The optimization of enzymatic hydrolysis conditions was applied to determine the optimal values of the independent variables (temperature, E/S, and pH), which would give the maximum ACE-inhibitory activity.

The response of DH and ACE-inhibitory activity (IP) were evaluated in CCD. The results obtained after running 20 trials according to CCD are presented in Table 1. The response of these three dependent variables to hydrolysis conditions, interactive terms, and probability values (p-values) are shown in Table 2 and Table 3. The effects with p-values lower than 0.05 indicated the statistical validity and significance of the DH and IP models.

Table 2 shows that X₁, X₂, and X₃ were the most significant ones affecting the DH. The interactions between the different factors significantly influenced the response variable (DH), except the interaction between X₁ and X₃.

As shown in Table 3, the independent variables X₁, X₂, and X₃ had a significant effect on IP. The interactive effects X₁*X₃, X₂*X₃ on IP were significant.

The coefficient of determination (adjusted R²) was used to check the fit of the models. The adjusted R² values corresponding to DH and IP are 0.9184 and 0.9010, respectively. The adjusted R² values were high, demonstrating that the two models were well-adapted to the responses and indicating the variability in the responses could be explained by the models (Equations 1 and 2). The lack of fit was not significant in both model equations, which, further validates the models.

Equations 1 and 2 describe the correlation between the variables and the response (DH and IP), respectively.

Y₁ = 23.77 − 0.81X₁ + 3.21X₂ − 1.65X₃ − 0.84X₁X₂ − 0.35X₁X₃ − 0.95X₂X₃ − 1.76X₁² − 0.99X₂² − 0.33X₃² (1)

Y₂ = 83.32 − 2.27X₁ + 2.94X₂ − 2.02X₃ − 0.33X₁X₂ − 1.76X₁X₃ + 1.64X₂X₃ − 3.35X₁² − 3.39X₂² − 2.30X₃² (2)

where Y₁ and Y₂ are the dependent variables (response variable) to be modeled; X₁ is the variable temperature; X₂ is the variable E/S; and X₃ is the variable pH.

Quadratic response surfaces and regression coefficients were used to study the effects of various parameters and their interactive effects on DH and IP. The response surfaces for DH and IP were drawn as three-dimensional plots of two factors, whereas the other factors were kept constant. Figure 1a,c shows that by increasing the E/S, the DH increased. However, a maximum DH is observed around temperature 45–50 °C and pH of circa 7.0. The DH was also affected by the interaction of pH and temperature (Figure 1b).

The response surface plot for ACE-inhibitory activity as function for interaction of temperature and E/S as variables indicated a progressive increase in IP up to 10,000 U/g E/S and temperature of circa 50 °C (Figure 1d). However, a decrease in ACE-inhibitory activity was observed with a further increase of both variables.

The effect of pH and temperature on ACE-inhibitory activity is displayed in Figure 1e. The results indicated that the ACE-inhibitory activity of hydrolysate increased with increasing temperature and pH up to an optimum point, beyond which a decrease in IP was observed for the process variables. The effect of pH and E/S is illustrated in Figure 1f, which shows that they had an interactive effect. The maximum IP value was also observed at a temperature of around 45–50 °C and pH of 7.0. The results suggested that an increase in some variables would promote the DH, but would not result in higher ACE-inhibitory activity.

To obtain the maximum ACE-inhibitory activity of the hydrolysates, the model was optimized using Design Expert^® 7.0 by setting the maximum IP value (Y₂) as the goal. The optimum conditions were temperature at 48 °C, E/S at 10,000 U/g, and pH at 7.0. Under these conditions, the predicted ACE-inhibitory activity of lizard fish hydrolysates was 84.45% and the predicted DH was 25.43%. To confirm the model’s validity, the experiment was performed at optimal conditions, in which the IP was 84% and the DH was 24%. These experimental values were in good agreement with the predicted value, confirming that these conditions were optimal for producing ACE-inhibitory peptides.

LFPH-І was fractionated by Sephadex G-15 chromatography into five portions: A, B, C, D, and E (Figure 2). Each fraction was measured for ACE-inhibitory activity, and fraction C was found to possess the strongest activity (Table 4). Active fraction C was purified by HPLC with the Hypersil ODS C₁₈ columns (the first HPLC run). The fractions were pooled and lyophilized, and fraction U7 exhibited the strongest ACE-inhibitory activity (Table 4 and Figure 3). At the second HPLC step, the fraction U7 was further purified and divided into three portions (Figure 4), among which fraction U73 showed the strongest ACE-inhibitory activity (Table 4). To purify the strongest ACE-inhibitory peptide, fraction U73 was then applied to a Zorbax SB C₁₈ column. As shown in Figure 5 and Table 4, the peak U73D showed the highest ACE-inhibitory activity and was applied to identify the amino acid sequence. The IC₅₀ value of U73D was determined as 41 ± 1 µM.

The amino acid sequences of active fraction U73D were identified as Ser-Pro-Arg-Cys-Arg (SPRCR). As shown in Figure 6, the molecular mass (617 Da) corresponded with its sequence.

ACE-inhibitory peptides containing hydrophobic amino acids at each of the three C-terminal positions showed a strong ACE-inhibitory activity [22]. It was found that inhibitory peptides with arginine as the C-terminal residues have potent inhibitory activity and the positive charge of the side-chain group of arginine contribute to ACE inhibitory potency [23]. In the current study, the ACE-inhibitory peptide SPRCR, which is composed of five amino acid residues and possesses a hydrophobic residue, arginine as the C-terminal residue, exhibited strong ACE-inhibitory activity. Furthermore, this ACE-inhibitory peptide was synthesized to confirm the ACE inhibitory activity. The IC₅₀ value of the synthesized peptide was 39 ± 1 µM, which corresponds to the IC₅₀ value (41 ± 1 µM) of the natural peptide isolated by us.

The lizard fish was purchased from a local market in Nanning, China. Its muscle was rapidly separated. After being rinsed with deionized water, the removed muscle of the lizard fish was dried with hot air (90 °C) over 8 h, and then powdered. ACE (from rabbit lung; 2.0 units/mg of protein) and hippuryl-L-histidyl-L-leucine (HHL) were purchased from the Sigma Chemical Company (USA). Neutral protease was kindly provided by Nanning Pangbo Biological Engineering Co., Ltd. (China). By using casein as the substrate, the activity of neutral protease was measured by Measurement of Proteinase Activity (SB/T10317-1999, China) and found to have a value of 400,000 U/g.

Under the conditions of E/S, pH, and temperature determined by the experimental design, lizard fish muscle protein was hydrolyzed with neutral protease. During the reaction of enzymatic hydrolysis, the pH was kept constant at the desired value by the addition of 0.1 M NaOH, and the volume of NaOH was recorded. After 2 h, the reaction was terminated by deactivating the enzyme at 95 °C in a water bath for 10 min. The pH was then adjusted to 7.0 by adding 0.1 M NaOH or 0.1 M HCl. The hydrolysate was centrifuged at 8000× g for 20 min (4 °C), and the supernates were lyophilized and used to measure ACE-inhibitory activity.

The degree of hydrolysis (DH) was estimated as the percentage of the peptide bonds cleaved during the enzymatic reaction (Equation 3) [24]:

DH% = B × N_b × (1/α)(1/M_p) × (1/h_tot) × 100 (3)

where B is the amount of NaOH consumed (mL); h_tot is the total number of peptide bonds in lizard fish muscle protein, assumed to be 7.836 eqv·g⁻¹; N_b is the normality of NaOH, M_p is the mass of protein; and α is the average degree of dissociation of α-NH₂ groups, calculated by the Equation 4:

where pK is the average pK value of the α-amino groups liberated during hydrolysis.

The ACE-inhibitory activity of LFPH was determined by HPLC methods with some modification [25]. Briefly, for each assay, a sample solution (120 µL of 0.1 M sodium borate buffer containing 0.3 M NaCl at pH 8.3 or 120 µL of ACE inhibitor) with 30 µL of ACE solution (0.04 U/mL in 0.1 M sodium borate buffer containing 0.3 M NaCl at pH 8.3) was pre-incubated for 10 min at 37 °C. The mixture was incubated with 50 µL of substrate (5 mM HHL in 0.1 M sodium borate buffer containing 0.3 M NaCl at pH 8.3) for 60 min at the same temperature. The enzymatic reaction was terminated by the addition of 150 µL of 1 M HCl. The amount of hippuric acid released by the action of ACE was measured by HPLC on a Hypersil ODS C₁₈ (4.0 mm × 250 mm, 5 μm, Agilent, Santa Clara, CA, USA) with 15% methanol containing 0.1% trifluoroacetic acid (TFA) at a flow rate of 1 mL/min. The absorbance was monitored at 228 nm.

The inhibitory ratios were calculated by the following Equation 5:

IP (%) = [1 − (A_inhibitor/A_control)] × 100 (5)

where IP is the inhibitory ratio; A_inhibitor and A_control are the peak areas of the sample and the control (buffer added instead of test sample), respectively. IC₅₀, the inhibitor concentration needed to inhibit 50% of enzyme activity, was determined by regression analysis of ACE inhibition (%) versus the log of the inhibitor concentration.

In the present study, the CCD of the three factors was used to optimize the enzymatic hydrolysis conditions of lizard fish muscle protein. Temperature (X₁), E/S (X₂), and pH (X₃) were employed at five levels. The experimental designs are shown in Table 5.

In the formula above (Equation 6), y (degree of hydrolysis or ACE-inhibitory activity in real value) is the response variable; x_i and x_j are independent variables; β₀, β_i, β_ii, and β_ij are coefficients estimated by the model. The model evaluated the effect of each independent variable to the response. Statistical analysis was performed with Design Expert^® 7.0 (Stat-Ease Inc., Hennepin, MN, USA). A P-value of less than 0.05 was chosen for statistical significance.

The peptide was synthesized by GL Biochem Ltd, Shanghai, China.