT1 and ERα at the inhibitor site and has a low binding affinity value. A low binding affinity value leads to a strong interaction between the protein and the ligand [41]. Kaempferol also forms hydrogen bonds, which help stabilize interactions [42]. The AKT1 and ERα protein structures were still stable after interacting with Kaempferol, as indicated by the RMSD backbone value, the number of hydrogen bonds, and RMSF. RMSD backbone calculates the average displacement of each atom in the protein backbone during the simulation. The protein structure is stable if the backbone RMSD value is below 3 Å [43]. The number of hydrogen bonds greatly influences the stability of the protein structure because hydrogen bonds form the secondary structure of the protein [44]. In more detail, the stability of protein structure can be seen through RMSF.

RMSF calculates the fluctuation of each amino acid in a protein. If most amino acids have RMSF values below 3 Å, then the protein structure is stable [45]. In addition to the stable structure of AKT1 and ERα proteins. The interaction between Kaempferol and AKT1 and ERα is also stable, as seen from the RMSD ligand movement and MD binding energy values. RMSD ligand movement represents the movement of the ligand during the simulation. RMSD values with minimal fluctuations indicate that the ligand is stable when it binds to a protein [46]. MM/PBSA binding energy represents the binding energy value of the ligand in the protein. A low binding energy value means a stable interaction between the protein and the ligand [47]. Kaempferol can bind stably to AKT1 and ERα proteins and is highly predicted to become an inhibitor of these proteins.

AKT1 is a central protein in the PI3K/Akt signaling pathway. The AKT1 protein has a size of ~ 55.9 kDa comprising three domains: the N-terminal pleckstrin homology, kinase, and regulatory [48]. AKT1 activation occurs when Thr308 and Ser473 residues are phosphorylated by PDK1, when PI3K has been activated. After that, AKT1 binds to the substrate, and the ATP molecule, AKT1, transfers phosphate from ATP to the substrate, activating the substrate [49]. The substrates of the AKT1 protein are TSC (Tuberous Sclerosis Complex) and Mdm2 (Mouse double minute 2 homolog). Phosphorylated TSCs become inactive and lose their ability to suppress mTORC1. mTORC1 activity is related to tumor cell growth. Mdm2 activated by AKT1 will inhibit p53 activity, thereby inducing tumor cell survival [50]. Therefore, inhibiting the AKT1 protein will inhibit the activation of proteins related to cancer progression [51].

ERα is an intracellular receptor protein and an intracellular transcription factor involved in regulating the expression of certain genes after capturing estrogen. ERα has a molecular weight of 65 kDa and 595 amino acids. This protein is divided into three: N-terminal domain (NTD), DNA binding domain (DBD), and Ligand binding domain (LBD) [52]. ERα activation occurs when LBD binds to estrogen, which then ERα forms a dimer. The ERα dimer translocates to the nucleus and acts as a transcription factor [53]. DBD from ERα will bind to the Estrogen Response Element in the 5′-GGTCAnnnTGACC-3′ sequence [54]. One of the target genes of ERα is CCND1, which regulates the cell cycle [55]. In breast cancer, ERα is overexpressed due to increased promoter activity of the ERα gene (ESR1), amplified the ESR1 gene, and inhibited ERα degradation through ubiquitination and proteasomal pathways [56]. The inhibition of ERα, a key growth factor for cancer cells, has demonstrated its effectiveness in suppressing the proliferation of breast cancer cells [57].

This study suggested that Kaempferol has promising anti-breast cancer properties. It is predicted that high Kaempferol can inhibit the activity of AKT1 and Erα proteins, which are involved in breast cancer progression. However, these in-silico predictions must be validated using in vitro and in vivo approaches. The discovery of Kaempferol as an anticancer agent will be a breakthrough in natural anticancer research.

Conclusion

Kaempferol, the most promising anticancer agent against breast cancer in E. hirta, exhibits drug-like properties, is nontoxic to humans, can efficiently penetrate the plasma membrane, and demonstrates high anticancer activity. Moreover, Kaempferol has shown stable binding to AKT1 and ERα, enabling the prediction of its inhibitory effect on the activity of these two proteins. Notably, AKT1 and ERα are important proteins of the PI3K/Akt and ER signaling pathways, which play critical roles in breast cancer. Thus, Kaempferol displays anti-breast cancer activity by effectively inhibiting the AKT1 and ERα proteins.

Acknowledgments

This research was supported by Bioinformatics course for giving facilities during this research.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data supporting the findings of this study, including figures, tables, and raw data, are in the figshare repository and can be accessed using the link: https://doi.org/10.6084/m9.figshare.23742036.

Additional information

Funding

This research was funded by the Ministry of Research and Technology of the Republic of Indonesia through Program Magister Menuju Doktor untuk Sarjana Unggul (PMDSU) [grant no. 015/E5/PG.02.00.PL/2023].