Quantitative Estimation of Mangiferin and Molecular Docking Simulation of Salacia reticulata Formulation

Jane B Mathew¹, Zakiya Fathima¹, Chaitra Raviraj¹, Arpith Mathew²

¹Dept. of Pharmaceutical Chemistry, NGSM Institute of Pharmaceutical Chemistry

(Nitte Deemed to be University), Mangalore - 575018, India.

²Manipal College of Pharmaceutical Sciences, Dr. Madhav Nagar, Manipal - 576104, Karnataka State, India.

*Corresponding Author E-mail: janej@nitte.edu.in

ABSTRACT:

The phytochemical constituents present in herbal products need to be determined in their prescribed strength in order to ensure their efficacy and product quality in formulations. The marker-based standardization of herbal products is a well-accepted concept. In this study Mangiferin is used as marker to estimate the amount of Mangiferin present in the formulation Salacia Lin. Veggie capsules containing 400mg of Salacia reticulata extract to treat type 2 diabetes mellitus. The method was validated as per the international conference on harmonization (ICH) guidelines that is applicable in industry as well as in academia. The method was developed using reverse phase, Analytical column used for the separation of analytes, Phenomenex HPLC C18 (250 X 4.6 mm, 5 μm). The run time was of 7 min. The mobile phase used was acetonitrile and orthophosphoric acid (pH adjusted to 3.5) in the ratio 85:15 at a flow rate of 0.5ml/min, column temperature was maintained at 28°C and a detection wavelength of 257 nm using a photodiode array detector. The optimized method that was developed resulted in the elution of Mangiferin at 4.83min and % recovery was between 97.09 to 101.57. Molecular docking investigation was done using Schrodinger software. The binding affinity of phytoconstituents present in Salacia reticulata to intestinal enzymes alpha amylase was investigated to study their possible inhibitory mechanism. The physicochemical and drug-likeness properties of the phytoconstituents were evaluated. The phytoconstituent salacinol showed highest docking score (- 9.592) with alpha amylase (2QV4 obtained from protein data bank) and Mangiferin showed a score of -8.235 in comparison with standard acarbose ( -10.274). Studies showed phytoconstituents Mangiferin, Salacinol and Kotalanol can be potential inhibitors of 2QV4, and potent drug candidates for T2DM. However, further studies on these phytoconstituents should be carried out by wet lab experiments to prove their effectiveness.

KEYWORDS: Salacia reticulata formulation, Mangiferin, HPLC, Molecular docking.

INTRODUCTION: 

The biodiversity of bio active principles presents in plants vary, which broadens their use in the treatment of diseases. In India plant extracts and formulations have been used in Ayurveda for the management of Type 2 diabetes mellitus(T2DM). Diabetes mellitus is among the top 10 diseases affecting mankind globally according to WHO¹.

Studies consistently indicate, diabetic patients adhering solely to conventional dosage forms are decreasing. May be the cost factor, patient beliefs and dose regime which limits patient compliance with conventional treatment^2-4. Folklore medicines are gaining more popularity due to less or no side effects. The medicinal value of a plant is based on the presence of bioactive constituents present in the plant⁴.

Herbal formulations are being widely considered as therapeutic agents for various conditions like diabetes, arthritis, liver diseases, cough remedies, memory enhancers and adaptogens⁵. As we know traditional herbal medicines are used in different oriental countries for centuries to treat different diseases. There is an important requirement to check the quality control of herbal products that are emerging into the medicinal market as main line therapeutic agents for treatment of various diseases⁶. But there is lack of adequate research methodology to gauge traditional medicines in their formulations. For which chromatographic techniques like HPLC, HPTLC, LC-MS, GC are useful for analysing herbal formulations^7,8. It is a known fact that due to variable chemical constituents in herbal formulation it is difficult to establish quality control effectively. One of the ways to ensure quality and quantity of active principles, is the concept marker based standardization to identify major components responsible for activity and to develop analytical methods to analyse the herbal formulations^9-11.

Markers are characteristic substances to a plant under investigation and are likely to be present in detectable amounts that can be easily isolated. Phytochemical estimation is one of the methods for the quality assessment for herbal formulation, and makes use of marker compound analysis using advanced analytical techniques like TLC, HPLC, HPTLC, GC to various kinds of raw materials and pharmaceutical preparations analysis. Analytical methods can be employed in order to establish the composition of herbal preparations, and HPLC is a versatile tool for the analysis of herbal medicines as its application is not restricted by volatility or stability of the product and is useful for the analytical separation of herbal medicines^7,9,12-15.

Drugs like Acarbose, Voglibose and Miglitol are oral hypoglycaemic agents that are in use but produces gastro intestinal disturbances. Salacia reticulata is a woody climber herb belonging to the family Hippocrateacea. The stem and root are extensively used in Ayurvedic medicine to treatment of T2DM. Salacia capsules consists of Salacia reticulata used for the prevention and healthy management of type 2 diabetes mellitus. Salacinol, Mangiferin and Kotalanol are some of the active principles present in the extract that is responsible for the hypoglycaemic activity^16-18. Alpha-glucosidase and Alpha-Amylase are intestinal enzymes and inhibitors of these enzymes delay the absorption of glucose, causing decreased levels of glucose in the blood and helps in attenuating the postprandial glucose rise in diabetic individuals. Alpha-Amylase is a carbohydrate hydrolysing enzyme and that are responsible for the breakdown of starch, carbohydrates, maltose and sucrose and these are further degraded to into simpler molecules that aids in digestion^19-22. Diabetes mellitus (Type 2 diabetes) is common in Asia, Africa and South America²³.

Mangiferin was the marker selected for quantification since it has been extensively studied and proved to have significant hypoglycemic properties^24,25. Presence of Mangiferin in Salacia oblonga have been reported but the same in Salacia reticulata have not been extensively studied. Hence Mangiferin in Salacia reticulata is estimated by RP-HPLC PDA detection. So, a simple, reproducible method was developed to determine the amount of Mangiferin in Salacia reticulata dosage form.

Mangiferin is a xanthone derivative and chemically is (C-glucosyl xanthone-1,3,6,7-tetra hydroxy xanthone C2-β-D-glucoside)²⁶ is depicted in figure 1.

Figure 1: Structure of Mangiferin

In the present study a simple practical isocratic elution HPLC method was developed and validated on the basis of limit of detection and quantification, sensitivity, linearity, precision and accuracy according to ICH guidelines and molecular docking simulation of phytoconstituents present in the formulation are investigated²⁷.

MATERIALS AND METHODS:

Materials:

The formulation consists of santarangi extract (Salacia reticulata) for the management of healthy blood sugar levels, was obtained from the local market. Each capsule contained 400mg of Salacia reticulata. Standardized to contain 20% saponins (80mg). Mangiferin was obtained from Sigma. Reagents used in the study was o- Phosphoric acid, acetonitrile, water and methanol was of HPLC grade. The sample and solvents were filtered through MILL Q membrane filter.

Chromatographic conditions:

Analysis was carried out on a Shimadzu LC,model CTO-10ASVP, with an SPD-M20A PDA detector and Lab solutions software. Separations was carried out on a Phenomenex C18 HPLC column (250mm x 4.6 mm i.d. ,5 μm pore size). The column was optimized and maintained at 28°C throughout the analysis and column effluent was monitored at 257nm using phot diode array detector.

Method for analytical method development:

Standard stock solution was prepared by accurately weighing 10mg of Mangiferin (1mg/ml) and dissolving in 2ml acetonitrile and the volume made upto 10ml mark with HPLC grade methanol. The working standard solution was prepared by diluting standard solution to a series of concentrations to enable construct the calibration curve. The standard and working concentrations were stored at 4°C until use.

Sample preparation:

Intact capsules 20 numbers of Salacia reticulata formulations were weighed and average weight of each capsule was estimated emptied of its contents in a clean dry china dish and average weight equivalent to 100mg was extracted with methanol (100ml), thrice then combined and concentrated to 100ml. A working concentration of 1mg/ml was prepared. The sample as well as working solution were filtered through a 0.45μm nylon membrane filter and, was refrigerated till use. Peak identification was achieved by comparing retention time (Rt) and UV absorption spectrum obtained from standard.

Molecular docking:

Molecular docking studies gives an understanding of the binding interactions of Mangiferin and other phytoconstituents present in the formulation, in order to identify important binding modes responsible for the inhibition of pancreatic enzyme, alpha amylase^28-30. The structures of seven phytoconstituents were drawn using CHEMDRAW, the ionization states were produced at pH 7.0. The 3D structure of human pancreatic α-amylase (2QV4) and was downloaded from RCSB protein data bank. Active site water molecules (<3 hydrogen bonds) were removed, and hydrogen bonds at pH seven were incorporated. The protein preparation wizard processed and prepared the proteins following the energy minimization OPLS force field. Ligand docking was performed by the Glide SP and Glide XP application in Schrodinger. The receptor-ligand complex binding energy was determined using the Prime module of Schrodinger, calculates the total free energy in dGbind (kcal/mol), and considers molecular mechanics energies, solvation model for polar and non-polar solvation. ADME and physicochemical properties of ligand molecules were determined by preADMET software.

Validation:

The method was validated asper ICH guidelines. The standard Mangiferin was determined by standard calibration curve with dilutions at various concentration and each concentration was measured six times as represented in figure 2. The corresponding peak area was plotted against concentration of standard Mangiferin. Peak identification was done by comparison of retention time with standard.  

Precision and accuracy: The intra and inter day precision was done to study the ruggedness of the method. Accuracy of the method was studied using the standard addition method. Standard Mangiferin solution was added to formulation of Salacia reticulata. The percent recovery was determined at three different levels 50%,100% and 150%. Mangiferin content was determined and percent recovery was calculated.

RESULT:

Optimized chromatographic conditions were obtained after several trials by varying mobile phases and flow rates with reverse phase C18 column. Better resolution and peak separation were obtained with acetonitrile and o-phosphoric acid in the ration 85:15 and a flow rate of 0.5ml /min and column temperature were maintained at 28°C throughout analysis. The run time was 7 min. The column effluent was monitored at 257 nm. The chromatographs of standard Mangiferin, formulation and spiked concentration are shown in figures 3,4, and 5 respectively.

Figure 2: Linearity plot

Figure 3: Chromatograph of Mangiferin

Figure 4: Salacia R formulation chromatogram

Figure 5: Spiked chromatograph

LOD and LOQ values were calculated as signal to noise ratio and found to be 51.13 μg/ml and 154.94 μg/ml for Mangiferin. Linear correlation between peak area and concentration were obtained in the concentration range 100-500 μg/ml. Regression coefficient was higher than 0.99 confirming the linearity of the method. The recovery values between 97.09 - 101.57 indicates the accuracy of the method and relative standard deviation of less than 2% indicates the repeatability of the developed method. The low coefficient of variation of intra and inter day precision shows the method to be precise. The marker found in formulation with respect to Mangiferin was 0.32± 0.2. The results are shown in Table 1.

Table 1: Results of Method Validation

Compound	Conc (µ g/ml)	Rt (min)	Regression equation	R^2
Mangiferin	100-500	4.830	y = 1.004465 -5E+06	0.99
	LOD	LOQ	Intraday RSD(%)	Interday RSD(%)
	51.13	154.94	0.564	0.335

In silico predictions

The oral effectiveness of a compound is analysed by the pharmacokinetic (PK) properties. By investigating the drug-like properties with optimal PK properties can be selected and predictions were done based on compliance with Lipinski’s rule of five. The parameters like molecular weight, partition coefficient (log P value), number of hydrogen bond donors and acceptors were considered for rule of five and the ADME properties of the phytoconstituents were predicted using preADMET. The drug-likeness and ADME properties are showed in Table 2 and Table 3 respectively. The docking results of the phytoconstituents and recorded in Table 4 and interactions are shown in figures 6,7and 8. The free binding energy of 2QV4 are reported in Table 5.

All the selected phytoconstituents obeyed the Lipinski RO5, except Mangiferin and acarbose displayed minor violations, however they were found to be in the acceptable range. The partition coefficient helps to predict/estimate the distribution of the drug within the body. The log P value of the compounds are within the acceptable range.

Table 2. Drug-likeness properties of phytoconstituents:

Ligands	Mol.wt	HB Donar	HB Accept	log p	RO5
Acceptable range	≤500 DA	≤5	≤10	≤5	≯4
Acarbose	645.6	14	19	-4.370	3
Mangiferin	422.3	8	11	-0.521	2
kotalanol	424.4	8	12	-3.416	1
salacinol	334.0	5	9	-2.727	0
Ponkoranol	394.4	7	11	-3.188	2
salaprinol	304.3	4	8	-2.502	0
(-)-Epicatechin	290.0	5	6	1.142	0
(-)-Epigallocatechin	306.07	1	6	0.736	0

Table 3: Predicted ADME properties of the phytoconstituents

Ligands	Caco-2	Human intestinal Absorption	BBB	hERG
Acarbose	-6.149	0.8467	0.8000	0.8586
Mangiferin	-6.216	0.9442	0.6472	0.9727
kotalanol	-0.915	0.7920	0.7978	0.7487
salacinol	-5.539	0.7920	0.7978	0.7487
Ponkoranol	-5.779	0.7920	0.7978	0.7487
salaprinol	-5.414	0.7920	0.7978	0.7487
(-)-Epicatechin	-5.971	0.9654	0.5331	0.9666
(-)-Epigallocatechin	-6.306	0.9654	0.5331	0.9666

The ADME properties of the phytoconstituents were predicted using preADMET. CaCO-2 cell permeability has been commonly used to estimate the drug permeability in human intestinal epithelium. It’s an important parameter for oral drug. The compounds like acarbose, Mangiferin, salacinol, Ponkoranol, salaprinol, (-)-Epigallocatechin shows poor Caco2 cell permeability. In order to determine the efficacy of the drug, HIA is considered as one of important parameter, All the selected phytoconstituents has showed medium to poor HIA.

The drugs which act on CNS needed to cross BBB, but for the drugs acting on peripheral targets there is no requirement to cross BBB, because penetration may cause CNS side effect. The compound Epicatechin and Mangiferin showed moderate CNS permeability, whereas remaining compounds shows poor permeability.

Inhibition of hERG (The human ether-a-go-go related gene), leads mainly to QT syndrome with fatal ventricular arrhythmia. All the selected compounds showed weak hERG inhibition. Hence all the compounds were considered to be relatively safer.

To predict the presumed binding mode of the active phytoconstituent with the target protein α-amylase, the docking study was carried out into the active site of co-crystal structure PDB: 2QV4, using Schrödinger module and the docking scores and binding free energy of phytoconstituents with 2QV4 are shown in tables 4 and 5 and figures 6,7 and 8 shows the 2D and 3D interactions of Acarbose, Mangiferin and Salacinol respectively.

Table 4: Docking of the phytoconstituents with 2QV4

Sl. no	Ligands	Docking score	Hydrogen bonding	Polar interaction with ligand	Pi-Pi Stacking
1.	Acarbose	-10.274	THR163 ASP197 GLU233 ASP300 TRP59	THR163
2.	Mangiferin	-8.285	THR163 ASP300 GLN63	THR163 GLN63	TYR62 TRP59
3.	kotalanol	-8.795	THR163 GLN63 TYR62 ASP197 GLU233	THR163 GLN63
4.	salacinol	-9.592	THR163 ASP197 GLU233	THR163
5.	Ponkoranol	-7.660	HIE299 ASP197 GLU233 LYS200	HIE299
6.	salaprinol	-8.969	TRP59 ASP300 GLU233 ASP197
7.	(-)-Epicatechin	-5.844	GLN63 ARG195 ASP197 GLU233 ASP300	GLN63	TYR62
8.	(-)-Epigallocatechin	-6.842	GLN63 ASP300 HIE299 GLU233	HIE299 GLN63

Figure 6: 2D and 3D interactions of Acarbose

Figure 7:2D and 3 D interactions of Mangiferin

Figure 8: 2D and 3D interactions of salacinol

Table 5: Binding free energy calculation of 2QV4

Ligands	MMGBSA dG bind	MMGBSA dG bind Coulomb	MMGBSA dG bind Lipo	MMGBSA dG Bind Covalent	MMGBSA dG Bind vdW	MMGBSA dG Bind Hbond	MMGBSA dG bind Solv GB
Acarbose	-61.96	-27.56	-43.63	3.62	-49.43	-3.29	58.34
Mangiferin	-56.21	-35.66	-24.97	4.74	-27.80	-2.96	31.71
kotalanol	-70.92	106.42	-25.65	-0.99	-33.98	-4.18	-112.54
salacinol	-54.34	112.55	-19.60	3.90	-27.55	-4.24	-119.40
Ponkoranol	-55.72	124.53	-26.16	5.04	-23.56	-4.68	-130.88
salaprinol	-41.69	126.56	-16.50	5.58	-28.26	-4.77	-124.30
(-)-Epicatechin	-31.23	-16.77	-19.53	2.89	-30.02	-3.04	36.11
(-)-Epigallocatechin	-46.96	-42.62	-21.85	9.00	-22.54	-3.44	35.27

DISCUSSION:

The results of the phytoconstituent showed significant interaction with active site. Salacinol showed highest docking score among selected phytoconstituent, of -9.592kcal/mol. THR16, ASP197, GLU233 are the residues with which salacinol showed hydrogen bonding and polar interaction at THR163.

The binding energy of acarbose towards active site of alpha amylase was found to be -10.274. Acarbose showed the hydrogen bonding interaction with THR163, ASP197, GLU233, ASP300, TRP59 residue of active site. Additionally, it also shows polar interaction with THR163. Mangiferin, an important constituent present in the formulation have the binding score of -8.285 Kcal/mol. Mangiferin showed hydrogen bonding with THR163, ASP300, GLN63 residues, polar interaction with THR163, GLN63 residue of the ligand and also Mangiferin is involved in pi-pi staking interaction withTYR62, TRP59.

All the phytoconstituents have a high free binding energy and will bind to receptors efficiently (Table 5). In the primary MM-GSBA study, the relative energies of each compound's binding to the receptor are presented. Multiple drug receptor interactions, such as polar contacts, hydrophobic interactions, covalent bond interactions, and so on, contribute to it. The binding free energies of the phytoconstituents kotanolol and Ponkoranol have the highest ΔG binding energy to 2QV4 with a value of -70.92 kcal/mol when compared to the known standard, acarbose which has a value of -61.96 kcal/mol. Because all of the phytoconstituents, showed substantial negative values, the energies that firmly bind in the binding pocket of 2QV4 are Van der Waals energy (GvdW) and non-polar solvation (GLipo). Furthermore, larger negative values of ΔGVdW and ΔGLipo demonstrate strong hydrophobic interaction with 2QV4 and ligands (Figure 6-8). Some of the phytoconstituents like Mangiferin and Salacinol have highly preferred ligand binding (ΔGCoul - kcal mol-1). This result is also related to the G score, as the phytoconstituents Salacinol, had the greatest docking score, showing that columb energy is important in the drug-receptor interaction. The MM-GSBA assay reveals that the phytoconstituents and the receptor have substantial binding affinities as shown in the Table 5.

The objective was to find the efficacy of this herbal formulation so that it can effectively prevent post prandial hyperglycaemia and decrease fasting glucose levels in patients suffering from type II diabetes so as to effectively improve insulin resistance and glucose metabolism, and Salacia reticulata is said to lower haemoglobin A1C(HbA1C) which gives a measure of blood glucose levels.

CONCLUSION:

The antidiabetic activity of S.reticulata is due to the presence of active principles Mangiferin, salacinol, kotalanol that have inhibitory action against the intestinal enzyme alpha amylase thereby helping in subduing postprandial hyperglycemia. 

CONFLICT OF INTEREST:

The authors have no conflicts of interest regarding this investigation.

ACKNOWLEDGMENTS:

The authors would like to thank Nitte (DU) and NGSM Institute of Pharmaceutical Sciences, Deralakatte for their support in carrying out this project.

REFERENCES:

1. https://www.healthline.com/type-2-diabetes.

2. Kamboj A. Analytical Evaluation of Herbal Drugs. 2012). 10.5772/26109.

3. Prokopenko Y, Tsyvunin V, Shtrygol' S, Georgiyants V. In Vivo Anticonvulsant Activity of Extracts and Protopine from the Fumaria schleicheri Herb. Sci Pharm. 2015 Dec 6;84(3):547-554. doi: 10.3390/scipharm84030547. PMID: 28117320; PMCID: PMC5064245.

4. Stohs SJ, Ray S. Anti-diabetic and Anti-hyperlipidemic Effects and Safety of Salacia reticulata and Related Species. Phytother Res. 2015 Jul;29(7):986-95. doi: 10.1002/ptr.5382. PMID: 26031882; PMCID: PMC5033029.

5. Derosa GMP. α-Glucosidase inhibitors and their use in clinical practice. Arch Med Sci. 2012; 8(5): 899–906. doi: 10.5114/aoms.2012.31621.

6. Balammal G, Sekar Babu M, Jayachandra Reddy P.Analysis of Herbal Medicines by Modern Chromatographic Techniques; International Journal of Preclinical and Pharmaceutical Research. 2012; 3(1): 50-63.

7. Patel KS, P Zaveri. Simultaneous quantification of pharmacological markers quercetin, berberine HCl and curcumin using High-performance thin-layer chromatography (HPTLC) from polyherbal formulation. Research Journal of Pharmacy and Technology. 2022; 15(11): 4919-4923 doi: 10.52711/0974-360X.2022.00826

8. Shraddha J, Varsha MJ, Vilasrao JK., Analytical method development and its validation for simultaneous estimation of catechin and curcumin by HPTLC from ancho lean tablets;Indian J. Pharm. Biol. Res. 2018; 6(2):23-30.

9. Manisha K, Gharatean, Veena SK. Development and validation of RP-HPLC method for determination of marker in polyherbal marketed Kankasava formulations. Der Pharmacia Lettre. 2011: 3 (5) 28-33

10. Swatantra KSK, Neelottama K, Neeleshwar M, AK Rai. Role of markers in standardization of herbal drugs:A Review.Archives of Applied Science Research. 2010;  2(1): 225-229

11. Mawlieh B, Shastry C, Chand S. Evaluation of anti-diabetic activity of two marketed herbal formulations. Research Journal of Pharmacy and Technology. 2020; 13(2): 664-668, 10.5958/0974-360X.2020.00127.4

12. Ashwini L, Nidhya G, Latha S et al. Comparison of Herbal formulation and Herbal extracts of seeds and fruits of selected medicinal plants for Antidiabetic Enzyme Inhibitory Studies. Research Journal of Pharmacy and Technology. 2022: 15(10):  4789-4794. 10.52711/0974-360X.2022.00804

13. Om P, Debarshi KM, Ruchi S, Namrata S, Neelam VAV. Development of a New Isolation Technique and Validated RP-HPLC method for Quercetin and Kaempferol from Azadirachta indica leaves. Asian J. Pharm. Ana. 2018; 8(3): 164-168.

14. M. Senthil R, Imran K, Perumal P. Quantitative Analysis of Glycyrrhizic Acid in Crude Drug and its Herbal Formulation by HPLC. Asian J. Research Chem. 2010; 3(3); 703-706.

15. Vishal Jain, Ambar Vyas, Swarnlata Saraf, S. Saraf. HPLC Determination of Piperine in ‘Trikatu Churna’ a Potent Ayurvedic Formulation for Routine Quality Control. Asian J. Research Chem. 2011; 4(2): 183-186.

16. Roy A, Gupta P, Bharadwaj S.Antidiabetic activity of polyherbal formulations from Chhattisgarh state. Research Journal of Pharmacy and Technology, 2021; 14(3): 1375-1379, 10.5958/0974-360X.2021.00245.6

17. Anurakumara KKIU,Subasinghe S. Salacia reticulata Wight: A review of botany, phytochemistry and pharmacology. Tropical Agricultural Research and Extension. 2010; 13(2): 41–5.

18. V SekarS. Chakraborty S, Mani VK, Sali HRV. Mangiferin from Mangifera indica fruits reduces post-prandial glucose level by inhibiting α-glucosidase and α-amylase activity. South African Journal of Botany. 2019;120: 129-134.  https://doi.org/10.1016/j.sajb.2018.02.001.

19. Matsuda H,Murakami T,Yashiro K et al. Antidiabetic principles of natural medicines. IV. Aldose reductase and α-glucosidase inhibitors from the roots of Salacia oblonga WALL. (Celastraceae): Structure of a new friedelane-type triterpene, kotalagenin 16-acetate. Chemical and Pharmaceutical Bulletin. 1999;  47(12):  1725-1729  10.1248/CPB.47.1725

20. Arunakumara K, Subasinghe S. Salacia reticulata Wight: A Review of Botany, Phytochemistry and Pharmacology. Tropical Agricultural Research and Extension. 2011; 13(2). 10.4038/tare.v13i2.3137

21. Yoshikawa MMT, Yashiro K, Matsuda H. Katalanol a potent alpha glucosidase inhibitor with thio sugar sulfonium sulphate structure from antidiabetic Ayurvedic medicine Salacia reticulata. Chem Pharm Bull. 1998; 46(8): 1339–40. doi: 10.1248/cpb.46.1339.

22. Radhakrishnan M, Ramesh S. In vitro glucose uptake activity of traditional polyherbal formulation in skeletal muscle cells. Research Journal of Pharmacy and Technology, 2016;506-508, 9(5). 10.5958/0974-360X.2016.00094.9

23. Deore N, Gupta S,Shrivastav B et al. Anti-diabetic potential of a polyherbal formulation–a review. Research Journal of Pharmacy and Technology. 2018; 11(6): 2625-2630. 10.5958/0974-360X.2018.00487.0

24. Medagama A. Salacia reticulata (Kothala himbutu) revisited; a missed opportunity to treat diabetes and obesity?. Nutrition Journal. 2015.14. 10.1186/s12937-015-0013-4.

25. Shivaprasad et al. Salacia reticulata improves serum lipid profiles and glycemic control in patients with prediabetes and mild to moderate hyperlipidemia: A double-blind, placebo-controlled, randomized trial. J Med Food. 2013; 16 (6): 564–568

26. https://pubchem.ncbi.nlm.nih.gov/compound/Mangiferin

27. Nadri M, Salleh W. Molecular docking studies of phytochemicals from piper species as potential dual inhibitor of group x secreted phospholipase a2 (Spla2-x) and cyclooxygenase-2 (cox-2). Research Journal of Pharmacy and Technology, 2020; 13(5): 2181-2186. 10.5958/0974-360X.2020.00392.3

28. Malik A, Malik N, Dhiman P et al. Molecular docking, synthesis, α-amylase inhibition, urease inhibition and antioxidant evaluation of 4-hydroxy-3-methoxy benzoic acid derivatives. Research Journal of Pharmacy and Technology, 2019; 12(12): 5653-5663,. 10.5958/0974-360X.2019.00978.8

29. Suganya J, Viswanathan T Radha M et al. In silico molecular docking studies to investigate interactions of natural camptothecin molecule with diabetic enzymes. Research Journal of Pharmacy and Technology, 2017;10(9): 2917-2922. 10.5958/0974-360X.2017.00515.7

30. Sindhu. TJ, Arathi. KN, Akhila D, Aswathi. TA, Noushida M, Midhun. M, Sajil SK. Synthesis, Molecular Docking and Antibacterial Studies of Novel Azole derivatives as Enoyl ACP Reductase Inhibitor in Escherichia coli. Asian J. Res. Pharm. Sci. 2019; 9(3): 174-180.

Received on 05.04.2023            Modified on 11.07.2023

Accepted on 03.10.2023           © RJPT All right reserved

Research J. Pharm. and Tech 2024; 17(2):578-584.

DOI: 10.52711/0974-360X.2024.00090