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Angiotensin-I Converting Enzyme Inhibitory Peptides from Sweet Sorghum Grain Protein: Optimisation of Hydrolysis Conditions and Hydrolysate Characterization.

Byline: Jun-Qiang Jia, Nan Miao, Jin-Juan Du and Qiong-Ying Wu

Summary: In order to utilize sweet sorghum grain protein (SSGP) for food applications, SSGP was hydrolyzed by alcalase to produce the hydrolysates with ACE-inhibitory activity. The Plackett-Burman design (PBD) was used to identify the important factors influencing the ACE-inhibitory activity of SSGP hydrolysates. The result of PBD indicated that hydrolysis temperature, pH and alcalase dosage had significant influence (P < 0.05) on the ACE-inhibitory activity of SSGP hydrolysates. Response surface methodology (RSM) was applied to optimize the three significant factors. The optimum hydrolysis conditions obtained from RSM were as follows: hydrolysis temperature 56 AdegC, pH 8.0, alcalase dosage 5200U/g.

Under the optimum conditions, SSGP hydrolysates contained 24.3% 1-5 kDa (IC50=0.305 mg/ml) and 15.2% <1 kDa (IC50=0.116 mg/ml) peptide fractions having potent in vitro ACE inhibitory activities. Moreover, the inhibition pattern against ACE investigated using Lineweaver-Burk plots revealed that the peptides with molecular weights above 5 kDa in the SSGP hydrolysates were non-competitive inhibitors with inhibition constants (Ki) between 1.098 and 1.171 mg/ml, while the peptides with molecular weights below 5 kDa in the hydrolysates were competitive inhibitors with Ki between 0.110 and 0.184 mg/ml. The results of this study suggest that SSGP may be considered as a source of functional ingredients for the prevention of hypertension.

Keywords: Sweet sorghum grain protein (SSGP); Optimisation of hydrolysis conditions; ACE-inhibitory activity; Response surface methodology; Amino acid composition; Lineweaver-Burk.

Introduction

Angiotensin- converting enzyme (ACE) is a zinc metallopeptidase that catalyzes the synthesis of angiotensin II having hypertensive effect and the degradation of bradykinin having antihypertensive effect [1]. ACE is well known to play a major role in controlling blood pressure by rennin-angiotensin system [2]. Therefore, inhibition of ACE has been studied in order to develop antihypertensive agents. Synthesized ACE inhibitors (e.g. enalapril, perindopril and lisinopril) have been used extensively in the prevention or treatment of high blood pressure in humans [3]. Studies, however, have shown that these chemical molecules may have some undesirable side effects such as taste disturbances, skin rash and coughing [4, 5]. Therefore, it is necessary to find safer and effective ACE inhibitors for the prevention or treatment of hypertension.

ACE-inhibitory peptides from food proteins, which can be released from the sequence of parent proteins by enzymolysis, are currently identified as an alternative for the treatment of hypertension [5]. Many ACE-inhibitory peptides have been produced by enzymolysis from animal and plant proteins, such as native collagenous [6], rice bran protein [7], Porcine skin gelatin [8] and bovine caseins [9]. However, there is little information on ACE-inhibitory peptides of sweet sorghum grain protein (SSGP) until now.

Sweet sorghum, an energy crop, which originates from Africa, is considered to be one of the most promising bio-energy crops because it has more tolerance to stress factors such as drought, salt and nutrient deficiencies [10]. The juice from its stalks, which contains sucrose, fructose and glucose, and is mainly used to produce ethanol, biodiesel and hydrogen [11]. Yet, the sweet sorghum grain source has poor utility for human applications. With the knowledge that alcalase-proteolysis leads to the production of large numbers of ACE inhibitory peptides with higher activities [12, 13]. This study, therefore, focused on the use of alcalase in preparing ACE inhibitory peptide from SSGP. Our objective was to optimize the hydrolysis conditions for the preparation of ACE-inhibitory peptides from SSGP with alcalase by Plackett-Burman design (PBD) and response surface methodology (RSM).

In addition, The SSGP hydrolysates were separated into different peptide fractions by ultrafiltration membrane. Then ACE inhibition patterns for the peptide fractions were analyzed.

Experimental

Materials and Chemicals

Sweet sorghum (Sorghum bicolor L.) grains were purchased from Xintai Seed Co. (Jiangsu, China). Angiotensin- converting enzyme (ACE) and Hippuryl-His-Leu (HHL) were purchased from Sigma-Aldrich Trading Co. (Shanghai, China). Alcalase was purchased from Novozymes Biotechnology Co. (Beijing, China). [alpha]-amylase was purchased from Solarbio Biotechnology Co. (Beijing, China). All other chemicals and solvents were of analytical grade.

Preparation of Sweet Sorghum Grain Protein (SSGP)

The sweet sorghum grains were crushed to powder (100 mesh particle size) using a WK-150 crusher (Jingcheng machinery manufacture Co., Qingzhou, China). The powder was dispersed in deionized water (1:10, w/v), and the pH of the dispersions was adjusted to 6.5 with 1 mol/L NaOH. Then the suspension was treated with [alpha]-amylase at 55AdegC (enzyme-to-substrate ratio 1:100, w/w) for 4 h. After treatment, the pH of the reaction mixture was adjusted to 11.0 by adding 1 mol/L NaOH to extract the proteins. The reaction mixture was centrifuged using a centrifuge (LR10-24A, Beijing LAB Centrifuge Co., Beijing, China) at 2,500 g for 10 min at 20AdegC. The supernatant was adjusted to pH 5.0 with 1 mol/L HCl to precipitate the proteins. The precipitates obtained by centrifugation at 2500 g for 10 min at 20AdegC were re-dispersed in distilled water, and adjusted to pH 7.0 by using 0.1 mol/L NaOH.

The dispersed product was freeze-dried at -80 AdegC and then stored at -20 AdegC until further tests.

Hydrolysis of Sweet Sorghum Grain Protein (SSGP)

SSGP were hydrolyzed with alcalase according to the hydrolysis conditions defined by the experimental design. During the enzymatic reaction process, the pH was maintained at the required values (the values are 6.4, 7.0, 8.0 and 9.0, respectively) by the addition of 1 mol/L NaOH and the reaction temperature was controlled at the required values (the values are 44AdegC , 50AdegC, 55AdegC and 60AdegC, respectively) using a water bath. At the end of the incubation period, the enzymatic hydrolysis was stopped by boiling for 10 min. Subsequently, the reaction mixture was centrifuged using a centrifuge (LR10-24A, Beijing LAB Centrifuge Co., Beijing, China) at 2500 g and 20AdegC for 10 min, and the supernatant was collected and stored at 4AdegC for subsequent analysis of ACE inhibition activity.

Measurement of ACE-Inhibitory Activity

ACE-inhibitory activity was measured by our previously described method [14]. Briefly, 10 ul of sample solution was mixed with 45 ul sodium borate buffer (pH 8.3) containing 6.5 mmol/L Hippuryl-His-Leu (HHL) and 0.3 mol/L NaCl, and the mixture was pre-incubated for 5 min at 37AdegC. The reaction was initiated by adding 10 ul ACE (ACE in 0.1 mol/L borate buffers containing the 0.3 mol/L NaCl, pH 8.3). Finally, the reaction mixture was incubated at 37AdegC for 30 min. The reaction was stopped by the addition of 85 ul of 1 mol/L HCl to the reaction mixture except for the blank (the HCl solution was added before the pre-incubation). Then 1000 ul of ethyl acetate was used to extract the hippuric acid formed from the reaction mixture.

Then 800 ul of the ethyl acetate layer was collected by centrifugation using a high-speed refrigerated centrifuge (H205DR-1, Changsha Xiangyi Centrifuge Co., Hunan, China) at 4000 g for 10 min, dried at 100AdegC for 20 min. Subsequently, the hippuric acid was re-dissolved in 800 ul of distilled water. The absorbance was determined at 228 nm with a spectrophotometer (UV-2100, Unico Instrument Co., Shanghai, China). ACE inhibition activity was calculated as follows:

ACE - inhibition activity (%) = C - S/C - B X 100 --------(1)

Where C is the absorbance without sample (buffer for samples), and S is the absorbance in the presence of both ACE and sample. B is the absorbance of blank (hydrochloric acid was added before ACE).

Experimental Design

Plackett-Burman Design (PBD)

Table-1: Factors levels in Plackett-Burman design.

###Experimental value

###Variables###Code

###Low level (-1) High level (+1)

Hydrolysis temperature (AdegC)###X1###44###55

###pH###X2###6.4###8.0

###Dummy 1###N1###0###0

###Hydrolysis time (min)###X3###70###90

###Alcalase dosage (U/g)###X4###4000###5000

###Dummy 2###N2###0###0

Substrate concentration (g/L)###X5###8###10

Table-2: Plackett-Burman design and response values.

###Code levels###ACE-inhibitory

Run###activity

###X1###X2###N1###X3###X4###N2###X5

###Y (%)

1###-1###1###-1###-1###-1###1###1###58.87

2###-1###-1###1###1###1###-1###1###46.86

3###1###1###-1###1###-1###-1###-1###57.14

4###1###-1###1###1###-1###1###-1###37.14

5###1###-1###1###-1###-1###-1###1###42.27

6###1###1###1###-1###1###1###-1###73.01

7###-1###-1###-1###1###1###1###-1###39.56

8###-1###-1###-1###-1###-1###-1###-1###30.31

9###-1###1###1###1###-1###1###1###45.45

10###1###-1###-1###-1###1###1###1###50.24

11###-1###1###1###-1###1###-1###-1###64.15

12###1###1###-1###1###1###-1###1###85.42

Plackett-Burman experimental design was applied to identify the factors that have significant effect on the ACE-inhibitory activity of SSGP hydrolysates [15]. In this study, the seven factors (including two dummy variables) were investigated using the PBD with a first-order polynomial equation. Each factor was examined as low and a high level, coded as (-1) and (+1), respectively. Table-1 shows the variables and their corresponding levels used in the experimental design. The PBD and the response value of ACE-inhibitory activity are shown in Table-2. The fitted first-order model was obtained by the equation [16]:

(Equation)

Where Y is the predicted response; [beta]0 is the intercept; [beta]i is the regression coefficient and Xi is the coded independent factor.

Path of Steepest Ascent

The path of steepest ascent is a procedure for moving along the path of steepest ascent to the maximum increase in the response [16]. The direction of steepest ascent was the direction in which response (ACE-inhibitory activity) increased rapidly. The zero level of the Plackett-Burman design was identified as the base point of the steepest ascent path. Experiments were performed along the steepest ascent path till no further increase in response was observed [16, 17].

Central Composite Design (CCD) and Response Surface Methodology (RSM)

Table-3: Factors levels in central composite design.

###Factors###Code

###Levels of factors

###-1###0###+1

###Hydrolysis temperature (AdegC)###A###50###55###60

###pH###B###7.0###8.0###9.0

###Alcalase dosage (U/g)###C###4000###5000###6000

Table-4: Central composite design and response values a.

###Code levels

###ACE-inhibitory activity

Run###Hydrolysis###pH###Alcalase

###(Y) (%)

###temperature (A)###(B)###dosage (C)

###1###0###0###0###80.33

###2###0###-1###-1###40.74

###3###-1###0###1###62.25

###4###1###0###1###68.41

###5###1###1###0###60.44

###6###-1###1###0###44.84

###7###-1###-1###0###48.08

###8###0###0###0###82.12

###9###-1###0###-1###49.06

10###0###-1###1###63.37

11###1###0###-1###58.89

12###0###0###0###82.26

13###0###1###-1###59.07

14###0###1###1###48.13

15###1###-1###0###54.79

The CCD was used to further investigate the three most significant factors (Hydrolysis temperature, pH and alcalase dosage) for increasing the ACE-inhibitory activity of SSGP hydrolysates, screened by Plackett-Burman design (PBD). The three independent factors were investigated at three different levels (-1, 0, +1) (Table-3), and a 15-run CCD used for study was shown in Table-4. The behavior of the system was explained by the second-order polynomial equation[17]:

(Equation)

Where Y is the predicted response, [beta]0 is the intercept, Xi and Xj are the coded independent factors, [beta]i is the linear coefficient, [beta]ii is the quadratic coefficient and [beta]ij is the interaction coefficient.

Fractionation of SSGP Hydrolysate

The SSGP hydrolysate was ultrafiltered sequentially using an ultrafiltration unit (Pellicon, Millipore, USA) through three ultrafiltration membranes with molecular weight cut-off of 10, 5 and 1 kDa, respectively. Four peptide fractions with molecular weights of <1 kDa (represented hydrolysates 10 kDa (represented hydrolysates >10 kDa) were obtained from SSGP hydrolysates. The Contents of peptide fractions were determined by micro-Kjeldahl method.

Determination of ACE Inhibition Pattern

To investigate the inhibition pattern on ACE, different concentrations of peptide fraction from SSGP hydrolysate were added to each reaction mixture according to the method of Barbana and Boye [18]. The enzyme activities (absorbance at 228 nm) were measured with different concentrations of the HHL (0.8125, 1.625, 3.25, 6.5 mmol/L).

Lineweaver-Burk plots of 1/absorbance versus 1/HHL were used to determine the ACE inhibitory pattern.

Statistical Analysis

All experiments were done in triplicate. Design-Expert statistical software package (Version 7.1.3, Stat-Ease Inc., Minneapolis, USA) was used for the experimental designs and statistical analysis of the experimental data. Statistical analysis of the model was performed to evaluate the analysis of variance (ANOVA).

Results and Discussion

Optimization of Hydrolysis Conditions for the Production of ACE-Inhibitory Peptides from SSGP Plackett-Burman Design (PBD)

Table-5: Analysis of variance (ANOVA) of Plackett-Burman test.

Variable###Degrees of freedom###Sum of squares###F-value###P-value

###X1###1###0.030011###8.49###0.044a

###X2###1###0.157949###44.68###0.003b

###N1###1###0.001339###0.38###0.572

###X3###1###0.000442###0.12###0.742

###X4###1###0.064617###18.28###0.013a

###N2###1###0.003992###1.13###0.348

###X5###1###0.006446###1.82###0.248

PBD has been widely used by many researchers as a screening method to determine significant factors in experiment design [15, 16]. A PBD in twelve runs was used to study the effect of seven factors (including two dummy variables) on the ACE-inhibitory activity of protein hydrolysates from SSGP and the result was shown in Table-2. The analysis of variance (ANOVA) of Plackett-Burman test in this study (Table-5) was obtained using Design-Expert version 7.1.3 (Stat-Ease Inc., USA). Table-5 showed that hydrolysis temperature, pH and alcalase dosage in the tested range had more than 95% of confidence level, and other variables had a confidence level less than 76%. The results implied that hydrolysis temperature, pH and alcalase dosage had significant influence on ACE-inhibitory activity of the hydrolysates (P < 0.05), while hydrolysis time and substrate concentration played a minor role on the ACE-inhibitory activity of the hydrolysates.

Therefore, hydrolysis temperature, pH and alcalase dosage were selected for optimization. Here, substrate concentration 10 g/L and hydrolysis time 90min were used for follow-up tests.

Path of Steepest Ascent

Table-6: Experiment design of the steepest ascent path and response values a.

###Hydrolysis###Alcalase dosage###ACE-inhibitory

Run###pH

###temperature (AdegC)###(U/g)###activity(%)

Origin###40###6.5###3500###39.82

1###45###7.0###4000###40.31

2###50###7.5###4500###68.86

3###55###8.0###5000###82.88

4###60###8.5###5500###74.13

5###65###9.0###6000###68.70

According to the result of PBD experiment, the path of steepest ascent was used to approach the optimal region of hydrolysis conditions subsequently [19]. In this study, the path of steepest ascent was designed on the basis of the zero level of PBD, and then was moved along the path of increase of hydrolysis temperature, pH and alcalase dosage. The path of steepest ascent result is presented in Table-6. The highest response (82.88%) was obtained under the hydrolysis conditions of the temperature 55AdegC, pH 8.0 and alcalase dosage 5000 U/g. Then the hydrolysis conditions were chosen for further optimization.

Table-7: Analysis of variance (ANOVA) of central composite design of RSM a.

###Source###Sum of squares###Degree of freedom###Mean Square###F-value###P-value

###Model###2495.07###9###277.23###61.48###0.0001 b

###A###183.36###1###183.36###40.66###0.0014 b

###B###3.78###1###3.78###0.84###0.4018

###C###147.92###1###147.92###32.80###0.0023 b

###AB###19.76###1###19.76###4.38###0.0905

###AC###3.37###1###3.37###0.75###0.4270

###BC###281.74###1###281.74###62.48###0.0005 b

###A2###475.97###1###475.97###105.55###0.0002 b

###B2###1220.19###1###1220.19###270.59###< 0.0001 b

###C2###412.04###1###412.04###91.37###0.0002 b

###Residual###22.55###5###4.51

###Lack of Fit###20.23###3###6.74###5.82###0.1501

###Pure Error###2.32###2###1.16

###Total###2517.62###14

The three selected variables (hydrolysis temperature, pH and alcalase dosage) were further explored using CCD of RSM. The matrix for CCD and the experimental results were shown in Table-4. Here, substrate concentration and hydrolysis time were 10 g/L and 90min, respectively. A second-order polynomial equation was obtained to explain the ACE-inhibitory activity of SSGP hydrolysates by applying multiple regression analysis on the CCD data:

Y = 81.57 + 4.79 A + 0.69 B + 4.3 C + 2.22 A B - 0.92 AC - 8.39 BC - 11.35 A2 - 18.18 B2 - 10.56 C2 --------(4)

Where Y is predicted ACE-inhibitory activity of SSGP hydrolysates (%), A-coded values of hydrolysis temperature, B-coded values of pH, C-coded values of alcalase dosage.

The result of ANOVA for second-order polynomial equation was shown in Table-7. The value of "P-value" of the model and lack of fit were 0.0001 and 0.1501, respectively, suggesting that the model was highly significant. Linear terms of A and C, interaction term of BC, and all the quadratic terms (A2, B2 and C2) were all significant within a 99% confidence interval (P 10 kDa###1.225###31.1+-1.2

###5-10 kDa###1.012###26.4+-0.9

###1-5 kDa###0.305###24.3+-0.5

###10 kDa, 5-10 kDa, 1-5 kDa, and 10 kDa fraction (31.1%) had the maximum content, followed by 5-10 kDa (26.4%), 1-5 kDa (24.3%), and 10 kDa, 5-10 kDa, 1-5 kDa and <1 kDa fractions were 1.225, 1.012, 0.305 and 0.116 mg/ml, respectively. The <1 kDa and 1-5 kDa fractions showed more potent ACE-inhibitory activities, indicating that the ACE inhibition could be attributed mainly to the mixture of short peptides in SSGP hydrolysates.

The results were in accordance with Ko et al. [22] who reported that 5 kDa fraction. Similar results were also reported by Lin et al. [23] for squid skin gelatin hydrolysates and by Jung et al. [24] for yellowfin sole frame protein hydrolysates. Thus, the product, enriched in ACE inhibitory peptides, could be obtained by the ultrafiltration membrane with 10 kDa and 5-10 kDa fractions were non-competitive, suggesting that the ACE-inhibitory peptides in those fractions did not bind to the active site of ACE but could bind to other sites on the ACE molecule to produce an inactive complex, regardless of substrate binding[18, 26].

The 1-5 kDa and 10 kDa, 5-10 kDa, 1-5 kDa and <1 kDa fractions were 1.171, 1.098, 0.184 and 0.110 mg/ml, respectively. In general, the lowest Ki value of inhibitor indicates that its inhibition is the strongest. The Ki values of 1-5 kDa and 10 kDa and 5-10 kDa fractions, indicating the peptides with molecular weights below 5 kDa have much stronger affinity to the ACE active sites than the peptides with molecular weights above 5 kDa [18].

In this study, although the Ki values of 1-5 kDa and <1 kDa fractions were almost 27500 fold higher than that of captopril (6.70 x10-6 mg/ml) [28], their Ki values were lower than that of green lentil protein hydrolysate (0.31 mg/ml)[18], red lentil protein hydrolysate (0.46 mg/ml)[18], milk whey fermented with lactic acid bacteria (0.188 mg/ml) [28] and rapeseed hydrolysates (0.2-0.3 mg/ml) [29]. Thus, our study results showed that the 1-5 kDa and 10 kDa, 26.4% 5-10 kDa, 24.3% 1-5 kDa and 15.2% <1 kDa fractions. The 1-5 kDa and 10 kDa and 5-10 kDa peptide fractions and a competitive pattern of ACE inhibition for 1-5 kDa and <1 kDa peptide fractions. In conclusion, SSGP hydrolysates can be considered as a potential source of natural antihypertensive agents for use in functional foods. Further studies on the bioavailability of SSGP hydrolysates using an animal model of hypertension (spontaneously hypertensive rats) would be necessary to evaluate the efficacy of the hydrolysates for lowering blood pressure.

Acknowledgement

This work was supported by Natural Science Foundation of Jiangsu Province (No. BK2012693).

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Author:Jia, Jun-Qiang; Miao, Nan; Du, Jin-Juan; Wu, Qiong-Ying
Publication:Journal of the Chemical Society of Pakistan
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Date:Feb 28, 2019
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