3.1. Antioxidant Activity
The optimization of antioxidant activity on ABTS-radical scavenging activity and phenolic content were studied using the simplex-centroid mixture design with three different
Melastoma extract components (
x1:
M. malabathricum,
x2: M. hirta,
x3:
M. decemfidum). The proportions of the mixtures used are presented in
Table 2 The experiments (1, 6, and 7) represent the pure components, the binary mixtures (2, 9, and 10), the tertiary mixtures (3, 4, and 11), and the center point (5, 8, and 12). The oxidant-ABTS radical cation is generated by persulphate oxidation of 2,2-azinobis (3-ethylbenzothiazoline-6-sulfonic acid). In this work, the radical-scavenging activity of each designed mixture was tested by measuring the decrease in its absorbance value at 734 nm, while the phenolic content of the mixtures of
Melastoma leaf extracts was measured based on the amount of phenolic compounds in dry weight gallic acid. The results show that the antioxidant activity from ABTS radical activity obtained from 100%
M. decemfidum gave the highest antioxidant activity at 93.11% and phenolic content at 29.25 mg/GAE. From this study, there is no significant difference between
M. hirta (92.96%) and
M. malabathricum (92.94%) in terms of ABTS radical activity. However, there were differences in the phenolic content of
M. hirta and
M. malabathricum which were 25.25 and 22.25 mg/GAE, respectively.
Furthermore, it can also be seen that the percentage inhibition in ABTS radical assays of all
Melastoma samples increased in each experimental mixture compared to its actual pure component. For instance, the binary mixture of
M. malabathricum and
M. decemfidum increased up to approximately 2%, yielding the highest antioxidant activity of ABTS (94.89%). It also showed that the combination of
M. hirta and
M. decemfidum increased the inhibition activities of the ABTS radical (94.57%) as compared to the pure components. Tertiary proportions (experiments 3, 4, and 11) represented the percentage inhibition of ABTS radical scavenging activities significantly increased compared to its pure components and binary combination. Moreover, the center point (experiments 5, 8, and 12), which corresponds to the equal proportions, also showed that percentage inhibition of ABTS and phenolic content increased. Recently, a similar study from Baj et al. [
18] revealed that the antioxidant potential measured in the mixtures of essential oils (EOs), basil, marjoram, and rosemary gave higher results than the pure samples.
The antioxidant activity of the
Melastoma leaf extract used in this study correlates with previous literature. For example, the decoction from the leaves of
M. decemfidum has been known to exhibit the phenol 2,4-bis (1,1-dimethylethyl) compound, which belongs to one of the important polyphenol antioxidant constituents, exhibiting antifungal effects [
19]. Phenolic compounds or polyphenols can be characterized as antioxidants, attractants (flavonoids and carotenoids), structural polymers (lignin), and defense response chemicals (tannins and phytoalexins) [
20]. Meanwhile, major antioxidant compounds were also found in both
M. malabathricum and
M. hirta. For example, Joffry et al. [
21] reported that the leaves of
M. malabathricum yielded a new compound of flavonol glycoside derivatives. Meanwhile, the phytochemical analysis of
M. hirta found positive phenolic compounds, such as flavonoids, tannins, and terpenoids [
22]. Hence, the presence of secondary metabolites in each
Melastoma leaf plays a vital role in human healthcare due to their free-radical scavenging effect, which is likely responsible for preventing various chronic diseases.
3.2. Statistical Analysis of the Model
Twelve mixture formulations were run according to the experimental design, and the respective coefficients of the regression model and ANOVA of the mathematical models were adjusted to the response function (
Table 3 and
Table 4). Based on
Table 3 and
Table 4, the model
F-value of ABTS radical activity was 45.41, while the phenolic content was 87.90, which implies that the models are significant. There is only a 0.03% and <0.0001% chance that a model
F-value this large could occur due to noise. Moreover, according to Fadil et al. [
13], it can be concluded that since the
p-values were 0.0003 and <0.0001, which are less than <0.05, the main effect of regression was statistically significant. Therefore, in this case, it shows that the model is significant.
Meanwhile, the entire model terms in the ABTS radical activity response (
x1,
x2, and
x3), where the values of probability > F are less than 0.05, indicate that the model terms are also significant. In this study, the linear mixture components
x1x2,
x1x3,
x2x3, and
x1x2x3 are significant model terms. According to the model terms in
Table 3, the ABTS antioxidant activity was highly significant (
p-value < 0.0001) for binary (
x1x3)
M. malabathricum and
M. decemfidum, followed by (
x2x3)
M. hirta and
M. decemfidum and tertiary (
x1x2x3)
M. malabathricum,
M. decemfidum, and
M. hirta. The mathematical model of ABTS antioxidant activity is presented in Equation (3), as follows:
Meanwhile, the model terms for the phenolic content response (
x1,
x2, and
x3), where the values of probability > F are less than 0.05, indicate that the model terms are significant. In this study, the linear mixture components
x1x3,
x2x3, and
x1x2x3 are significant model terms, except for the interaction between
x1x2 with a larger
p-value (0.2585), indicating that the combination of the mixtures produced the least response of interest. According to the model terms in
Table 4, the phenolic content activity was highly significant (
p-value < 0.0001) for tertiary (
x1x2x3)
M. malabathricum,
M. decemfidum, and
M. hirta, followed by binary (
x1x3)
M. malabathricum and
M. decemfidum and binary (
x2x3)
M. hirta and
M. decemfidum. The mathematical model of phenolic content activity is presented as follows in Equation (4):
This study shows that the models of the coefficients of determination were 98.20% for ABTS radical activity and 99.06% for phenolic content, which present the maximum degree of correlation between the observed and predicted values. Moreover, the high value of the adjusted R
2 (96.04% and 97.93%) also indicates a significant correlation between the experimental and predicted runs by the software. These results can be explained by a similar study by Yolmeh et al. [
23] where the model was considered accurate when R
2 was close to one.
Figure 2 and
Figure 3 show a linear curve for the experimental values in terms of the predicted ones. Next, the fitness of the models was also studied through a lack of fit test, where the values for all responses were not significant (
p-value > 0.05), which showed the suitability of models selected to predict the responses [
23].
3.3. Response Surface Analysis and Optimization
According to Ladeira et al. [
17], in the statistical methods, the response surface design is used to discover the effects of process variables on the specific responses of a system. In our study, the response surface for ABTS antioxidant activity with respect to the different proportions of the three
Melastoma leaf extracts,
M. malabathricum (
x1),
M. hirta (
x2), and
M. decemfidum (
x3), are shown in
Figure 4. The mixture contour plots in
Figure 4A,B show that the percentage inhibition of ABTS radical scavenging activity significantly increased with the addition of the
x3 component to both interactions of
x1 and
x2 components. This interaction can also be supported through the greater
F-values of these coefficients,
x1x3,
x2x3, and
x1x2x3, which yielded 164.86, 115.74, and 89.61, respectively in
Table 3.
Simultaneously, the response surface for the phenolic content activity of the
Melastoma leaf mixture extract is shown in
Figure 5. The mixture contour plots in
Figure 5a,b show that the phenolic content activity also increased with the addition of the
x3 component to both interactions of mixtures
x1 and
x2 components. From this result, the highest interaction between the mixtures can be seen from the coefficients of
x1x3 and
x1x2x3 where the greater
F-values of both coefficients yielded 140.51 and 150.81, respectively, in
Table 4. This result can be justified using the study of antimicrobial efficacy of essential oils by Quedrhiri et al. [
24] where different compounds can interact to either reduce or increase the response outcomes. On the other hand, in terms of ABTS radical activity, the component
x1 had a slight effect on the interaction of both
x2 and
x3 components, where the synergistic effect was found between the mixtures of
x1 and
x3, while antagonistic effects were found in the mixture of
x1 and
x2. Meanwhile, for the phenolic content activity of the mixture of
Melastoma extracts, the component
x3 showed a significant synergistic effect on either
x1 or
x2 coefficients. Therefore, it can be seen that the interaction between the three
Melastoma leaf extracts resulted in a significant effect on the scavenging activity of radical species and on the phenolic content activity.
The optimization technique was further evaluated after considering the simultaneous response surface and contour plot from the interaction between the independent variables and the response. This technique has been applied by Moreira et al. [
25] where a visual inspection of the contour charts was evaluated and studied in order to determine good operational conditions. In this study, a desirability function was generated to predict (1.00) the optimal points for each
Melastoma leaf extract. By performing real experiments on each optimal point mixture based on the prediction, the best optimum antioxidant activity for the simultaneous three
Melastoma leaf extracts was 30%
M. malabathricum, 40%
M. hirta, and 30%
M. decemfidum, yielding 93.0% antioxidant activity against radical species for the ABTS assay and 30.96 mg/g GAE for phenolic content.
Table 5 shows the optimal points for optimum antioxidant activity in the mixture of
Melastoma leaf extracts for both the ABTS radical assay and phenolic content.
3.4. Isolated Bioactive Compounds in Melastoma Leaf Extract Using HPLC
The isolation and identification of major and unique compounds in medicinal plants as markers are crucial steps in analytical methodologies for marker-based standardization. HPLC has recently emerged as a preferred analytical tool since it is simple, rapid, and precise for fingerprinting isolated compounds in plants. For instance, HPLC is commonly used by many researchers due to the small particle size and length in the HPLC column, which allows for an efficient separation and good resolution for biomarker identification. The HPLC method was developed in this study for the simultaneous identification of flavonoid constituents, such as quercetin and rutin, from the mixture of Melastoma leaf extracts. The HPLC system used in the present work was a reverse-phase C18 column, which can produce promising results with most common eluents. In the present work, the binary solvent system in gradient mode with acetonitrile and water/formic acid was able to achieve good peak resolution and symmetry due to buffering in the solution. Meanwhile, the separations of quercetin and rutin in a mixture of Melastoma plants were accomplished by gradient elution with a mobile phase consisting of water, formic acid, and acetonitrile. Furthermore, applying gradient solvents of acetonitrile with water gives sharp and symmetrical peaks with minimal noise, which supports the precise measurement of the peak area ratio. In this study, 0.1% formic acid was used due to its buffering capacity in the pH range of 2 to 4, and it provided a good volatile mobile phase that was efficient for separating flavonoid constituents.
HPLC chromatograms of flavonoid constituents (quercetin and rutin) of all the samples and standards were separated within 18 min and showed good resolution between the matrix and analyte peaks recorded at 254 nm, as shown in
Figure 6. From the observations, there were four peaks in the chromatogram of the optimized mixtures of
Melastoma extract. The first and second peaks were excluded in this study, which belongs to solvent and unknown peaks. Meanwhile, the third and fourth peaks were identified and confirmed from significant antioxidant constituents. In this analysis, both rutin and quercetin were identified in the mixture of
Melastoma leaf extract. The retention times of the mixture of
Melastoma leaf extracts were 7.770 min for rutin and 8.769 min for quercetin (
Table 6). They were confirmed and identified by comparing the retention time with two reference standard compounds from the standard response, such as in rutin (RT = 7.024 min) and quercetin (RT = 8.741 min) in
Table 7. On the other hand, it can be seen that the retention of rutin was shorter than quercetin. Wu et al. [
26] also found the same elution order in the chromatogram of rutin and quercetin obtained with an high performance liquid chromatography- ultraviolet (HPLC-UV) detector from a sample extract of Flos Sophorae Immaturus. The differences in retention time are mainly due to the role of flavonoid constituents of their differences in chemical structure and chemical variation, such as hydroxylation, methoxylation, the type of conjugation (glycosylation, sulfonation, malonylation), and the degree of polymerization [
27]. Meanwhile, the HPLC-UV peak area of rutin and quercetin shows that quercetin exhibits the largest quantity mass fraction (1498.90 mAU) as compared to rutin, which was 391.7 mAU. Saraf and Sankhla [
28] also found that the amount of quercetin is large compared to rutin in the methanolic extract of
Tecomella undulata.
Plant polyphenols, such as flavonoids, are a class of secondary metabolites that are also collectively known as “Vitamin-p” [
28]. The chemical structure of flavonoids consists of a C15 (C6–C3–C6) skeleton, and they are grouped into four major classes according to the position of the aromatic ring in the phenyl-benzopyran rings [
29]. They are widely distributed throughout the plant kingdom, and, to date, there are about 300 known flavonoids [
30]. Quercetin and rutin are considered the two main and most significant flavonoid compounds. Quercetin is known as 5,7,31,41-tetra hydroxy flavonol. Meanwhile, according to Ashok and Saini [
31], rutin is the rhamnoglucoside of the flavonoid quercetin (quercetin-3- rutinoside or 3,3′,4′,5,7-pentahydroxy flavones-3-rutinoside), and it is present in several plant parts. They both possess important phytochemicals and medicinal properties [
28]. For example, they provide several defense protections against ROS in humans. Moreover, flavonoids display a remarkable role in various pharmacological activities, such as antioxidant, anti-inflammatory, anti-diabetic, and anti-cancer effects [
31]. Therefore, these significant bioactive compounds of rutin and quercetin in the mixture of
Melastoma leaf extracts provide therapeutic value as the natural antioxidants against attacks caused by reactive oxygen species.
3.5. In Vitro Anti-Elastase and Collagenase Activity of the Mixture of Melastoma Leaf Extracts
Human skin is a complex structure that provides various important functions, including thermoregulation and protection against harmful substances. For instance, under normal conditions, the skin produces enzymes, such as elastase and collagenase, at a normal rate through the aging process. However, overexposure to ultraviolet radiation and harmful pollution results in enzymes that are produced at a faster rate following faster degradation of elastin and collagen, which are the main basis of the extracellular matrix (ECM) of the dermis [
32]. Additionally, the imbalance of ROS on the skin can interact with protein, DNA, and lipids and alter their cellular functions, thus causing premature aging and other skin-related disorders [
33]. Therefore, more research is needed to determine the inhibitors of these enzymes that can be used in cosmetics and medications to protect the skin from aging.
In this study, the in vitro inhibitory potential of bioactive compounds from the optimum mixture of Melastoma extract was carried out against elastase and collagenase enzymes. Prior to the analysis, the elastase inhibitory activity was determined by inhibition of the studied sample with the neutrophil elastase enzyme, which is a purified human neutrophil elastase combined with synthetic peptides as substrate molecules. Meanwhile, the collagenase inhibitory activity was determined by inhibition of the studied sample with the MMP-1 enzyme (interstitial collagenase) combined with synthetic peptides as substrates molecules. In this study, a slope of remaining activity for the tested sample against the control (without sample) was determined and the percentage and inhibition percentage were obtained by subtracting the obtained value from 100.
From the results in
Table 8, the elastase reduction activity of the optimum mixture of
Melastoma extract gave a good R
2 (0.9508), showing that it is not significantly different between the studied sample and positive inhibitor. Based on the results, the studied sample exhibited 27.78% in remaining elastase activity when compared to the positive control (elastastinal), which was recorded to have 27.77% (
Figure 7). Moreover,
Table 8 also revealed that there was about 72.22% inhibition of the elastase enzyme by an optimum mixture of the
Melastoma extract versus the positive inhibitor, which exhibited 72.23% inhibition. Meanwhile, for collagenase inhibition activity, it can be seen that the optimum mixture of the
Melastoma extract exhibited 29.13% remaining collagenase activity compared to the positive inhibitor (20.43%) (
Table 9,
Figure 7). It also shows that there was about 70.87% inhibition of collagenase activity by an optimum mixture of the
Melastoma extract versus the positive inhibitor, which exhibited 79.57% inhibition. From the results, the higher percentage inhibition activity for both elastase and collagenase enzymes by optimum
Melastoma extract can be supported by the bioactive compounds that are present in the
Melastoma leaf. For instance, rutin and quercetin compounds that are found in the leaf can significantly inhibit or slow down the generation of enzymes and radical activities. Moreover, an optimum mixture of
Melastoma extract exhibited numerous terpenoid compounds that can increase the rate of inhibition enzyme activity, as it was previously reported that terpenoid compounds in plant extracts can act as natural inhibitor agents [
32]. Therefore, it is interesting to note that the optimum mixture of the
Melastoma extract demonstrated good anti-elastase and anti-collagenase activity against premature skin aging.