INTRODUCTION:

Trees from the Acacia genus, which come from the Fabaceae family, are the species that are widely found in Indonesia. Acacia trees, such as Acacia mangium Willd.¹, A. auriculiformis A. Cunn. ex Benth², and A. crassicarpa A. Cunn. ex Benth³, are included in the fast-growing species group and can adapt to a good environment. In 2019, log production in Indonesia reached 57.93 million m³, dominated by Acacia wood production (57.93%)⁴.

The wood production process produces waste in the form of bark and the production of this log produces 22.32% of bark waste which has not been utilized⁵. In order to increase the added value of forest products, the whole tree utilization concept should be done by utilizing all wood parts such as stems, branches, roots, twigs, and bark. For example, the bark can be used for its bioactive compounds with medicinal properties such as antioxidant and antidiabetic compounds.

Research on antioxidant and antidiabetic bioactive compounds in acacia bark has not been done much, especially on A. mangium, A. auriculiformis, and A. crassicarpa species. Previous research showed the methanol extract of the heartwood of A. crassicarpa had the highest activity compared to A. auriculiformis and A. mangium on the DPPH, ABTS, and FRAP methods⁶. Another research showed that the ethanolic extract of the leaves of A. auriculiformis had antioxidant activity because, at a concentration of 100µg/mL, it could inhibit the free radical 1,1-Diphenyl-2-picrylhydrazyl (DPPH) by 91.75%⁷. The ethanol extract of A. crassicarpa knots had a higher antioxidant activity (IC₅₀ 19µg/mL) when compared to the ethanolic extract of A. mangium buds (IC₅₀ 24µg/mL) based determination on the DPPH⁸. Antidiabetic ethanolic extract of A. mangium peel has α-glucosidase inhibition (IC₅₀ 22µg/mL)⁹. The aim of the research was to determine the most active extract based on antioxidant activity and α-glucosidase inhibition from the bark of A. mangium, A. auriculiformis, and A. crassicarpa methanol extracts. The most active fractions were isolated and identified using Liquid Chromatography-Mass Spectrometry (LC-MS) and Fourier-Transform Nuclear Magnetic Resonance (FT-NMR) (¹H and ¹³C).

MATERIALS AND METHODS:

Materials:

The bark of the three types of Acacia was obtained from trees with diameters at breast height of 20, 23, and 27 cm, respectively for A. mangium, A. crassicarpa, and A. auriculiformis from Parung Panjang, West Java, Indonesia. The chemicals used in the study were DPPH reagent, ABTS, Folin-Ciocalteu, α-glucosidase enzyme, acetate buffer solvent pH 3.6, 10 mM 2,4,6-tri(2-pyridyl)-s-triazine, ρ-nitrophenyl-α-D-glucopyranoside (PNP), phosphate buffer pH 7.0, FeSO₄.7H₂O, K₂S₂O₈, Na₂CO₃, NaNO 5%, gallic acid, HCl, FeCl₃, NaOH, Na₂CO₃, AlCl₃, trolox, dimethylsulfoxide (DMSO), quercetin, distilled water, aquabides, silica gel 60 (0.040-0.063 mm), deuterated chloroform, Pro Analysis solvents MeOH, n-hexane, ethyl acetate, and distilled technical solvents such as EtOH, n-hexane, MeOH, BuOH, and ethyl acetate.

Extraction:

In this study, the bark used for the extraction process was the inner bark. The inner bark was chopped and air-dried. The pieces of bark were ground into a size of 40-60 mesh. Samples weighing 500 g each were extracted by the maceration method in methanol (1:15) for 24 hours. A sieve separated the extraction results, then the filtrate was concentrated with a rotary evaporator and dried in an oven at a temperature of ±50 C.

Determination of Total Phenolic and Flavonoid Contents:

Total phenol was determined using the Folin-Ciocalteu¹⁰. Phenolic was determined using a concentration of 50µg/mL, extract solvent as much as 250µL added 250µL Folin-Ciocalteu reagent mixed in a test tube. After that, the solvent was homogenized and added with 750µL of sodium carbonate (Na₂CO₃) and 3750µL of distilled water (incubated for 30 minutes). The absorbance results were measured with a spectrophotometer at a wavelength of 750nm.

Total flavonoids were determined using AlCl₃ colorimetric method¹¹. Flavonoids were determined using a concentration of 20µg/mL, extract solvent as much as 100µL added 2600µL distilled water and 150 µL NaNO 5% (incubated for 5 minutes). Then 10µL of 10% AlCl₃ solvent was mixed with 200µL of NaOH and homogenized. A spectrophotometer was used to measure the absorbance results at a wavelength of 518nm.

In vitro determination of antioxidants:

a) Antioxidant Activity 1,1-Diphenyl-2-picrylhydrazyl (DPPH) Assay:

Determination of antioxidant activity was conducted using the DPPH method¹², using 500µL of DPPH radical solvent in methanol and adding extract solvents with various concentrations of 20, 10, 5, and 1µg/mL. The samples were 500, 250, 125, and 25µL and put in a test tube. Then the sample was added with MeOH up to a total volume of 2500µL. The sample was incubated at room temperature for 30 minutes in a dark room. The absorbance results were measured with a UV-Vis spectrophotometer at a wavelength of 515nm, and the percentage of DPPH radical inhibition was also calculated. A regression equation was resulted from the percentage value of the inhibition, and the IC₅₀ value was determined. The higher the antioxidant activity is indicated, the lower the IC₅₀ value.

b) Antioxidant Activity (2,2-Azinobis 3-ethyl benzothiazoline 6- sulfonic acid) ABTS Assay:

Determination of antioxidant activity was conducted using the ABTS^12,13 method, using 5mL of 7mM ABTS reagent added 88µL of K₂S₂O₈ dissolved in distilled water and stored in a dark room for 16 hours. Then it was diluted with deionized water until the absorbance reached 0.7±0.02. Mix 1000µL of ABTS reagent with 1000 µL of extract solvent to make sample analysis. The extract solvent was made with variations in final concentrations of 50, 25, 10, and 5µg/mL. The mixed solvent was incubated for 6 minutes, and the absorbance results were measured by UV-Vis spectrophotometer at a wavelength of 734nm.

c) Antioxidant Power (Ferric Reducing) FRAP Assay:

Determination of antioxidant activity was conducted using the FRAP method using a solvent under new conditions before testing¹². The determination was made by observing the color change of Fe³⁺ tripiridyltriazine (colorless) to Fe²⁺-tripyrydyltriazine (blue). The absorbance results were measured with a spectrophotometer at a wavelength of 593nm. The FRAP reagent was prepared in a 10:1:1 ratio between 300mM acetate buffer solvent pH 3.6, 10mM 2,4,6-tri(2-pyridyl)-s-triazine and 20mM FeCl₃. Extract sample as much as 40µL added 1200µL FRAP reagent. The sample was incubated at 37°C in a water bath for 30 minutes. A UV-Vis spectrometer was used to measure the absorbance results at a wavelength of 593nm. The FRAP calculation was based on the standard trolox calibration curve. The test result data was measured to determine the total antioxidant in the form of absorbance, and the regression equation was obtained. The FRAP value is expressed in the mmol TE/g sample. The higher the antioxidant activity was indicated, the higher the mmol TE/g sample.

Determination of α-glucosidase inhibition:

The method of determining inhibition of α-glucosidase activity in vitro was using enzymatic¹⁴. This determination used 5µL of DMSO (standard solvent) and 5µL of extract added with 250 µL of 5 mM PNP solvent, and 495 µL of phosphate buffer pH 7 0,1M. The solvent was pre-incubated for 5 minutes at 37ºC. Add α-glucosidase solvent after pre-incubation and then incubated for 15 minutes. The reaction was stopped by the addition of 1mL Na₂CO₃ 0.2 M. Enzyme activity was measured based on the absorption reading of ρ-nitrophenyl formed at 400nm. Quercetin was used as a comparison.

Liquid-liquid fractionation, Prospective Fraction Determination, and Vacuum Liquid Chromatography (VLC):

The results of the most active extraction were separated by the liquid-liquid fractionation method using n-hexane, ethyl acetate, butanol, and water as solvents. Extract fractionation was carried out using a mixture of two solvents having different polarities. Fractionation was conducted to obtain compounds based on different polarity levels. The first solvent used n-hexane and water, the second used ethyl acetate and water, and the third used butanol and water. Fractionation was carried out on a separating funnel and shaken to obtain water fraction and n-hexane fraction. Then the two fractions were separated. The n-hexane, ethyl acetate, butanol, and water fractions were evaporated in a rotary evaporator. VLC carried out the most active fraction to obtain the compound. The use of VLC eluent used hexane, ethyl acetate, and methanol as solvents.

Identification of active component:

The most active fraction was analyzed using LC-MS, which was dissolved at a concentration of 1000µg/mL (1mg/1mL), and 1µL was taken to be injected into the LC-MS instrument, then identified the compound using a reference database to determine the type of compound. Identification of compound isolates using NMR instruments to determine the structure of the compound. FT-NMR analysis was conducted using ¹H-NMR (500 MHz) and ¹³C-NMR (125 MHZ) was conducted using deuterated chloroform solvent.

Data analysis:

This study used statistical analysis in a completely randomized design (CRD). The variable used in this study was the type of bark for response analysis (yield, antioxidant activity, and inhibition of -glucosidase extract) which consisted of 3 levels (3 tree species). Analysis of variance (ANOVA) was conducted at the 95% confidence level (level 0.05). If the ANOVA results show a significant effect, it will be continued by using Duncan's multiple range test. The analysis was carried out using SPSS 25.

RESULT:

Extract Yield of Three Types of Acacia Bark:

Table 1 shows that the yield of acacia bark extraction ranged from 7-13%. The statistical analysis results showed that the yield of A. mangium bark extract was the highest and significantly different compared to the other two extracts. However, the yield of extracts of A. auriculiformis and A. crassicarpa was relatively the same. The three types of acacia bark extract have different colors and aromas. The bark of A. auriculiformis has a chocolate-like aroma, while the bark of A. crassicarpa has a nutty aroma.

Table 1. Acacia bark methanol extract yield

Sample	Yield (%)	Extract visual characteristics
A. mangium	13,41±0,61^b	Dry solid, odorless, dark brown
A. auriculiformis	7,64±0,28^a	Dry solid, flavorful, brown in color
A. crassicarpa	7,61±0,02^a	Dry solid, flavorful, reddish-brown

*The letter after the value shows a significant difference with a p value lower than 0.05 with Duncan's multiple-distance test

Total Phenolic and Flavonoid Contents

Table 2 shows that the total value of phenolic contents (TPC) of the three acacia bark extracts is lower than the total value of flavonoid contents (TFC). The statistical analysis results showed that the TPC of A. auriculiformis bark extract was the highest, but the TPC value was not significantly different from that of A. mangium. The TFC of A. mangium bark extract was highest and significantly different from the other two extracts.

Table 2. Total phenol and total flavonoid content of Acacia bark extract

Sample	Phenolic (mg GAE/g extract	Flavonoid (mg QE/g extract)
A. mangium	203,01±1,55^b	604,74±12,36^c
A. auriculiformis	221,64±0,38^b	264,98±3,79^b
A. crassicarpa	111,23±15,11^a	232,05±4,46^a

*The letter after the value shows a significant difference with a p value lower than 0.05 with Duncan's multiple-distance test

In vitro antioxidant activity Assay:

The antioxidant activity of acacia extract is shown in Table 3. A. mangium bark extract showed the highest antioxidant activity based on the three antioxidant test methods: DPPH, ABTS, and FRAP. Based on the ABTS and FRAP methods, the antioxidant activity of the A. mangium bark extract was significantly different from the other two extracts. However, based on the DPPH method, the antioxidant activity of A. mangium bark extract was not significantly different from the antioxidant activity of A. crassicarpa bark extract. The three extracts had lower antioxidant activity than standard antioxidant compounds.

Table 3 Antioxidant activity of Acacia bark methanol extract

Sample	DPPH (µg/mL)	ABTS (µg/mL)	FRAP (mmol TE/g extract)
A. mangium	22,88±1,33^a	2,73±0,04^a	3,35±0,37^b
A. auriculiformis	28,55±0,11^b	9,80±0,14^b	0,98±0,03^a
A. crassicarpa	24,52±0,65^a	9,54±0,02^b	1,19±0,06^a
Quercetin	7,09±0,51	-	-
Trolox	-	1,98±0,48	-

*The letter after the value shows a significant difference with a p value lower than 0.05 with Duncan's multiple-distance test

In vitro α-glucosidase inhibition testing:

The results showed that the α-glucosidase inhibition of the three extracts was higher than the standard antidiabetic compounds. The statistical analysis results showed that the bark extract of A. mangium had the highest α-glucosidase inhibition and was significantly different from the other two extracts.

Table 4 Inhibition of α-glucosidase

Sampel	IC₅₀(µg/mL)
A. mangium	1,17±0,19^a
A. auriculiformis	7,85±0,11^c
A. crassicarpa	6,85±0,44^b
Quercetin	9,15±0,1

* The letter after the value shows a significant difference with a p value lower than 0.05 with Duncan's multiple-distance test

Prospective Faction:

Based on antioxidant and antidiabetic activity (Table 3 and Table 4), the most active extract was A. mangium bark. Furthermore, the methanol extract of A. mangium bark was fractionated using hexane, ethyl acetate, butanol, and water as solvents. Table 5 shows that the methanol extract of A. mangium bark was dominated by the butanol fraction, followed by the ethyl acetate and water fractions. Fractionation with n-hexane did not produce a fraction.

Table 5 Yield of fraction from fractionation of methanol bark extract A. mangium

Fraction	Yield (%)
n-hexane	Not dissolved
Ethyl Acetate	24,40
Butanol	47,43
Water	17,61

Based on the determination of antioxidant activity using the DPPH method at a concentration of 50 µg/Ml, the highest antioxidant activity of butanol fraction was indicated by the percentage of DPPH inhibition. However, the α-glucosidase inhibition of the butanol fraction was lower than the ethyl acetate fraction, which had the highest antidiabetic activity (Table 6). Furthermore, the ethyl acetate fraction was selected as a prospective fraction to isolate the active compound based on its antidiabetic activity and purification process by the method of column chromatography, which is easier to perform.

Table 6 Antioxidant activity of DPPH and α-glucosidase inhibition of the ethyl acetate fraction fractionated

Sub-fraction	DPPH (%inhibition)	IC₅₀α-glukosidase (µg/mL)
Ethyl acetate	16.869	1.334
Butanol	92.437	3.598
Water	91.418	11.618

The results of the separation of the ethyl acetate fraction resulted in 7 sub-fractions. The antioxidant testing results using the DPPH method and α-glucosidase inhibition showed that sub-fraction 5 had the highest antioxidant activity because it was able to inhibit at a concentration of 100 µg/mL DPPH by 70.52%. However, sub-fraction 5 had the lowest α-glucosidase inhibition. The highest α-glucosidase inhibition was obtained from sub-fraction 6 at a concentration of 50 µg/mL, which was able to inhibit α-glucosidase by 96.84% (Table 7).

Table 7 Antioxidant activity and -glucosidase sub-fraction of the ethyl acetate fraction

Sub-fraction	DPPH (%inhibition)	α-glukosidase (%inhibition)
F1	NA	69,85
F2	NA	82,70
F3	NA	13,77
F4	7,29	26,89
F5	70,52	3,76
F6	3,07	96,84
F7	NA	36,29

* Not Active (NA)

Identification of F-6 Sub-Fraction (Isolate 1) by LC-MS and FT H-NMR:

The results of identification using LC-MS, show that’s compound had molecular weight is m/z 192.04226. In the H-NMR spectrum, the sample extract of the prospective ethyl acetate fraction from sub-fraction 6 showed that this compound was relatively pure (isolate 1), and the signal at δH 3.92 (s, 3H) was a methoxy group (-OCH₃), and other signals appeared at aromatic regions or double bonds. Figure 1 shows the expansion of the H-NMR spectrum, which was visible in the signal's shape. Signals at δH 7.60 (d) and 6.26 (d) indicated a double bond in the cis form because it had a value of J = 9.5 Hz. The signal at δH 6.92 and 6.84 each has a single signal (s). It is estimated that this compound has a para position, while the signal at δH 6.18 in the broad singlet form is a proton (H) signal from the group hydroxyl (–OH).

Figure 1. H-NMR spectra of prospective extract for F-6 and its expansion.

The results of the C-NMR measurements in Figure 2 strengthen the alleged ¹H-NMR results, the presence of a methoxy group at C 56.57. Quaternary C (=C-OH or -C=O) is seen at δC 111.66; 144.17; 149.84, and 150.39. The signal at δC 161.70 is believed to be the cyclic carbonyl group (=C=O) of a lacton.

Figure 2. C-NMR Spectrum

Figure 3. Partial structure of F-6 –para H-H of aromatic and Cis double bond

DISCUSSION:

Table 1 shows that the type of wood affects the extraction yield. The environment in which it is grown, the species, and the solvent used can affect the yield. The phenomenon of the effect of different species on extract yields has been previously reported, the methanol extract of the bark of A. pennata (8.7%) had a higher yield than A. leucophloea (6.6%), A. dealbata (6.5%), and A. ferruginea (3, 6%)¹⁵. A. auriculiformis had a highes yield of but A. mangium and A. crassicarpa had a lower yield of 7.66 and 3.01% respectively⁶. The results of previous studies showed that the yield of methanol extract of A. catechu bark was higher than that of terrace wood¹⁶. The yield of methanol extract of A. mangium bark was not much different from previous studies, with methanol solvents having yields ranged from 14-18% and higher than n-hexane extracts with yields ranged from 0.9-2%¹⁷. The yield of A. auriculiformis extract is lower than previous studies using various extraction methods, such as ultrasonic bath, microwave, water bath, reflux, and autoclave with water solvent¹⁸. This difference in yield value can be influenced by differences in extraction methods using heating and vibration and solvent polarity¹⁹.

The results of this study indicate that there are differences in TPC and TFC of the three barks. These differences may be due to species differences. Bark extracts of A. leucophloea, A. pennata, A. ferruginea, and A. dealbata had different phenolic content, 76.3, 58.6, 53.5, and 46.5 mg GAE/100 g extract14. Previous research reported A. crassicarpa heartwood had a highes phenolic content, whereas A. mangium and A. auriculiformis had a lower phenolic content⁶. In this research, the TPC of the methanolic bark extract of A. auriculiformis was lower than the previous study using acetone²⁰. Extraction in this study used methanol which has a higher polarity than acetone, and the use of different types of solvents can affect the TPC. Acetone has a lower polarity than methanol, and phenolic compounds can be affected by the molecular weight of the solvent used²¹. Previous studies have shown that acetone contains the highest phenolic compounds compared to methanol and ethanol²². The known class of compounds includes phenolics, namely flavonoids, polyphenols, phenolic acids, lignans, and stilbenes. Phenolics have an aromatic ring with one or more hydroxyl groups so that they are readily soluble in polar solvents, such as methanol, ethanol, and acetone. Acetone solvent has the highest phenol activity compared to ethanol and methanol based on the previous research²³.

The flavonoid content has a higher value than the phenolic content. Determination of flavonoid levels using the AlCl₃ method aims to determine the levels of flavonoids from the flavone and flavonol groups²⁴. The high TFC in the three extracts was due to the high content of flavones and flavonols. Previous research has shown that identifying flavonoids with the AlCl₃ staining method is selective for flavonoids and flavonol types²⁵. Flavonoids are compounds that can dissolve nicely in ethanol, methanol, butanol, and acetone solvents.

The high antioxidant results in the DPPH and ABTS methods showed that the bark of A. mangium could scavenge free radicals well. In addition, the antioxidant activity of the three extracts used in this research was classified as very strong because it had an IC₅₀ of less than 50 µg/mL²⁶. The two methods used in this research have congruent results. Previous research has shown a good correlation between determination DPPH and ABTS²⁷. However, the antioxidant activity using ABTS is considered to have a higher sensitivity than other methods13. The bark of A. mangium has the highest antioxidant activity in the FRAP method. Hydroxyl and carbonyl groups in flavonoids can affect antioxidant activity. The bark of A. mangium showed that it could donate electrons, and its FRAP potential was better than other extracts²⁸. Previous research has shown differences in the trend of antioxidant activity, namely that A. crassicarpa heartwood has the highest activity compared to A. auriculiformis and A. mangium in the DPPH, ABTS, and FRAP assays⁶. The lower TPC content is because TPC does not always correlate with antioxidant activity because the Follin-Ciocalteu reagent used can react with glycosides in plants²⁹. High antioxidant activity in bark A. mangium was thought to be due to its high flavonoid content³⁰, although the DPPH test was different. Previous studies have identified that the knots of A. mangium have flavonoid compounds such as melacidin, isomelacidin, and biflavonoids⁸. The components of these compounds are thought to affect the antioxidant activity of A. mangium. In addition, high antioxidant activity is influenced by the number and position of different hydroxyl groups in flavonoids. Solvent polarity can also affect antioxidant activity³¹. The quercetin compound is an example of a compound with high activity because of its position on the hydroxyl group of ring B in the adjacent OH position (ortho).

The inhibitory activity of α-glucosidase in the three types of bark was classified as very active. However, A. mangium has a higher IC₅₀ value than previous studies using 50% ethanol as a solvent⁹. Another research with different species reported that the methanolic extract of A. macrostachya had vigorous α-glucosidase inhibitory activity on root bark and tree bark with IC₅₀ values of 2.48 µg/mL and 1.65 µg/mL³². The high inhibition of α-glucosidase in the bark of A. mangium is influenced by the flavonoid content and high antioxidant activity^{33, 34}.

Subfraction 6 was the most active in inhibiting the α-glucosidase enzyme but was not acting as an antioxidant. On the other hand, fraction 5 (not pure) is the most active fraction of antioxidants but is not acting as an α-glucosidase inhibitor. These results are quite interesting because the active compounds as inhibitors of α-glucosidase enzymes and antioxidants are different. The same phenomenon occured to the bark of Anthocephalus macrophyllus, the ethyl acetate fraction from the methanol extract was also the most active antidiabetic fraction³⁵.

Based on the molecular weight and ¹H and ¹³C NMR data characteristics in Figure 4A, this compound is suspected to be a scopoletin compound that is very similar to the measurement results in previous studies (Figure 4B)³⁶. Scopoletin belongs to the simple coumarin group. Scopoletin was also found in the ethyl acetate fraction of the methanolic bark extract of A. macrophyllus and noni fruit extract^35,37. Previous research has that scopoletin has antidiabetic activity³⁸.

Figure 4. (A) Chemical shift of the most active fraction & (B) chemical shift of scopoletin (Isma et al. 2018)

CONCLUSION:

The three methanol extracts of A. mangium, A. auriculiformis, and A. crassicarpa are antioxidants and inhibitors of α-glucosidase enzymes. The bark extract of A. mangium has the best antioxidant activity based on the DPPH, ABTS, and FRAP methods and the best inhibition of the α-glucosidase enzyme, supported by a high content of TPC and TFC. The most active fraction of the methanol extract of A. mangium as α-glucosidase inhibitor is the ethyl acetate fraction, while the butanol fraction is used as an antioxidant. The ethyl acetate fraction results in 7 sub-fractions, and sub-fraction 6 has the highest α-glucosidase enzyme inhibitory activity. By used LC-MS and FT-NMR data was identified the active isolate as scopoletin.

CONFLICT OF INTEREST:

We declare there is no conflict of interest in this study.

ACKNOWLEDGMENTS:

We would like to thank Perum Perhutani (Indonesia) and the Research Center and Development for Forest Tree Seed Technology (Indonesia) for providing bark samples. We also thank Research Center of Chemistry, Indonesian Institute of Science (LIPI) hich has assisted in this research activity.

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Received on 06.09.2021 Modified on 15.10.2021

Research J. Pharm. and Tech 2022; 15(9):3847-3853.

DOI: 10.52711/0974-360X.2022.00645