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Research Article
Molecular mechanism elucidation of Ocimum basilicum as anticancer using system bioinformatic approach supported by in vitro assay
expand article infoKurnia Agustini, Frangky Sangande, Nuralih Nuralih, Armansyah Maulana Harahap§, Sri Ningsih, Anton Bahtiar§
‡ National Research and Innovation Agency, Bogor, Indonesia
§ Universitas Indonesia, Depok, Indonesia
Open Access

Abstract

Breast cancer (BC) is a multifactorial disease involving many pathways and target molecules. Multi-target therapy through multi-compound herbal medicines is an alternative strategy to treat BC. In the present study, we elucidate the molecular mechanism of Ocimum basilicum (OB) as an anticancer agent using system bioinformatic approach and investigate its cytotoxic effect against MCF-7 cells. We performed network pharmacology (NP) and molecular docking studies to provide scientific information regarding the underlying anti-BC mechanism of OB. Based on topology parameters obtained from protein-protein interaction (PPI), we identified six potential targets that play a significant role in the network including SRC, PI3KCA, EGFR, ESR1, AKT1, and MAPK1. Furthermore, consensus docking suggested rutin, quercetin-3-O-diglucoside, and kaempferol-3-O-β-D-rutinoside as the potential compounds of OB. Moreover, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated that the cytotoxic effect of OB might be related to the modulation of several pathways such as PI3K-Akt, VEGF, and HIF-1, breast cancer, and estrogen signaling pathways. The in vitro assay revealed that various extracts of OB demonstrated cytotoxic effects against MCF-7 with IC50 = 231 µg/mL (OB ethanolic extract), 408 µg/mL (OB methanolic extract), 479 µg/mL (OB ethyl acetate extract), 1887 µg/mL (OB n-hexanoic extract) and 767 µg/mL (OB butanolic extract) respectively.

Keywords

Ocimum basilicum, MCF-7 cells, Cytotoxicity, Network Pharmacology, Molecular Docking

Introduction

Breast cancer (BC) is one of the most common cancers diagnosed in women worldwide, and its occurrence exceeded lung cancer for the first time in 2020 (Zhang et al. 2022). The latest statistics from the International Agency for Research on Cancer (IARC) estimated that there were 2.26 million new BC cases in 2020 and the incidence of BC was predicted to increase to more than 3 million new cases and 1 million deaths in 2040 (Arnold et al. 2022).

The underlying molecular mechanisms of BC are complex involving dysregulation of various signaling pathways with their respective target molecules (Feng et al. 2018). As a consequence, the treatment of BC and other cancers requires a multi-target approach rather than a single-target to optimize the efficacy in certain cases (e.g. resistance) (Giordano and Petrelli 2008). This multi-target approach can be achieved by applying a combination of drugs (drug cocktail), or a single drug with multiple targets (Bolognesi and Rossi 2020; Makhoba et al. 2020). Moreover, multi-compound herbal medicine also offers multi-target effects, thus it can be an alternative therapy for cancer treatment. It has been suggested that combining herbal medicine with conventional cancer drugs might improve bioavailability and decrease adverse effects or toxicity by reducing the dose of standard medicines (Baktiar Laskar et al. 2020).

Based on current data, of 250,000 plant species found in the kingdom Plantae, only 10% of species have been explored for their anticancer activity (Baktiar Laskar et al. 2020). This indicates there is still a great opportunity to find anticancer agents from plants. Ocimum basilicum (OB) belongs to Lamiaceae (Labiatae) family and is a medicinal plant with several pharmacological activities including bronchodilatory effect, antioxidant, anti-inflammatory, and anticancer activity (Aminian et al. 2022). Methanol extract OB has been reported to show anti-BC activity but the molecular mechanism was not determined (Al-Ali et al. 2013). The molecular mechanism study of OB decoct preparation as anti-BC had been conducted previously by manually selecting targets without considering the chemical contribution of OB (Torres et al. 2018).

As a multifactorial disease, molecular mechanism elucidation of BC is challenging at the cellular level, particularly when using multi-compound substances (e.g. extract) since the biological activity is an accumulation of multi-target and multi-compound interactions. Therefore, it is important to consider all possible targets modulated by the compounds. To address this, network pharmacology (NP) offers a systematic and comprehensive approach to analyzing the molecular mechanism of extract materials (Yang et al. 2022). To our knowledge, there were no studies to investigate the molecular mechanism of OB through NP. Therefore, in this study, the underlying molecular mechanisms of OB as an anticancer were elucidated through NP. Molecular docking was conducted for preliminary validation that active compounds of OB can bind to the potential targets suggested by NP. Furthermore, we also explored the cytotoxic activity of various extracts of OB leaves against the MCF-7 cells. The current study provides basic knowledge before performing future experimental studies in developing OB as an anti-BC agent.

Materials and methods

Collection of active compounds of OB and their potential targets

The active compounds of OB were collected from Dr. Duke’s Phytochemical and Ethnobotanical Databases (https://phytochem.nal.usda.gov/) by focusing on leaf part and their potential targets with probability ≥ 0.1 were predicted using SwissTargetPrediction (http://www.swisstargetprediction.ch/). The target obtained in this step was termed “compound-related target”.

ERPBC-related targets of OB identification

To collect disease-related targets of OB, we used two databases: GeneCards and DisGeNet. Due to ~75% of all BC cases being diagnosed as estrogen receptor alpha-positive (ERα+) and MCF-7 representing this BC subtype (Nordin et al. 2018), we used the keyword “estrogen receptor-positive breast cancer” (ERPBC) in target fishing using GeneCards database. In this database, only targets marked as “protein-coding” were selected. In DisGeNet, all targets included in CUI: C2938924 were selected. After deleting the duplicate targets from the two databases, we overlaid these ERPBC-related targets with the compound-related targets of OB using the Venny 2.1 tool (https://bioinfogp.cnb.csic.es/tools/venny/index.html). The intersection targets were considered ERPBC-related targets of OB.

Protein-protein interaction (PPI) construction and KEGG analysis

The STRING database (https://string-db.org/) on Homo sapiens with a high confidence score (0.7) was used to construct the PPI network by submitting ERPBC-related targets of OB. Unconnected targets were deleted and the remaining targets were submitted to ShyniGO 0.77 (http://bioinformatics.sdstate.edu/go/) to analyze KEGG enrichment at the p-value of ≤ 0.05. This step resulted in the top 20 enriched pathways ranked by false discovery rate (FDR).

Potential targets identification

The result of the PPI construction above was then submitted to Cytoscape 3.9.3 and the topological features for each target include local average connectivity (LAC), closeness centrality (CC), eigenvector centrality (EC), network centrality (NC), and degree centrality (DC) were analyzed using CytoNCA. Targets with topological scores greater than the average score were considered potential targets.

Potential compounds identification

Molecular docking was used to identify the virtual hits for every potential target by screening all compounds having targets with probability ≥ 0.1 in step 2.4. The 3D structure of these compounds was retrieved from PubChem. The structures of the main targets: SRC (PDB: 2BDJ), PI3KCA (PDB: 5DXT), EGFR (PDB: 1M17), ESR1 (PDB: 3ERT), AKT1 (PDB: 4GV1), MAPK1 (PDB: 3I5Z) were downloaded from RCSB. DOCK6 and Vina were used for docking simulations using a consensus method and the protocols were developed based on a previous study (Sangande et al. 2023).

In DOCK6, targets and ligands were added charge using AM1-BBC method. A probe radius of 1.4 Å was used to generate the molecular surface. The active site of a target was determined using spheres within 8 Å of the native ligand which is surrounded by a box with a margin of 5 Å.

In Vina, the targets were prepared by adding polar hydrogens followed by Kollman charges. Meanwhile, Gestaiger charges were used in ligand preparation. A grid box centered on a native ligand position at a spacing of 1 Å was applied to generate the center coordinate. The size box of SRC, PI3KCA, ESR1, AKT1, and MAPK1 was set to 22 × 22 × 22 Å, while the size of 20 × 18 × 18 Å was used in EGFR.

The 10 conformations per ligand generated from the two docking tools were compared with each other, and compounds having duplet conformation in DOCK6 and Vina were calculated for their consensus score by averaging the binding energy (kcal/mol) of these conformations in each tool. Compounds getting the best consensus score were defined as virtual hits.

Sample preparation

OB was collected in July 2023 from Bogor, West Java, Indonesia. The leaves were dried, grinded, and extracted with various solvents such as methanol, ethanol, ethyl acetate, butanol, and n-hexane. Then a vacuum rotating evaporator was used to dry the filtrate.

Cell culture

We used MCF-7 cell lines from Human Breast Adenocarcinoma, that were obtained from the cell culture collection at the Laboratory for Development of Industrial Agro and Biomedical Technology (LAPTIAB) PUSPIPTEK, National Research and Innovation Agency (BRIN), Serpong, South Tangerang, Indonesia. MCF-7 cells were cultivated in medium RPMI 1640 (Gibco Life Technologies) supplemented with 10% heat-inactivated Fetal Bovine Serum (FBS, Gibco Life Technologies), phenol red, 100 U/ml penicillin, 0.1 mg/ml streptomycin, 2 mM glutamine and 1 mM sodium pyruvate. Cells were maintained in 75 cm2 flasks at 37 °C, 5% CO2, and 95% humidity.

Cytotoxic assay

In 96-well plates, 10,000 cells/well were platted using medium RPMI with phenol red containing 10% Fetal Bovine Serum (FBS), 0.1 mg/ml streptomycin, 100 U/ml penicillin and 1mM sodium pyruvate. Cells were incubated for 24 hours at 37 °C, 5% CO2 and in a 95% humidified atmosphere, then the medium was changed with samples in growth medium in six variation concentrations and incubated for another 24 hours at 37 °C, 5% CO2, and in a 95% humidified atmosphere. After that, Phosphate Buffer Saline (PBS) solution was added to wash the cell. To identify the living cells, we added the solution of MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium) in medium followed by incubation for 4 hours at 37 °C, 5% CO2, and in a 95% humidified atmosphere. During this incubation, the crystal of formazan blue will be formed. At last, we added the Sodium Dodecyl Sulphate (SDS) into every well to stop the reaction and leave the plate in a dark place for 12 hours (overnight). The intensity of the color formed was measured by ELISA reader at 570 nm. Data were analyzed with Probit Analysis to obtain the IC50. (Agustini et al. 2023).

Results

Active compounds of OB and their target prediction

A total of 44 compounds contained in OB leaves were retrieved from the database, and among them, only 28 compounds were found to have targets at probability ≥ 0.1 by SwissTargetPrediction. After analyzing, we identified 321 compound-related targets at this step.

ERPBC-related targets of OB

From GeneCards and DisGeNet, we collected 756 ERPBC-related targets. After merging these ERPBC-related targets with compound-related targets, we found 67 common targets in the intersection area (Fig. 1).

Figure 1. 

Venn diagram of overlapping between ERPBC-related targets and compound-related targets.

PPI and potential target

For further analysis, the PPI of the common targets was constructed using STRING. Of 67 targets, only 58 were connected to each other, and their interactions are shown in Fig. 2. Afterward, we calculated the six topology parameters of these targets and identified six potential targets: SRC, PI3KCA, EGFR, ESR1, AKT1, and MAPK1 that have topology parameters above the average (Table 1) thus they might play a significant role in pathogenesis of ERPBC.

Figure 2. 

PPI network of the common target. Larger and darker green color nodes represent a higher degree of targets in the network.

Table 1.

Topology parameters of the most potential targets.

Target Topology Parameter
Degree Eigenvector LAC Betweenness Closeness Network
SRC 21 0.4 5.0 638.6 0.5 15.5
PIK3CA 17 0.4 5.3 243.3 0.5 12.5
EGFR 13 0.3 4.5 212.1 0.4 7.1
ESR1 14 0.3 3.4 1267.0 0.5 7.0
AKT1 14 0.2 2.6 426.3 0.5 6.3
MAPK1 16 0.2 2.4 542.9 0.5 5.6
Cutoff 5.3 0.1 1.7 118.3 0.3 2.9

KEGG analysis

After submitting the 58 targets mentioned above to ShinyGO, 20 enriched pathways were obtained. Interestingly, in addition to PI3K-Akt, VEGF, and HIF-1 signaling pathways, breast cancer and estrogen signaling pathways which are closely related to ERPBC were also detected in this result (Fig. 3).

Figure 3. 

KEGG enrichment pathways.

Potential compounds

Based on NP studies, six potential targets might be modulated by OB for ERPBC treatment. To verify whether active compounds of OB can bind to these targets, we performed molecular docking simulations. Before simulations, the docking protocol of DOCK6 and Vina was validated by redocking the co-crystals to their corresponding target. Table 2 showed that our docking protocols resulted in RMSD values ≤ 2 Å, thus they were valid for simulation.

Table 2.

Docking pose of co-crystal ligands and their redocking pose.

Target DOCK6 Vina
SRC
PI3KCA
EGFR
AKT1
MAPK1

Docking results of 28 active compounds of OB revealed that there were different hits between DOCK6 and Vina. For instance, kaempferol-3-O-β-D-rutinoside and quercetin-3-O-diglucoside were compounds with the most negative score (-10.5 kcal/mol) on SRC based on Vina (Table 3), while DOCK6 (Table 4) suggested rutin was the best-scored compounds (-82.7 kcal/mol). These biased results were caused by the difference in the scoring function of Vina and DOCK6 (Li et al. 2016). Several studies have found that the accuracy of consensus docking is better than single docking (Houston and Walkinshaw 2013). In the present study, therefore, we used consensus docking to identify the most potent compounds of OB against the six core targets.

Table 3.

Docking score (kcal/mol) of duplet conformation on main targets using Vina.

No Compound Vina score
SRC PI3KCA EGFR ESR1 AKT1 MAPK1
1 Rosmarinic acid -7.5 -7.3 -8.1
2 Cinnamic acid -6.3 -6.4
3 Ferulic acid -6.6 -6.3 -6.0 -5.8 -6.1
4 Narigenin -9.0 -8.9 -8.6 -8.7 -7.8 -8.3
5 Aesculetin -6.6 -6.5 -6.3 -6.7 -6.4
6 Aesculin -8.2 -7.6 -9.1 -7.4 -8.2
7 Benzyl acetate -5.8 -5.9 -5.3
8 Caffeic acid -6.6 -6.3
9 Caffeic acid n-butyl ester -6.6 -7.1 -6.6 -6.2
10 Campesterol -8.7 -7.7 -8.0
11 Cinnamic acid methyl ester -5.2 -5.7
12 Eriodictyol -9.4 -9.2 -8.6 -8.0 -7.9 -8.7
13 Eriodictyol-7-O-β-D-glucoside -9.8 -10.2 -9.7 -7.7 -9.3 -9.6
14 Estragole -5.6 -5.8 -5.8 -5.5
15 Eugenol -6.0 -5.5 -5.4 -6.5
16 Isoquercitrin -10.3 -9.0 -8.2 -7.5
17 Kaempferol -9.6 -8.5 -8.7 -8.2 -7.4
18 Kaempferol-3-O-β-D-rutinoside -10.5 -9.4 -8.6 -9.0 -9.2
19 p-coumaric acid -6.7 -6.0 -6.6 -6.3
20 Quercetin -9.7 -8.5 -8.9 -7.9 -7.7 -8.9
21 Quercetin-3-O-diglucoside -10.5 -9.2 -9.4 -7.7 -8.9
22 Rutin -9.9 -9.8 -9.2 -9.1
23 Salicylic acid-2-β-D-glucoside -7.3 -6.6 -8.6 -6.6 -6.7 -6.7
24 Thymol -6.4 -6.0 -5.8 -6.3 -6.1
25 Ursolic acid -6.7 -8.5 -9.1 -7.0
26 Vanillic acid-4-β-D-glucoside -7.1 -6.8 -7.9 -6.2 -7.8 -7.2
27 Vicenin 2 -9.9 -9.1 -9.1 -8.3
28 Xanthomicrol
29 Co-crystal of SRC -10.1
30 Co-crystal of PI3KCA -9.1
31 Co-crystal of EGFR -7.4
32 Co-crystal of ESR1 -9.9
33 Co-crystal of AKT1 -8.5
34 Co-crystal of MAPK1 -10.5
Table 4.

Docking score (kcal/mol) of duplet conformation on main targets using DOCK6.

No Compound DOCK6 score
SRC PI3KCA EGFR ESR1 AKT1 MAPK1
1 Rosmarinic acid -58.6 -62.2 -62.7
2 Cinnamic acid -29.9 -32.2
3 Ferulic acid -40.9 -35.8 -35.6 -38.6 -38.0
4 Narigenin -48.4 -46.4 -46.3 -47.4 -46.8 -47.2
5 Aesculetin -32.3 -33.2 -33.0 -34.8 -33.9
6 Aesculin -51.9 -51.7 -52.7 -51.9 -54.4
7 Benzyl acetate -33.7 -29.9 -31.4
8 Caffeic acid -37.2 -35.1
9 Caffeic acid n-butyl ester -47.5 -46.4 -47.4 -47.4
10 Campesterol -51.6 -57.1 -48.4
11 Cinnamic acid methyl ester -34.1 -32.2
12 Eriodictyol -50.4 -49.1 49.5 -46.7 -50.7 -47.7
13 Eriodictyol-7-O-β-D-glucoside -67.3 -67.4 -61.8 -56.9 -68.3 -65.7
14 Estragole -32.9 -29.5 -32.1 -31.4
15 Eugenol -34.8 -32.6 -32.9 -34.7
16 Isoquercitrin -62.7 -61.3 -55.5 -54.2
17 Kaempferol -50.0 -48.5 -47.2 -46.8 -46.6
18 Kaempferol-3-O-β-D-rutinoside -80.7 -75.8 -72.0 -75.5 -73.4
19 p-coumaric acid -33.2 -32.4 -34.6 -34.2
20 Quercetin -52.4 -49.9 -49.9 -46.8 -45.8 -48.1
21 Quercetin-3-O-diglucoside -80.5 -77.1 -62.9 -70.3 -83.6
22 Rutin -82.7 -75.5 -70.9 -79.9
23 Salicylic acid-2-β-D-glucoside -49.2 -46.2 -49.6 -51.9 -47.6 -51.8
24 Thymol -31.3 -30.3 -29.8 -30.7 -30.6
25 Ursolic acid -44.4 -42.0 -52.6 -52.3 -41.3
26 Vanillic acid-4- β-D-glucoside -50.9 -50.1 -52.2 -53.0 -53.5 -54.2
27 Vicenin 2 -78.3 67.4 -68.9 -62.1
28 Xanthomicrol
29 Co-crystal of SRC -85.4
30 Co-crystal of PI3KCA -73.2
31 Co-crystal of EGFR -64.3
32 Co-crystal of ESR1 -88.3
33 Co-crystal of AKT1 -95.0
34 Co-crystal of MAPK1 -88.0

As shown in Table 5, consensus docking revealed that rutin, quercetin-3-O-diglucoside, and kaempferol-3-O-β-D-rutinoside were the potential compounds of OB. Rutin was predicted to be active on SRC. Quercetin-3-O-diglucoside was active on PI3KCA, ESR1, and AKT1. Meanwhile, kaempferol-3-O-β-D-rutinoside was active on EGFR and MAPK1. The binding of these compounds on their corresponding target is shown in Figs 4, 5.

Figure 4. 

H-bond profiles of co-crystal on SRC (A1); rutin on SRC (A2); co-crystal on PI3KCA (B1); quercetin-3-O-diglucoside on PI3KCA (B2); co-crystal on EGFR (C1); kaempferol-3-O-β-D-rutinoside on EGFR (C2). Dashed green lines represent hydrogen bonds. Yellow sticks represent the residues of targets. Brown sticks represent the ligands.

Figure 5. 

H-bond profiles of co-crystal on ESR1 (A1); quercetin-3-O-diglucoside on ESR1 (A2); co-crystal on AKT1 (B1); quercetin-3-O-diglucoside on AKT1 (B2); co-crystal on MAPK1 (C1); kaempferol-3-O-β-D-rutinoside on MAPK1 (C2). Dashed green lines represent hydrogen bonds. Yellow sticks represent the residues of targets. Brown sticks represent the ligands.

Table 5.

Consensus score (kcal/mol) of duplet conformation on main targets.

No Compound Consensus score
SRC PI3KCA EGFR ESR1 AKT1 MAPK1
1 Rosmarinic acid -33.1 -34.8 -35.4
2 Cinnamic acid -18.1 -19.3
3 Ferulic acid -23.8 -21.1 -20.8 -22.2 -22.1
4 Narigenin -28.7 -27.7 -27.5 -28.1 -27.3 -27.8
5 Aesculetin -19.5 -19.9 -19.7 -20.8 -20.2
6 Aesculin -30.1 -29.7 -30.9 -29.7 -31.3
7 Benzyl acetate -19.8 -17.9 -18.4
8 Caffeic acid -21.9 -20.7
9 Caffeic acid n-butyl ester -27.1 -26.8 -27.0 -26.8
10 Campesterol -30.2 -32.4 -28.2
11 Cinnamic acid methyl ester -19.7 -19.0
12 Eriodictyol -29.9 -29.2 -20.5 -27.4 -29.3 -28.2
13 Eriodictyol-7-O-β-D-glucoside -38.6 -38.8 -35.8 -32.3 -38.8 -37.7
14 Estragole -19.3 -17.7 -19.0 -18.5
15 Eugenol -20.4 -19.1 -19.2 -20.6
16 Isoquercitrin -36.5 -35.2 -31.9 -30.9
17 Kaempferol -29.8 -28.5 -28.0 -27.5 -27.0
18 Kaempferol-3-O-β-D-rutinoside -45.6 -42.6 -40.3 -42.3 -41.3
19 p-coumaric acid -20.0 -19.2 -20.6 -20.3
20 Quercetin -31.1 -29.2 -29.4 -27.4 -26.8 -28.5
21 Quercetin-3-O-diglucoside -45.5 -43.2 -36.2 -39.0 -46.3
22 Rutin -46.3 -42.7 -40.1 -44.5
23 Salicylic acid-2-β-D-glucoside -28.3 -26.4 -29.1 -29.3 -27.2 -29.3
24 Thymol -18.9 -18.2 -17.8 -18.5 -18.4
25 Ursolic acid -25.6 -25.3 -26.3 -30.7 -24.2
26 Vanillic acid-4-β-D-glucoside -29.0 -28.5 -30.1 -29.6 -30.7 -30.7
27 Vicenin 2 -44.1 29.2 -39.0 -35.2
28 Xanthomicrol
29 Co-crystal of SRC -47.8
30 Co-crystal of PI3KCA -41.2
31 Co-crystal of EGFR -35.9
32 Co-crystal of ESR1 -49.1
33 Co-crystal of AKT1 -51.8
34 Co-crystal of MAPK1 -49.3

Influence of OB extracts on viability of MCF-7 cells

From cell assay, we found that ethanolic extract has a better cytotoxic effect on MCF-7 cells than the extract with other solvents (Fig. 6). Ethanolic extract of OB exhibited cytotoxic activity in MCF-7 cells with IC50 = 231+37 µg/mL while methanolic extract gives IC50 = 408+24 µg/mL; ethyl acetate extract gives IC50 = 479+15 µg/mL; n-hexanoic extract gives IC50 = 1887+159 µg/mL; and buthanolic extract gives IC50 = 767+75 µg/mL

Figure 6. 

Percent viability of Ethanolic extract (A), Methanolic extract (B), Ethyl acetate extract (C), n-Hexane extract (D), and Buthanolic extract (E) of BO on MCF7 cells.

Discussion

OB is a spicy plant commonly used in traditional medicine for treating several conditions such as dysentery, flatulence, colds, and nausea (Eid et al. 2023). Through network pharmacology and molecular docking studies, we hypothesized that the cytotoxic effect of OB on MCF7 is achieved by inhibiting six main targets including SRC, PI3KCA, EGFR, ESR1, AKT1, and MAPK1. Interestingly, these targets are closely related to each other. SRC is a partner for EGFR in its signal transduction (de Diesbach et al. 2010). SRC:EGFR interaction induces activation of PIK3/AKT and MAPK pathways (Irwin et al. 2011). Both pathways in turn induce ligand-independent activation of ESR1 (Eanes and Patel 2016). It has been known that this relationship is involved in the mechanism of resistance to endocrine therapy in ERPBC (Xu and Sun 2010). Therefore, the extract of OB is promising for further development as an alternative treatment for endocrine-resistant ERPBC.

Our docking simulation revealed that almost all compounds were able to bind to these main targets simultaneously, indicating OB has a multitarget and synergic effect, thus increasing their anticancer activity. Based on the consensus score (Table 5), quercetin-3-O-diglucoside was the most potent compound against three targets: PI3KCA, ESR1, and AKT1.

On PI3KCA, the score of this compound was better than the co-crystal ligand. It formed H-bonds with Ser773, Ser774, and Asp933. Asp933 was reported as the residue that most frequently forms an H-bond with many inhibitors (Sabbah et al. 2010). This residue belongs to the conserved DFG motif in many kinase proteins that orient the γ-phosphate of ATP for transfer by binding to Mg2+ thus the catalytic process occurs (Maherwari et al. 2017). Meanwhile, an H-bond with Ser774 might be used to increase selectivity (Sabbah et al. 2010) and design mutant-specific inhibitors of PI3KCA (Sabbah et al. 2012). On ESR1, this compound occupies a slightly different position compared to the co-crystal (Fig. 4A). However, it can form an H-bond with Asp351, an essential residue in stabilizing the active conformation of ESR1. By interacting with this residue, an inhibitor will disturb the stability of the active conformation and inhibit ESR1 activity (Kim et al. 2005). On AKT1, this compound formed H-bonds with Lys179, Thr195, Glu198, and Asp292. A molecular dynamic simulation demonstrated that the complex of AKT1 with IN00145, the most active compound according to enzymatic assay, was stabilized by forming H-bonds with two residues included in our docking study, i.e. Lys179 and Asp292 (Mahajan et al. 2020).

Kaempferol-3-O-β-D-rutinoside, on the other hand, was the best-scored compound on EGFR and MAPK1. This compound binds to EGFR by forming H-bonds with Asp766 and Met769, while on MAPK1, it formed H-bonds with Met106, Lys115, and Ser151. Meanwhile, rutin showed the most negative score on SRC and formed H-bonds with Ala293, Lys295, Met341, and Asn391. Met769, Met106, and Met341 are the key residues at the hinge region of EGFR, MAPK1, and SRC, respectively. These targets are members of kinase protein, and it has been reported that H-bonds interaction with the kinase hinge is usually indispensable for potent inhibition (Xing et al. 2015).

In this study, we also investigated the potential anticancer activity of some extracts of OB on MCF-7 and found that they have cytotoxic effects with IC50 = 231 µg/mL (ethanolic extract), 408 µg/mL (methanolic extract), 479 µg/mL (ethyl acetate extract), 1887 µg/mL (n-hexanoic extract) and 767 µg/mL (buthanolic extract). MCF-7 is one of BC cell cultures with estrogen receptors. Ethanolic extract provides better cytotoxic activity compared to other extracts. It seems that the compounds responsible for providing cytotoxic activity are absorbed in the ethanol solvent.

Several studies have tested the cytotoxic effect of OB. However, they used different parts (aerial part, seed, essential oil) of OB and different solvents. Moreover, the molecular mechanisms were not characterized (Arshad Qamar et al. 2010; Eid et al. 2023). So far, we found a study that determined the mechanism of aqueous leaf extracts of OB from decoction. This extract decreased MCF-7 cell growth by 80% at 1000 µg/mL. Here, Akt, mTOR, and AMPK were suggested as the target molecules of OB (Torres et al. 2018). Another study used machine learning-based screening to collect the potential active compounds of the essential oil of OB. BRCA1 and BRCA2 were selected as the target molecules for investigation through molecular docking. However, this study cannot represent comprehensively the total activity of the essential oil of OB against MCF-7 (Nguyen et al. 2022).

According to National Cancer Institute (NCI) and Geran protocol, the cytotoxic effect of a substance is categorized as strong (IC50< 20 µg/mL), moderate (IC50 = 21–200 µg/mL), weak (IC50 = 201–500 µg/mL), and non-cytotoxic (IC50 >501 µg/mL) (Youssef et al. 2022). Based on this, all extracts were classified as weak cytotoxic agents. However, by considering the potential anticancer activity suggested by NP and molecular docking described above, future development of the crude extract of OB is still needed. Several studies have shown that after fractionating, the cytotoxic effect of medicinal plants increases (Charles-Okhe et al. 2022). Thus, the fractionating step focuses on the presence of three potential compounds (rutin, quercetin-3-O-diglucoside, and kaempferol-3-O-β-D-rutinoside) which can be considered for future studies.

Conclusion

Although OB has a weak cytotoxic effect on MCF-7, it showed a good potential for development as an alternative anticancer agent after optimization, such as through the fractionation process. NP studies suggested that OB has cytotoxic activity possibly by modulating several pathways including breast cancer, estrogen, PI3K-Akt, VEGF, and HIF-1 signaling pathways, and targeting six main targets: SRC, PI3KCA, EGFR, ESR1, AKT1, and MAPK1. Meanwhile, three compounds: rutin, quercetin-3-O-diglucoside, and kaempferol-3-O-β-D-rutinoside were considered as the potential compounds of OB. Thus, the cytotoxic activity of OB might partly be due to thebiological activity of these compounds. For the next studies, an in vitro assay against the six main targets is needed to validate this hypothesized molecular mechanism of OB. Moreover, fractionating the crude extract by focusing on the potential compounds might be a strategy to improve the cytotoxic activity.

Conflicts of Interest

There is no conflict of interest between any of the authors. The manuscript hasn’t been released yet, nor has it been offered for publication anywhere. The manuscript’s publishing has the unanimous approval of all authors.

Acknowledgements

This work was funding by Research Grant 2023 from Health Research Organization, National Research and Innovation Agency (BRIN), Indonesia.

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