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In silico exploration of Elaeocarpus ganitrus extract phytochemicals on STAT3, to assess their anticancer potential

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  • Elaeocarpus ganitrus Rox of the Elaeocarpaceae family is a broad-leaved medicinal plant and exhaustively used in orthodox systems of treating diseases. However, its anticancer impact and propensity to STAT3 has not yet been analyzed. The plant's extracts were in vitro assayed on the HeLa cell line and subsequently, GC-MS chromatogram of the methanolic, and chloroform extracts of the plant revealed that 106 compounds were present in the extracts. Subsequent filtration using Lipinski rules resulted in 81 phytochemicals being selected for the docking process with pre-selected receptor STAT3 (6NJS). Twenty-six out of 81 phyto-ligands showed high binding energy. Many drugs have weak pharmacokinetic properties and cellular toxicity and consequently, cannot pass through clinical trials. Hence, it is essential to determine the pharmacokinetic parameters of the phytoligands showing preferred binding with receptor 6NJS to consider the apparent bioavailability. The data for pharmacokinetics behavior, bioavailability extent, drug-likeness properties, medicinal chemistry friendliness, and toxicity of 26 phytochemicals with referenced inhibitors was explored. These 26 compounds were further checked for their ADMET properties by using the swissADME and PROTOX-II web server with the known inhibitors plumbagin and sanguinarine to determine the lead phytocompounds. The predictions of ADMET properties obtained six suitable phytocompounds (EG-9, EG-12, EG-13, EG-15, EG-16 and EG-26) of E. ganitrus, and found to be a perfect fit in the bioavailability radar. 2D and 3D interaction of phytoligands with the STAT3 show that the binding is through lys97, suggesting NH2-terminal domain binding of STAT3 with ligands which is the main mono-ubiquitin conjugation spot. Most of the phytoligands interactions exist in the Linker domain and Transactivation domain of the STAT3.
  • Salvia rosmarinus L. (old name Rosmarinus officinalis), common name Rosemary thrives well in dry regions, hills and low mountains, calcareous, shale, clay, and rocky substrates[1]. Salvia rosmarinus used since ancient times in traditional medicine is justified by its antiseptic, antimicrobial, anti-inflammatory, antioxidant, and antitumorigenic activity[1,2]. The main objective of the study is to evaluate the antimicrobial activity of different extracts of Salvia rosmarinus in vitro, and its compounds related to in silico targeting of enzymes involved in cervical cancer. Since the start of the 20th century, some studies have shown that microbial infections can cause cervical cancers worldwide, infections are linked to about 15% to 20% of cancers[3]. More recently, infections with certain viruses like Human papillomaviruses (HPV) and Human immunodeficiency virus (HIV), bacteria like Chlamydia trachomatis, and parasites like schistosomiasis have been recognized as risk factors for cancer in humans[3]. Then again, cancer cells are a group of diseases characterized by uncontrolled growth and spread of abnormal cells. Many things are known to increase the risk of cancer, including dietary factors, certain infections, lack of physical activity, obesity, and environmental pollutants[4]. Some studies have found that unbalanced common flora Lactobacillus bacteria around the reproductive organ of females increases the growth of yeast species (like Candida albicans) and some studies have found that women whose blood tests showed past or current Chlamydia trachomatis infection may be at greater risk of cervical cancer. It could therefore be that human papillomavirus (HPV) promotes cervical cancer growth[3]. Salvia rosmarinus is traditionally a healer chosen as a muscle relaxant and treatment for cutaneous allergy, tumors, increases digestion, and the ability to treat depressive behavior; mothers wash their bodies to remove bacterial and fungal infections, promote hair growth, and fight bad smells[5] .

    The study of plant-based chemicals, known as phytochemicals, in medicinal plants is gaining popularity due to their numerous pharmacological effects[6] against drug resistance pathogens and cancers. The causes of drug resistance to bacteria, fungi, and cancer are diverse, complex, and only partially understood. The factors may act together to initiate or promote infections and carcinogenesis in the human body is the leading cause of death[7]. Antimicrobial medicines are the cornerstone of modern medicine. The emergence and spread of drug-resistant pathogens like bacteria and fungi threaten our ability to treat common infections and to perform life-saving procedures including cancer chemotherapy and cesarean sections, hip replacements, organ transplantation, and other surgeries[7]. On the other hand, information about the current magnitude of the burden of bacterial and fungal drug resistance, trends in different parts of the world, and the leading pathogen–drug combinations contributing to the microbial burden is crucial. If left unchecked, the spread of drug resistance could make many microbial pathogens much more lethal in the future than they are today. In addition to these, cancers can affect almost any part of the body and have many anatomies and molecular subtypes that each require specific management strategies to avoid or inhibit them. There are more than 200 different types of cancer that have been detected. The world's most common cancers affecting men are lung, prostate, colorectal, stomach, and liver cancers[8]. While breast, cervix, colorectal, lung, and stomach cancers are the most commonly diagnosed among women[8]. Although some cancers said to be preventable they seem to still be one of the causes of death to humans, for example cervical cancer. The need to fill the gap to overcome the problem of searching for antimicrobials and anticancers from one source of Salvia rosmarinus is of importance.

    Cervical cancer is a common cancer in women and a prominent cause of death[9]. In Ethiopia, cervical cancer is a big deal for women aged 15 to 44, coming in as the second most common cancer[9]. Globally, it's the fourth most common prevalent disease for women[10]. Aberrant methylation of tumor-suppressor genes' promoters can shut down their important functions and play a big role in causing cervical tumors[10]. There are various cervical cancer repressor genes (proteins turn off or reduce gene expression from the affected gene), such as CCNA1, CHF, HIT, PAX1, PTEN, SFRP4, and TSC1. The genes play a crucial role in causing cervical cancer by regulating transcription and expression through promoter hypermethylation, leading to precursor lesions during cervical development and malignant transformation[11]. The process of DNA methylation is primarily carried out by a group of enzymes known as DNA methyltransferases (DNMT1). It has been reported that DNMT1 (PDB ID: 4WXX), a protein responsible for DNA methylation can contribute to the development of cervical cancer. DNMT1 inhibits the transcription of tumor suppressor genes, facilitating tumorigenesis, which finally develops into cervical cancer. Tumor suppressor gene transcription is inhibited by DNMT1, which helps cancer grow and eventually leads to cervical cancer. Repressive genes' hypermethylation may be decreased, their expression can be increased, and the phenotype of malignant tumors can be reversed by inhibiting the DNMT1 enzyme.

    On the other hand, infection by the human papilloma virus (HPV) phenotype 16, enzyme 6 (PDB ID: 4XR8) has been correlated with a greatly increased risk of cervical cancer worldwide[12]. Based on variations in the nucleotide sequences of the virus genome, over 100 distinct varieties of the human papilloma virus (HPV) have been identified (e.g. type 1, 2 etc.). Genital warts can result from certain types 6 and 11 of sexually transmitted HPVs. Other HPV strains, still, that can infect the genitalia, do not show any symptoms of infection[8]. Persistent infection with a subset of approximately 13 so-called 'high-risk' sexually transmitted HPVs, including such as types 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, and 68 different from the ones that cause warts may lead to the development of cervical intraepithelial neoplasia (CIN), vulvar intraepithelial neoplasia (VIN), penile intraepithelial neoplasia (PIN), and/or anal intraepithelial neoplasia (AIN). These are precancerous lesions and can progress to invasive cancer. Almost all occurrences of cervical cancer have HPV infection as a required component[13]. Superfluous infection by HPV type 16 E6 (PDB ID: 4XR8) has been correlated with a greatly increased genital risk of precursor cervical cancer worldwide[11]. Scholars more defined in major biochemical and biological activities of HPV type 16 E6 (PDB ID: 4XR8) in high-risk HPV oncogenes and how they may work together in the development of cervical disease and cancer[13].

    One potential approach to treat cervical cancer is to inhibit the activity of the DNMT1 and HPV type 16 E6 enzymes specifically[1316]. Over 50% of clinical drug forms worldwide originate from plant compounds[17]. In the past, developing new drugs was a lengthy and costly process. However, with the emergence of bioinformatics, the use of computer-based tools and methods have become increasingly important in drug discovery. One such method is molecular docking and ADMET profiling which involves using the structure of a drug to screen for potential candidates. This approach is known as structure-based drug design and can save both time and resources during the research process[15]. Structural-based drug designing addresses ligand binding sites with a known protein structure[15]. Using free binding energies, a computational method known as docking examines a large number of molecules and suggests structural theories for impeding the target molecule[17]. Nowadays, due to increasing antibiotic resistance like bacteria, fungi, and cancer cells, natural products remain an important source for discovering antimicrobial compounds and novel drugs for anti-cancers like cervical cancers. Therefore, the purpose of this research is to assess the antimicrobial activity of extracts, molecular docking, ADMET profiling in anticancer properties of compounds isolated from Salvia rosmarinus, on a targeting DNMT1 and HPV type 16 E6 in human cervical cancer. In the present study, various solvent crude extracts obtained from Salvia rosmarinus were used for antimicrobial activity and the isolated compounds 1 and 2 were submitted for in silico study to target the DNMT1 and HPV type 16 E6 enzymes to inhibit the growth of human cervical cancer cells.

    Healthy Salvia rosmarinus leaves were collected in Bacho district, Southwest Showa, Oromia, Ethiopia, during the dry season of November 2022. The plant materials were authenticated by Melaku Wondafrish, Natural Science Department, Addis Ababa University and deposited with a voucher number 3/2-2/MD003-80/8060/15 in Addis Ababa University's National Herbarium.

    The most common organic solvent used in extractions of medicinal plants is 2.5 L of petroleum ether, chloroform/methanol (1:1), and methanol. The test culture medium for microbes was used and performed in sterile Petri dishes (100 mm diameter) containing sterile Muller–Hinton Agar medium (25 mL, pH 7) and Sabouraud Dextrose Agar (SDA) for bacteria and fungi, respectively. A sterile Whatman filter paper (No. 1) disc of 6 mm diameter was used to determine which antibiotics an infective organism is sensitive to prescribed by a minimum zone of inhibition (MZI). Ciprofloxacin antibiotic reference (manufactured by Wellona Pharma Ciprofloxacin tablet made in India) and Ketoconazole 2% (made in Bangladesh) were used as a positive controls for antibacterial and antifungal, respectively and Dimethyl sulfoxide (DMSO) 98.9% was used as a negative control for antimicrobial tests. In the present study, the height of the column was 650 mm and the width was 80 mm. Several studies by previous researchers showed the acceptable efficiency of column chromatography (up to 43.0% w/w recovery) in the fractionation and separation of phenolic compounds from plant samples[18]. In column chromatography, the ideal stationary phase used silica gel 60 (0.200 mm) particles. The 1H-NMR spectrums of the compounds were analyzed using a 600 MHz NMR machine and 150 MHz for 13C NMR. The compounds were dissolved in MeOD for compound 1 and in DMSO for compound 2 for NMR analysis. On the other hand, UV spectroscopy (made in China) used 570 nm ultraviolet light to determine the absorbency of flavonoids (mg·g−1) phytochemicals.

    The samples (extracts) were analyzed to detect the presence of certain chemical compounds such as alkaloids (tested using Wagner's reagents), saponins (tested using the froth test), steroids (tested with Liebermann Burchard's tests), terpenoids (tested with Lidaebermann Burchard's tests), quinones, and flavonoids (tested using Shinoda tests)[19].

    The leaves of Salvia rosmarinus (500 g) were successively extracted using maceration using petroleum ether, chloroform/methanol (1:1), and methanol, every one 2.5 L for 72 h to afford 3.6, 6, and 53 g crude extracts, respectively. The methanol/chloroform (1:1) extract (6 g) was loaded to silica gel (150 g) column chromatography using the increasing polarity of petroleum ether, methanol/chloroform (1:1) solvent system to afford 80 fractions (100 mL each). The fraction obtained from chloroform/methanol 1:1 (3:2) after repeated column chromatography yielded compound 1 (18 mg). Fractions 56-65, eluted with chloroform/methanol (1:1) were combined and purified with column chromatography to give compound 2 (10 mg).

    The microorganisms were obtained from the Ethiopia Biodiversity Institution (EBI). Two gram-positive bacteria namely Staphylococcus aureus serotype (ATCC 25923) and Streptococcus epidermidis (ATCC14990); and three gram-negative bacteria, namely Escherichia coli (ATCC 25922), Pseudomonas aeruginosa (ATCC 5702), and Klebsiella pneumonia (ATCC e13883) were inoculated overnight at 37 °C in Muller–Hinton Agar/MHA culture medium and two fungus strains of Candida albicans (ATCC 16404) and Aspergillus niger (ATCC 11414) were inoculated overnight at 27−30 °C in Sabouraud Dextrose Agar/SDA culture medium[20].

    The antibacterial and antifungal activities of different crude extracts obtained from Salvia rosmarinus plant leaves were evaluated by the disk diffusion method (in accordance with the 13th edition of the CLSI M02 document on hardydiagnostics.com/disk-diffusion). Briefly, the test was performed in sterile Petri dishes (100 mm diameter) containing solid and sterile Muller–Hinton Agar medium (25 mL, pH 7) and Sabouraud Dextrose Agar (SDA) for bacteria and fungi, respectively. The extracts were placed on the surface of the media that had previously been injected with a sterile microbial suspension (one microbe per petri dish) after being adsorbed on sterile paper discs (5 μL per Whatman disc of 6 mm diameter). To prevent test samples from eventually evaporating, all Petri dishes were sealed with sterile laboratory films. They were then incubated at 37 °C for 24 h, and the zone diameter of the inhibition was measured and represented in millimeters. Ciprofloxacin antibiotic reference (manufactured by Wellona Pharma Ciprofloxacin tablet, India) was used as a positive control and DMSO was used as a negative control for antibacterial activity test while Ketoconazole 2% (Bangladesh) was used as a positive control and 10 μL of 0.2% agar as a negative control for antifungal activity tests[20]. The term 'inhibitory concentration' refers to the minimum sample concentration required to kill 99.9% of the microorganisms present[21]. Three repetitions of the crude extract sample were used to precisely measure the inhibitory halo diameter (in mm), which was then expressed as mean ± standard deviation to assess the anti-microbial activity.

    Cervical cancer-causing protein was identified through relevant literature. The protein molecule structure of DNA (cytosine-5)-methyltransferase 1 (DNMT1) (PDB ID: 4WXX)[21] and HPV type 16 E6 (PDB ID: 4XR8)[21] - a protein known to cause cervical cancer - were downloaded from the Protein Data Bank[22]. The stability of the protein molecule was assessed using Rampage[23].

    Phytochemical constituents of Salvia rosmarinus plant leaves were used to select a source of secondary metabolites (ligands). Ligand molecules were obtained through plant extraction, and isolation, and realized with PubChem (https://pubchem.ncbi.nlm.nih.gov/). The ligands were downloaded in Silver diamine fluoride format (SDF) and then converted to PDB format using an online SMILES translator (https://cactus.nci.nih.gov/translate/). The downloaded files were in PDB format, which was utilized for running various tools and software[24].

    The Biovia Discovery Studio Visualizer software was used to analyze the protein molecule. The protein molecule was converted into PDB format and its hierarchy was analyzed by selecting ligands and water molecules. Both the protein molecule and the water molecules lost their attached ligands during the analysis. Finally, the protein's crystal structure was saved in a PDB file[25].

    PyRx software was utilized to screen secondary metabolites and identify those ligands with the lowest binding energy to the protein target. The ligands with the lowest binding energy were further screened for their drug-likeliness property through analysis. It is worth noting that PyRx runs on PDBQT format. To begin using PyRx, it needs to load a protein molecule. This molecule should be converted from PDB to the protein data bank, partial charge (Q), and Atom Type (PDBQT) format. Once the protein molecule is loaded, it can import ligands from a specific folder in Silver diamine fluoride format. The ligand energy was minimized and changed to PDBQT format. The protein was docked with the ligand and screened based on minimum binding energy (https://cactus.nci.nih.gov/translate/).

    The optimal ligand was selected for final docking using AutoDock Vina and Biovia by modifying the reference of Discovery Studio Client 2021 (https://cactus.nci.nih.gov/translate/).

    The protein target from the Protein Data Bank (PDB) was loaded onto the graphical interface of AutoDock Vina. To prepare the protein for docking, water molecules were removed, hydrogen polar atoms were added, and Kollman charges were assigned to the protein molecule. Ultimately, PDBQT format was used to store the protein. After being imported in PDB format, the Ligand molecule was transformed to PDBQT format. Next, a grid box was chosen to represent the docked region. The command prompt was used to run AutoDock Vina and the outcomes were examined (https://cactus.nci.nih.gov/translate/).

    Docking the ligand with the protein target DNMT1(PDB ID: 4WXX)[22] and HPV type 16 E6 (PDB ID: 4XR8)[21] enzymes were performed using Biovia Discovery Studio Client 2021 by loading the protein target first followed by the ligand in PDB format. The charges were attached to the protein molecule, and the energy was minimized for the ligands. Both the protein and ligand molecules were prepared for docking. Once the docking process was complete, the results were analyzed based on several parameters, including absolute energy, clean energy, conf number, mol number, relative energy, and pose number. The interaction between the protein and ligand was analyzed using structure visualization tools, such as Biovia Discovery Studio Visualizer and PyMol (https://cactus.nci.nih.gov/translate/).

    The process of visualizing the structure was carried out using the PyMol tool. PyMol is a freely available software. Firstly, the protein molecule in PDBQT form was loaded on the PyMol graphical screen. Then, the output PDBQT file was added. The docked structure was visualized and the 'molecule' option was changed to 'molecular surface' under the 'shown as' menu (https://cactus.nci.nih.gov/translate/).

    Drug likeliness properties of the screened ligands were evaluated using the SwissADME online server. SMILE notations were obtained from PubChem and submitted to the SwissADME web server for analysis. The drugs were subjected to Lipinski's rule of five[20] for analysis. Lipinski's rules of five were selected for final docking through AutoDock Vina and Biovia Discovery Studio Client 2021. Ligands 1 and 2 were analyzed using Lipinski's rule of five for docking with AutoDock Vina and Biovia Discovery Studio Client 2021.

    The antimicrobial analysis data generated by triplicate measurements reported as mean ± standard deviation, and a bar graph also generated by GraphPad Prism version 8.0.1 (244) for Windows were used to perform the analysis. GraphPad Prism was used and combined with scientific graphing, comprehensive bar graph fitting (nonlinear regression), understandable statistics, and data organization. Prism allows the performance and modification of basic statistical tests commonly used and determined through the statistical applications in microbiology labs (https://graphpad-prism.software.informer.com/8.0/).

    Phytochemical screening of the different extracts for the presence (+) and absence (−) of alkaloids, steroids, glycosides, coumarins, terpenoids, flavonoids, carbohydrates, tannins, and saponins were done. The present study showed that alkaloids, terpenoids, flavonoids, and tannins tests in S. rosmarinus leaves of petroleum ether, chloroform/methanol (1:1), and methanol extracts were high whereas glycoside, coumarins, and carbohydrates had a moderate presence. The extract of S. rosmarinus leaves contain commonly bioactive constituents such as alkaloids, steroids, terpenoids, flavonoids, tannins, and saponins. These bioactive chemicals have active medicinal properties. Phytochemical compounds found in S. rosmarinus leaves have the potential to treat cancer cells and pathogens. The study also found that these flavonoids are related to natural phenolic compounds with anticancer and antimicrobial properties in the human diet (Table 1).

    Table 1.  Phytochemical screening tests result of petroleum ether, chloroform/methanol (1:1) and methanol extracts of Salvia rosmarinus leaves.
    Botanical name Phytochemicals Phytochemical screening tests Different extracts
    Petroleum ether Chloroform/methanol (1:1) Mehanol
    Salvia rosmarinus Alkaloids Wagner's test ++ ++ ++
    Steroids Libermann Burchard test ++ + ++
    Glycoside Keller-Killiani test +
    Coumarins Appirade test + +
    Terpenoids Libermann Burchard test ++ ++ ++
    Flavonoids Shinoda test ++ ++ ++
    Carbohydrate Fehling's test ++ ++
    Tannins Lead acetate test ++ ++ ++
    Saponins Foam test + + +
    + indicates moderate presence, ++ indicates highly present, − indicates absence.
     | Show Table
    DownLoad: CSV

    Two compounds were isolated and characterized using NMR spectroscopic methods (Fig. 1 & Supplementary Fig. S1ac). Compound 1 (10 mg) was isolated as yellow crystals from the methanol/chloroform (1:1) leaf extract of Salvia rosmarinus. The TLC profile showed a spot at Rf 0.42 with methanol/chloroform (3:2) as a mobile phase. The 1H-NMR spectrum (600 MHz, MeOD, Table 2, Supplementary Fig. S1a) of compound 1 showed the presence of one olefinic proton signal at δ 5.3 (t, J = 3.7 Hz, 1H), two deshielded protons at δ 4.7 (m, 1H), and 4.1 (m, 1H) associated with the C-30 exocyclic methylene group, and one O-bearing methine proton at δH 3.2 (m, 1H), and six methyl protons at δ 1.14 (s, 3H), 1.03 (d, J = 6.3 Hz, 3H), 1.00 (s, 3H), 0.98 (s, 3H), 0.87 (s, 3H), and 0.80 (s, 3H). A proton signal at δ 2.22 (d, J = 13.5 Hz, 1H) was attributed to methine proton for H-18. Other proton signals integrate for 20 protons were observed in the range δ 2.2 to 1.2. The proton decoupled 13C-NMR and DEPT-135 spectra (151 MHz, MeOD, Supplementary Fig. S1b & c) of compound 1 revealed the presence of 30 well-resolved carbon signals, suggesting a triterpene skeleton. The analysis of the 13C NMR spectrum displayed signals corresponding to six methyl, nine methylene, seven methine, and eight quaternary carbons. Among them, the signal observed at δ 125.5 (C-12) belongs to olefinic carbons. The methylene carbon showed signals at δC 39.9, 28.5, 18.1, 36.7, 23.9, 30.4, 26.5, 32.9, and 38.6. The quaternary carbons showed a signal at δC 39.4, 41.9, 38.4, 138.2, 41.8, and 47.8. The signals of exocyclic methylene carbon signals appeared at δ 153.1 and 103.9. The spectrum also showed sp3 oxygenated methine carbon at δ 78.3 and carboxyl carbon at δ 180.2. The spectrum revealed signals due to methyl groups at δC 27.4, 16.3, 15.0, 20.2, 22.7, and 16.4. The remaining carbon signals for aliphatic methines were shown at δC 55.3, 55.2, 53.0, and 37.1. The NMR spectral data of compound 1 is in good agreement with data reported for micromeric acid, previously reported from the same species by Abdel-Monem et al.[26]. (Fig. 1, Table 2).

    Figure 1.  Structure of isolated compounds from the leaves of Salvia rosmarinus.
    Table 2.  Comparison of the 13C-NMR spectral data of compound 1 and micromeric acid (MeOD, δ in ppm).
    Position NMR data of compound 1 Abdel-Monem
    et al.[26]
    1H-NMR 13C-NMR 13C-NMR
    1 38.60 39.9
    2 27.8 28.5
    3 3.2 (m, 1H) 78.3 80.3
    4 39.4 39.9
    5 55.3 56.7
    6 18.1 18.3
    7 36.7 34.2
    8 41.9 40.7
    9 53 48.8
    10 38.4 38.2
    11 23.9 24.6
    12 5.3 (t, J = 3.7 Hz, 1H) 125.5 127.7
    13 138.2 138
    14 41.8 43.3
    15 30.4 29.1
    16 26.5 25.6
    17 47.8 48
    18 δ 2.22 (d, J = 13.5 Hz, 1H) 55.2 56.1
    19 37.1 38.7
    20 153.1 152.8
    21 32.9 33.5
    22 39.0 40.1
    23 27.4 29.4
    24 16.3 16.9
    25 15.0 16.6
    26 20.2 18.3
    27 22.7 24.6
    28 180.2 177.8
    29 16.4 17.3
    30 4.7 (m, 1H), and 4.1 (m, 1H) 103.9 106.5
     | Show Table
    DownLoad: CSV

    Compound 2 (18 mg) was obtained as a white amorphous isolated from 40% methanol/chloroform (1:1) in petroleum ether fraction with an Rf value of 0.49. The 1H NMR (600 MHz, DMSO, Supplementary Fig. S2a) spectral-data showed two doublets at 7.79 (d, J = 8.7 Hz, 2H), and 6.90 (d, J = 8.7 Hz, 2H) which are evident for the presence of 1,4-disubstituted aromatic group. The oxygenated methylene and terminal methyl protons were shown at δ 4.25 (q, J = 7.1 Hz, 2H) and 1.29 (t, J = 7.1 Hz, 3H), respectively. The13C-NMR spectrum, with the aid of DEPT-135 (151 MHz, DMSO, Table 3, Supplementary Fig. S2b & c) spectra of compound 2 confirmed the presence of well-resolved seven carbon peaks corresponding to nine carbons including threee quaternary carbons, one oxygenated methylene carbon, one terminal methyl carbon, and two symmetrical aromatic methine carbons. The presence of quaternary carbon signals was shown at δ 120.9 (C-1), 148.2 (C-4), and ester carbonyl at δ 166.0 (C-7). The symmetry aromatic carbons signal was observed at δ 131.4 (C-2, 6), and 116.8 (C-3, 5). The oxygenated methylene and terminal methyl carbons appeared at δC 60.4 (C-8) and 14.7 (C-9), respectively. The spectral results provided above were in good agreement with those for benzocaine in the study by Alotaibi et al.[27]. Accordingly, compound 2 was elucidated to be benzocaine (4-Aminobenzoic acid-ethyl ester) (Table 3, Fig. 1, Supplementary Fig. S2ac), this compound has never been reported before from the leaves of Salvia rosmarinus.

    Table 3.  Comparison of the 1H-NMR, and 13C-NMR spectral data of compound 2 and benzocaine (DMSO, δ in ppm).
    Position NMR data of compound 2 Alotaibi et al.[27]
    1H-NMR 13C-NMR 1H-NMR 13C-NMR
    1 120.9 119
    2 7.79 (d, J = 8.7 Hz, 2H) 131.4 7.86 (d, J = 7.6 Hz) 132
    3 6.90 (d, J = 8.7 Hz, 2H) 116.8 6.83 (d, J = 7.6 Hz) 114
    4 148.2 151
    5 6.90 (d, J = 8.7 Hz, 2H) 116.8 6.83 (d, J = 7.6 Hz) 114
    6 7.79 (d, J = 8.7 Hz, 2H) 131.4 7.86 (d, J = 7.6 Hz) 132
    7 166.0 169
    8 4.3 (q, J = 7.1 Hz, 2H) 60.4 4.3 (q, J = 7.0 Hz) 61
    9 1.3 (t, J = 7.1 Hz, 3H) 14.7 1.36 (t, J = 7.0 Hz) 15
     | Show Table
    DownLoad: CSV

    The extracts and isolated compounds from Salvia rosmarinus were evaluated in vitro against microbes from gram-positive bacteria (S. aureus and S. epidermidis), gram-negative bacteria (E. coli, P. aeruginosa, and K. pneumoniae) and fungi (C. albicans and A. Niger) (Table 4). The petroleum ether extracts exhibited significant activity against all the present study-tested microbes at 100 μg·mL−1, resulting in an inhibition zone ranging from 7 to 21 mm. Chloroform/methanol (1:1) and methanol extracts demonstrated significant activity against all the present study-tested microbes at 100 μg·mL−1 exhibiting inhibition zones from 6 to 14 mm and 6 to 13 mm, respectively (Table 4). The chloroform/methanol (1:1) extracts were significantly active against bacteria of E. coli and K. pneumonia, and A. Niger fungi at 100 μg·mL−1. On the other hand, chloroform/methanol (1:1) extracts were significantly inactive against the S. rosmarinus and P. aeruginosa of bacteria and C. albicans of fungi, and again chloroform/methanol (1:1) extracts overall significantly active produced an inhibition zone of 12 to 14 mm (Table 4). Methanol extracts exhibited significant activity against S. aureus, E. coli bacteria, and A. Niger fungi at 100 μg·mL−1. The inhibition zone was recorded to be 11 to 13 mm. However, methanol extracts exhibited significant inactivity against K. pneumoniae (Table 4). The overall result of our studies shows that Salvia rosmarinus was extracted and evaluated in vitro, exhibiting significant antibacterial and antifungal activity, with inhibition zones recorded between 6 to 21 mm for bacteria and 5 to 21 mm for fungi. In our study, the positive control for ciprofloxacin exhibited antibacterial activity measured at 21.33 ± 1.15 mm, 15.00 ± 0.00 mm, and 14.20 ± 0.50 mm for petroleum ether, chloroform/methanol (1:1), and methanol extracts, respectively. Similarly, the positive control for ketoconazole demonstrated antifungal activity of 22.00 ± 1.00 mm, 13.67 ± 0.58 mm, and 15.00 ± 0.58 mm for petroleum ether, chloroform/methanol (1:1), and methanol extracts, respectively. Additionally, our findings indicated that the mean values of flavonoids (mg/g) tested were 92.2%, 90.4%, and 94.0% for petroleum ether, chloroform/methanol (1:1), and methanol extracts, respectively. This suggests that the groups of phenolic compounds evaluated play a significant role in antimicrobial activities, particularly against antibiotic-resistant strains.

    Table 4.  Comparison of mean zone of inhibition (MZI) leaf extracts of Salvia rosmarinus.
    Type of specimen, and standard antibiotics for
    each sample
    Concentration (μg·mL−1) of extract
    in 99.8% DMSO
    Average values of the zone of inhibition (mm)
    Gram-positive (+) bacteria Gram-negative (−) bacteria Fungai
    S. aurous S. epidermidis E. coli P. aeruginosa K. pneumoniae C. albicans A. niger
    Petroleum ether extracts
    S. rosmarinus 50 18.50 ± 0.50 15.33 ± 0.58 0.00 ± 0.00 0.00 ± 0.00 10.00 ± 0.00 15.93 ± 0.12 4.47 ± 0.50
    75 19.87 ± 0.06 17.00 ± 0.00 9.33 ± 0.29 10.53 ± 0.50 10.93 ± 0.12 18.87 ± 0.23 5.47 ± 0.50
    100 21.37 ± 0.78 17.50 ± 0.50 11.47 ± 0.50 13.17 ± 0.29 12.43 ± 0.51 20.83 ± 0.76 6.70 ± 0.10
    Standard antibiotics Cipro. 21.33 ± 1.15 18.33 ± 0.58 9.33 ± 0.58 12.30 ± 0.52 15.00 ± 0.00
    Ketocon. 22.00 ± 1.00 10.67 ± 0.58
    Chloroform/methanol (1:1) extracts
    50 5.47 ± 0.42 0.00 ± 0.00 10.33 ± 0.00 0.00 ± 0.00 9.70 ± 0.00 0.00 ± 0.12 8.47 ± 0.50
    S. rosmarinus
    75 5.93 ± 0.06 0.00 ± 0.00 11.33 ± 0.29 0.00 ± 0.50 12.50 ± 0.12 0.00 ± 0.23 10.67 ± 0.50
    100 6.47 ± 0.06 0.00 ± 0.00 14.17 ± 0.50 7.33 ± 0.29 14.17 ± 0.51 0.00 ± 0.76 12.67 ± 0.10
    Standard antibiotics Cipro. 15.00 ± 0.00 11.00 ± 1.00 11.33 ± 0.58 10.00 ± 0.52 12.67 ± 0.00
    Ketocon. 7.00 ± 1.00 13.67 ± 0.58
    Methanol extracts
    50 9.17 ± 0.29 5.50 ± 0.50 0.00 ± 0.00 7.50 ± 0.00 0.00 ± 0.00 6.57 ± 0.12 0.00 ± 0.50
    S. rosmarinus
    75 9.90 ± 0.10 6.93 ± 0.12 9.33 ± 0.29 8.50 ± 0.50 0.00 ± 0.00 8.70 ± 0.23 0.00 ± 0.50
    100 11.63 ± 0.55 7.97 ± 0.06 11.47 ± 0.50 9.90 ± 0.10 0.00 ± 0.00 10.83 ± 0.76 13.13 ± 0.10
    Standard antibiotics Cipro. 13.00 ± 0.00 11.50 ± 0.50 14.20 ± 0.58 13.33 ± 0.29 10.00 ± 0.00
    Ketocon. 12.00 ± 1.00 15.00 ± 0.58
    Mean values of flavonoids (mg·g−1) by 570 nm
    S. rosmarinus
    Petroleum ether extracts Chloroform/methanol (1:1) extracts Methanol extracts
    50 0.736 0.797 0.862
    75 0.902 0.881 0.890
    100 0.922 0.904 0.940
    Samples: Antibiotics: Cipro., Ciprofloxacin; Ketocon., ketoconazole (Nizoral); DMSO 99.8%, Dimethyl sulfoxide.
     | Show Table
    DownLoad: CSV

    Determining the three solvent extracts in S. rosmarinus plants resulted in relatively high comparable with positive (+) control. Especially, the S. rosmarinus petroleum ether leaf extracts against drug resistance human pathogenic bacteria S. aureus, S. epidermidis, E. coli, P. aeruginosa, and K. pneumoniae were minimum zone of inhibition (MZI) recorded that 21.37 ± 0.78, 17.50 ± 0.50, 11.47 ± 0.50, 13.17 ± 0.29, and 12.43 ± 0.51 mm, respectively and against human pathogenic fungi C. albicans and A. niger were minimum zone of inhibition (MZI) recorded that 20.83 ± 0.76 and 6.70 ± 0.10 mm, respectively which was used from bacteria against S. aureus MZI recorded that 21.37 ± 0.78 mm higher than the positive control (21.33 ± 1.15 mm). The S. rosmarinus of chloroform/methanol (1:1) extracts were found to be against E. coli (14.17 ± 0.50 mm) and K. pneumoniae (14.17 ± 0.51 mm) higher than the positive control 11.33 ± 0.58 and 12.67 ± 0.00 mm, respectively. The methanol extracts of leaves in the present study plants were found to have overall MZI recorded less than the positive control. The Salvia rosmarinus crude extracts showed better antifungal activities than the gram-negative (−) bacteria (Table 4, Fig 2, Supplementary Fig. S3). Therefore, the three extracts, using various solvents of different polarity indexes, have been attributed to specific biological activities. For example, the antimicrobial activities of Salvia rosmarinus extracts may be due to the presence of alkaloids, terpenoids, flavonoids, tannins, and saponins in natural products (Table 1).

    Figure 2.  Microbes' resistance with drugs relative to standard antibiotics in extracts of Salvia rosmarinus. The figures represent understudy of three extracts derived from Salvia rosmarinus. (a) Petroleum ether, (b) chloroform/methanol (1:1), and (c) methanol extracts tested in Salvia rosmarinus.

    Compounds 1 and 2 were isolated from chloroform/methanol (1:1) extract of Salvia rosmarinus (Fig. 1, Tables 2 & 3). The plant extract exhibited highest antibacterial results recorded a mean inhibition with diameters of 21 and 14 mm at a concentration of 100 mg·mL−1 against S. aureus and E. coli/K. pneumoniae, respectively. After testing, overall it was found that the highly active petroleum ether extract of Salvia rosmarinus was able to inhibit the growth of S. aureus and C. albicans, with inhibition zones of 21 and 20 mm, respectively. The petroleum ether extracts showed good efficacy against all tested microbes, particularly gram-positive bacteria and fungi (Table 4). This is noteworthy because gram-negative bacteria generally exhibit greater resistance to antimicrobial agents. Petroleum ether and chloroform/methanol (1:1) extracts of the leaves were used at a concentration of 100 mg·mL−1, resulting in impressive inhibition zone diameters of 11 and 14 mm for E. coli, 13 and 7 mm for P. aeruginosa, and 12 and 14 mm for K. pneumoniae, respectively.

    The present study found that at a concentration of 50 μg·mL−1, petroleum ether, chloroform/methanol (1:1), and MeOH extracts did not display any significant inhibition zone effects against the tested microbes. This implies that the samples have a dose-dependent inhibitory effect on the pathogens. The leaves of Salvia rosmarinus have been found to possess remarkable antimicrobial properties against gram-negative bacteria in different extracts such as E. coli, P. aeruginosa, and K. pneumoniae with 14.17 ± 0.50 in chloroform/methanol (1:1), 13.17 ± 0.29 in petroleum ether and 14.17 ± 0.51 in chloroform/methanol (1:1), respectively. However, in the present study, Salvia rosmarinus was found to possess remarkable high zones of inhibition with diameters of 21.37 ± 0.78 and 17.50 ± 0.50 mm antimicrobial properties against S. aureus, and S. epidermidis of gram-positive bacteria, respectively (Supplementary Fig. S3). The results are summarized in Fig. 2ac.

    The crystal structure of human DNMT1 (351-1600), classification transferase, resolution: 2.62 Å, PDB ID: 4WXX. Active site dimensions were set as grid size of center X = −12.800500 Å, center Y = 34.654981 Å, center Z = −24.870231 Å (XYZ axis) and radius 59.081291. A study was conducted to investigate the binding interaction of the isolated compounds 1 and 2 of the leaves of Salvia rosmarinus with the binding sites of the DNMT1 enzyme in human cervical cancer (PDB ID: 4WXX), using molecular docking analysis.

    The study also compared the results with those of standard anti-cancer agents Jaceosidin (Table 5 & Fig. 3). The compounds isolated had a final fixing energy extending from −5.3 to −8.4 kcal·mol−1, as shown in Table 4. It was compared to jaceosidin (–7.8 kcal·mol−1). The results of the molecular docking analysis showed that, compound 1 (−8.4 kcal·mol−1) showed the highest binding energy values compared with the standard drugs jaceosidin (–7.8 kcal·mol−1). Compound 2 has shown lower docking affinity (–5.3 kcal·mol−1) but good matching amino acid residue interactions compared to jaceosidin. After analyzing the results, it was found that the isolated compounds had similar residual interactions and docking scores with jaceosidin.

    Table 5.  Molecular docking results of ligand compounds 1 and 2 against DNMT1 enzyme (PDB ID: 4WXX).
    Ligands Binding affinity

    ( kcal·mol−1)
    H-bond Residual interactions
    Hydrophobic/electrostatic Van der Waals
    1 −8.4 ARG778 (2.85249), ARG778 (2.97417), VAL894 (2.42832) Lys-889, Pro-879, Tyr-865, His-795, Cys-893, Gly-760, Val-759, Phe-892, Phe-890, Pro-884, Lys-749
    2 −5.3 ARG596 (2.73996), ALA597 (1.84126), ILE422 (2.99493), THR424 (2.1965), ILE422 (2.93653) Electrostatic Pi-Cation-ARG595 (3.56619), Hydrophobic Alkyl-ARG595 (4.15839), Hydrophobic Pi-Alkyl-ARG595 (5.14967) Asp-423, Glu-428, Gly-425, Ile-427, Trp-464, Phe-556, Gln-560, Gln-594, Glu-559, Gln-598, Ser-563
    Jaceosidin −7.8 ASP571 (2.93566), GLN573 (2.02126), GLU562 (2.42376), GLN573 (3.49555), GLU562 (3.46629) Hydrophobic Alkyl-PRO574 (4.59409), Hydrophobic Alkyl-ARG690 (5.09748), Hydrophobic Pi-Alkyl-PHE576 (5.1314), Hydrophobic Pi-Alkyl-PRO574 (4.97072), Hydrophobic Pi-Alkyl-ARG690 (5.07356) Glu-698, Cys-691, Ala-695, Pro-692, Val-658, Glu-566, Asp-565
     | Show Table
    DownLoad: CSV
    Figure 3.  The 2D and 3D binding interactions of compounds against DNMT1 enzyme (PDB ID: 4WXX). The 2D and 3D binding interactions of compound 1 and 2 represent against DNMT1 enzyme, and jaceosidin (standard) against DNMT1 enzyme.

    Hence, compound 1 might have potential anti-cancer agents. However, anti-cancer in vitro analysis has not yet been performed. Promising in silico results indicate that further research could be beneficial. The 2D and 3D binding interactions of compounds 1 and 2 against human cervical cancer of DNMT1 enzyme (PDB ID: 4WXX) are presented in Fig. 3. The binding interactions between the DNMT1 enzyme (PDB ID: 4WXX), and compound 1 (Fig. 3) and compound 2 (Fig. 3) were displayed in 3D. Compounds and amino acids are connected by hydrogen bonds (green dash lines) and hydrophobic interactions (non-green lines).

    Crystal structure of the HPV16 E6/E6AP/p53 ternary complex at 2.25 Å resolution, classification viral protein, PDB ID: 4XR8. Active site dimensions were set as grid size of center X = −43.202782 Å, center Y = −39.085513 Å, center Z = −29.194115 Å (XYZ axis), R-value observed 0.196, and Radius 65.584122. A study was conducted to investigate the binding interaction of the isolated compounds 1 and 2 of the leaves of Salvia rosmarinus with the binding sites of the enzyme of human papilloma virus (HPV) type 16 E6 (PDB ID: 4XR8), using molecular docking analysis software. The study also compared the results with those of standard anti-cancer agents jaceosidin (Table 6 & Fig. 4). The compounds isolated had a bottom most fixing energy extending from −6.3 to −10.1 kcal·mol−1, as shown in Table 6. It was compared to jaceosidin (–8.8 kcal·mol−1). The results of the molecular docking analysis showed that, compound 1 (−10.1 kcal·mol−1) showed the highest binding energy values compared with the standard drugs jaceosidin (–8.8 kcal·mol−1). Compound 2 has shown lower docking affinity (–6.3 kcal·mol−1) but good matching amino acid residue interactions compared to jaceosidin. After analyzing the results, it was found that the isolated compounds had similar residual interactions and docking scores with jaceosidin.

    Table 6.  Molecular docking results of ligand compounds 1 and 2 against HPV type 16 E6 (PDB ID: 4XR8).
    Ligands Binding affinity
    (kcal·mol−1)
    H-bond Residual interactions
    Hydrophobic/electrostatic Van der Waals
    1 −10.1 ASN101 (2.25622), ASP228 (2.88341) Asp-148, Lys-176, Lys-180, Asp-178, Ile-179, Tyr-177, Ile-334, Glu-382, Gln-336, Pro-335, Gln-73, Arg-383, Tyr-100
    2 −6.5 TRP63 (1.90011), ARG67 (2.16075), ARG67 (2.8181) Hydrophobic Pi-Sigma-TRP341 (3.76182), Hydrophobic Pi-Pi Stacked-TYR156 (4.36581), Hydrophobic Pi-Pi T-shaped-TRP63 (5.16561), Hydrophobic Pi-Pi T-shaped-TRP63 (5.44632), Hydrophobic Alkyl-PRO155 (4.34691), Hydrophobic Pi-Alkyl-TRP341 (4.11391), Hydrophobic Pi-Alkyl-ALA64 (4.61525) Glu-154, Arg-345, Asp-66, Met-331, Glu-112, Lys-16, Trp-231
    Jaceosidin −8.8 ARG146 (2.06941), GLY70 (3.49991), GLN73 (3.38801) Electrostatic Pi-Cation-ARG67 (3.93442), Hydrophobic Pi-Alkyl-PRO49 (5.40012) Tyr-342, Tyr-79, Ser-338, Arg-129, Pro-335, Leu-76, Tyr-81, Ser-74, Tyr-71, Ser-80, Glu-46
     | Show Table
    DownLoad: CSV
    Figure 4.  The 2D and 3D binding interactions of compounds against HPV type 16 E6 (PDB ID: 4XR8). The 2D and 3D binding interactions of compound 1 and 2 represent against HPV type 16 E6 enzyme, and jaceosidin (standard) against HPV type 16 E6 enzyme.

    Hence, compounds 1 and 2 might have potential anti-cancer agents of HPV as good inhibitors. However, anti-cancer in vitro analysis has not been performed yet on HPV that causes cervical cancer agents. Promising in silico results indicate that further research could be beneficial. The 2D and 3D binding interactions of compounds 1 and 2 against human papilloma virus (HPV) type 16 E6 enzyme (PDB ID: 4XR8) are presented in Fig. 4. The binding interactions between the HPV type 16 E6 enzyme (PDB ID: 4XR8) and compound 1 (Fig. 4) and compound 2 (Fig. 4) were displayed in 3D. Compounds and amino acids are connected by hydrogen bonds (magenta lines) and hydrophobic interactions (non-green lines).

    In silico bioactivities of a drug, including drug-likeness and toxicity, predict its oral activity based on the document of Lipinski's Rule[25] was stated and the results of the current study showed that the compounds displayed conform to Lipinski's rule of five (Table 7). Therefore, both compounds 1 and 2 should undergo further investigation as potential anti-cancer agents. Table 8 shows the acute toxicity predictions, such as LD50 values and toxicity class classification (ranging from 1 for toxic, to 6 for non-toxic), for each ligand, revealing that none of them were acutely toxic. Furthermore, they were found to be similar to standard drugs. Isolated compound 1 has shown toxicity class classification 4 (harmful if swallowed), while 2 showed even better toxicity prediction giving results of endpoints such as hepatotoxicity, mutagenicity, cytotoxicity, and irritant (Table 8). All the isolated compounds were predicted to be non-hepatotoxic, non-irritant, and non-cytotoxic. However, compound 1 has shown carcinogenicity and immunotoxicity (Table 9). Hence, based on ADMET prediction analysis, none of the compounds have shown acute toxicity, so they might be proven as good drug candidates.

    Table 7.  Drug-likeness predictions of compounds computed by Swiss ADME.
    Ligands Formula Mol. Wt. (g·mol−1) NRB NHA NHD TPSA (A°2) Log P (iLOGP) Log S (ESOL) Lipinski's rule of five
    1 C30H46O3 454.68 1 3 2 57.53 3.56 −6.21 1
    2 C 9H11NO2 165.19 3 2 1 52.32 1.89 −2.21 0
    Jaceosidin C17H14O7 330.3 3 7 3 105 1.7 1 0
    NHD, number of hydrogen donors; NHA, number of hydrogen acceptors; NRB, number of rotatable bonds; TPSA, total polar surface area; and log P, octanol-water partition coefficients; Log S, turbid metric of solubility.
     | Show Table
    DownLoad: CSV
    Table 8.  Pre ADMET predictions of compounds, computed by Swiss ADME.
    Ligands Formula Skin permeation value
    (logKp - cm·s−1)
    GI
    absorption
    Inhibitor interaction
    BBB permeability Pgp substrate CYP1A2 inhibitor CYP2C19 inhibitor CYP2C9 inhibitor CYP2D6 inhibitor
    1 C30H46O3 −4.44 Low No No No No No No
    2 C 9H11NO2 −5.99 High Yes No No No No No
    Jaceosidin C17H14O7 −6.13 High No No Yes No Yes Yes
    GI, gastrointestinal; BBB, blood brain barrier; Pgp, P-glycoprotein; and CYP, cytochrome-P.
     | Show Table
    DownLoad: CSV
    Table 9.  Toxicity prediction of compounds, computed by ProTox-II and OSIRIS property explorer.
    Ligands Formula LD50
    (mg·kg−1)
    Toxicity
    class
    Organ toxicity
    Hepatotoxicity Carcinogenicity Immunotoxicity Mutagenicity Cytotoxicity Irritant
    1 C30H46O3 2,000 4 Inactive Active Active Inactive Inactive Inactive
    2 C 9H11NO2 NA NA Inactive Inactive Inactive Inactive Inactive Inactive
    Jaceosidin C17H14O7 69 3 Inactive Inactive Inactive Inactive Inactive Inactive
    NA, not available.
     | Show Table
    DownLoad: CSV

    Rosemary is an evergreen perennial plant that belongs to the family Lamiaceae, previously known as Rosmarinus officinalis. Recently, the genus Rosmarinus was combined with the genus Salvia in a phylogenetic study and became known as Salvia rosmarinus[28,29] and it has been used since ancient times for various medicinal, culinary, and ornamental purposes. In the field of food science, rosemary is well known as its essential oil is used as a food preservative, thanks to its antimicrobial and antioxidant properties, rosemary has many other food applications such as cooking, medicinal, and pharmacology uses[30]. According to the study, certain phytochemical compounds found in Salvia rosmarinus leaves have the potential to halt the growth of cancer cells, and pathogens or even kill them[31]. In literature, alkaloids are found mostly in fungi and are known for their strong antimicrobial properties, which make them valuable in traditional medicine[32,33]. However, in the present study, S. rosmarinus species have been shown to possess alkaloids. Most alkaloids have a bitter taste and are used to protect against antimalarial, antiasthma, anticancer, antiarrhythmic, analgesic, and antibacterial[33] also some alkaloids containing nitrogen such as vincristine, are used to treat cancer.

    Steroids occur naturally in the human body. They are hormones that help regulate our body's reaction to infection or injury, the speed of metabolism, and more. On the other hand, steroids are reported to have various biological activities such as chronic obstructive pulmonary disease (COPD), multiple sclerosis, and imitate male sex hormones[34]. It is a natural steroid compound occurring both in plants and animals[35]. Thus, were found in the present study. Terpenoids are derived from mevalonic acid (MVA) which is composed of a plurality of isoprene (C5) structural units. Terpenoids, like mono-terpenes and sesquiterpenes, are widely found in nature and more than 50,000 have been found in plants that reduce tumors and cancers. Many volatile terpenoids, such as menthol and perillyl alcohol, are used as raw materials for spices, flavorings, and cosmetics[36]. In the present study, high levels of these compounds were found in Salvia rosmarinus leaves.

    Flavonoids are a class of phenolic compounds commonly found in fruits and vegetables and are considered excellent antioxidants[37]. Similarly, the results of this study revealed that S. rosmarinus contain flavonoids. According to the literature, these flavonoids, terpenoids, and steroid activities include anti-diabetic, anti-inflammatory, anti-cancer, anti-bacterial, hepatic-protective, and antioxidant effects[36]. Tannins are commonly found in most terrestrial plants[38] and have the potential to treat cancer, and HIV/AIDS as well as to treat inflamed or ulcerated tissues. Similarly, in the present study, tannins were highly found in the presented plant. On the other hand, due to a sudden rise in the number of contagious diseases and the development of antimicrobial resistance against current drugs, drug development studies are vital to discovering novel medicinal compounds[30] and add to these cancer is a complex multi-gene disease[39] as in various cervical cancer repressor genes[11] that by proteins turn off or reduce gene expression from the affected gene to cause cervical cancer by regulating transcription and expression through promoter hypermethylation (DNMT1), leading to precursor lesions during cervical development and malignant transformation.

    In a previous study[40], a good antibacterial result was recorded at a median concentration (65 μg·mL−1). Methanol extract showed a maximum and minimum zone antibacterial result against negative bacteria E. coli 14 + 0.71 and most of the petroleum ether tests show null zone of inhibition. However, in the present study at a concentration of 100 μg·mL−1, the methanol extract demonstrated both maximum and minimum antibacterial zones against E. coli 11.47 ± 0.50. Conversely, the test conducted with petroleum ether exhibited a good zone of inhibition by increasing concentration. Further research may be necessary to determine the optimal concentration for this extract to maximize its efficacy. The results obtained in gram-negative bacteria such as E. coli, P. aeruginosa, and K. pneumoniae are consistent with previous research findings[41]. However, in the present study, Salvia rosmarinus has been found to possess high zones of inhibition with diameters of 21.37 ± 0.78 and 17.50 ± 0.50 mm antimicrobial properties against S. aureus, and S.epidermidis of gram-positive bacteria, respectively (Table 4 & Fig. 2, Supplementary Fig. S3). According to a previous study[42], the ethanolic leaf extract of Salvia rosmarinus did exhibit activity against C. albicans strains. In the present study, the antifungal activity of petroleum ether extracts from Salvia rosmarinus were evaluated against two human pathogenic fungi, namely C. albicans and A. niger. The findings showed that at a concentration of 100 μg·mL−1, the extracts were able to inhibit the growth of C. albicans 20.83 ± 0.76 resulting in a minimum zone of inhibition.

    Antimicrobial agents can be divided into groups based on the mechanism of antimicrobial activity. The main groups are: agents that inhibit cell wall synthesis, depolarize the cell membrane, inhibit protein synthesis, inhibit nucleic acid synthesis, and inhibit metabolic pathways in bacteria. On the other hand, antimicrobial resistance mechanisms fall into four main categories: limiting the uptake of a drug; modifying a drug target; inactivating a drug; and active drug efflux. Because of differences in structure, etc., there is a variation in the types of mechanisms used by gram-negative bacteria vs gram-positive bacteria. Gram-negative bacteria make use of all four main mechanisms, whereas gram-positive bacteria less commonly use limiting the uptake of a drug[43]. The present findings showed similar activity in chloroform/methanol (1:1) and methanol extracts of leaves of Salvia rosmarinus than gram-negative bacteria like P. aeruginosa and Klebsiella pneumoniae. However, Staphylococcus epidermidis of gram-positive bacteria under chloroform/methanol (1:1) extracts have similarly shown antimicrobial résistance. This occurred due to intrinsic resistance that may make use of limiting uptake, drug inactivation, and drug efflux that need further study. The structure of the cell wall thickness and thinners of gram-negative and gram-positive bacteria cells, respectively when exposed to an antimicrobial agent, there happen two main scenarios may occur regarding resistance and persistence. In the first scenario, resistant cells survive after non-resistant ones are killed. When these resistant cells regrow, the culture consists entirely of resistant bacteria. In the second scenario, dormant persistent cells survive. While the non-persistent cells are killed, the persistent cells remain. When regrown, any active cells from this group will still be susceptible to the antimicrobial agent.

    Ferreira et al.[44] explained that with molecular docking, the interaction energy of small molecular weight compounds with macromolecules such as target protein (enzymes), and hydrophobic interactions and hydrogen bonds at the atomic level can be calculated as energy. Several studies have been conducted showing natural products such as epigallocatechin-3-gallate-3-gallate (EGCG), curcumin, and genistein can be used as an inhibitor of DNMT1[4547] . In the literature micromenic (1) is used for antimicrobial activities and for antibiotic-resistance like methicillin-resistant Staphylococcus aureus (MRSA)[48], and benzocaine (2) is used to relieve pain and itching caused by conditions such as sunburn or other minor burns, insect bites or stings, poison ivy, poison oak, poison sumac, minor cuts, or scratches[49]. However, in the present study, Salvia rosmarinus was used as a source of secondary metabolites (ligands) by using chloroform/methanol (1:1) extract of the plant leaves yielded to isolate micromeric (1) and benzocaine (2) in design structure as a candidate for drugs as inhibitors of the DNMT1 enzyme by inhibiting the activity of DNMT1 that prevent the formation of cervical cancer cells.

    Cervical cancer is one of the most dangerous and deadly cancers in women caused by Human papillomaviruses (HPV). Some sexually transmitted HPVs (type 6 owner of E6) may cause genital warts. There are several options for the treatment of early-stage cervical cancer such as surgery, nonspecific chemotherapy, radiation therapy, laser therapy, hormonal therapy, targeted therapy, and immunotherapy, but there is no effective cure for an ongoing HPV infection. In the present study, Salvia rosmarinus leaves extracted and isolated compounds 1 and 2 are one of the therapeutic drugs design structure as a candidate drug for inhibiting HPV type 16 E6 enzyme. Similarly, numerous researchers have conducted studies on the impact of plant metabolites on the treatment of cervical cancer. Their research has demonstrated that several compounds such as jaceosidin, resveratrol, berberin, gingerol, and silymarin may be active in treating the growth of cells[47].

    Small-molecule drugs are still most commonly used in the treatment of cancer[50]. Molecular docking in in silico looks for novel small-molecule (ligands) interacting with genes or DNA or protein structure agents which are still in demand, newly designed compounds are required to have a specific even multi-targeted mechanism of action to anticancer and good selectivity over normal cells. In addition to these, in the literature, anti-cancer drugs are not easily classified into different groups[51]. Thus, drugs have been grouped according to their chemical structure, presumed mechanism of action, and cytotoxic activity related to cell cycle arrest, transcription regulation, modulating autophagy, inhibition of signaling pathways, suppression of metabolic enzymes, and membrane disruption[52]. Another problem for grouping anticancers often encountered is the resistance that may emerge after a brief period of a positive reaction to the therapy or may even occur in drug-naïve patients[50]. In recent years, many studies have investigated the molecular mechanism of compounds affecting cancer cells and results suggest that compounds exert their anticancer effects by providing free electron charge inhibiting some of the signaling pathways that are effective in the progression of cancer cells[53] and numerous studies have shown that plant-based compounds such as phenolic acids and sesquiterpene act as anticancer agents by affecting a wide range of molecular mechanisms related to cancer[53]. The present investigations may similarly support molecular mechanisms provided for the suppression of metabolic enzymes of cervical cancer.

    The main aim of the study was to evaluate the antimicrobial activity of different extracts of Salvia rosmarinus in vitro, and its compounds related to in silico targeting of enzymes involved in cervical cancer. The phytochemical screening tests indicated the presence of phytochemicals such as alkaloids, terpenoids, flavonoids, and tannins in its extracts. The plant also exhibited high antimicrobial activity, with varying efficacy in inhibiting pathogens in a dose-dependent manner (50−100 μg·mL−1). However, this extract exhibited a comparatively high inhibition zone in gram-positive and gram-negative bacteria had lower inhibition zones against E. coli, P. aeruginosa, and K. pneumoniae, respectively, and stronger antifungal activity 20.83 ± 0.76 mm inhibition zone against C. albicans fungi. Molecular docking is a promising approach to developing effective drugs through a structure-based drug design process. Based on the docking results, the in silico study predicts the best interaction between the ligand molecule and the protein target DNMT1 and HPV type 16 E6. Compound 1 (–8.3 kcal·mol−1) and 2 (–5.3 kcal·mol−1) interacted with DNMT1 (PDB ID: 4WXX) and the same compound 1 (–10.1 kcal·mol−1) and 2 (–6.5 kcal·mol−1) interacted with HPV type 16 E6 (PDB ID: 4XR8). Compounds 1 and 2 may have potential as a medicine for treating agents of cancer by inhibiting enzymes DNMT1 and HPV type 16 E6 sites, as well as for antimicrobial activities. None of the compounds exhibited acute toxicity in ADMET prediction analysis, indicating their potential as drug candidates. Further studies are required using the in silico approach to generate a potential drug through a structure-based drug-designing approach.

  • The authors confirm contribution to the paper as follows: all authors designed and comprehended the research work; plant materials collection, experiments performing, data evaluation and manuscript draft: Dejene M; research supervision and manuscript revision: Dekebo A, Jemal K; NMR results generation: Tufa LT; NMR data analysis: Dekebo A, Tegegn G; molecular docking analysis: Aliye M. All authors reviewed the results and approved the final version of the manuscript.

  • All data generated or analyzed during this study are included in this published article.

  • This work was partially supported by Adama Science and Technology University under Grant (ASTU/SP-R/171/2022). We are grateful for the fellowship support from Adama Science and Technology University (ASTU), the identification of plants by Mr. Melaku Wendafrash, and pathogenic strain support from the Ethiopian Biodiversity Institute (EBI). We also thank the technical assistants of the Applied Biology and Chemistry departments of Haramaya University (HU) for their help.

  • The authors declare that they have no conflict of interest.

  • [1]

    Yu H, Lee H, Herrmann A, Buettner R, Jove R. 2014. Revisiting STAT3 signalling in cancer: new and unexpected biological functions. Nature Reviews Cancer 14:736−46

    doi: 10.1038/nrc3818

    CrossRef   Google Scholar

    [2]

    Zou S, Tong Q, Liu B, Huang W, Tian Y, et al. 2020. Targeting STAT3 in cancer immunotherapy. Molecular Cancer 19:145

    doi: 10.1186/s12943-020-01258-7

    CrossRef   Google Scholar

    [3]

    Fan Y, Mao R, Yang J. 2013. NF-κB and STAT3 signaling pathways collaboratively link inflammation to cancer. Protein & Cell 4:176−85

    doi: 10.1007/s13238-013-2084-3

    CrossRef   Google Scholar

    [4]

    Yang X, Xu L, Yang L, Xu S. 2023. Research progress of STAT3-based dual inhibitors for cancer therapy. Bioorganic & Medicinal Chemistry 91:117382

    doi: 10.1016/j.bmc.2023.117382

    CrossRef   Google Scholar

    [5]

    Dong J, Cheng XD, Zhang WD, Qin JJ. 2021. Recent update on development of small-molecule STAT3 inhibitors for cancer therapy: from phosphorylation inhibition to protein degradation. Journal of Medicinal Chemistry 64:8884−915

    doi: 10.1021/acs.jmedchem.1c00629

    CrossRef   Google Scholar

    [6]

    Siveen KS, Sikka S, Surana R, Dai X, Zhang J, et al. 2014. Targeting the STAT3 signaling pathway in cancer: role of synthetic and natural inhibitors. Biochimica et Biophysica Acta 1845:136−54

    doi: 10.1016/j.bbcan.2013.12.005

    CrossRef   Google Scholar

    [7]

    Ijaz S, Akhtar N, Khan MS, Hameed A, Irfan M, et al. 2018. Plant derived anticancer agents: a green approach towards skin cancers. Biomedicine & Pharmacotherapy 103:1643−51

    doi: 10.1016/j.biopha.2018.04.113

    CrossRef   Google Scholar

    [8]

    Salehi B, Machin L, Monzote L, Sharifi-Rad J, Ezzat SM, et al. 2020. Therapeutic potential of quercetin: new insights and perspectives for human health. ACS Omega 5:11849−72

    doi: 10.1021/acsomega.0c01818

    CrossRef   Google Scholar

    [9]

    Majolo F, de Oliveira Becker Delwing LK, Marmitt DJ, Bustamante-Filho IC, Goettert MI. 2019. Medicinal plants and bioactive natural compounds for cancer treatment: important advances for drug discovery. Phytochemistry Letters 31:196−207

    doi: 10.1016/j.phytol.2019.04.003

    CrossRef   Google Scholar

    [10]

    Patel B, Das S, Prakash R, Yasir M. 2010. Natural bioactive compound with anticancer potential. International Journal of Advances in Pharmaceutical Sciences 1:32−41

    doi: 10.5138/ijaps.2010.0976.1055.01003

    CrossRef   Google Scholar

    [11]

    Mousavi SM, Hashemi SA, Behbudi G, Mazraedoost S, Omidifar N, et al. 2021. A review on health benefits of Malva sylvestris L. nutritional compounds for metabolites, antioxidants, and anti-inflammatory, anticancer, and antimicrobial applications. Evidence-Based Complementary and Alternative Medicine 2021:5548404

    doi: 10.1155/2021/5548404

    CrossRef   Google Scholar

    [12]

    Krishna P, Kumari NR, Manisree V, Rani KS, Deepthi BVP, Sharma JVC. 2019. Medicinal benefits of Elaeocarpus Ganitrus (Rudraksha) - A divine herb. World Journal of Pharmaceutical Research 8:552−65

    Google Scholar

    [13]

    Mahajanakatti AB, Deepak TS, Achar RR, Pradeep S, Prasad SK, et al. 2022. Nanoconjugate synthesis of Elaeocarpus ganitrus and the assessment of its antimicrobial and antiproliferative properties. Molecules 27:2442

    doi: 10.3390/molecules27082442

    CrossRef   Google Scholar

    [14]

    Das PK. 2015. Phytochemical screening of methanolic extracts of different parts of rudraksh plant (Elaeocarpus ganitrus). Journal of Biological Sciences 15:111−12

    doi: 10.3844/OJBSCI.2015.111.112

    CrossRef   Google Scholar

    [15]

    Motallebi M, Bhia M, Rajani HF, Bhia I, Tabarraei H, et al. 2022. Naringenin: a potential flavonoid phytochemical for cancer therapy. Life Sciences 305:120752

    doi: 10.1016/j.lfs.2022.120752

    CrossRef   Google Scholar

    [16]

    Zhang Y, Liu X, Ruan J, Zhuang X, Zhang X, et al. 2020. Phytochemicals of garlic: promising candidates for cancer therapy. Biomedicine & Pharmacotherapy 123:109730

    doi: 10.1016/j.biopha.2019.109730

    CrossRef   Google Scholar

    [17]

    Fulda S, Debatin KM. 2006. Resveratrol modulation of signal transduction in apoptosis and cell survival: a mini-review. Cancer Detection and Prevention 30:217−23

    doi: 10.1016/j.cdp.2006.03.007

    CrossRef   Google Scholar

    [18]

    Ahmad K, Bhat AR, Athar F. 2017. Pharmacokinetic evaluation of Callistemon viminalis derived natural compounds as targeted inhibitors against δ-opioid receptor and farnesyl transferase. Letters in Drug Design & Discovery 14:488−99

    doi: 10.2174/1570180814666161214114322

    CrossRef   Google Scholar

    [19]

    Sudradjat SE, Timotius KH. 2022. Pharmacological properties and phytochemical components of Elaeocarpus: a comparative study. Phytomedicine Plus 2:100365

    doi: 10.1016/j.phyplu.2022.100365

    CrossRef   Google Scholar

    [20]

    Kumar TS, Shanmugam S, Palvannan T, Bharathi Kumar VM. 2008. Evaluation of antioxidant properties of Elaeocarpus ganitrus roxb. leaves. Iranian Journal of Pharmaceutical Research 7(3):211−15

    Google Scholar

    [21]

    Sultana B, Anwar F, Ashraf M. 2009. Effect of extraction solvent/technique on the antioxidant activity of selected medicinal plant extracts. Molecules 14:2167−80

    doi: 10.3390/molecules14062167

    CrossRef   Google Scholar

    [22]

    Ozigis HO, Olaifa KA, Agbeja AO, Asabia LO, Akindolu DR, et al. 2023. Qualitative phytochemical analysis of leave and stem bark of Zanthoxylum zanthoxyloides and Zanthoxylum gilletti. Journal of Chemical Society of Nigeria 48(3):891

    doi: 10.46602/jcsn.v48i3.891

    CrossRef   Google Scholar

    [23]

    Dhivya R, Jaividhya P, Riyasdeen A, Palaniandavar M, Mathan G, et al. 2015. In vitro antiproliferative and apoptosis-inducing properties of a mononuclear copper(II) complex with dppz ligand, in two genotypically different breast cancer cell lines. BioMetals 28:929−43

    doi: 10.1007/s10534-015-9877-1

    CrossRef   Google Scholar

    [24]

    Daina A, Michielin O, Zoete V. 2017. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific Reports 7:42717

    doi: 10.1038/srep42717

    CrossRef   Google Scholar

    [25]

    Lipinski CA. 2004. Lead- and drug-like compounds: the rule-of-five revolution. Drug Discovery Today Technologies 1:337−41

    doi: 10.1016/j.DDTec.2004.11.007

    CrossRef   Google Scholar

    [26]

    Khan A, Mohammad T, Shamsi A, Hussain A, Alajmi MF, et al. 2022. Identification of plant-based hexokinase 2 inhibitors: combined molecular docking and dynamics simulation studies. Journal of Biomolecular Structure & Dynamics 40:10319−31

    doi: 10.1080/07391102.2021.1942217

    CrossRef   Google Scholar

    [27]

    Banerjee P, Eckert AO, Schrey AK, Preissner R. 2018. ProTox-II: a webserver for the prediction of toxicity of chemicals. Nucleic Acids Research 46:W257−W263

    doi: 10.1093/nar/gky318

    CrossRef   Google Scholar

    [28]

    Beg A, Khan FI, Lobb KA, Islam A, Ahmad F, et al. 2019. High throughput screening, docking, and molecular dynamics studies to identify potential inhibitors of human calcium/calmodulin-dependent protein kinase IV. Journal of Biomolecular Structure & Dynamics 37:2179−92

    doi: 10.1080/07391102.2018.1479310

    CrossRef   Google Scholar

    [29]

    Tsaioun Katya, Kates SA. (Eds) 2011. ADMET for medicinal chemists: a practical guide. Hoboken, New Jersey (simultaneously in Canada): John Wiley & Sons. https://doi.org/10.1002/9780470915110

    [30]

    Onawole AT, Sulaiman KO, Adegoke RO, Kolapo TU. 2017. Identification of potential inhibitors against the Zika virus using consensus scoring. Journal of Molecular Graphics & Modelling 73:54−61

    doi: 10.1016/j.jmgm.2017.01.018

    CrossRef   Google Scholar

    [31]

    Siramshetty VB, Nickel J, Omieczynski C, Gohlke BO, Drwal MN, et al. 2016. WITHDRAWN—a resource for withdrawn and discontinued drugs. Nucleic Acids Research 44:D1080−D1086

    doi: 10.1093/nar/gkv1192

    CrossRef   Google Scholar

    [32]

    Ray S, Zhao Y, Jamaluddin M, Edeh CB, Lee C, et al. 2014. Inducible STAT3 NH2 terminal mono-ubiquitination promotes BRD4 complex formation to regulate apoptosis. Cellular Signalling 26:1445−55

    doi: 10.1016/j.cellsig.2014.03.007

    CrossRef   Google Scholar

  • Cite this article

    Mehnaj, Bhat AR, Athar F. 2024. In silico exploration of Elaeocarpus ganitrus extract phytochemicals on STAT3, to assess their anticancer potential. Medicinal Plant Biology 3: e009 doi: 10.48130/mpb-0024-0010
    Mehnaj, Bhat AR, Athar F. 2024. In silico exploration of Elaeocarpus ganitrus extract phytochemicals on STAT3, to assess their anticancer potential. Medicinal Plant Biology 3: e009 doi: 10.48130/mpb-0024-0010

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In silico exploration of Elaeocarpus ganitrus extract phytochemicals on STAT3, to assess their anticancer potential

Medicinal Plant Biology  3 Article number: e009  (2024)  |  Cite this article

Abstract: Elaeocarpus ganitrus Rox of the Elaeocarpaceae family is a broad-leaved medicinal plant and exhaustively used in orthodox systems of treating diseases. However, its anticancer impact and propensity to STAT3 has not yet been analyzed. The plant's extracts were in vitro assayed on the HeLa cell line and subsequently, GC-MS chromatogram of the methanolic, and chloroform extracts of the plant revealed that 106 compounds were present in the extracts. Subsequent filtration using Lipinski rules resulted in 81 phytochemicals being selected for the docking process with pre-selected receptor STAT3 (6NJS). Twenty-six out of 81 phyto-ligands showed high binding energy. Many drugs have weak pharmacokinetic properties and cellular toxicity and consequently, cannot pass through clinical trials. Hence, it is essential to determine the pharmacokinetic parameters of the phytoligands showing preferred binding with receptor 6NJS to consider the apparent bioavailability. The data for pharmacokinetics behavior, bioavailability extent, drug-likeness properties, medicinal chemistry friendliness, and toxicity of 26 phytochemicals with referenced inhibitors was explored. These 26 compounds were further checked for their ADMET properties by using the swissADME and PROTOX-II web server with the known inhibitors plumbagin and sanguinarine to determine the lead phytocompounds. The predictions of ADMET properties obtained six suitable phytocompounds (EG-9, EG-12, EG-13, EG-15, EG-16 and EG-26) of E. ganitrus, and found to be a perfect fit in the bioavailability radar. 2D and 3D interaction of phytoligands with the STAT3 show that the binding is through lys97, suggesting NH2-terminal domain binding of STAT3 with ligands which is the main mono-ubiquitin conjugation spot. Most of the phytoligands interactions exist in the Linker domain and Transactivation domain of the STAT3.

    • Cancer is a cluster of diseases and STAT3 protein has significant roles in all types of cancer. Signal transducer and activator of transcription (STAT), belong to the family of cytoplasmic transcription factors, activate and transduce extracellular growth factor, and also affect cytokine signals and affect gene transcriptional events. STAT3 mutant intrinsically alone is enough to instigate oncogenic transformation, and tumorigenesis[13]. A survey of the current literature reveals that STATs have transactivated domains and play a significant role in cancer migration and invasion. Hampering of c-Src kinase activity or downregulation of STAT3 signaling stimulates apoptosis[4]. The study of chemical interactions between STAT3 receptor and phytochemicals assist in drug designing and hence in cancer therapy[5]. There are a variety of phytochemicals that have a high propensity to modulate directly or indirectly the STAT3 signaling pathway. Triterpenoids like betulinic acid, polyphenols curcuminoids, plumbagin a naphthoquinone, diosgenin a steroid, hydroxycinnamic acid, and thymoquinone are the phytochemicals that suppress STAT3 expression[6]. Many plant-derived phytochemicals manifest high anticancer activity and lead researchers to adopt integrated multifaceted research techniques[711]. Though, Elaeocarpus ganitrus Roxb. (also known as Rudraksha) constitutively placed in Ayurvedic system, also has anticancer potential[12]. Recently its silver nanoparticle has been assessed for anticancer and antiproliferative activities[13]. Its impact on STAT is yet to be explored. In the last few decades, phytochemical composition of Elaeocarpus genus has been extensively investigated. Phytochemicals of various extracts of different parts of the plant showed the presence of alkaloids, flavonoids, carbohydrates, glycosides, proteins, quinine, coumarins, tannins, minerals, vitamins, saponins, phenolic compounds, and fixed oils in a high concentration, thus adding to its medicinal value[14]. The pharmacological screening of metabolites like polyphenols, alkaloids, terpenoids and flavonoids have been explored to demonstrate cancer pathways to ascertain possible mechanism[1518]. As stated in the literature, the beads and the bark of the plants have been extensively studied while the leaves of the E. ganitrus have not been studied for their anticancer efficiency. Besides, leaves of the plants were shown to have good antioxidant potential[19,20]. The emphasis of the study is to identify phytochemicals retrieved from Elaeocarpus ganitrus leaf research data and GC-MS profiling. To accentuate, the binding role of Elaeocarpus ganitrus phytochemicals with STAT3 receptor, their ADME properties and pharmacokinetic studies were investigated.

    • The chemicals and solvents used in the extraction and phytochemical analysis were of analytical grade, sourced from Sigma-Aldrich. MTT (3-[4,5-dimethylthiazol-2-1yl]-2,5 diphenyl tetrazolium bromide) was also procured from Sigma-Aldrich. HeLa cells were obtained from the National Centre for Cell Sciences (NCCS), Pune, India. Fetal bovine serum and Dulbecco's Modified Eagle's Media were acquired from Gibco-life technologies.

    • Fresh leaves of E. ganitrus were purchased from Patanjali Herbal Garden Nursery in Panchayanpur, Uttarakhand, India. Authentication of the Elaeocarpus ganitrus was conducted by the Department of Botany, Jamia Hamdard, New Delhi, India, and the voucher specimen was deposited at the University.

    • Leaves of E. ganitrus were carefully washed, air-dried for ten days, and ground to a fine powder. A sample of 1,000 grams of powder was exhaustively extracted three times with 100% methanol (10 times weight/volume) at room temperature for 72 h using a soxhlet apparatus. The resulting crude methanol extract was fractionated successively with solvents in increasing polarity order: heptane, chloroform, ethyl acetate, methanol, and water. The residue was air-dried and utilized for the subsequent solvents. The fractions obtained from each solvent were filtered, dried under vacuum using a rotary evaporator, and stored at 40 °C until use[21].

    • The presence or absence of phytochemicals such as terpenoids, steroids, saponins, flavonoids, glycosides, tannins, and phenols in the chloroform and methanol extracts of E. ganitrus leaves was determined following the standard methodology[22].

    • The HeLa cell line was stored in Dulbecco's Modified Eagle's Medium which is rich in 10% Fetal Bovine Serum, 1% antibiotic solution, 25 mM sodium bicarbonate, and 10 mM HEPES in a 5% CO2 humidified atmosphere at 37 °C in an air jacketed incubator. The stock culture was perpetuated in the exponentially growing phase by passaging as, monolayer culture with 0.02% EDTA. Dislodged cells suspended in complete medium were routinely reseeded.

    • The cytotoxic effects of the various fractions of E. ganitrus leaf on the HeLa cancer cell line were evaluated using the MTT assay. Cells were seeded overnight, and exposed to different concentrations of the prepared fractions (ranging from 50 to 200 μg/ml), and incubated for 48 h. After treatment, cells were incubated with MTT solution and the formazan crystals were solubilized and the absorbance was read at 570 nm[23].

    • Binding energies of phytochemicals retrieved from plant leave extract with STAT3 were calculated by using software InstaDock for molecular docking. Discovery Studio Visualizer, and PyMOL, were used to visualize the chemical interactions of ligands and proteins. SWISS-ADME tool and ProTox-II were used for pharmacokinetic profiling studies. The X-ray crystal structure of STAT3 (PDB ID: 6NJS) was downloaded from Protein Data Bank (PDB). All co-crystallized hetero atoms and attached water molecules and co-crystallized ligands, were eliminated from the original coordinates. The Polar hydrogen atoms were inculcated, the residue structures having lower occupancy were removed, and the incomplete side chains were then substituted by using ADT. Three-dimensional structures of phytocompounds were sketched using Chem3D.

    • Determination of the analogous behavior to the drug of phytoligands with the help of cheminformatics was done using online tool SwissADME developed by the Molecular Modelling Group, Swiss Institute of Bioinformatics[24]. The computation of pharmacokinetics and physicochemical molecular properties help medicinal chemists in their routine drug discovery processes. Significant basic molecular information can be excavated from the chemical structure. The methods were preferred over other methods because of the speed, but also for the ease of interpretating results by fingerprinting method to enable researchers move through translation to medicinal chemistry and in molecular designing[25].

    • The rationale behind molecular docking is to steer medicinal chemists for translational research. The affinity of a molecule to the receptor changes with small structural changes in the molecule[26]. For molecular docking, STAT3 core complex PDB id (PMID: 31715132) was remodeled to ascertain binding energies with the best conformational poses of Elaeocarpus ganitrus leaves phytoligands. The InstaDock software is used to dock phytoligands with blind search space having a grid size of 110, 70, and 108 Å for X, Y, Z coordinates, correspondingly. The center of the grid was confined to X: 63.09, Y: 14.98, and Z: −76.91 axis, which covers all the heavy atoms embedded in the protein. The conformational site selected was so that the movement of the ligands was free to probe their best binding coordinates. Default docking specifications were employed to calculate various parameters. All the docking conformational poses were generated using PyMOL, a molecular visualization system and Discovery Studio Predictor.

    • Physicochemical parameters, water solubility, lipophilicity, pharmacokinetics, and drug-likeness were elicited from SwissADME. To retrieve the toxicological profile of the phytoligands ProTox-II servers were employed[27]. Early estimation of the Absorption, Distribution, Metabolism, Excretion and Toxicity abbreviated as ADMET imperative to ascribe the pharmacodynamics success of the lead phytoligands. (SMILES) strings to encode chemical structures were imported from PubChem, open chemistry database and implemented in SWISS-ADME tool[24] to auspicate lipophilicity to show hydrophobic and hydrophilic nature, water solubility, necessary for absorption across membranes, and drug-likeness rules to assess metabolic profiles. Toxicology prediction of phytoligands is a crucial and fundamental aspect in the drug discovery process. ProTox-II is used to estimate computational toxicity, to accelerate the course to drug discovery, compute animal toxicity, and also help to attenuate animal experiments. In the PROTOX-II web server, toxicity classes are designated into four segments. Category I comprised of chemical entities with LD50 (LD = lethal Dose) values (LD50 ≤ 5) mg/kg, Category II comprised of compounds with LD50 values (5 < LD50 ≤ 50) mg/kg, Category III comprised of chemical entities having LD50 values (50 < LD50 ≤ 300) mg/kg, Category IV comprised of compounds which have LD50 values (300 < LD50 ≤ 2,000) mg/kg, Category V comprised of compounds with LD50 values (2,000 < LD50 ≤ 5,000) mg/kg and Category VI comprised of compounds showing LD50 values (LD50 > 5,000) mg/kg[28]. Category I and II manifested high toxicity, Category III and IV are comparatively less toxic and Category V and VI are considered to be non-toxic.

    • The solvent extraction technique is usually employed to prepare extracts from plant materials attributable to its convenience to operate. The importance lies in that a large amount of plant material can be extracted with minimal solvent[26]. Fresh leaves of Elaeocarpus ganitrus were purchased from Patanjali Herbal Garden Site Nursery located in Panchayanpur, Uttarakhand 249405, India. The confirmation of the authenticity of the Elaeocarpus ganitrus was done by the Department of Botany, Jamia Hamdard, New Delhi, India, and the leaf specimens deposited in the University. The crude methanol extract was unintermittedly fractionated in the solvents heptane, chloroform, ethyl acetate, methanol, and water according to their increasing polarity[16]. The anticancer activity of extracts was analyzed on the basis of their IC50 values. Cancerous HeLa cell line when treated with E. ganitrus leaf extracts exhibited a substantial inhibition of cells. The half maximal inhibitory concentration of chloroform and methanol extracts of E. ganitrus was (IC50 = 304.39 μg/ml) and (IC50 = 308.59 μg/ml) respectively followed by water (IC50 = 340.14 μg/ml), ethyl acetate (IC50 = 350.72 μg/ml) and heptane (IC50 = 381.76 μg/ml) extracts (Fig. 1ae & Fig. 2). The qualitative investigation using standard methodology[22] of chloroform and methanol fractions of E. ganitrus leaves disinterred the presence of major phytochemicals namely steroids, saponins, terpenoids, tannins, phenols, glycosides and flavonoids Table 1. GC-MS analysis of the chloroform and methanolic fractions was done based on their lowest half maximal inhibitory concentration to get a complete profiling of the plant compounds. The peaks in the total ion current (TIC) chromatogram of GC-MS profile of the phytoligands commensurate with the spectrum of known chemical databases stockpiled in the GC-MS library. The gas chromatogram depicts the relative concentrations of different phytoligands getting eluted according to the retention time. The heights of the peak represent the comparative concentrations of the compounds present in the plant appear as peaks at different m/z ratios. The components present with their retention time, molecular formula, molecular weight and concentration (peak area %) are provided in Tables 2 & 3 showing the presence of 56 and 50 bioactive phytochemicals in the chloroform and methanol extracts respectively. Of 106 phytoligands obtained from chloroform and methanol extracts of E. ganitrus leaves, 81 phytoligands were identified has having the best drug-like properties following Lipinski's rule of five. Lipinski's rule states that molecular properties, physical or chemical of a compound are significant for a drug's pharmacokinetics behavior inside a biological system. The drug molecules that go along with the RO5 have fewer attrition rates when undergoing clinical trials. The cheminformatics study to identify potential chemical entities having propensity for predefined biological targets is called virtual screening[28]. To endeavor in vitro experiments time diminution, molecular docking-based virtual screening of 81 selected compounds with two reference inhibitors having substantial binding energies with 6NJS were preferred for further analysis. The STAT3 has dual nature as an oncogene or as a tumor suppressor during cancer progression. It has a SH2 domain, linker domain, DNA binding domain, and all-alpha domain. The total energy of binding, Vander Waals forces, hydrogen bonding, electrostatic attraction, desolvation, and also a number of rotatable bonds present in the phytoligand, contribute to observe the free energy of binding of phytoligands with the receptor. Twenty-six (EG-1 to EG-26) compounds were selected as having appreciable binding affinities towards the 6NJS receptor (Table 4).

      Figure 1. 

      Effects of (a) heptane, (b) chloroform, (c) methanol, (d) ethyl acetate and (e) water fractions of E. ganitrus leaves on the human cancer cell lines HeLa using MTT assay.

      Figure 2. 

      IC50 values of different extracts of E. ganitrus leaves against human cancer cell lines HeLa.

      Table 1.  Qualitative analysis of phytochemicals in E. ganitrus leaf extracts.

      Tested compounds Chloroform extractMethanol extract
      Steroids++
      Terpenoids++
      Saponins++
      Glycosides++
      Tannins++
      Flavonoids++
      Phenols++
      + → Present; − → Absent.

      Table 2.  GC–MS analysis of chloroform fraction of E. ganitrus leaves.

      Peak no.R. TimeAreaArea %Name
      17.32833924513.60Phenol, 2-methoxy-4-(2-propenyl)-
      27.4944325420.46Cyclododecane
      37.92550188745.32Bicyclo[7.2.0]undec-4-ene,4,11,11-trimethyl-8-methylene-
      48.3922645730.281,4,8-Cycloundecatriene, 2,6,6,9-tetramethyl-,(e,e,e)-
      59.13715685461.66Phenol, 3,5-bis(1,1-dimethylethyl)-
      610.01627271302.891-Heptadecene
      712.22129599333.141-Octadecene
      812.6701789630.19Neophytadiene
      912.7821478930.162-Pentadecanone, 6,10,14-trimethyl-
      1013.4961275110.147,9-Di-tert-butyl-1-oxaspiro(4,5)deca-6,9-diene-2,8-dione
      1113.59421053742.23Hexadecanoic acid, methyl ester
      1213.8011860960.20Isophytol
      1314.00325829872.74Dibutyl phthalate
      1414.2331264020.141-Nonadecene
      1515.1432629120.281-Octadecanol
      1615.1964093250.439,12-Octadecadienoic acid (z,z)-, methyl ester
      1715.25614188331.509,12,15-Octadecatrienoic acid, methyl ester, (z,z,z)-
      1815.39682671938.76P-menth-1-ene-3,3-d2
      1915.77642684864.53Cholest-24-ene, (5.alpha.,20.xi.)-
      2016.08118351251.95Behenic alcohol
      2117.0155746820.61Glycidyl palmitate
      2217.5023567620.384,8,12,16-Tetramethylheptadecan-4-olide
      2317.79215482661.64N-tetracosanol-1
      2418.5078929660.95Glycidyl oleate
      2518.6333870750.41Pentacosane
      2618.88511608121.23Hexadecanoic acid, 2-hydroxy-1-(hydroxymethyl)ethyl ester
      2718.94925201262.671,2-Benzenedicarboxylic acid
      2819.38317228801.83Hexacosyl pentafluoropropionate
      2919.9972957890.31Carbonic acid, propyl 3,5-difluophenyl ester
      3020.15216559811.76Tetracontane
      3120.2877183500.769-Otadecenoic acid (z)-, 2,3-dihydroxypropyl ester
      3220.43716334241.73Octadecanoic acid, 2,3-dihydroxypropyl ester
      3320.87585309029.04Carbonic acid, eicosyl prop-1-en-2-yl ester
      3421.22511697911.24 .alpha.-tocospiro b
      3521.37114757101.56 .alpha.-tocospiro b
      3621.56627907932.96Tetracosane
      3721.6195665540.601-Heptacosanol
      3821.9782082850.22Tetracontane
      3922.24431468313.34Tetracontane
      4022.3391988570.21Triacontyl acetate
      4122.7586025580.64 .gamma.-tocopherol
      4222.98737696614.00Tetracontane
      4323.0833075630.33Octacosanol
      4423.3688043680.852,5,7,8-Tetramethyl-2-(4,8,12-trimethyltridecyl)-3,4-dihydro-2h-chromen-6-yl hexofuranoside
      4523.83228257813.00Hexatriacontane
      4624.4422247490.24Ergost-5-en-3-ol
      4724.6971463260.162,6,10,15,19,23-Hexamethyl-tetracosa-2,10,14,18,22-pentaene-6,7-diol
      4824.81625792062.73Tetracontane
      4925.34444036834.67 .gamma.-sitosterol
      5025.8972474510.26Phenol, 2,4-bis(1,1-dimethylethyl)-, phosphite (3:1)
      5125.97110509901.11Tetracontane
      5227.36910622631.13Tetracontane
      5329.04944683384.74Benzenepropanoic acid, 3,5-bis(1,1-dimethylethyl)-4-hydroxy-,octadecyl ester
      5431.0618597260.91Tetrapentacontane
      5533.5056890170.73Tetrapentacontane
      5636.5155702640.60Tetrapentacontane

      Table 3.  GC–MS analysis of methanol fraction of E. ganitrus leaves.

      Peak no.R. timeAreaArea %Name
      14.56217160622.754h-pyran-4-one, 2,3-dihydro-3,5-dihydroxy-6-methyl-
      25.5451328910.211,5-Dimethyl-1-vinyl-4-hexenyl 2-aminobenzoate
      36.130664200.11E-6-octadecen-1-ol acetate
      46.658982694115.754-Hydroxy-3-methylacetophenone
      57.421592600.091-Undecanol
      67.7462900200.46Methyl2,3,6,7-tetra-o-acetyl-4-o-methyl-.beta.-glycero-d-glucoheptopyranoside
      78.93519327693.10Guanosine
      89.1785358220.861,3:2,5-Dimethylene-l-rhamnitol
      99.9494638700.74Octadecanoic acid
      1010.1442790410.451,2-Benzenedicarboxylic acid, diethyl este
      1110.37016839662.70 .alpha.-methyl-l-sorboside
      1210.60613007272.08 .alpha.-d-galactopyranoside, methyl
      1310.9202805730.45Butanoic acid, 3-methyl-, hexahydro-4- methylspiro[cyclopenta[c]pyran-7(1h),2'-oxirane]-1,6-diyl ester
      1411.090803800.13Tricyclo[7.2.0.0(2,6)]undecan-5-ol, 2,6,10,10-tetramethyl- (isomer 3)
      1511.2241616060.26 .alpha.-d-galactopyranoside, methyl
      1611.4921894850.30Octadecanoic acid, methyl ester
      1712.4372606340.422(4h)-benzofuranone, 5,6,7,7a-tetrahydro-6- hydroxy-4,4,7a-trimethyl-, (6s-cis)-
      1812.6431237680.20Neophytadiene
      1913.56528660454.59Hexadecanoic acid, methyl ester
      2013.780340440.051-hexadecen-3-ol, 3,5,11,15-tetramethyl-
      2113.910475350.08Silane, ethenylethyldimethyl-
      2214.555735350.12Pentadecanoic acid, methyl ester
      2315.18817688992.839,12-Octadecadienoic acid (z,z)-, methyl ester
      2415.24959714079.57(9e,12e)-9,12-octadecadienoyl chloride #
      2515.385793321212.711,1'-Bicyclohexyl, 2-methyl-, cis-
      2615.4819100731.46Methyl stearate
      2715.758823962913.21Cholest-24-ene, (5.alpha.,20.xi.)-
      2816.0753964310.64Methyl octadeca-9,12-dienoate
      2916.444772460.12Methyl 4-(dimethylamino)bicyclo[2.2.2]oct- 5-ene-2-carboxylate
      3016.612548090.09Hexadecanoic acid, 2-hydroxy-1-(hydroxymethyl)ethyl ester
      3116.9992156190.3517-octadecynoic acid
      3217.2492190610.35Eicosanoic acid, methyl ester
      3318.1272324800.37Oleoyl chloride
      3418.5093011250.48Undec-10-ynoic acid, undec-2-en-1-yl ester
      3518.7051353320.22Hexadecanoic acid, 1-(hydroxymethyl)-1,2-ethanediyl ester
      3618.89946078647.38Hexadecanoic acid, 2-hydroxy-1-(hydroxymethyl)ethyl ester
      3719.6551063120.17Hexadecanoic acid, methyl ester
      3820.3005806710.93Oleoyl chloride
      3920.4629943041.59Octadecanoic acid, 2,3-dihydroxypropyl ester
      4020.91235840275.749-octadecenamide
      4121.2252214500.35 .alpha.-tocospiro b
      4221.3783841650.62 .alpha.-tocospiro b
      4321.6261759730.28Eicosyl heptafluorobutyrate
      4421.803899870.14Hexacosanoic acid, methyl ester
      4522.7691609600.26 .gamma.-tocopherol
      4622.989867570.14Tetracontane
      4723.174924420.15Stigmast-5-en-3-ol, (3.beta.)-
      4823.38010301431.65Vitamin e
      4925.37212372631.98 .gamma.-sitosterol
      5027.0841838260.29Di-o-acetyltetrahydrostapelogenin

      Table 4.  Docking results of 81 phytoligands.

      S. no.Name of the ligandBinding free energy
      (kcal/mol)
      pKiLigand efficieny (kcal/mo/non-H atom)Torsional energy
      1Phenol, 2-methoxy-4-(2-propenyl)-–5.64.110.46671.2452
      2Cyclododecane–5.94.330.49170
      3Bicyclo[7.2.0]undec-4-ene,4,11,11-trimethyl-8-methylene-–6.64.840.440
      41,4,8-Cycloundecatriene, 2,6,6,9-tetramethyl-,(e,e,e)-–6.54.770.43330
      5Phenol, 3,5-bis(1,1-dimethylethyl)-–6.54.770.43330.9339
      61-Heptadecene–4.63.370.27064.3582
      71-Octadecene–42.930.24.0469
      8Neophytadiene–5.94.330.2954.0469
      92-Pentadecanone, 6,10,14-trimethyl-–5.43.960.28423.7356
      107,9-Di-tert-butyl-1-oxaspiro(4,5)deca-6,9-diene-2,8-dione–6.54.770.3250.6226
      11Hexadecanoic acid, methyl ester–4.93.590.25794.6695
      12Isophytol–4.93.590.23334.3582
      13Dibutyl phthalate–5.23.810.263.113
      141-Nonadecene–4.93.590.25794.9808
      151-octadecanol–53.670.26325.2921
      169,12-Octadecadienoic acid (z,z)-, methyl ester–53.670.23814.6695
      179,12,15-Octadecatrienoic acid, methyl ester, (z,z,z)-–5.43.960.25714.3582
      18P-Menth-1-ene-3,3-d2–4.93.590.490.3113
      19Behenic alcohol–4.73.450.20436.5373
      20Glycidyl palmitate–5.43.960.28423.7356
      214,8,12,16-Tetramethylheptadecan-4-olide–6.34.620.27393.7356
      22N-tetracosanol-1–4.43.230.1767.1599
      23Glycidyl oleate–4.63.370.19175.6034
      24Pentacosane–4.73.450.1886.8486
      25Hexadecanoic acid, 2-hydroxy-1-(hydroxymethyl)ethyl ester–4.63.370.26.226
      261,2-Benzenedicarboxylic acid–5.74.180.4751.2452
      27Carbonic acid, propyl 3,5-difluophenyl ester–6.14.470.40671.5565
      289-Octadecenoic acid (z)-, 2,3-dihydroxypropyl ester–53.670.26.5373
      29Octadecanoic acid, 2,3-dihydroxypropyl ester–4.93.590.1966.8486
      30Carbonic acid, eicosyl prop-1-en-2-yl ester–5.13.740.18896.8486
      31Tetracosane–4.93.590.20426.5373
      321-Heptacosanol–5.13.740.18218.0938
      33Triacontyl acetate–3.92.860.11479.339
      34Gamma.-tocopherol–6.84.990.22674.0469
      35Octacosanol–4.23.080.14488.4051
      362,5,7,8-Tetramethyl-2-(4,8,12-trimethyltridecyl)-3,4-dihydro-2h-chromen-6-yl hexofuranoside–7.25.280.17146.226
      37Ergost-5-en-3-ol–7.35.350.25171.8678
      382,6,10,15,19,23-Hexamethyl-tetracosa-2,10,14,18,22-pentaene-6,7-diol–64.40.18755.6034
      39Gamma.-sitosterol–96.60.32.1791
      404h-pyran-4-one,2,3-dihydro-3,5-dihydroxy-6-methyl-–53.670.50.6226
      411,5-Dimethyl-1-vinyl-4-hexenyl 2-aminobenzoate–6.44.690.322.4904
      42E-6-octadecen-1-ol acetate–4.73.450.21365.2921
      434-Hydroxy-3-methylacetophenone–5.74.180.51820.6226
      441-undecanol–4.53.30.3753.113
      45Methyl2,3,6,7-tetra-o-acetyl-4-o-methyl-.beta.-glycero-d-glucoheptopyranoside–5.54.030.19643.7356
      46Guanosine–6.84.990.26151.5565
      471,3:2,5-Dimethylene-l-rhamnitol–5.43.960.41540.3113
      48Octadecanoic acid–5.33.890.2655.2921
      491,2-benzenedicarboxylic acid, diethyl este–5.43.960.33751.8678
      50 .alpha.-methyl-l-sorboside–4.73.450.36151.8678
      51 .alpha.-d-galactopyranoside, methyl–5.23.810.41.8678
      52Butanoic acid, 3-methyl-, hexahydro-4- methylspiro[cyclopenta[c]pyran-7(1h),2'-oxirane]-1,6-diyl ester–6.84.990.22673.4243
      53Tricyclo[7.2.0.0(2,6)]undecan-5-ol, 2,6,10,10-tetramethyl- (isomer 3)–6.54.770.40620.3113
      54 .alpha.-d-galactopyranoside, methyl–5.33.890.40771.8678
      55Octadecanoic acid, methyl ester–4.13.010.19525.2921
      562(4h)-benzofuranone, 5,6,7,7a-tetrahydro-6- hydroxy-4,4,7a-trimethyl-, (6s-cis)-–6.54.770.46430.3113
      57Neophytadiene–53.670.254.0469
      58Hexadecanoic acid, methyl ester–4.93.590.25794.6695
      591-Hexadecen-3-ol, 3,5,11,15-tetramethyl-–5.74.180.27144.3582
      60Pentadecanoic acid, methyl ester–4.43.230.24444.3582
      619,12-Octadecadienoic acid (z,z)-, methyl ester–5.43.960.25714.6695
      62(9e,12e)-9,12-octadecadienoyl chloride #–4.73.450.2354.3582
      631,1'-bicyclohexyl, 2-methyl-, cis-–5.64.110.43080.3113
      64Methyl stearate–53.670.23815.2921
      65Cholest-24-ene, (5.alpha.,20.xi.)-–9.26.750.34071.2452
      66Methyl octadeca-9,12-dienoate–4.53.30.21434.6695
      67Methyl 4-(dimethylamino)bicyclo[2.2.2]oct- 5-ene-2-carboxylate–5.74.180.380.9339
      68Hexadecanoic acid, 2-hydroxy-1-(hydroxymethyl)ethyl ester–4.83.520.20876.226
      6917-octadecynoic acid–5.13.740.2555.2921
      70Eicosanoic acid, methyl ester–4.83.520.20875.9147
      71Undec-10-ynoic acid, undec-2-en-1-yl ester–5.13.740.21255.9147
      72Hexadecanoic acid, 2-hydroxy-1-(hydroxymethyl)ethyl ester–4.73.450.20436.226
      73Hexadecanoic acid, methyl ester–4.53.30.23684.6695
      74Oleoyl chloride–4.63.370.234.6695
      75Octadecanoic acid, 2,3-dihydroxypropyl ester–4.63.370.1846.8486
      769-octadecenamide–4.73.450.2354.6695
      77 .alpha.-tocospiro b–6.44.690.19394.3582
      78Eicosyl heptafluorobutyrate–5.64.110.16977.1599
      79Hexacosanoic acid, methyl ester–4.73.450.16217.7825
      80Stigmast-5-en-3-ol, (3.beta.)-–7.65.570.25332.1791
      81Vitamin e–7.15.210.2294.0469
      82Plumbagin–5.94.330.42140.3113
      83Sanguinarine–8.96.530.3560

      The absorption of drugs by the body is related to their pharmacokinetic properties and also cellular toxicity. The potency of the drug depends mostly on the pharmacokinetic parameters because ADME processes command the rate and extent of absorption when an administered dose of a drug approaches to its action site. Hence, in silico pharmacokinetic profile of filtered compounds was surveyed to gather the putative bioavailability data for receptor 6NJS. The cumulative findings for pharmacokinetics profiling, bioavailability data, drug-likeness properties and drug friendliness and toxicity effects of selected 26 phytoligands with known inhibitors (Plumbagin and Sanguinarine) are given in Tables 510. The prediction revealed that the six molecules (EG-9, EG-12, EG-13, EG-16, and EG-26) can be lead compounds for new drug candidates for anti-cancer phytomedicine. The Half maximal Inhibitory concentration of EG-13 was (IC50 = 254.29 µg/ml) further support our results (Fig. 3).

      Table 5.  Pharmacokinetics prediction of phytoligands established in E. ganitrus.

      S. no.Phytochemical
      Gastro- intestinal absorptionBlood-brain permeantP-glycoprotein substrateCYP450 1A2 inhibitorCYP450 2C19 inhibitorCYP450 2C9 inhibitorCYP450 2D6 inhibitorCYP450 3A4 inhibitorSkin permeation as log Kp (cm/s)
      EG-1Cholest-24-ene, (5.alpha.,20.xi.)-LowNoNoNoNoYesNoNo–1.02
      EG-2gamma.-sitosterolLowNoNoNoNoNoNoNo–2.65
      EG-3Stigmast-5-en-3-ol, (3.beta.)-LowNoNoNoNoNoNoNo–2.20
      EG-4Ergost-5-en-3-olLowNoNoNoNoNoNoNo–2.50
      EG-52,5,7,8-Tetramethyl-2-(4,8,12-trimethyltridecyl)-3,4-dihydro-2h-chromen-6-yl hexofuranosideLowNoNoNoNoNoNoYes–3.60
      EG-6Vitamin eLowNoYesNoNoNoNoNo–1.33
      EG-7GuanosineLowNoNoNoNoNoNoNo–9.37
      EG-8gamma.-tocopherolLowNoYesNoNoNoNoNo–1.51
      EG-9Butanoic acid, 3-methyl-, hexahydro-4- methylspiro[cyclopenta[c]pyran-7(1h),2'-oxirane]-1,6-diyl esterHighYesNoNoNoNoYesYes–6.18
      EG-10Bicyclo[7.2.0]undec-4-ene,4,11,11-trimethyl-8-methylene-LowNoNoNoYesYesNoNo–4.44
      EG-111,4,8-Cycloundecatriene, 2,6,6,9-tetramethyl-,(e,e,e)-LowNoNoNoNoYesNoNo–4.32
      EG-12Phenol, 3,5-bis(1,1-dimethylethyl)-HighYesNoNoNoNoYesNo–4.07
      EG-137,9-Di-tert-butyl-1-oxaspiro(4,5)deca-6,9-diene-2,8-dioneHighYesNoNoYesYesNoNo–5.28
      EG-142(4h)-benzofuranone, 5,6,7,7a-tetrahydro-6- hydroxy-4,4,7a-trimethyl-, (6s-cis)-HighYesNoNoNoNoNoNo–6.79
      EG-15Tricyclo[7.2.0.0(2,6)]undecan-5-ol, 2,6,10,10-tetramethyl- (isomer 3)HighYesNoNoYesYesNoNo–4.75
      EG-161,5-Dimethyl-1-vinyl-4-hexenyl 2-aminobenzoateHighYesNoNoYesYesNoNo–4.54
      EG-17alpha.-tocospiro bHighNoNoNoNoNoNoNo–3.90
      EG-184,8,12,16-Tetramethylheptadecan-4-olideLowNoNoYesNoYesNoNo–2.70
      EG-19Carbonic acid, propyl 3,5-difluophenyl esterHighYesNoYesYesNoNoNo–5.37
      EG-202,6,10,15,19,23-Hexamethyl-tetracosa-2,10,14,18,22-pentaene-6,7-diolLowNoNoYesNoYesNoNo–2.37
      EG-21CyclododecaneLowNoNoNoNoNoNoNo–4.42
      EG-22NeophytadieneLowNoYesNoNoYesNoNo–1.17
      EG-231,2-Benzenedicarboxylic acidHighNoNoNoNoNoNoNo–6.80
      EG-244-Hydroxy-3-methylacetophenoneHighYesNoYesNoNoNoNo–6.54
      EG-251-Hexadecen-3-ol, 3,5,11,15-tetramethyl-LowNoYesNoNoYesNoNo–2.41
      EG-26Methyl 4-(dimethylamino)bicyclo[2.2.2]oct- 5-ene-2-carboxylateHighYesNoNoNoNoNoNo–6.65
      PlumbaginHighYesNoYesNoNoNoNo–5.82
      SanguinarineHighYesYesYesYesNoNoNo–5.17

      Table 6.  Bioavailability prediction of phytoligands established in E. ganitrus.

      Phyto-ligands Bioavailability scoreWater solubility as logSiLOGPXLOGP3WLOGPMLOGPSILICOS-IT
      EG-10.55Poorly soluble as –6.255.1210.628.428.327.14
      EG-20.55Poorly soluble as –6.194.758.867.965.807.04
      EG-30.55Poorly soluble as –6.194.799.348.026.737.04
      EG-40.55Moderately soluble as –5.794.928.807.636.546.63
      EG-50.55Poorly soluble as –7.376.148.896.313.498.12
      EG-60.55Poorly soluble as –9.165.9210.708.846.149.75
      EG-70.55Very Soluble as 0.51–0.23–1.89–3.00–2.76–2.22
      EG-80.55Poorly soluble as –8.795.7610.338.535.949.20
      EG-90.55Soluble as –2.863.873.342.932.073.34
      EG-100.55Soluble as –3.773.294.384.734.634.19
      EG-110.55Soluble as –3.523.274.555.044.533.91
      EG-120.55Soluble as –4.252.864.913.993.873.81
      EG-130.55Soluble as –3.812.913.813.592.873.82
      EG-140.55Very Soluble as –1.821.881.001.411.491.86
      EG-150.55Soluble as –3.183.014.093.613.813.40
      EG-160.55Moderately soluble as –4.283.374.834.123.633.75
      EG-170.55Poorly soluble as –7.194.947.246.583.677.85
      EG-180.55Poorly soluble as –6.314.157.866.524.966.99
      EG-190.55Soluble as –3.592.843.173.732.912.81
      EG-200.55Poorly soluble as –6.306.119.388.776.019.10
      EG-210.55Soluble as –3.213.014.104.685.004.00
      EG-220.55Poorly soluble as –6.115.059.627.176.217.30
      EG-230.85Soluble as –1.140.600.731.081.200.61
      EG-240.55Very Soluble as –2.531.540.951.901.442.14
      EG-250.55Moderately soluble as –5.514.978.026.365.256.57
      EG-260.55Very Soluble as –1.352.701.311.451.771.11
      Plumbagin0.55Soluble as –2.851.792.291.720.592.22
      Sanguinarine0.55Poorly soluble as –6.09–0.044.453.432.723.85

      Table 7.  Drug-likeness prediction of phytoligands established in E. ganitrus.

      Phyto-ligandsLipinski
      rule
      Ghose
      filter
      Veber
      filter
      Egan
      filter
      Muegge
      filter
      EG-1YesNoYesNoNo
      EG-2YesNoYesNoNo
      EG-3YesNoYesNoNo
      EG-4YesNoYesNoNo
      EG-5YesNoNoNoNo
      EG-6YesNoNoNoNo
      EG-7YesNoNoNoNo
      EG-8YesNoNoNoNo
      EG-9YesYesYesYesYes
      EG-10YesYesYesYesYes
      EG-11YesYesYesYesYes
      EG-12YesYesYesYesNo
      EG-13YesYesYesYesYes
      EG-14YesYesYesYesNo
      EG-15YesYesYesYesNo
      EG-16YesYesYesYesYes
      EG-17YesNoNoNoNo
      EG-18YesNoNoNoNo
      EG-19YesYesYesYesYes
      EG-20YesNoNoNoNo
      EG-21YesYesYesYesNo
      EG-22YesNoNoNoNo
      EG-23YesNoYesYesNo
      EG-24YesNoYesYesNo
      EG-25YesNoNoNoNo
      EG-26YesYesYesYesYes
      PlumbaginYesYesYesYesNo
      SanguinarineYesYesYesYesYes

      Table 8.  Medicinal chemistry prediction of phytoligands established in E. ganitrus.

      SI. No.PAINS structural alertBrenk structural alertLead-
      likeness
      Synthetic accessibility score
      EG-10125.61
      EG-20126.42
      EG-30126.30
      EG-40126.17
      EG-50037.10
      EG-60035.17
      EG-70003.86
      EG-80035.00
      EG-90225.59
      EG-100124.51
      EG-110123.66
      EG-120021.37
      EG-130014.35
      EG-140013.63
      EG-150023.77
      EG-160212.91
      EG-170036.76
      EG-180024.12
      EG-190112.23
      EG-200135.52
      EG-210022.21
      EG-220124.08
      EG-230011.00
      EG-240011.00
      EG-250123.89
      EG-260114.38
      Plumbagin2012.41
      Sanguinarine0212.59

      Table 9.  Toxicity prediction of phytoligands established in E. ganitrus.

      Phyto-ligandsLD50 (mg/kg)Toxicity classHepatotoxicityCarcinogenicityImmunotoxicityMutagenicityCytotoxicity
      EG-150005InactiveInactiveActiveInactiveInactive
      EG-28904InactiveInactiveActiveInactiveInactive
      EG-38904InactiveInactiveActiveInactiveInactive
      EG-48904InactiveInactiveActiveInactiveInactive
      EG-530005InactiveInactiveActiveInactiveInactive
      EG-650005InactiveInactiveInactiveInactiveInactive
      EG-7132InactiveInactiveInactiveInactiveInactive
      EG-850005InactiveInactiveInactiveInactiveInactive
      EG-980006InactiveActiveInactiveActiveInactive
      EG-1053005InactiveInactiveActiveInactiveInactive
      EG-1136505InactiveInactiveInactiveInactiveInactive
      EG-128004InactiveInactiveInactiveInactiveInactive
      EG-139004InactiveInactiveInactiveInactiveInactive
      EG-14342InactiveActiveInactiveInactiveInactive
      EG-1520505InactiveInactiveInactiveInactiveInactive
      EG-1642505InactiveInactiveInactiveInactiveInactive
      EG-173003InactiveInactiveInactiveInactiveActive
      EG-1844005InactiveInactiveInactiveInactiveInactive
      EG-1915004InactiveInactiveInactiveInactiveInactive
      EG-2043005InactiveInactiveInactiveInactiveInactive
      EG-217503InactiveActiveInactiveInactiveInactive
      EG-2250506InactiveInactiveInactiveInactiveInactive
      EG-2325305InactiveInactiveInactiveInactiveInactive
      EG-2428305InactiveInactiveInactiveInactiveInactive
      EG-253404InactiveInactiveInactiveInactiveInactive
      EG-2620004InactiveInactiveInactiveInactiveInactive
      Plumbagin162InactiveActiveInactiveActiveInactive
      Sanguinarine7784InactiveActiveActiveActiveInactive

      Table 10.  Bioavailability prediction of phytoligands established in E. ganitrus.

      Phyto-ligandLipophilicity
      (XLOGP3)
      Size
      (MW g/mol)
      Polarity
      (TPSA)
      Insolubility
      [Log S (ESOL)]
      Insaturation
      (Fraction Csp3)
      Flexibility
      (Num. rotatable bonds)
      EG-93.34368.4674.36–3.700.908
      EG-124.91206.3220.23–4.380.572
      EG-133.81276.3743.37–3.820.652
      EG-154.09222.3720.23–3.801.000
      EG-164.83273.3752.32–4.340.357
      EG-261.31209.2829.54–1.760.753
      Plumbagin2.29188.1854.37–2.770.090
      Sanguinarine4.45332.3340.80–5.240.150

      Figure 3. 

      IC50 values of EG-13 phytochemical of E. ganitrus leaves against human cancer cell lines HeLa.

      In Table 5, for pharmacokinetics prognostication, the gastrointestinal (GI) absorption rate was fetched for all preferred six phytoligands and both reference drugs. The blood-brain permeability was seen as positive for all the six phytoligands and both reference drugs. The prediction of bioavailability (Table 6) demonstrated that similar bioavailability scores were observed for all the filtered six phytoligands (0.55) like reference drugs. The water solubility data showed all the six compounds and plumbagin are soluble while Sanguinarine is poorly soluble. For drug-likeness prediction (Table 7), all the six compounds and both known inhibitors were obtained suitable for the Lipinski rule as zero violation. For Ghose, Veber, and Egan filter 0 violation was obtained for all the six phytoligands and both inhibitors. In the case of medicinal chemistry friendliness prediction (Table 8), the PAINS structural alert obtained 0 violations for all the six phytoligands and sanguinarine while two alerts for plumbagin. Table 9 shows EG-9 belongs to the non-toxic class VI, EG-15, and EG-16 also belong to the non-toxic class V, EG-12, EG-13, EG-26 and Sanguinarine belongs to the less toxic class IV while plumbagin belongs to the high-toxic class II. The bioavailability radar (Fig. 3) for phytoligands depicting bioavailability prognostic showed that all six phytoligands were found within the data range of lipophility nature (−0.7 < XLOGP3 < +5.0), molecule size (150 g/mol < MW < 500g/mol), polarity (20 Ų < TPSA < 130Ų), insolubility [−6 < LogS (ESOL) < 0], insaturation (0.25 < Fraction Csp3 < 1) and flexible bonds (0 < Num. rotatable bonds < 9) and colored part of radar while known inhibitors plumbagin and sanguinarine does not fit the bioavailability radar (Table 10). As mentioned in Table 5, all the phytoligands and reference compounds have higher gastrointestinal (GI) absorption rates, therefore they can instantly be absorbed by the human intestine. All phytoligands have the ability to pass the blood brain barrier (BBB permeant) and values for the aqueous solubility (log S) of the phytochemicals fall in the recommended range that is −1 to −5[29], thus, have improved absorption and distribution properties. The bioavailability scores were identical for all six molecules, standing at 0.55, similar to the reference drugs. In drug-likeness prediction, none of the six compounds and both known inhibitors violated the Lipinski rule, Ghose, Veber, and Egan filters. Regarding medicinal chemistry friendliness, the PAINS structural alert identified zero violations for all six phytoligands and Sanguinarine, whereas Plumbagin had two alerts. Table 9 revealed that EG-9 belonged to the non-toxic class VI, while EG-15 and EG-16 were in harmless class V. Other compounds EG-12, EG-13, EG-26 and sanguinarine was from less harmful class IV which could be modified to a non-toxic class during the lead optimization stage of drug discovery[30] while selected standard plumbagin showed high toxic class II. Drug-induced hepatotoxicity often lead to abrupt liver failure and drug rejections[31]. Drug-induced liver injury might be long-term or occur only once. Obviously, the selected compounds and standards are non-hepatotoxic. The bioavailability radar (Fig. 4) depicted that all six phytoligands were within the data range for oral bioavailability prediction. Conversely, standards plumbagin and sanguinarine did not fit within the bioavailability radar. The pink area shown in the radar corresponds to the most promising zone for all the bioavailability properties. In Table 10, all the phytochemicals satisfied 150 g/mol and 500 g/mol criteria for (SIZE) of good drug candidates. The polarity (POLAR) was observed with the Total Polarity Surface Area (TPSA) and all the phytochemicals show good TPSA values. Besides, the flexibility (FLEX) property evaluated by the number of rotatable bonds falls within the recommended range. Lipophilicity (LIPO) and insolubility (INSOLU) were evaluated and come in the range The Unsaturation (INSATU) was calculated using Fraction Csp3 falls within a recommended range of 0.25 < Fraction Csp3 < 1) for all phytoligands. However, Plumbagin and Sanguinarine exhibit lower values (0.09 and 0.15, respectively).

      Figure 4. 

      Bioavailability radar (pink area exhibits optimal range of particular property) for leading phytocompounds molecules. LIPO = lipophilicity as XLOGP3, SIZE = size as molecular weight, POLAR = polarity as TPSA (topological polar surface area), INSOLU = insolubility in water by log S scale, INSATU = insaturation as per fraction of carbons in the sp3 hybridization, and FLEX = flexibility as per rotatable bonds.

      2D and 3D interactions of the five phytoligands (EG-9, EG-12, EG-13, EG-15, EG-16 and EG-26) with 6njs are shown in Table 11. EG-9 divulged two assenting hydrogen bond interactions at the active site having amino acids of Glu96 and Lys97. In additon to that a non-classical C-H bond Vander Waals interaction was also noticed at the active site involving Arg93 residue and alkyl and pi-alkyl interactions were observed at Leu525 and Trp501 respectively. In EG-12 a conventional hydrogen bond interaction was observed at Asn538, a pi-pi T-shaped, two alkyl and a pi-alkyl interactions were observed at Tyr539, Ile522, Trp501 and Leu525 respectively. EG-13 showed one favorable hydrogen bond interaction and two hydrophobic alkyl interactions at the active site with the residue of Glu96, Leu95 and Lys97 respectively. EG-15 showed two alkyl and two pi-alkyl interactions at the active site of the residues of Leu95, Ile522, Trp501 and Tyr539 respectively. In EG-16 two conventional hydrogen bonds were observed at Leu731 and Thr716. EG-26 formed three favorable hydrogen bonds with Asp369, Asp370 and Asp371 at the active site of the receptor. Plumbagin showed a conventional hydrogen bond interaction, a pi-pi T-shaped and a carbon-hydrogen bond interaction at Tyr539, Trp501 and Ser540 respectively. Sanguinarine showed a carbon hydrogen bond, a pi-sigma, a alkyl, and a pi-alkyl interaction at the site of Glu696, Leu731, Pro769 and Pro695 respectively (Table 11). Previously it has been shown that residue at 97 could have amprospective ubiquitin acceptor position in STAT3 NH2 terminal domain, suggesting lysine amino acid may have a significant role and location in a sumolation/ubiquitination consensus sequence[32]. The majority of phytoligand interactions exist in the Linker domain and Transactivation domain of the STAT3.

      Table 11.  2D and 3D binding interactions between the receptor 6NJS and molecules.

      Phyto-ligands2D- Binding interaction3D- Binding interaction
      EG-9 (-6.8)
      EG-12 (-6.5)
      EG-13 (-6.5)
      EG-15 (-6.5)
      EG-16 (-6.4)
      EG-26
      (-5.7)
      Plumbagin
      Sanguinarine
    • All the six compounds (EG-9, EG-12, EG-13, EG-15, EG-16 and EG-26) significantly bind with STAT3. The phytochemicals epitomized good in silico results as reflected by their promising binding affinity, considerable inhibitory constant with optimum protein-ligand stabilization energy. Consecutively, binding signifies that phytoligands interact with STAT3 by the NH2 terminal and boosts its transcriptional activity and interferes with the cellular proliferation process and apoptosis[32]. Bioavailability radar and toxicological profiles of the preferred phytoligands revealed that these compounds compel to have ample drug likeliness properties. Moreover, EG-9, EG-13, EG-15, EG-16 and EG-26 have not been explored for their anticancer potential and can be derivatized or have the probability of being used as lead compounds.

    • The authors confirm contribution to the paper as follows: study design and draft manuscript preparation (equal): Mehnaj, Bhat AR, Athar F; supervision: Athar F; experimentation and writing of manuscript: Mehnaj; characterization and editing: Bhat AR. All authors reviewed the results and approved the final version of the manuscript.

    • This study involved the use of established human cell lines. The cell lines used in this research were obtained from the National Centre for Cell Sciences (NCCS), Pune, India and were used in accordance with institutional and national ethical standards. The cell lines have been previously published or validated, and no new human tissues were used in this study.

    • The supplementary data will be made available by the authors to all upon reasonable request.

    • Miss Mehnaj is grateful to UGC for obtaining the non-NET fellowship allowing completion of this work.

      • The authors declare that they have no conflict of interest.

      • Copyright: © 2024 by the author(s). Published by Maximum Academic Press, Fayetteville, GA. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
    Figure (4)  Table (11) References (32)
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    Mehnaj, Bhat AR, Athar F. 2024. In silico exploration of Elaeocarpus ganitrus extract phytochemicals on STAT3, to assess their anticancer potential. Medicinal Plant Biology 3: e009 doi: 10.48130/mpb-0024-0010
    Mehnaj, Bhat AR, Athar F. 2024. In silico exploration of Elaeocarpus ganitrus extract phytochemicals on STAT3, to assess their anticancer potential. Medicinal Plant Biology 3: e009 doi: 10.48130/mpb-0024-0010

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