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Kinetic of α-amylase inhibition by Gracilaria corticata and Sargassum angustifolium extracts and zinc oxide nanoparticles
Biocatalysis and Agricultural Biotechnology 23 (2020) 101478
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Biocatalysis and Agricultural Biotechnology
Kinetic of α-amylase inhibition by Gracilaria corticata and Sargassum angustifolium extracts and zinc oxide nanoparticles Soudeh Bahramian Nasab a, Ahmad Homaei a, *, Leila Karami b a b
Department of Marine Biology, Faculty of Marine Science and Technology, University of Hormozgan, Bandar Abbas, Iran Department of Horticulture, Faculty of Agriculture and Natural Resources, Persian Gulf University, Bushehr, Iran
ARTICLE INFO
ABSTRACT
Keywords: α-Amylase Zinc oxide Diabetes mellitus Enzyme inhibition Macroalgae
In this research, Gracilaria corticata red algae and Sargassum angustifolium brown algae were collected from tidal zones of the coastal areas of Bushehr (Persian Gulf coastline), and were extracted with methanol, ethanol, and sodium phosphate buffer. Zinc oxide nanoparticles were synthesized by chemical deposition. α-Amylase inhibition was evaluated using a colorimetric method based on the reduction of maltose released from a starch solution. The results showed that with increased sample concentration, the α-amylase was increasingly inhibited. The phosphate buffer extract of Gracilaria corticata showed the highest α-amylase inhibition, with an IC50 of 0.44 mg/mL and with inhibition following a competitive mechanism. The phosphate buffer extract of Sargassum angustifolium showed the lowest α-amylase inhibition with an IC50 of 1.85 mg/mL. Zinc oxide nanoparticles inhibited with an IC50 of 0.34 mg/mL with inhibition following a competitive mechanism. The two species of algae studied in this research, which both exhibited anti-diabetic activity, have potential for lowering intestinal glucose uptake in diabetic patients.
1. Introduction Diabetes mellitus is a metabolic disorder characterized by chronic hyperglycemia along with an impaired metabolism of carbohydrates, fats and proteins (Kaneto et al., 2007). The disorder is caused by defects in the secretion or function of insulin, and usually originates from a defect in the pancreatic beta cells (Jain and Saraf, 2010) Two main types of diabetes mellitus exist. In type 1 diabetes, called “insulin-dependent diabetes”, the body does not have the ability to make insulin (Cardozo et al., 2007; Danaei et al., 2011) Patients with this type of diabetes need to inject insulin to control their glucose metabolism. In type 2 diabetes, which is called “non-insulin-dependent diabetes”, insulin secretion is normal, but the body is resistant to insulin resulting in high blood glucose levels (Jain and Saraf, 2010). Type 2 diabetes can be managed by modifying lifestyle and taking antidiabetic oral medication. Currently, about 425 million people worldwide are suffering from diabetes, of which 90 percent have type 2 diabetes (Nam Han Cho (chair) et al., 2017). Diabetes is considered to be the most expensive endocrine disorder in the world, because of the high cost of treating its complications, including cardiovascular dis-
ease, and problems with eyes, kidneys, and feet (Nam Han Cho (chair), Mbanya et al., 2017). Diabetes may be asymptomatic in the early stages, but diabetes symptoms become more pronounced when blood glucose levels rise (Gokce and Haznedaroglu, 2008). “Postprandial hyperglycemia” is one of the most important risk factors for the development of type 2 diabetes, since continued high blood sugar levels generate “free radicals” (Olaokun et al., 2013), which play a major role in the onset and progression of diabetes and its secondary disorders (Gholamhoseinian et al., 2008). Therefore, it is important to keep blood glucose levels in the normal range. One of the treatment options is to limit the absorption of carbohydrates after ingesting food (Gholamhoseinian et al., 2008; Olaokun et al., 2013). This can be done by inhibiting the digestive carbohydrate-hydrolyzing enzymes such as α-amylase and α-glucosidase (Vardhini et al., 2013). α-Amylase catalyzes the breakdown of amylose and amylopectin, which are the long-chain carbohydrates of starch (Tarling et al., 2008). The produced free glucose is absorbed by the intestine and causes hyperglycemia. Inhibition of these starch-degrading enzymes reduces the digestion of carbohydrates, and thus reduces glucose absorption and consequently lowers blood glucose levels (Tarling et al.,
* Corresponding author. Department of Marine Biology, Faculty of Marine Science and Technology, University of Hormozgan, P.O. Box 3995, Bandar Abbas, Iran. E-mail address: [email protected], [email protected] (A. Homaei).
https://doi.org/10.1016/j.bcab.2019.101478 Received 23 November 2019; Received in revised form 15 December 2019; Accepted 16 December 2019 Available online 19 December 2019 1878-8181/© 2019 Elsevier Ltd. All rights reserved.
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Fig. 1. (a–c). Percentage of α-amylase activity in the presence of various concentrations of methanolic, ethanolic and sodium phosphate buffer extracts of S. angustifolium (a), G. corticata (b), and zinc oxide nanoparticles (c).
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Fig. 2. (a–c). Percentage of α-amylase inhibition in the presence of various concentrations of methanolic, ethanolic and sodium phosphate buffer extracts of S. angustifolium (a), G. corticata (b), and zinc oxide nanoparticles (c).
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Fig. 3. (a–c). Inhibition of α-amylase as represented by the IC50 value in the presence of various concentrations of methanolic, ethanolic and sodium phosphate buffer extracts of S. angustifolium (a), G. corticata (b), and zinc oxide nanoparticles (c).
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compounds has attracted broad attention of researchers (O'sullivan, O'Callaghan et al., 2011), because the compounds may include potential therapeutic agents to treat chronic diseases, such as diabetes, through the inhibition of starch digesting enzymes (Lee et al., 2010). A recent revolutionary development in medicine is the use of nanotechnology. The advantages of nanotechnology include controlled transfer of drugs to target organs, topical release of drugs, increased treatment efficacy resulting from increased drug solubility and absorption, reduced side effects, reduced toxicity of drugs, and lower dose (Fariq et al., 2017). Zinc nanoparticles are particularly interesting, since Zn2+ ions are involved in insulin secretion by the pancreatic islets of Langerhans (Dodson and Steiner, 1998) and they are beneficial for insulin function and carbohydrate metabolism (Arquilla et al., 1978). The present study was conducted to evaluate the inhibition of αamylase by Gracilaria corticata and Sargassum angustifolium algal extracts, as well as by zinc oxide nanoparticles, to determine their antidiabetic activity.
Table 1
Results of inhibition of α- amylase enzyme based on IC50 (The IC50 represents the concentration of the extract that inhibits 50% of the activity of the enzyme.). inhibitor
IC50 (mg/mL)
log IC50
Zinc oxide Methanolic extract of S. angustifolium Ethanolic extract of S. angustifolium Buffer extract of S. angustifolium Methanolic extract of G. corticata Etanolic extract of G. corticata Buffer extract of G.corticata
0.34 1.02 0.68 1.85 1.38 0.71 0.44
2.5 3.008 2.832 3.268 3.142 2.854 2.644
Table 2
Comparison of the kinetics parameters related to the α- amylase enzyme in the presence and absence of inhibitors and the type of inhibition. Title
Km (mM)
Vmax (μM/min)
Variation of Km and Vmax
Type of inhibition
Absence of inhibitors In the presence of methanolic extract of S. angustiflium In the presence of ethanolic extract of S. angustiflium
1.6
0.1665
0.62
0.0631
Uncompetitive inhibition
1.42
0.0778
In the presence of buffer extract of S. angustiflium
0.44
0.081
Mixed (Orientation to none- competitive inhibition) Mixed inhibition
In the presence of methanolic extract of G. corticata In the presence of ethanolic extract of G. corticata
0.34
0.0661
Mixed inhibition
2.92
0.1521
Competitive inhibition
In the presence of buffer extract of G .corticata
4.04
0.1714
Competitive inhibition
ZnO
4.48
0.1398
Competitive inhibition
2. Materials and methods 2.1. Sample preparation 2.1.1. Preparation of zinc oxide nanoparticles Zinc oxide nanoparticles were synthesized by the chemical deposition method. First, 0.46 g of Zn(CH₃COO)2 H₂O was added to 5 mL of PEG 600. Then, while warming up in an oil bath, sodium hydroxide was added under stirring until it was dissolved. Next, the reaction mixture was refluxed for 1.5 h, resulting in completely stable, colloidal ZnO nanoparticles with a small particle size. Then, the flask was covered with Parafilm and stored at 4 °C. The concentration of the dispersed ZnO nanoparticles solution was 5400 ppm. 2.1.2. Preparation of algae samples Red Gracilaria corticata and brown Sargassum angustifolium algae were collected from tidal zones of the coastal areas of Bushehr (Persian Gulf coastline). Their morphological characteristics (type, color, texture, shape and habitat) were recorded, resulting in a consistent assignment of the species. The collected algae were individually washed with distilled water to remove sand particles, epiphytes and sea salt, and transferred to the lab in a numbered bag. The numbered specimens were dried at room temperature. The dried samples were then powdered and stored at 4 °C for further testing.
2008). Therefore, enzyme inhibitors can be useful in the management of type 2 diabetes. The use of synthetic drugs is less preferred because of their side effects such as stomach bloating, diarrhea, and vomiting, and other side effects resulting from the long-term use of these drugs. Therefore, much research is devoted to find more effective alternative low-cost treatments with fewer side effects. Most people in developing countries consider alternative therapies, including the use of natural sources (traditional medicine), for their primary health care (Hassan et al., 2010). A wide range of active therapeutic agents have successfully been isolated from natural sources and are now subject to clinical investigation (Yasuhara-Bell and Lu, 2010). One of these sources is the huge marine environment, and bioactive compounds from many marine organisms are being considered for the development of new medicines (Liu et al., 2011; Sun et al., 2011). Macro-algae are organisms that produce a wide range of biologically active secondary metabolites. For instance, brown algae produce a variety of polysaccharide compounds, including laminarin, fucoidan and alginate, which have anti-diabetic properties (Rioux et al., 2007). Poly-phenolic compounds in red algae also act as effective antidiabetic ingredients through their inhibitory effect on starch-digesting enzymes (Lee et al., 2007). The identification and separation of these
2.1.3. Preparation of extracts To prepare the extracts, 30 g of each powdered alga species were weighed on a scale, and transferred to Erlenmeyer flasks. Then, 200 mL ethanol, or 200 mL methanol, or 200 mL 0.1M sodium phosphate buffer (pH 7) were added to the Erlenmeyer flask, and the suspensions were incubated at 37 °C. After 48 h, the raw extracts were filtered with filter paper (Whatman plc) and the alcoholic extracts were concentrated in a rotary evaporator. Non-alcoholic filtered extracts and alcoholic condensate extracts were individually placed in Petri dishes. The non-alcoholic filtered extracts were placed in an oven at 40 °C for 72 h, and the alcoholic condensate extracts were dried at room temperature for 48 h. The resulting powders were pre-weighed in micro tubes, and stored in a freezer at -80 °C. 2.2. Evaluation of the inhibition of α-amylase activity The inhibition of the α-amylase activity was evaluated using a colorimetric method (DNS) based on the reduction of the release of maltose from a starch solution, according to the method reported by Miller (1959) with slight changes. 40 μl of different concentrations 5
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Fig. 4. (a–c). Michaelis-Menten enzyme kinetics in presence and absence of methanolic (a), ethanolic (b) and phosphate buffer extracts (c) of S. angustifolium.
(0.2, 0.4, 0.6, 0.8 and 1 mg/mL dry material) of the extracts was added to separate test tubes. For the nanoparticles 410 μl suspension in 0.1 M sodium phosphate buffer (pH 7) was used. Next, 500 μl of 1% starch solution and 50 μl of α-amylase (500 k-unit/mg purchased from SIGMA) were added. After incubation at 60 °C for 20 min 1 mL of DNS solution was added, and the mixture was placed at 100 °C for 5 min, and then cooled to room temperature in a water bath. Finally, the absorbance at 540 nm was measured using a spectrophotometer. A sample with only sodium phosphate buffer was used as a positive
control (100% enzyme activity). Negative controls contained no enzyme, and had 0% enzyme activity. The percentage reaction activity was calculated using Formula (1) and the percentage inhibition was calculated using Formula (2).
(1)
Inhibition(%) = 100 − Reaction(%) 6
(2)
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Fig. 5. (a–c). Michaelis-Menten enzyme kinetics in presence and absence of methanolic (a), ethanolic (b) and phosphate buffer extracts (c) of G. corticata.
were determined for each of the inhibitors discussed in this study. The IC50 represents the concentration of the extract that inhibits 50% of the activity of the enzyme. The inhibitory power of the extracts based on IC50 was compared.
2.3. Statistical analysis The α-amylase inhibition was determined three times for each of the extracts and the zinc oxide nanoparticles (at different concentrations), and the mean and standard deviation were calculated using Excel software. Then, using the GraphPad Prism software, the enzyme activity, the percentage of enzyme inhibition, and the IC50 values 7
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Fig. 6. Michaelis-Menten enzyme kinetics in presence and absence of ZnO nanoparticles.
the highest Vmax was obtained with the sodium phosphate buffer extract of Gracilaria corticata. The highest Km value was obtained with the zinc oxide nanoparticles.
2.4. Enzyme kinetics To determine the kinetics of the α-amylase catalyzed reaction in the absence and presence of inhibitors (IC50-related concentrations), 50 μl of a constant concentration of α-amylase and 500 μl of different substrate concentrations were used. In this study, the Michaelis-Menten equation was used to determine the enzyme kinetics and inhibition mechanism. From the Michaelis-Menten kinetics, the maximum velocity (Vmax) and the Michaelis-Menten constant (Km) were determined. By comparing the kinetic parameters of the enzyme (Km and Vmax) in the presence and absence of inhibitor, the type of inhibition was determined.
4. Discussion The significant increase in the incidence of diabetes, and particular of type 2 diabetes, is a major concern of the World Health Organization in the 21st century (DeVille-Almond, Tahrani et al., 2011). In diabetic patients, controlling blood glucose levels after eating is one of the most important factors of disease control (KWON, Apostolidis et al., 2008). To this end, a major goal of the treatment is to control the enzymes involved in carbohydrate metabolism and to prevent glucose uptake from food intake (Kurihara et al., 1999). α-Amylase is one of the key enzymes in the digestive carbohydrate metabolism. It breaks down the large carbohydrate chains of starch and glycogen by hydrolyzing α-D-(1–4) glycosidic bonds and producing simpler sugars such as glucose and maltose (Brayer et al., 2000; Tangphatsornruang et al., 2005). α-Amylase inhibitors reduce the activity of α-amylase enzymes, thereby decreasing the amount of glucose produced in the intestine and reducing blood glucose levels. Several compounds have been found to be efficacious α-amylase inhibitors (Moorthy et al., 2012). In the present study, the effect of zinc oxide nanoparticles and methanolic, ethanolic and sodium phosphate buffer extracts of two species of algae, Gracilaria corticata red algae and Sargassum angustifolium brown algae, on the activity of α-amylase was determined. Our investigations showed that the ethanolic extract of Sargassum angustifolium gave the strongest α-amylase inhibition (68% inhibition). Other investigators have also observed strong α-amylase inhibition by macro-algal extracts. For instance, α-amylase was found to be inhibited by methanolic extracts of Sirophysalis trinodis brown algae (97% inhibition), ethyl acetate extracts of Polycladia myrica (97% inhibition), and methanolic extracts of Sargassum glaucesens (77.8% inhibition) (Payghami et al., 2015; Pirian et al., 2017). By comparing our results with those of others, some differences are apparent. For example, in a study conducted by Kumar and Sellappa (2012) on other Gracilaria and Sargassum species (Gracilaria corticata, Gracilaria gracilis, Sargassum polycystum), IC50 values in the range of 60 to 83 μg/mL were reported (Kumar and Sellappa, 2012), while our research gave IC50 values of 0.44 mg/mL and higher (Table 1). Our IC50 values are similar to the IC50 values of 0.42 to 7.5 mg/mL reported by Pirian et al. (2017) for methanol, hexane and ethyl acetate extracts of various Persian Gulf macro algae, including Gracilaria corticata and Sargassum angustifolium (Pirian et al., 2017). Such species-related differences are common in many similar studies. For
3. Results 3.1. Inhibition of enzyme activity Fig. 1(a–c) shows the relative activity of the enzyme as a function of the inhibitor concentration. In all cases, as the inhibitor concentration increases, the enzyme activity decreases. At the highest inhibitor concentration of 1 mg/mL dry material the S. angustifolium buffer extract had the lowest inhibition power (about 69%). Fig. 2(a–c) shows the percentage inhibition of the enzyme as a function of the inhibitor concentration (0.2–1 mg/mL). At 1 mg/mL of the S. angustifolium extracts, the most powerful α-amylase inhibitor is the ethanolic extract (68% inhibition, compared to 49% and 31% inhibition by the methanolic and buffer extracts, respectively). In contrast, for the Gracilaria corticata extracts, the phosphate buffer extract is the best (72% inhibition, compared to 41% and 69% inhibition by the methanolic and ethanolic extracts. At 1 mg/mL zinc oxide nanoparticles gave 78% inhibition, which is somewhat better than the inhibition by the various algal extracts. 3.2. IC50 values of inhibitory action Fig. 3(a–c) and Table 1 show the α-amylase inhibition based on IC50 in the presence of each extract. In this study, the highest inhibitory effect was found for the sodium phosphate buffer extract of Gracilaria corticata, which gave an IC50 of 0.44 mg/mL. 3.3. Results of kinetics of α-amylase enzyme and determination of the type inhibition of enzyme The results of the α-amylase inhibition kinetics are reported in Table 2, and Figs. 4–6. According to the Michaelis-Menten analysis, 8
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example, the IC50 value reported by Lee and Han (2012) for a methanol extract of Sargassum ringgoldianum is about 0.8 mg/mL, but the IC50 reported by Payghami et al. (2015) for methanolic extracts of Sargassum glaucesens is about 8.9 mg/mL (Lee and Han, 2012; Payghami et al., 2015). Thus, differences in species type may strongly affect the α-amylase inhibition potency of the extracts. The type of extraction solvent may also affect the degree of αamylase inhibition. For instance, in a study by Kumar et al. (2012) water was used as a solvent, while in the present study methanol, ethanol and sodium phosphate buffer were used. Pirian et al. (2017) used n-hexane, methanol and ethyl acetate as extraction solvents (Kumar and Sellappa, 2012; Pirian et al., 2017), showing that ethyl acetate extracts had a higher α-amylase inhibitory effect than nhexane. The superiority of methanol and ethyl acetate compared to nhexane has also been reported in other studies of α-amylase inhibition (SHN Moorthy, J Ramos et al., 2012). As another example, the IC50 of the aqueous extract of Ascophyllum nodosum reported by Lee et al. (2010) was about 10 times higher than that of phenolic compounds studied by Nwosu et al. (2011)(Nwosu et al., 2011). Another reason for the different results is related to differences in the extraction methods. The extraction method used in the current study consisted of soaking and drying at room temperature and then in an oven, while in other studies extraction was done by percolation, decoction, extraction with a soxhlet extractor, or by ultrasonic extraction (Heo et al., 2009; Lee et al., 2010; Payghami et al., 2015). Comparing the degree of α-amylase inhibition in the various studies, there are significant differences in the inhibition of the enzyme (in term of percentage) for a similar composition of what, which can be linked to different methods for enzyme inhibition control. Among these methods, two types of tests are widely used to determine the effect on α-amylase activity. One is based on use of dinitrosalicylic acid reagent for determination of reducing sugar (Miller, 1959), and another on the basis of change of the color of starch-iodine complexes in the substrate coloring (Fuwa, 1954). In the present study, DNS coloring was used to determine the degree of inhibition. Enzymatic kinetics is a laboratory method that measures the amount of enzyme response at close to zero times. From the Michaelis-Menten kinetics the maximum rate (Vmax) can be calculated. Vmax is the rate achieved by the system at saturating substrate concentration. In this study, in the absence of an inhibitor, Vmax was found to be 0.1665 μmol/min, while this value in the presence of inhibitors was found to be between 0.0631 to 0.1714 μmol/min. Another kinetic parameter determined in this study was the Michaelis constant Km, which is the substrate concentration at which the reaction rate is half of Vmax. In the absence of inhibitors, the Km was found to be 1.6 mmol, but in the presence of inhibitors it ranged from 0.34 to 4.04 mmol. From the values of Vmax and Km the type of inhibitory process (competitive, uncompetitive, non-competitive, or mixed inhibitory) can be deduced. In the presence of competitive inhibitors, Vmax stays the same, but Km increases. Our study indicates that the ethanolic and sodium phosphate buffer extracts of Gracilaria corticata and zinc oxide nanoparticles act as competitive inhibitors. Non-competitive inhibitors reduce the value of Vmax, and Km does not change. The Sargassum angustifolium ethanolic extract thus acted as a non-competitive inhibitor. Uncompetitive inhibitors reduce both Vmax and Km. The Sargassum angustifolium methanolic extract appeared to act as an uncompetitive inhibitor. Other inhibitors of this study showed mixed inhibitory behaviour. Mixed inhibitors can be tend to other types of inhibition (uncompetitive, competitive and non-competitive). Zinc oxide nanoparticles inhibited α-amylase for 78% at 1 mg/mL concentration and gave an IC50 of 0.34 mg/mL. In a study by Dhobale et al. (2008), the inhibitory effect of zinc oxide nanoparticles de-
posited in the presence of thioglycerol was 49% at 20 μg/mL concentration (Dhobale et al., 2008). Shaik and Kumar (2016) found that 30 μg/mL zinc oxide nanoparticles (in the presence of thioglycerol) gave 56% α-amylase inhibition, but 30 μg/mL zinc oxide nanoparticles coated with acarbose gave 75% inhibition (Shaik and Kumar 2016). These results show that zinc oxide nanoparticles on their own can inhibit α-amylase. The inhibition mechanism is not known, although it can be envisaged that the nanoparticles bind to reactive amino or carboxyl groups near the active site of the enzyme (Dhobale et al., 2008). 5. Conclusion Zinc oxide nanoparticles as well as extracts of Gracilaria corticata and Sargassum angustifolium algae show promising inhibitory activity towards α-amylase, which suggests that they may be good starting points for the development of drugs for controlling blood glucose levels in diabetic patients. Moreover, nanoparticles represent a new class of materials in the field of biomedicine, with high potential for broad application in diagnostics, drug delivery, and therapeutics. Author statment The authors declare that there is no conflict of interest regarding the publication of this paper. We concur with the submission and have seen a draft copy of the manuscript and agree with its publication. Declaration of competing interest The authors of this manuscript declare that have no conflict of interest. Acknowledgements The authors are grateful to the University of Hormozgan for the financial support to this research. References Arquilla, E.R., Packer, S., Tarmas, W., Miyamoto, S., 1978. The effect of zinc on insulin metabolism. Endocrinology 103 (4), 1440–1449. Brayer, G.D., Sidhu, G., Maurus, R., Rydberg, E.H., Braun, C., Wang, Y., Nguyen, N.T., Overall, C.M., Withers, S.G., 2000. Subsite mapping of the human pancreatic αamylase active site through structural, kinetic, and mutagenesis techniques. Biochemistry 39 (16), 4778–4791. Cardozo, K.H., Guaratini, T., Barros, M.P., Falcão, V.R., Tonon, A.P., Lopes, N.P., Campos, S., Torres, M.A., Souza, A.O., Colepicolo, P., 2007. Metabolites from algae with economical impact. Comp. Biochem. Physiol. C Toxicol. Pharmacol. 146 (1–2), 60–78. Danaei, G., Finucane, M.M., Lu, Y., Singh, G.M., Cowan, M.J., Paciorek, C.J., Lin, J.K., Farzadfar, F., Khang, Y.-H., Stevens, G.A., 2011. National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370 country-years and 2· 7 million participants. The Lancet 378 (9785), 31–40. DeVille-Almond, J., Tahrani, A.A., Grant, J., Gray, M., Thomas, G.N., Taheri, S., 2011. Awareness of obesity and diabetes: a survey of a subset of British male drivers. Am. J. Men’s Health 5 (1), 30–37. Dhobale, S., Thite, T., Laware, S.L., Rode, C.V., Soumya, J., Koppikar, Ghanekar, R.-K., Kale, S.N., 2008. Zinc oxide nanoparticles as novel alpha-amylase inhibitors. J. Appl. Phys. 104 (9). Dodson, G., Steiner, D., 1998. The role of assembly in insulin’s biosynthesis. Curr. Opin. Struct. Biol. 8 (2), 189–194 8(2), 189-194. Fariq, A., Khan, T., Yasmin, A., 2017. Microbial synthesis of nanoparticles and their potential applications in biomedicine. J. Appl. Biomed. 15 (4), 241–248. HIDETSUGU FUWA, 1954. A new method for micro determination cf amylase activity by the use of amylose as the substrate. J. Biochem. 41 (5), 583–603. Gholamhoseinian, A., Fallah, H., Sharifi-far, F., Mirtajaddini, M., 2008. The inhibitory effect of some Iranian plants extracts on the alpha glucosidase. Iranian journal of basic medical sciences 11 (1), 1–9. Gokce, G., Haznedaroglu, M.Z., 2008. Evaluation of antidiabetic, antioxidant and vasoprotective effects of Posidonia oceanica extract. J. Ethnopharmacol. 115 (1), 122–130. Hassan, Z., Yam, M.F., Ahmad, M., Yusof, A.P.M., 2010. Antidiabetic properties and
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Reja, A., 2017. IDF Diabetes Atlas. eighth ed. Nwosu, F., Morris, J., Lund, V.A., Stewart, D., Ross, H.A., McDougall, G.J., 2011. Antiproliferative and potential anti-diabetic effects of phenolic-rich extracts from edible marine algae. Food Chem. 126 (3), 1006–1012. O’sullivan, A., O’Callaghan, Y., O’Grady, M., Queguineur, B., Hanniffy, D., Troy, D., Kerry, J., O’Brien, N., 2011. In vitro and cellular antioxidant activities of seaweed extracts prepared from five brown seaweeds harvested in spring from the west coast of Ireland. Food Chem. 126 (3), 1064–1070. Olaokun, O.O., McGaw, L.J., Eloff, J.N., Naidoo, V., 2013. Evaluation of the inhibition of carbohydrate hydrolysing enzymes, antioxidant activity and polyphenolic content of extracts of ten African Ficus species (Moraceae) used traditionally to treat diabetes. BMC Complement Altern. Med. 13 (1), 94. Payghami, N., Jamili, S., Rustaiyan, A., Saeidnia, S., Nikan, M., Gohari, A.R., 2015. Alpha-amylase inhibitory activity and sterol composition of the marine algae, Sargassum glaucescens. Pharmacogn. Res. 7 (4), 314. Pirian, K., Moein, S., Sohrabipour, J., Rabiei, R., Blomster, J., 2017. Antidiabetic and antioxidant activities of brown and red macroalgae from the Persian Gulf. J. Appl. Phycol. 29 (6), 3151–3159. Rioux, L.-E., Turgeon, S.L., Beaulieu, M., 2007. Characterization of polysaccharides extracted from brown seaweeds. Carbohydr. Polym. 69 (3), 530–537. Shaik, F., Kumar, A., 2016. ZnO nanoparticles and their acarbose-capped nanohybrids as inhibitors for human salivary amylase. IET Nanobiotechnol. 11 (3), 329–335. SHN Moorthy, N., J Ramos, M., A Fernandes, P., 2012. Studies on α-glucosidase inhibitors development: magic molecules for the treatment of carbohydrate mediated diseases. Mini Rev. Med. Chem. 12 (8), 713–720. Sun, H.-H., Mao, W.-J., Jiao, J.-Y., Xu, J.-C., Li, H.-Y., Chen, Y., Qi, X.-H., Chen, Y.-L., Xu, J., Zhao, C.-Q., 2011. Structural characterization of extracellular polysaccharides produced by the marine fungus Epicoccum nigrum JJY-40 and their antioxidant activities. Mar. Biotechnol. 13 (5), 1048–1055. Tangphatsornruang, S., Naconsie, M., Thammarongtham, C., Narangajavana, J., 2005. Isolation and characterization of an α-amylase gene in cassava (Manihot esculenta). Plant Physiol. Biochem. 43 (9), 821–827. Tarling, C.A., Woods, K., Zhang, R., Brastianos, H.C., Brayer, G.D., Andersen, R.J., Withers, S.G., 2008. The search for novel human pancreatic α-amylase inhibitors: high-throughput screening of terrestrial and marine natural product extracts. Chembiochem 9 (3), 433–438. Vardhini, R.S., Naik, B.R., Neelima, M., Ramesh, B.P., Sciences, P., 2013. Screening and production of α-amylase from Aspergillus Niger using zero, value material for solid state fermentation. Int. J. Pharm. Pharm. Sci. 5 (1), 55–60. Yasuhara-Bell, J., Lu, Y., 2010. Marine compounds and their antiviral activities. Antivir. Res. 86 (3), 231–240.
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Contents lists available at ScienceDirect
Biocatalysis and Agricultural Biotechnology
Kinetic of α-amylase inhibition by Gracilaria corticata and Sargassum angustifolium extracts and zinc oxide nanoparticles Soudeh Bahramian Nasab a, Ahmad Homaei a, *, Leila Karami b a b
Department of Marine Biology, Faculty of Marine Science and Technology, University of Hormozgan, Bandar Abbas, Iran Department of Horticulture, Faculty of Agriculture and Natural Resources, Persian Gulf University, Bushehr, Iran
ARTICLE INFO
ABSTRACT
Keywords: α-Amylase Zinc oxide Diabetes mellitus Enzyme inhibition Macroalgae
In this research, Gracilaria corticata red algae and Sargassum angustifolium brown algae were collected from tidal zones of the coastal areas of Bushehr (Persian Gulf coastline), and were extracted with methanol, ethanol, and sodium phosphate buffer. Zinc oxide nanoparticles were synthesized by chemical deposition. α-Amylase inhibition was evaluated using a colorimetric method based on the reduction of maltose released from a starch solution. The results showed that with increased sample concentration, the α-amylase was increasingly inhibited. The phosphate buffer extract of Gracilaria corticata showed the highest α-amylase inhibition, with an IC50 of 0.44 mg/mL and with inhibition following a competitive mechanism. The phosphate buffer extract of Sargassum angustifolium showed the lowest α-amylase inhibition with an IC50 of 1.85 mg/mL. Zinc oxide nanoparticles inhibited with an IC50 of 0.34 mg/mL with inhibition following a competitive mechanism. The two species of algae studied in this research, which both exhibited anti-diabetic activity, have potential for lowering intestinal glucose uptake in diabetic patients.
1. Introduction Diabetes mellitus is a metabolic disorder characterized by chronic hyperglycemia along with an impaired metabolism of carbohydrates, fats and proteins (Kaneto et al., 2007). The disorder is caused by defects in the secretion or function of insulin, and usually originates from a defect in the pancreatic beta cells (Jain and Saraf, 2010) Two main types of diabetes mellitus exist. In type 1 diabetes, called “insulin-dependent diabetes”, the body does not have the ability to make insulin (Cardozo et al., 2007; Danaei et al., 2011) Patients with this type of diabetes need to inject insulin to control their glucose metabolism. In type 2 diabetes, which is called “non-insulin-dependent diabetes”, insulin secretion is normal, but the body is resistant to insulin resulting in high blood glucose levels (Jain and Saraf, 2010). Type 2 diabetes can be managed by modifying lifestyle and taking antidiabetic oral medication. Currently, about 425 million people worldwide are suffering from diabetes, of which 90 percent have type 2 diabetes (Nam Han Cho (chair) et al., 2017). Diabetes is considered to be the most expensive endocrine disorder in the world, because of the high cost of treating its complications, including cardiovascular dis-
ease, and problems with eyes, kidneys, and feet (Nam Han Cho (chair), Mbanya et al., 2017). Diabetes may be asymptomatic in the early stages, but diabetes symptoms become more pronounced when blood glucose levels rise (Gokce and Haznedaroglu, 2008). “Postprandial hyperglycemia” is one of the most important risk factors for the development of type 2 diabetes, since continued high blood sugar levels generate “free radicals” (Olaokun et al., 2013), which play a major role in the onset and progression of diabetes and its secondary disorders (Gholamhoseinian et al., 2008). Therefore, it is important to keep blood glucose levels in the normal range. One of the treatment options is to limit the absorption of carbohydrates after ingesting food (Gholamhoseinian et al., 2008; Olaokun et al., 2013). This can be done by inhibiting the digestive carbohydrate-hydrolyzing enzymes such as α-amylase and α-glucosidase (Vardhini et al., 2013). α-Amylase catalyzes the breakdown of amylose and amylopectin, which are the long-chain carbohydrates of starch (Tarling et al., 2008). The produced free glucose is absorbed by the intestine and causes hyperglycemia. Inhibition of these starch-degrading enzymes reduces the digestion of carbohydrates, and thus reduces glucose absorption and consequently lowers blood glucose levels (Tarling et al.,
* Corresponding author. Department of Marine Biology, Faculty of Marine Science and Technology, University of Hormozgan, P.O. Box 3995, Bandar Abbas, Iran. E-mail address: [email protected], [email protected] (A. Homaei).
https://doi.org/10.1016/j.bcab.2019.101478 Received 23 November 2019; Received in revised form 15 December 2019; Accepted 16 December 2019 Available online 19 December 2019 1878-8181/© 2019 Elsevier Ltd. All rights reserved.
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Fig. 1. (a–c). Percentage of α-amylase activity in the presence of various concentrations of methanolic, ethanolic and sodium phosphate buffer extracts of S. angustifolium (a), G. corticata (b), and zinc oxide nanoparticles (c).
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Fig. 2. (a–c). Percentage of α-amylase inhibition in the presence of various concentrations of methanolic, ethanolic and sodium phosphate buffer extracts of S. angustifolium (a), G. corticata (b), and zinc oxide nanoparticles (c).
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Fig. 3. (a–c). Inhibition of α-amylase as represented by the IC50 value in the presence of various concentrations of methanolic, ethanolic and sodium phosphate buffer extracts of S. angustifolium (a), G. corticata (b), and zinc oxide nanoparticles (c).
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compounds has attracted broad attention of researchers (O'sullivan, O'Callaghan et al., 2011), because the compounds may include potential therapeutic agents to treat chronic diseases, such as diabetes, through the inhibition of starch digesting enzymes (Lee et al., 2010). A recent revolutionary development in medicine is the use of nanotechnology. The advantages of nanotechnology include controlled transfer of drugs to target organs, topical release of drugs, increased treatment efficacy resulting from increased drug solubility and absorption, reduced side effects, reduced toxicity of drugs, and lower dose (Fariq et al., 2017). Zinc nanoparticles are particularly interesting, since Zn2+ ions are involved in insulin secretion by the pancreatic islets of Langerhans (Dodson and Steiner, 1998) and they are beneficial for insulin function and carbohydrate metabolism (Arquilla et al., 1978). The present study was conducted to evaluate the inhibition of αamylase by Gracilaria corticata and Sargassum angustifolium algal extracts, as well as by zinc oxide nanoparticles, to determine their antidiabetic activity.
Table 1
Results of inhibition of α- amylase enzyme based on IC50 (The IC50 represents the concentration of the extract that inhibits 50% of the activity of the enzyme.). inhibitor
IC50 (mg/mL)
log IC50
Zinc oxide Methanolic extract of S. angustifolium Ethanolic extract of S. angustifolium Buffer extract of S. angustifolium Methanolic extract of G. corticata Etanolic extract of G. corticata Buffer extract of G.corticata
0.34 1.02 0.68 1.85 1.38 0.71 0.44
2.5 3.008 2.832 3.268 3.142 2.854 2.644
Table 2
Comparison of the kinetics parameters related to the α- amylase enzyme in the presence and absence of inhibitors and the type of inhibition. Title
Km (mM)
Vmax (μM/min)
Variation of Km and Vmax
Type of inhibition
Absence of inhibitors In the presence of methanolic extract of S. angustiflium In the presence of ethanolic extract of S. angustiflium
1.6
0.1665
0.62
0.0631
Uncompetitive inhibition
1.42
0.0778
In the presence of buffer extract of S. angustiflium
0.44
0.081
Mixed (Orientation to none- competitive inhibition) Mixed inhibition
In the presence of methanolic extract of G. corticata In the presence of ethanolic extract of G. corticata
0.34
0.0661
Mixed inhibition
2.92
0.1521
Competitive inhibition
In the presence of buffer extract of G .corticata
4.04
0.1714
Competitive inhibition
ZnO
4.48
0.1398
Competitive inhibition
2. Materials and methods 2.1. Sample preparation 2.1.1. Preparation of zinc oxide nanoparticles Zinc oxide nanoparticles were synthesized by the chemical deposition method. First, 0.46 g of Zn(CH₃COO)2 H₂O was added to 5 mL of PEG 600. Then, while warming up in an oil bath, sodium hydroxide was added under stirring until it was dissolved. Next, the reaction mixture was refluxed for 1.5 h, resulting in completely stable, colloidal ZnO nanoparticles with a small particle size. Then, the flask was covered with Parafilm and stored at 4 °C. The concentration of the dispersed ZnO nanoparticles solution was 5400 ppm. 2.1.2. Preparation of algae samples Red Gracilaria corticata and brown Sargassum angustifolium algae were collected from tidal zones of the coastal areas of Bushehr (Persian Gulf coastline). Their morphological characteristics (type, color, texture, shape and habitat) were recorded, resulting in a consistent assignment of the species. The collected algae were individually washed with distilled water to remove sand particles, epiphytes and sea salt, and transferred to the lab in a numbered bag. The numbered specimens were dried at room temperature. The dried samples were then powdered and stored at 4 °C for further testing.
2008). Therefore, enzyme inhibitors can be useful in the management of type 2 diabetes. The use of synthetic drugs is less preferred because of their side effects such as stomach bloating, diarrhea, and vomiting, and other side effects resulting from the long-term use of these drugs. Therefore, much research is devoted to find more effective alternative low-cost treatments with fewer side effects. Most people in developing countries consider alternative therapies, including the use of natural sources (traditional medicine), for their primary health care (Hassan et al., 2010). A wide range of active therapeutic agents have successfully been isolated from natural sources and are now subject to clinical investigation (Yasuhara-Bell and Lu, 2010). One of these sources is the huge marine environment, and bioactive compounds from many marine organisms are being considered for the development of new medicines (Liu et al., 2011; Sun et al., 2011). Macro-algae are organisms that produce a wide range of biologically active secondary metabolites. For instance, brown algae produce a variety of polysaccharide compounds, including laminarin, fucoidan and alginate, which have anti-diabetic properties (Rioux et al., 2007). Poly-phenolic compounds in red algae also act as effective antidiabetic ingredients through their inhibitory effect on starch-digesting enzymes (Lee et al., 2007). The identification and separation of these
2.1.3. Preparation of extracts To prepare the extracts, 30 g of each powdered alga species were weighed on a scale, and transferred to Erlenmeyer flasks. Then, 200 mL ethanol, or 200 mL methanol, or 200 mL 0.1M sodium phosphate buffer (pH 7) were added to the Erlenmeyer flask, and the suspensions were incubated at 37 °C. After 48 h, the raw extracts were filtered with filter paper (Whatman plc) and the alcoholic extracts were concentrated in a rotary evaporator. Non-alcoholic filtered extracts and alcoholic condensate extracts were individually placed in Petri dishes. The non-alcoholic filtered extracts were placed in an oven at 40 °C for 72 h, and the alcoholic condensate extracts were dried at room temperature for 48 h. The resulting powders were pre-weighed in micro tubes, and stored in a freezer at -80 °C. 2.2. Evaluation of the inhibition of α-amylase activity The inhibition of the α-amylase activity was evaluated using a colorimetric method (DNS) based on the reduction of the release of maltose from a starch solution, according to the method reported by Miller (1959) with slight changes. 40 μl of different concentrations 5
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Fig. 4. (a–c). Michaelis-Menten enzyme kinetics in presence and absence of methanolic (a), ethanolic (b) and phosphate buffer extracts (c) of S. angustifolium.
(0.2, 0.4, 0.6, 0.8 and 1 mg/mL dry material) of the extracts was added to separate test tubes. For the nanoparticles 410 μl suspension in 0.1 M sodium phosphate buffer (pH 7) was used. Next, 500 μl of 1% starch solution and 50 μl of α-amylase (500 k-unit/mg purchased from SIGMA) were added. After incubation at 60 °C for 20 min 1 mL of DNS solution was added, and the mixture was placed at 100 °C for 5 min, and then cooled to room temperature in a water bath. Finally, the absorbance at 540 nm was measured using a spectrophotometer. A sample with only sodium phosphate buffer was used as a positive
control (100% enzyme activity). Negative controls contained no enzyme, and had 0% enzyme activity. The percentage reaction activity was calculated using Formula (1) and the percentage inhibition was calculated using Formula (2).
(1)
Inhibition(%) = 100 − Reaction(%) 6
(2)
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Fig. 5. (a–c). Michaelis-Menten enzyme kinetics in presence and absence of methanolic (a), ethanolic (b) and phosphate buffer extracts (c) of G. corticata.
were determined for each of the inhibitors discussed in this study. The IC50 represents the concentration of the extract that inhibits 50% of the activity of the enzyme. The inhibitory power of the extracts based on IC50 was compared.
2.3. Statistical analysis The α-amylase inhibition was determined three times for each of the extracts and the zinc oxide nanoparticles (at different concentrations), and the mean and standard deviation were calculated using Excel software. Then, using the GraphPad Prism software, the enzyme activity, the percentage of enzyme inhibition, and the IC50 values 7
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Fig. 6. Michaelis-Menten enzyme kinetics in presence and absence of ZnO nanoparticles.
the highest Vmax was obtained with the sodium phosphate buffer extract of Gracilaria corticata. The highest Km value was obtained with the zinc oxide nanoparticles.
2.4. Enzyme kinetics To determine the kinetics of the α-amylase catalyzed reaction in the absence and presence of inhibitors (IC50-related concentrations), 50 μl of a constant concentration of α-amylase and 500 μl of different substrate concentrations were used. In this study, the Michaelis-Menten equation was used to determine the enzyme kinetics and inhibition mechanism. From the Michaelis-Menten kinetics, the maximum velocity (Vmax) and the Michaelis-Menten constant (Km) were determined. By comparing the kinetic parameters of the enzyme (Km and Vmax) in the presence and absence of inhibitor, the type of inhibition was determined.
4. Discussion The significant increase in the incidence of diabetes, and particular of type 2 diabetes, is a major concern of the World Health Organization in the 21st century (DeVille-Almond, Tahrani et al., 2011). In diabetic patients, controlling blood glucose levels after eating is one of the most important factors of disease control (KWON, Apostolidis et al., 2008). To this end, a major goal of the treatment is to control the enzymes involved in carbohydrate metabolism and to prevent glucose uptake from food intake (Kurihara et al., 1999). α-Amylase is one of the key enzymes in the digestive carbohydrate metabolism. It breaks down the large carbohydrate chains of starch and glycogen by hydrolyzing α-D-(1–4) glycosidic bonds and producing simpler sugars such as glucose and maltose (Brayer et al., 2000; Tangphatsornruang et al., 2005). α-Amylase inhibitors reduce the activity of α-amylase enzymes, thereby decreasing the amount of glucose produced in the intestine and reducing blood glucose levels. Several compounds have been found to be efficacious α-amylase inhibitors (Moorthy et al., 2012). In the present study, the effect of zinc oxide nanoparticles and methanolic, ethanolic and sodium phosphate buffer extracts of two species of algae, Gracilaria corticata red algae and Sargassum angustifolium brown algae, on the activity of α-amylase was determined. Our investigations showed that the ethanolic extract of Sargassum angustifolium gave the strongest α-amylase inhibition (68% inhibition). Other investigators have also observed strong α-amylase inhibition by macro-algal extracts. For instance, α-amylase was found to be inhibited by methanolic extracts of Sirophysalis trinodis brown algae (97% inhibition), ethyl acetate extracts of Polycladia myrica (97% inhibition), and methanolic extracts of Sargassum glaucesens (77.8% inhibition) (Payghami et al., 2015; Pirian et al., 2017). By comparing our results with those of others, some differences are apparent. For example, in a study conducted by Kumar and Sellappa (2012) on other Gracilaria and Sargassum species (Gracilaria corticata, Gracilaria gracilis, Sargassum polycystum), IC50 values in the range of 60 to 83 μg/mL were reported (Kumar and Sellappa, 2012), while our research gave IC50 values of 0.44 mg/mL and higher (Table 1). Our IC50 values are similar to the IC50 values of 0.42 to 7.5 mg/mL reported by Pirian et al. (2017) for methanol, hexane and ethyl acetate extracts of various Persian Gulf macro algae, including Gracilaria corticata and Sargassum angustifolium (Pirian et al., 2017). Such species-related differences are common in many similar studies. For
3. Results 3.1. Inhibition of enzyme activity Fig. 1(a–c) shows the relative activity of the enzyme as a function of the inhibitor concentration. In all cases, as the inhibitor concentration increases, the enzyme activity decreases. At the highest inhibitor concentration of 1 mg/mL dry material the S. angustifolium buffer extract had the lowest inhibition power (about 69%). Fig. 2(a–c) shows the percentage inhibition of the enzyme as a function of the inhibitor concentration (0.2–1 mg/mL). At 1 mg/mL of the S. angustifolium extracts, the most powerful α-amylase inhibitor is the ethanolic extract (68% inhibition, compared to 49% and 31% inhibition by the methanolic and buffer extracts, respectively). In contrast, for the Gracilaria corticata extracts, the phosphate buffer extract is the best (72% inhibition, compared to 41% and 69% inhibition by the methanolic and ethanolic extracts. At 1 mg/mL zinc oxide nanoparticles gave 78% inhibition, which is somewhat better than the inhibition by the various algal extracts. 3.2. IC50 values of inhibitory action Fig. 3(a–c) and Table 1 show the α-amylase inhibition based on IC50 in the presence of each extract. In this study, the highest inhibitory effect was found for the sodium phosphate buffer extract of Gracilaria corticata, which gave an IC50 of 0.44 mg/mL. 3.3. Results of kinetics of α-amylase enzyme and determination of the type inhibition of enzyme The results of the α-amylase inhibition kinetics are reported in Table 2, and Figs. 4–6. According to the Michaelis-Menten analysis, 8
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example, the IC50 value reported by Lee and Han (2012) for a methanol extract of Sargassum ringgoldianum is about 0.8 mg/mL, but the IC50 reported by Payghami et al. (2015) for methanolic extracts of Sargassum glaucesens is about 8.9 mg/mL (Lee and Han, 2012; Payghami et al., 2015). Thus, differences in species type may strongly affect the α-amylase inhibition potency of the extracts. The type of extraction solvent may also affect the degree of αamylase inhibition. For instance, in a study by Kumar et al. (2012) water was used as a solvent, while in the present study methanol, ethanol and sodium phosphate buffer were used. Pirian et al. (2017) used n-hexane, methanol and ethyl acetate as extraction solvents (Kumar and Sellappa, 2012; Pirian et al., 2017), showing that ethyl acetate extracts had a higher α-amylase inhibitory effect than nhexane. The superiority of methanol and ethyl acetate compared to nhexane has also been reported in other studies of α-amylase inhibition (SHN Moorthy, J Ramos et al., 2012). As another example, the IC50 of the aqueous extract of Ascophyllum nodosum reported by Lee et al. (2010) was about 10 times higher than that of phenolic compounds studied by Nwosu et al. (2011)(Nwosu et al., 2011). Another reason for the different results is related to differences in the extraction methods. The extraction method used in the current study consisted of soaking and drying at room temperature and then in an oven, while in other studies extraction was done by percolation, decoction, extraction with a soxhlet extractor, or by ultrasonic extraction (Heo et al., 2009; Lee et al., 2010; Payghami et al., 2015). Comparing the degree of α-amylase inhibition in the various studies, there are significant differences in the inhibition of the enzyme (in term of percentage) for a similar composition of what, which can be linked to different methods for enzyme inhibition control. Among these methods, two types of tests are widely used to determine the effect on α-amylase activity. One is based on use of dinitrosalicylic acid reagent for determination of reducing sugar (Miller, 1959), and another on the basis of change of the color of starch-iodine complexes in the substrate coloring (Fuwa, 1954). In the present study, DNS coloring was used to determine the degree of inhibition. Enzymatic kinetics is a laboratory method that measures the amount of enzyme response at close to zero times. From the Michaelis-Menten kinetics the maximum rate (Vmax) can be calculated. Vmax is the rate achieved by the system at saturating substrate concentration. In this study, in the absence of an inhibitor, Vmax was found to be 0.1665 μmol/min, while this value in the presence of inhibitors was found to be between 0.0631 to 0.1714 μmol/min. Another kinetic parameter determined in this study was the Michaelis constant Km, which is the substrate concentration at which the reaction rate is half of Vmax. In the absence of inhibitors, the Km was found to be 1.6 mmol, but in the presence of inhibitors it ranged from 0.34 to 4.04 mmol. From the values of Vmax and Km the type of inhibitory process (competitive, uncompetitive, non-competitive, or mixed inhibitory) can be deduced. In the presence of competitive inhibitors, Vmax stays the same, but Km increases. Our study indicates that the ethanolic and sodium phosphate buffer extracts of Gracilaria corticata and zinc oxide nanoparticles act as competitive inhibitors. Non-competitive inhibitors reduce the value of Vmax, and Km does not change. The Sargassum angustifolium ethanolic extract thus acted as a non-competitive inhibitor. Uncompetitive inhibitors reduce both Vmax and Km. The Sargassum angustifolium methanolic extract appeared to act as an uncompetitive inhibitor. Other inhibitors of this study showed mixed inhibitory behaviour. Mixed inhibitors can be tend to other types of inhibition (uncompetitive, competitive and non-competitive). Zinc oxide nanoparticles inhibited α-amylase for 78% at 1 mg/mL concentration and gave an IC50 of 0.34 mg/mL. In a study by Dhobale et al. (2008), the inhibitory effect of zinc oxide nanoparticles de-
posited in the presence of thioglycerol was 49% at 20 μg/mL concentration (Dhobale et al., 2008). Shaik and Kumar (2016) found that 30 μg/mL zinc oxide nanoparticles (in the presence of thioglycerol) gave 56% α-amylase inhibition, but 30 μg/mL zinc oxide nanoparticles coated with acarbose gave 75% inhibition (Shaik and Kumar 2016). These results show that zinc oxide nanoparticles on their own can inhibit α-amylase. The inhibition mechanism is not known, although it can be envisaged that the nanoparticles bind to reactive amino or carboxyl groups near the active site of the enzyme (Dhobale et al., 2008). 5. Conclusion Zinc oxide nanoparticles as well as extracts of Gracilaria corticata and Sargassum angustifolium algae show promising inhibitory activity towards α-amylase, which suggests that they may be good starting points for the development of drugs for controlling blood glucose levels in diabetic patients. Moreover, nanoparticles represent a new class of materials in the field of biomedicine, with high potential for broad application in diagnostics, drug delivery, and therapeutics. Author statment The authors declare that there is no conflict of interest regarding the publication of this paper. We concur with the submission and have seen a draft copy of the manuscript and agree with its publication. Declaration of competing interest The authors of this manuscript declare that have no conflict of interest. Acknowledgements The authors are grateful to the University of Hormozgan for the financial support to this research. References Arquilla, E.R., Packer, S., Tarmas, W., Miyamoto, S., 1978. The effect of zinc on insulin metabolism. Endocrinology 103 (4), 1440–1449. Brayer, G.D., Sidhu, G., Maurus, R., Rydberg, E.H., Braun, C., Wang, Y., Nguyen, N.T., Overall, C.M., Withers, S.G., 2000. Subsite mapping of the human pancreatic αamylase active site through structural, kinetic, and mutagenesis techniques. Biochemistry 39 (16), 4778–4791. Cardozo, K.H., Guaratini, T., Barros, M.P., Falcão, V.R., Tonon, A.P., Lopes, N.P., Campos, S., Torres, M.A., Souza, A.O., Colepicolo, P., 2007. Metabolites from algae with economical impact. Comp. Biochem. Physiol. C Toxicol. Pharmacol. 146 (1–2), 60–78. Danaei, G., Finucane, M.M., Lu, Y., Singh, G.M., Cowan, M.J., Paciorek, C.J., Lin, J.K., Farzadfar, F., Khang, Y.-H., Stevens, G.A., 2011. National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370 country-years and 2· 7 million participants. The Lancet 378 (9785), 31–40. DeVille-Almond, J., Tahrani, A.A., Grant, J., Gray, M., Thomas, G.N., Taheri, S., 2011. Awareness of obesity and diabetes: a survey of a subset of British male drivers. Am. J. Men’s Health 5 (1), 30–37. Dhobale, S., Thite, T., Laware, S.L., Rode, C.V., Soumya, J., Koppikar, Ghanekar, R.-K., Kale, S.N., 2008. Zinc oxide nanoparticles as novel alpha-amylase inhibitors. J. Appl. Phys. 104 (9). Dodson, G., Steiner, D., 1998. The role of assembly in insulin’s biosynthesis. Curr. Opin. Struct. Biol. 8 (2), 189–194 8(2), 189-194. Fariq, A., Khan, T., Yasmin, A., 2017. Microbial synthesis of nanoparticles and their potential applications in biomedicine. J. Appl. Biomed. 15 (4), 241–248. HIDETSUGU FUWA, 1954. A new method for micro determination cf amylase activity by the use of amylose as the substrate. J. Biochem. 41 (5), 583–603. Gholamhoseinian, A., Fallah, H., Sharifi-far, F., Mirtajaddini, M., 2008. The inhibitory effect of some Iranian plants extracts on the alpha glucosidase. Iranian journal of basic medical sciences 11 (1), 1–9. Gokce, G., Haznedaroglu, M.Z., 2008. Evaluation of antidiabetic, antioxidant and vasoprotective effects of Posidonia oceanica extract. J. Ethnopharmacol. 115 (1), 122–130. Hassan, Z., Yam, M.F., Ahmad, M., Yusof, A.P.M., 2010. Antidiabetic properties and
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