INTRODUCTION:

Herbal plants can produce compounds or secondary metabolites. It has been widely used as preservatives, food flavoring, and traditional medicine for thousands of years. Currently, it is essential to know the biological activities and direct benefits to humans, especially traditional medicines that will be marketed and processed with industrial standards. Ginger in previous studies has antioxidant-like activity¹.

Ginger is commonly used as an anti-vomiting drug in cancer patients². Zingiber officinale is commonly used as a spice in a wide range of foods and beverages³. Cancer is the leading cause of death in 57 countries globally, such as Australia, China, Europe, America, and others⁴. The active compounds found in Zingiber officinale are gingerol, zingerone, and shogaol⁵. 6-gingerol is effective in influencing the inflammatory process that causes carcinogenesis⁶.

Gingerol carbon chains containing hydroxyl and carbonyl groups have increased activity. The glycosylation of shogaol phenolic hydroxyl groups boosted the inhibitory effect against melanogenesis⁷. Primary metabolites are basically needed for plant growth and development⁸^,⁹.

Shogaol has also been shown to exhibit anticancer activity against breast cancer through reduced inhibition of cell invasion matrix metalloproteinase^9,¹⁰. In vitro studies showed positive results, namely ginger has activity against cardiovascular disease, inflammation, hyperlipidemia, and hypertension¹¹.

Arbuscular Mycorrhizal Fungi (AMF) grow on host plants, this mutually beneficial relationship between plants and fungi increases the rate of photosynthesis and gas exchange¹². This pathway is formed through hyphal fusion (anastomosis) and the exchange of genetic material¹³. Our study aimed to determine Cytotoxic Activity and Phytochemical Study of Arbuscular Mycorrhizal Fungi Induced Red Ginger. When a molecule is being investigated for drug development, it is a time-consuming, multidisciplinary process¹⁴^,¹⁵. Microorganisms, cells, and biological molecules are studied outside of their natural biological context in in vitro investigations¹⁶^,¹⁷^,¹⁸.

In silico method is a new trend in developing new drugs using Artificial Intelligence (AI), databases, and big data. This method can simulate structure from natural compounds to clarify their interactions and ability at active target sites¹⁹. It can help understand physical and chemical properties much more quickly and effectively screen new drug candidates²⁰^,²¹^,²². According to computer models, Zingiber officinale has a potential antioxidant activity, anti-inflammatory effect, influences TLR6 and pathways suppress inflammatory mediators, including serotonin and prostaglandins²³^,²⁴.

The purpose of this study was to conduct an initial in silico and in vitro screening of Zingiber officinale var. Rubrum as an anticancer treatment. The computational method is expected to see the potential for bonding between ligands and proteins, physicochemical properties, and drug-likeness. Molecular docking uses a receptor protein that plays a role in the action of the drug tamoxifen.

MATERIALS AND METHODS:

In Silico Prediction:

Analysis of Physical Chemical Properties and Geometry Optimization:

Active compound from Zingiber officinale var. Rubrum, namely 6-Gingerol and 6-shogaol²⁵ were analyzed computationally to see physics and chemistry and determine the rule of five using the SWISS ADME Web Server (www.swissadme.ch)²⁶. The molecular structure of the test compound was drawn using Marvin Sketch, then optimized geometry using Avogadro software by selecting Force Field MMFF94²⁷

Docking Preparation:

The target macromolecule used in this study was obtained from the website (www.rcsb.org), it is a receptor recognition and the antagonism of this interaction by tamoxifen with PDB ID (3ERT)²⁸. Preparation using software Autodok Vina Version 1.2.3 (2021)²⁹^,³⁰ and MGLTools version 1.5.7 (2019). This stage of preparation of target macromolecules is carried out by removing water molecules and natural ligands and adding hydrogen atoms and Gasteiger Charge and marge non polar¹⁹. Molecular Docking Using Autodock Vina software with center X= 30.412, Y = -1.913, Z = 24.207 and size X = 32 Y= 18 Z = 30 and exhaustiveness = 32.

Identification of Molecular Docking Simulation Results:

The results of the molecular docking simulation using Autodock Vina were selected from the minimum bond free energy, then analyzed for each residue involved, and the molecular interactions formed between the macromolecules and the molecules of the test compound. Amino acid residues that play a role in the molecular interactions formed were analyzed for the type of bond using the BIOVIA Discovery Studio Version 2020¹⁹.

In vitro Cytotoxic Activity:

Extraction:

The plant material was sliced and dried for three days, then oven-dried at 40°C for 24 hours. Dried rhizomes are ground into a fine powder using a grinder. 2 kg ginger rhizome powder was macerated in 7 L 70% ethanol for three days. This process is repeated three times. The ethanol extract was evaporated and concentrated with a rotary evaporator at a temperature of 40°C. The resulting extract is stored in the refrigerator. It was dried under pressure using a rotary evaporator. Then it was dissolved in DMSO (Sigma) at 100 μg/mL.

Cytotoxic Assay and Cell Viability:

The breast cancer cell line T47D was cultured in RPMI with 10% complete medium (Gibco). The medium contained 10% heat-activated fetal bovine serum, 100 μg/ml streptomycin, and penicillin G. Cell lines were subjected to 37ºC in a 5% CO2 incubator. Cells were seeded into 96-well plates (Nunc, Denmark), precultured for 24 h, and treated with Ginger-Ethanolic Extract (MGE) for 48 h. Cell cytotoxicity was analyzed by MTT test, i.e., 20 μL extract at a concentration of 0.1 μg /mL; 1.0 μg/mL; 10 μg/mL; 100 μg/mL completely dissolved in DMSO was added to a 180 μL cell suspension in RPMI medium. After incubation for 24 hours, 20 μL of MTT reagent (Merck, Germany) in phosphate buffer saline (PBS) was added to each well. The plate was incubated at 37ºC, the medium was removed, and a purple precipitate formed in a cell was then dissolved in 100 L of DMSO. The absorbance was measured at a wavelength of 550 nm with an Automated Microplate Reader (Bio-Teck), and cell death was calculated. Cell viability was analyzed with a trypan blue stain. After 24 h incubation, the cultures were observed under the microscope, and the morphological changes of the cells were identified.

Determination of gingerol:

The determination content of gingerol on MGE was carried out by TLC densitometry. The maximum wavelength of (6)-gingerol obtained is 525 nm, the r-value of the standard calibration curve equation (6)-gingerol is close to 1. The eluent that gives the best separation in MGE TLC is n-hexane-ethyl acetate (13:7) with an Rf value of 0.3.

Data Analysis:

The connection between the concentration of the test solution with cell viability is shown in graphical form and the determined IC₅₀ (concentration that inhibits 50% living cells) of the test solution. The experiments were repeated three times, and the data were presented as the mean ± SD. Data processing using ways analysis of variance (ANOVA) followed by analysis Duncan's multiple range test.

RESULT AND DISCUSSION:

In Silico Prediction:

6-Gingerol and 6-shogaol predicted physicochemical properties, pharmacokinetics (Table 1), and drug-likeness. These two compounds are drugs that can be absorbed orally according to Lipinski's rule of five. The solubility of these two compounds is moderately soluble. Drug solubility is considered a basic property that should be evaluated in the early stages of drug discovery. Due to the highly complex procedure for detecting solubility in water, computational predictions were made. The pharmacokinetic aspect of this compound has a high GI absorption, can pass through the BBB, and is metabolized in CYP1A2 and CYP2D6. Geometry optimization is carried out to find the minimum energy³¹, conformation using the MMFF94 force field. In a combined "organic/protein" force field that is equally relevant to proteins and other biological systems, MMFF94 aims to attain MM3-like accuracy for small molecules²⁷.

Validation is carried out first using the redocking method with an assessment of the RMSD value. RMSD serves to evaluate the docking program in producing poses that are close to the original conformation. The RMSD reference that we use in this study is 2.0 Å³². The result of redocking is that the energy of RMSD protein with its native ligand is 1.28 with affinity energy -9.653 (kcal/mol), the RMSD is at the recommended value. The bond energy taken is the most negative because it is a strong interaction between the ligand and protein. Based on the results of gibbs free energy, the best compounds were selected that could inhibit the receptor by spontaneously forming binding energy, which was indicated by a decrease in negative Gibbs Energy. The compound having the minimum affinity is 6-Gingerol with value -7.686 (kcal/mol) (Table 2). Hydrogen bonding is an interaction that occurs between 2 molecules, one of which acts as a donor and the other as an acceptor.

Table 2. Score Gibs free energy and Interaction with Residue

Compound

Gibbs free energy (kkal/mol)

Residue

Interaction With Residue

6-Gingerol

-7.686

Gly420, His524, Met343, Leu525, Val418, Ala350, Leu349, Arg394, Glu353, Gly521, Leu346, Leu391, Phe404, Leu387, Leu428

Hydrogen Bond: Arg394, Glu353, Ala350.

π-Alkil: Leu525, Leu346

6-Shogaol

-7.279

Gly521, Ile424, Met343, Leu391, Leu525, Leu384, Arg394, Glu353, Trp383, Met388, Met421, Phe404, Leu349, Leu346, Leu387, Ala350

Hydrogen Bond: Arg394.

π-Alkyl: Met421, Met388

Molecular docking simulations were carried out using MGLTools 1.5.7 Autodock vina software to observe the best affinity between the two molecules of the test compound and identify and evaluate the molecular interactions that occur on macromolecules receptor recognition and the antagonism of this interaction by tamoxifen. The program thoroughly examines the ligand's rotational space in relation to the receptors. A molecular docking research was carried out to determine how they interacted with the target location²¹.The ligand-receptor binding model with the best confirmation due to molecular bonding was selected and compared based on the value of the free bond energy. The minimum binding free energy value is at 6-gingerol, predicting better binding to the receptor. These variables have a crucial impact in a compound's biological function³¹.

Table 3. Absorbance viability of cells on each plate was treated with MGE

No	Blank	Control	Concentration (microgram/mL)
No	Blank	Control	100	10	1	0.1
1	0.075	1.531	0.463	0.805	0.887	1.057
2	0.082	1.528	0.443	0.879	0.966	1.063
3	0.079	1.556	0.452	1.025	1.053	1.112
4	0.082	1.438	0.451	0.884	1.037	1.062
Average	0.080	1.513	0.455	0.898	0.986	1.074
Standard Deviation	0.003317	0.051713	0.00556	0.091896	0.075918	0.025801
		Log Concentration	2	1	0	-1
		% cell viablility	26.17	57.11	63.21	72.33

Figure 1. Identification of interaction 6-Gingerol and 6-Shogaol with protein

Figure 1 shows the molecular interactions between 6-gingerols, 6-Shogaol, and proteins. The interactions between the 6-gingerols consist of 3 hydrogen bond in amino acid such as Arg394, Glu353, and Ala350, and two π-Alkyl bonds in Leu525, Leu346. The ability of gingerols in tumor cells is to convert conjugated molecules into free forms with the help of glucuronidase, which acts selectively on tumor tissue³³. 6-Shogaol has one Hydrogen Bond on Arg394, and have two π-Alkyl bonds on Met421, Met388. Hydrogen bonding is a specific interaction that plays an essential role in the ligand-receptor interaction process. hydrogen bonds also contribute to the affinity of a molecule for the target protein³⁴. 6-Shogaol has the potential to be used as an antimetastatic treatment. This compound is capable of reducing matrix metalloproteinase-9 expression via blockade of nuclear factor-κB activation¹⁰. Active site analysis can be predicted using software, it can be analyzed using software namely LIGSITE. It is an online tool for predicting various active sites in a protein²².

In vitro Cytotoxic Activity

The effect of Ginger-Ethanolic Extract (MGE) on the T47D breast cancer cell line was determined by MTT Assay. The examination of the cytotoxicity effect of MGE in multiple concentrations on human breast cancer T47D. The effective concentration was calculated from the concentration-response curve. The absorbance of the viability of each plate is shown in Table 3. The MTT assay found that MGE had a cytotoxic activity with Inhibitory Concentration (IC₅₀) 16.51 ± 3.67 μg/mL (Figure 2). This result is slightly lower than previous studies on large white ginger with an IC₅₀ value of 12.25 μg/mL³⁵. At a dosage of 40 μg/mL, the optimized extract shown more significant anticancer effects in HeLa cancer cells, with no damage to normal cells²⁵. In vitro bioassay is well-known and commonly used to evaluate sunscreen efficacy in synthetic and herbal products/formulations. It is simple, rapid, sensitive, reliable, validated, and affordable.

Morphological changes evaluation upon treatment with extract. Figure 3 shows a different image when viewed with a microscope, where the difference in concentration shows a different morphological form compared to the control. At concentrations of 0.1 μg/mL and 1.0 μg/mL, and 10 μg/mL, many cells grew and adhered to the bottom of the flask. It has grown very close together, and the distance from one cell to another is minimal. There was almost no difference compared to the control. On the other hand, at a concentration of 100 μg/mL, cells were seen to be smaller than the concentrations of 0.1 and 1.0 μg/mL and 10 μg/mL, cells were seen in small groups, and the distance between groups of cells and other cells was far from each other No cell nucleus is visible, it shows a low absorbance value.

Figure 2. Dose-response relationship of MGE with the percent viability of T47D breast cancer cell line (24h)

a) b)

c) d)

Figure 3. Morphological profile of the T47D cells after treated with MGE at concentration 0.1 μg/mL, 1.0 μg/mL, 10 μg/mL and 100 μg/mL (b, c, d, e) compared to control (a) for 24 hours. (100 x enlargement).

CONCLUSION:

The active compound of Zingiber officinale var. Rubrum is predicted to be taken orally. Prediction of hydrogen bonding at 6-Gingerol in the amino acids Arg394, Glu353, Ala350. Hydrogen bonding in shogaol on the amino acid Arg394. MGE has cytotoxic activity with Inhibition concentratin (IC₅₀) was 16.51 ± 3.67 µg/mL. The results showed that the MGE was potential as herbal medicine for cancer-related ailments.

CONFLICT OF INTEREST:

The authors have no conflicts of interest regarding this investigation

ACKNOWLEDGMENTS:

The research funding by the Ministry of Research and Technology-National Agency for the Research and Innovation Republic of Indonesia through National Research Priority with the contract number 92/E1/PRN/2020.

REFERENCES:

1. Ghlissi Z. Atheymen R. Ali Boujbiha M. Sahnoun Z. Ayedi FM. Zeghal K. et al. Antioxidant and androgenic effects of dietary ginger on reproductive function of male diabetic rats. Int J Food Sci Nutr. 2013;64(8):974–8. doi.org/10.3109/09637486.2013.812618

2. Ravindran PN. Babu KN. Ginger: The genus Zingiber. Ginger: The Genus Zingiber. CRC Press; 2016. 1–576 p.

3. Baliga MS. Latheef L. Haniadka R. Fazal F. Chacko J. Arora R. Ginger (Zingiber officinale Roscoe) in the Treatment and Prevention of Arthritis. Bioact Food as Interv Arthritis Relat Inflamm Dis. 2013;529–44. doi.org/10.1016/B978-0-12-397156-2.00199-X

4. Bray F. Laversanne M. Weiderpass E. Soerjomataram I. The ever-increasing importance of cancer as a leading cause of premature death worldwide. Cancer. 2021;127(16):3029–30. doi.org/10.1002/cncr.33587

5. Srinivasan K. Ginger rhizomes (Zingiber officinale): A spice with multiple health beneficial potentials. PharmaNutrition. 2017;5(1):18–28. doi.org/10.1016/j.phanu.2017.01.001

6. Bode AM. Ma WY. Surh YJ. Dong Z. Inhibition of epidermal growth factor-induced cell transformation and activator protein 1 activation by [6]-gingerol. Cancer Res. 2001;61(3):850–3.

7. Yamauchi K. Natsume M. Yamaguchi K. Batubara I. Mitsunaga T. Structure-activity relationship for vanilloid compounds from extract of Zingiber officinale var rubrum rhizomes: effect on extracellular melanogenesis inhibitory activity. Med Chem Res. 2019;28(9):1402–12. doi.org/10.1007/s00044-019-02380-y

8. Rangasamy P. Hansiya VS. Maheswari PU. Suman T. Geetha N. Phytochemical Analysis and Evaluation of In vitro Antioxidant and Anti-urolithiatic Potential of various fractions of Clitoria ternatea L. Blue Flowered Leaves. Asian J Pharm Anal. 2019;9(2):67. doi.org/10.5958/2231-5675.2019.00014.0

9. Rebecca. Kumar R. Swamy VN. Formulation and in vitro Evaluation of Mouth Dissolving Tablets of Labetalol HCl by Sublimation Method . Asian J Pharm Technol. 2016;6(2):70. doi.org/10.5958/2231-5713.2016.00010.6

10. Ling H. Yang H. Tan SH. Chui WK. Chew EH. 6-Shogaol, an active constituent of ginger, inhibits breast cancer cell invasion by reducing matrix metalloproteinase-9 expression via blockade of nuclear factor-κB activation. Br J Pharmacol. 2010;161(8):1763–77. doi.org/10.1111/j.1476-5381.2010.00991.x

11. Singletary K. Ginger: An overview of health benefits. Nutr Today. 2010;45(4):171–83. doi.org/10.1097/NT.0b013e3181ed3543

12. Birhane E. Sterck FJ. Fetene M. Bongers F. Kuyper TW. Arbuscular mycorrhizal fungi enhance photosynthesis, water use efficiency, and growth of frankincense seedlings under pulsed water availability conditions. Oecologia. 2012;169(4):895–904. doi.org/10.1007/s00442-012-2258-3

13. Chagnon PL. Ecological and evolutionary implications of hyphal anastomosis in arbuscular mycorrhizal fungi. FEMS Microbiol Ecol. 2014;88(3):437–44. doi.org/10.1111/1574-6941.12321

14. Sindhu TJ. Arathi . K.N. Akhilesh K. Jose A. Binsiya KP. Thomas B. et al. Antiviral screening of Clerodol derivatives as COV 2 main protease inhibitor in Novel Corona Virus Disease: In silico approaches. Asian J Pharm Technol. 2020;10(2):60. doi.org/10.5958/2231-5713.2020.00012.4

15. Nirmala D. Durga L. Sudhakar M. Formulation and In Vitro Characterisation of Capecitabine Gastro Retentive Floating Tablets. Asian J Pharm Technol. 2019;9(3):154. doi.org/10.5958/2231-5713.2019.00026.6

16. Waghmare RA. Synthesis and In Vitro Anti-inflammatory Activity of 5-arylidene-1-[(2 (Methyl suphonyl amino) thiazol-4-yl) methyl]-2-thioxoimidazolidin-4-ones. . Asian J Res Chem. 2017;10(6):739. doi.org/10.5958/0974-4150.2017.00125.0

17. Rahmani Z. Douadi A. Rahmani Z. in Vitro Inhibition of a-Amylase Enzyme, Phytochemical Study and Antioxidant Capacity for Cupressus Sempervirens Extracts Growing in Arid Climat. Asian J Res Chem. 2019;12(6):359. doi.org/10.5958/0974-4150.2019.00068.3

18. Zeroual S. Daoud I. Gaouaoui R. Ghalem S. In vitro and Molecular Docking Studies of DPPH with Phoenix dactylifera L. (Deglet-Nour) Crude Fruits extracts and Evaluation of their Antioxidant Activity . Asian J Res Chem. 2020;13(1):52. doi.org/10.5958/0974-4150.2020.00012.7

19. Putra PP. Armin F. Florida N. Yusuf GV. Suharti N. Molecular Dynamics, Prediction of Toxicity, and Interaction of the Active Compound Caesalpinia sappan on Essential Lipids Klebsiella pneumoniae. 2021;(November). doi.org/10.2991/ahsr.k.211105.044

20. Putra PP. Fauzana A. Lucida H. In Silico Analysis of Physical-Chemical Properties, Target Potential, and Toxicology of Pure Compounds from Natural Products. Indones J Pharm Sci Technol. 2020;7(3):107. doi.org/10.24198/ijpst.v7i3.26403

21. Hemalatha K. Selvin J. Girija K. Synthesis, In silico Molecular Docking Study and Anti-bacterial Evaluation of some Novel 4-Anilino Quinazolines. Asian J Pharm Res. 2018;8(3):125. doi.org/10.5958/2231-5691.2018.00022.9

22. Rani V. Lal N. In silico drug designing for Jaundice. Res J Sci Technol. 2017;9(1):155. doi.org/10.5958/2349-2988.2017.00025.0

23. Zammel N. Saeed M. Bouali N. Elkahoui S. Alam JM. Rebai T. et al. Antioxidant and Anti-Inflammatory Effects of Zingiber officinale roscoe and Allium subhirsutum: In Silico, Biochemical and Histological Study. Foods. 2021;10(6):1383. doi.org/10.3390/foods10061383

24. Bhavani A. Hemalatha B. Padmalatha K. Formulation development and in vitro Evaluation of sustained release matrix tablets of Cefpodoxime proxetil. Asian J Pharm Technol. 2021;273–8. doi.org/10.52711/2231-5713.2021.00045

25. Ghasemzadeh A. Jaafar HZE. Rahmat A. Optimization protocol for the extraction of 6-gingerol and 6-shogaol from Zingiber officinale var. rubrum Theilade and improving antioxidant and anticancer activity using response surface methodology. BMC Complement Altern Med. 2015;15(1). doi.org/10.1186/s12906-015-0718-0

26. Daina A. Michielin O. Zoete V. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep. 2017;7(March):1–13. doi.org/10.1038/srep42717

27. Halgren TA. Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94. J Comput Chem. 1996;17(5–6):490–519. doi.org/10.1002/(SICI)1096-987X(199604)17:5/6<490::AID-JCC1>3.0.CO;2-P

28. Shiau AK. Barstad D. Loria PM. Cheng L. Kushner PJ. Agard DA. et al. The structural basis of estrogen receptor/coactivator recognition and the antagonism of this interaction by tamoxifen. Cell. 1998;95(7):927–37. doi.org/10.1016/S0092-8674(00)81717-1

29. Trott O. Olson AJ. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. 2009;NA-NA. doi.org/10.1002/jcc.21334

30. Eberhardt J. Santos-Martins D. Tillack AF. Forli S. AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings. J Chem Inf Model. 2021;61(8):3891–8. doi.org/10.1021/acs.jcim.1c00203

31. Otuokere IE. Amaku FJ. Alisa CO. In Silico Geometry Optimization, Excited-State Properties of (2 E )- N -Hydroxy-3-[3-(Phenylsulfamoyl) Phenyl] prop-2-Enamide (Belinostat) and its Molecular Docking Studies with Ebola Virus Glycoprotein. Asian J Pharm Res. 2015;5(3):131. doi.org/10.5958/2231-5691.2015.00020.9

32. Cole JC. Murray CW. Nissink JWM. Taylor RD. Taylor R. Comparing protein-ligand docking programs is difficult. Proteins Struct Funct Genet. 2005;60(3):325–32. doi.org/10.1002/prot.20497

33. Mukkavilli R. Yang C. Tanwar RS. Saxena R. Gundala SR. Zhang Y. et al. Pharmacokinetic-pharmacodynamic correlations in the development of ginger extract as an anticancer agent. Sci Rep. 2018;8(1). doi.org/10.1038/s41598-018-21125-2

34. Chopra N. Kaur D. Chopra G. Nature and Hierarchy of Hydrogen-Bonding Interactions in Binary Complexes of Azoles with Water and Hydrogen Peroxide. ACS Omega. 2018;3(10):12688–702. doi.org/10.1021/acsomega.8b01523

35. Suharty N. Sri Wahyuni F. Dachriyanus. Cytotoxic activity of ethanol extract of arbuscular mycorrhizal fungi induced ginger rhizome on T47D breast cancer cell lines. Pharmacogn J. 2018;10(6):1133–6. doi.org/10.5530/pj.2018.6.193

Received on 14.12.2021 Modified on 10.02.2022

Research J. Pharm. and Tech 2022; 15(11):4913-4918.

DOI: 10.52711/0974-360X.2022.00825

Compound	Molecular Weight (g/mol)	Log P	Lipinski	TPSA (Å²)	Water Solubility	Geometry Optimization Energy (kj/mol
6-Gingerol	294.39	3.16	Yes	66.76	Modereately Soluble	3930.92
6-Shogaol	276.37	3.69	Yes	46.53	Moderately Soluble	1798.64