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Novel membrane peptidase inhibitory peptides with activity against angiotensin converting enzyme and dipeptidyl peptidase IV identified from hen eggs
Journal of Functional Foods xxx (xxxx) xxxx
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Novel membrane peptidase inhibitory peptides with activity against angiotensin converting enzyme and dipeptidyl peptidase IV identified from hen eggs Wenzhu Zhaoa, Dan Zhanga, Zhipeng Yua, , Long Dingb, Jingbo Liuc ⁎
a
College of Food Science and Engineering, Bohai University, Jinzhou 121013, PR China College of Food Science and Engineering, Northwest A&F University, Yangling 712100, PR China c Lab of Nutrition and Functional Food, Jilin University, Changchun 130062, PR China b
ARTICLE INFO
ABSTRACT
Keywords: Angiotensin converting enzyme inhibitory peptides Dipeptidyl peptidase IV inhibitory peptides Virtual screening Molecular docking
Angiotensin converting enzyme (ACE) and dipeptidyl peptidase IV (DPP-IV) are important membrane peptidases. The inhibition of ACE and DPP-IV enzymes has become a key therapeutic target for the treatment of hypertension and diabetes. This study was conducted to discover membrane peptidase inhibitory peptides that inhibit ACE and DPP-IV. Egg proteins were cleaved by pepsin and trypsin in silico. The potential activity, solubility, absorption, distribution, metabolism, excretion, and toxicity of the peptides were then predicted online. Finally, ACE and DPP-IV were applied as molecular docking targets for the potential peptides. After simulating gastrointestinal digestion, the IC50 values of ADF, MIR, and FGR against ACE activity were 27.75 ± 0.90 mM, 24.97 ± 0.80 mM, and 66.98 ± 1.40 μM, against DPP-IV activity were 16.83 mM, 4.86 mM, and 46.22 mM, respectively. The ACE and DPP-IV inhibitory peptides identified from hen egg proteins can be used as functional food ingredients for controlling hypertension and diabetes.
1. Introduction Bioactive peptides are inactivated amino acid sequences in food proteins, which are released and activated by enzymes during gastrointestinal digestion (Moller, Scholz-Ahrens, Roos, & Schrezenmeir, 2008). These peptides regulate biological activity and human health (Patil, Mandal, Tomar, & Anand, 2015) and exist in food sources such as soybean, eggs, and milk (Erdmann, Cheung, & Schroder, 2008). In addition, egg proteins are excellent sources of bioactive peptides (Fan, Wang, Liao, Jiang, & Wu, 2019). The potential roles of bioactive peptides rely on their ability to be absorbed into the blood circulation after entering the human body and transported to the target organ in the active form and in a sufficient amount, wherein the gastrointestinal tract (GIT) is a major absorption channel (Sayd et al., 2018). GITmembrane peptidases may alter the structures of peptides, thereby affecting their biological activity (Bleakley, Hayes, O’Shea, Gallagher, & Lafarga, 2017; Wang & Li, 2017). The human colon cell line, Caco-2, has been widely studied because it can differentiate into intestinal cell-
like cells and express characteristics of mature small intestinal cells. Eight membrane peptidases have been identified from Caco-2, i.e., dipeptidyl peptidase IV (DPP-IV), peptidyl dipeptidase A (angiotensin converting enzyme; ACE), amino peptidase N (AP-N), aminopeptidase P (AP-P), aminopeptidase W (AP-W), endopeptidase-24.11 (E-24.11), γglutamyl transpeptidase (γ-GT) and membrane dipeptidase (MDP). The activities of these membrane peptidases differ (Howell, Kenny, & Turner, 1992). ACE and DPP-IV are important membrane peptidases. Bioactive peptides with both ACE and DPP-IV inhibitory activity are more stable in vivo because they are resistant to membrane peptidase degradation and can enter the cell as active molecules. Peptides with dual ACE and DPP-IV inhibitory activities are also important functional bioactive peptides and can inhibit ACE and DPP-IV activity in vitro, thereby helping to lower blood pressure (Gangopadhyay et al., 2016) and exerting antihyperglycemic effects (Conarello et al., 2003). Isolating and purifying bioactive peptides is time-consuming and expensive; however, the process can be advanced by multistep virtual screening methods and in silico GI digestion (Vercruysse, Smagghe,
Abbreviations: ACE, angiotensin converting enzyme; DPP-IV, dipeptidyl peptidase IV; GIT, gastrointestinal tract; AP-N, amino peptidase N; AP-P, aminopeptidase P; AP-W, aminopeptidase W; E-24.11, endopeptidase-24.11; γ-GT, γ-glutamyl transpeptidase; MDP, membrane dipeptidase; HHL, hippuryl-histidyl-leucine; ADMET, absorption, distribution, metabolism, excretion, toxicity; DS, Discovery Studio ⁎ Corresponding author at: Jinzhou City, Liaoning Province, PR China. E-mail address: [email protected] (Z. Yu). https://doi.org/10.1016/j.jff.2019.103649 Received 11 April 2019; Received in revised form 15 October 2019; Accepted 21 October 2019 1756-4646/ © 2019 Elsevier Ltd. All rights reserved.
Please cite this article as: Wenzhu Zhao, et al., Journal of Functional Foods, https://doi.org/10.1016/j.jff.2019.103649
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peptide structures were drawn in Discovery Studio (DS) 2017 client software. The CDOCKER protocol of DS 2017 was used for molecular docking. The docking was conducted with coordinates x: 42.007562, y: 33.97662, and z: 45.631287 and x: 39.239388, y: −7.930548, and z: 94.02401, with a radius of 9 Å. The best pose was output based on the CDOCKER score.
Matsui, & Van Camp, 2008). Computer analysis of bioactive peptides released after food proteolysis is useful, and this technique complements experimental procedures. Many studies have confirmed the reliability of in silico screening methods, which can be considered valid alternatives to classic enzymatic methods (Fu et al., 2016). The main objective of this study was to reveal membrane peptidase inhibitory di- and tripeptides that can overcome GIT degradation and inhibit both ACE and DPP-IV activity using multistep virtual screening methods. Besides, this study also verified whether peptides with ACE and DPP-IV inhibitory activity could resist gastrointestinal degradation via in vitro simulated GIT digestion experiments. The egg protein sequences were searched from the NCBI database and hydrolyzed in silico using pepsin (pH 1.3, EC 3.4.23.1) and trypsin (EC 3.4.21.4). All di- and tripeptides were screened for activity scores. The studied peptide sequences were searched in the BIOPEP-UWM, the database of antihypertensive peptides (AHTPDB) and PepBank, and the peptides have been reported was excluded. The remaining dipeptides and tripeptides were synthesized using the solid-phase method. In addition, potent ACE and DPP-IV inhibitory peptides were docked with ACE and DPP-IV to discover ACE and DPP-IV inhibitory peptides with anti-GIT digestion properties from egg proteins.
2.4. Solid-phase peptide synthesis Hen egg protein-derived peptides, i.e., ADF, MIR, FGR, FK, and CDR, were synthesized using standard Fmoc solid-phase peptide conditions on an AAPPTEC Apex 396 peptide synthesizer as previously described (Yu et al., 2012). The molecular mass and purity of the synthetic peptides were tested via high performance liquid chromatography-electrospray ionization-quadrupole-mass spectrometer (Shimadzu CO., LTD, Beijing, China). 2.5. ACE inhibitory activity assay The ACE inhibitory activity in vitro was determined per the HPLC method of Yu et al. (2018). Thirty microliters of HHL solution and 10 μL of the peptide were added and mixed uniformly, then incubated at 37 °C for 5 min. ACE solution (20 μL) was added and mixed thoroughly. After incubating at 37 °C for 30 min, the reaction solution was obtained and analyzed via HPLC. Data were expressed as means ± SD and subjected to one-way analysis of variance (ANOVA).
2. Materials and methods 2.1. Materials and reagents ACE (protease from rabbit lungs), hippuryl-histidyl-leucine (HHL), and the DPP-IV Inhibitor Screening Kit were obtained from SigmaAldrich Co. (St. Louis, MO, USA). Trifluoroacetic acid, acetonitrile, and methanol were acquired from Fisher Scientific Co. (Waltham, MA, USA) and were chromatographic grade. All other reagents and chemicals used were analytical grade. All synthetic peptides used were supplied by Shanghai Top Peptide Biological Technology Corporation (Shanghai, China).
2.6. DPP-IV inhibition assay In vitro DPP-IV inhibition assay of the peptides isolated from eight egg proteins was performed per the manufacturer’s instructions (DPP-IV Inhibitor Screening Assay Kit, Sigma-Aldrich Co, St. Louis, MO, USA). Two solutions were required for the assay. For the enzyme control solution (uninhibited enzyme), DPP-IV assay buffer was used to substitute the sample inhibitor. First, 25 µL of DPP-IV assay buffer was added to 50 µL diluted DPP-IV enzyme buffer, mixed well using a Vortex Mixer XW-80A, and incubated at 37 °C for 10 min in the dark. Next, 25 µL of diluted DPP-IV substrate buffer was added to the sample and mixed well. The sample inhibitor differed only at the first step, in which 25 µL of peptide was added at 10 mg/mL. Fluorescence was read with excitation wavelengths of 360 nm and emission wavelengths of 460 nm using a fluorescence spectrophotometer (PerkinElmer, Waltham, Massachusetts, USA). The percentage inhibition was computed using the following equation:
2.2. In silico digestion Two representative proteases of pepsin (pH 1.3, EC 3.4.23.1) and trypsin (EC 3.4.21.4) were chosen in the present study. Pepsin and trypsin are two typical enzymes in the gastrointestinal tract and are currently industrialized. The program ExPASy PeptideCutter (http:// web.expasy.org/peptide_cutter/) (Zhao et al., 2016) was used to hydrolyze the peptide sequences released from eight proteins (ovotransferrin, myosin-10, ovomucoid, lysozyme, ovomacroglobulin, avidin, phosvitin, and ovalbumin) of hen eggs. PeptideRanker was used to predict whether the peptides were biologically active and express the theoretical biological activity as a calculated score (http://bioware.ucd. ie/~compass/biowareweb/Serverpages/peptideranker.php) (Mooney, Haslam, Pollastri, & Shields, 2012). Peptides were obtained and compared with known ACE and DPP-IV inhibitory peptides in BIOPEPUWM database (http://www.uwm.edu.pl/biochemia/index.php/en/ biopep) (Minkiewicz, Dziuba, Iwaniak, Dziuba, & Darewicz, 2008), AHTPDB (http://crdd.osdd.net/raghava/ahtpdb/pep.php) and PepBank (http://pepbank.mgh.harvard.edu/) (Solanki, Hati, & Sakure, 2017) after screening. The peptide property calculator (http://www. innovagen.com/) was used to estimate the solubility (Lafarga, O'Connor, & Hayes, 2015). Subsequently, unknown di- and tripeptides were selected, and their water solubility and absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties were predicted.
% Relative Inhibition = (Slope EC
Slope SM)/Slope EC × 100%
Slope SM = slope of the sample inhibitor Slope EC = slope of the enzyme control 3. Results and discussion 3.1. In silico GIT digestion of egg proteins The amino acid sequences of eight egg proteins were chosen from the NCBI database (Table 1). Two typical proteases, pepsin (pH 1.3, EC 3.4.23.1) and trypsin (EC 3.4.21.4), were selected for the study. ExPASy PeptideCutter was used to generate in silico peptide sequences from eight egg proteins. PeptideRanker results were ranked based on active scores. Typically, PeptideRanker training peptides above 0.5 thresholds are considered biologically active. Peptides at 0.5 or more may be biologically active. Peptides were obtained and compared with known ACE and DPP-IV inhibitory peptides in BIOPEP-UWM, AHTPDB and PepBank. Unknown di- and tripeptides were subsequently selected. Besides, water solubility influenced the degree of absorption of the bioactive peptides. The ADMET properties of human intestinal
2.3. Molecular docking The crystal structures of ACE (PDB: 1O86) and DPP-IV (PDB: 5J3J) were selected for molecular docking with peptides. Both ACE and DPPIV were prepared by removing water and adding hydrogen atoms. The 2
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In the docked complex, Glu411 (OE1), Glu384 (OE2), Lys511 (HZ1), Asp453 (OD1), and Glu376 (OE2) formed attractive charge interactions with N55, N55, O63, N1, and H4 of MIR, at distances of 4.94 Å, 4.84 Å, 1.79 Å, 4.09 Å and 1.84 Å, respectively (shown in Fig. 1b). Furthermore, one alkyl interaction between Val380 of ACE and the carbon atom (C14) of MIR (4.33 Å) was observed. Besides, His353 and His383 established two pi-alkyl interactions with MIR at 4.06 Å and 4.48 Å, respectively. MIR interacted with the amino acids Tyr523 (OH), Ala354 (O), His513 (NE2), Glu384 (OE2), Gln281 (HE21), Lys511 (HZ1), Lys511 (HZ3), Asn277 (HD22), Thr282 (HG1), and Thr282 (OG1) via eleven conventional carbon hydrogen bonds. Atoms OE2 and OE2 of Glu376 and Glu384 of ACE formed attractive charge interactions with N46 and N1 of FGR, generating lengths of 5.26 Å and 4.2 Å, respectively (Fig. 1c). Tyr523 (OH), His353 (HE1), and His513 (HE1) of ACE also formed carbon hydrogen bonds with atoms H6, O53, and O54 of FGR at 2.63 Å, 2.43 Å, and 2.62 Å, respectively. FGR formed a pi-alkyl interaction with Val518 (5.03 Å). Three salt bridges were observed in the complex; the first involved the oxygen atom OD1 of Asp377 with the hydrogen atom H48 of FGR (2.62 Å), the second involved OE2 of Glu162 with the hydrogen atom H47 of FGR (2.37 Å), and the third involved the hydrogen atom HZ1 of Lys511 with the oxygen atom O54 of FGR (1.83 Å). Additionally, six conventional carbon hydrogen bonds were involved with Glu376, Asp377, Ala354, Lys511, His353, and Tyr520 of ACE. The interaction of fosinopril with ACE was shown in Fig. 1d, the CDOCKER-ENERGY value was −61.8988 kcal/mol. Fosinopril interacted with ACE at Glu162, Asp377, Val380, Val518, Ala354, His513, Ser355, His353, Ala356, His387, Lys511, Trp279, Gln281, Tyr523, Phe457, and ZN701. Therefore, His353, His513, and Lys511 of ACE may play major roles in ACE binding and may be important screening indicators. The interaction of NTF, CDR, QGF, NAF, FK, QGL, and FYQ with ACE were shown in Fig. 2, respectively. The ACE active sites were composed of three pockets: S1 (Ala354, Glu384, and Tyr523), S2 (Gln281, His353, His513, Lys511, and Tyr520) and S1′ (Glu162) (Abdelhedi et al., 2018; Ko et al., 2017; Rohit, Sathisha, & Aparna, 2012; Wang, Chen, Fu, Li, & Wei, 2017). And the Cterminal Phe of ADF was linked to His513 and His353 forming carbonhydrogen bonds and a conventional hydrogen bond and an attractive charge interaction with Lys511. The results were confirmed using docking analysis. Besides, an ADF and Zn701 interaction was identified. The Arg residue of FGR included two conventional hydrogen bonds with Lys511 and His353 and two carbon hydrogen bonds with His353 and His513. No reaction occurred between FGR and Zn701. Analogous to FGR, the C-terminal Arg generated conventional hydrogen bonds with Lys511 and His513 and displayed an interaction between His353 and MIR. The current research suggested that the C-terminal Phe and Arg may enhance ACE inhibitory activity of peptides. Molecular docking studies showed that the formation of hydrogen bonding interactions caused the firm interaction between ACE active sites and peptides (Wu, Du, Jia, & Kuang, 2016). In this study, ADF contained Phe at the C-terminus. Furthermore,
Table 1 Proteins searched from NCBI in egg. Protein
Accession
Amino Acid Length
Ovotransferrin myosin-10 Ovomucoid Lysozyme Ovomacroglobulin Avidin Phosvitin Ovalbumin
CAA26040 NP_990805 ACJ04729 ACL81750 CAA55385 CAC34569 P67869 0705172A
705 aa 2007 aa 210 aa 147 aa 1454 aa 152 aa 215 aa 385 aa
absorption, Caco-2 permeability, and metabolic parameters were predicted using ADMET in Discovery Studio (DS) 2017. After combining GIT digestion, 10 unknown di- and tripeptides (as shown in Table 2) were selected for solubility and ADMET property prediction; the results showed that they were all nontoxic. The screening of the polypeptides throughout the process was shown in the supporting materials (Tables S1–S3). Moreover, the peptides CDR, ADF, FGR, MIR and FK showed good water solubility, while others showed poor water solubility. 3.2. Prediction of ACE inhibitory activity of the di- and tripeptides Peptides NTF, CDR, QGF, ADF, NAF, FGR, MIR, FK, QGL, and FYQ meeting the requirements of the previous GI screening were subjected to molecular docking using CDOCKER (shown in Table 2). The ACE crystal structure (PDB: 1O86) was treated as the target for screening peptides that bound tightly with ACE (Ke et al., 2017). ACE was prepared by removing water and adding hydrogen atoms. Peptides were drawn in Discovery Studio (DS) 2017 client software. Molecular docking was conducted using CDOCKER protocol in DS 2017. The best position was based on the CDOCKER score output. Fig. 1 showed that the ACE docking postures of the tripeptides, ADF, MIR and FGR. The CDOCKER-ENERGY values of tripeptides ADF, MIR and FGR were −96.527, −93.3993 and −93.3051 kcal/mol, respectively (as shown in Table 2). A lower 'CDOCKER -ENERGY' score indicates a more favorable combination. Val518 of ACE formed a pi-alkyl interaction with the ADF, generating lengths of 5.29 Å (Fig. 1a). The hydrogen atom (H28) of ADF formed a carbon hydrogen bond with OH of the residue TYR523 (2.51 Å). Moreover, His513 (HE1) and His353 (HE1) of ACE also formed carbon hydrogen bonds with atoms O24 and O22 of ADF at distances of 2.76 Å and 2.54 Å, respectively. Asp377 (OD1), Zn701 and Lys511 (HZ3) of ACE formed attractive charge interactions with ADF (N1), ADF (O45) and ADF (O22) generating lengths of 5.24 Å, 2.22 Å and 2.57 Å, respectively. Two conventional carbon hydrogen bonds were also observed in the complex, with the first involving the hydrogen atom (HZ1) of Lys511 with the oxygen atom (O21) of ADF (1.85 Å). The second was Tyr520 (HH) with the oxygen atom (O21) of ADF (2.29 Å). Salt bridges formed between ADF (H2) and Glu162 (OE2) at 1.95 Å. Additionally, a pi-donor hydrogen bond formed between ADF (H14) and His353 at 2.71 Å.
Table 2 PeptideRanker score, Docking score, predicted solubility, and ADMET properties of selected peptides using in silico hydrolysis with pepsin and trypsin. Peptide
PeptideRanker score
Docking score with ACE (-CDOCKER ENERGY)
Docking score with DPP-IV (-CDOCKER ENERGY)
Water Solubility
ADMET/Toxicity
NTF CDR QGF ADF NAF FGR MIR FK QGL FYQ
0.52 0.6 0.94 0.81 0.77 0.97 0.66 0.86 0.53 0.8
90.9827 97.4362 91.5552 96.527 91.1912 93.3051 93.3993 86.6082 88.9634 102.046
81.979 81.3713 81.061 80.2084 78.7809 78.7061 77.2295 75.3097 74.103 73.7114
POOR GOOD POOR GOOD POOR GOOD GOOD GOOD POOR POOR
Non-toxin Non-toxin Non-toxin Non-toxin Non-toxin Non-toxin Non-toxin Non-toxin Non-toxin Non-toxin
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Fig. 1. Molecular interactions of the tripeptides Ala-Asp-Phe (ADF) (a), Met-Ile-Arg (MIR) (b), Phe-Gly-Arg (FGR) (c), fosinopril (d) into the active site of ACE. In (a), green color represents conventional hydrogen bond, carbon hydrogen bond and pi-donor hydrogen bond, the orange color represents salt bridge and attractive charge, and pink color represents pi-alkyl. In (b), green color represents conventional hydrogen bond and carbon hydrogen bond, orange color represents salt bridge and attractive charge, and pink color represents alkyl and pi-alkyl. In (c), green color represents conventional hydrogen bond and carbon hydrogen bond, orange color represents salt bridge and attractive charge, pink color represents pi-alkyl. In (d), green color represents conventional hydrogen bond and carbon hydrogen bond, orange color represents pi-anion, pink color represents pi-alkyl and alkyl, gray color represents metal-acceptor. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
many studies have shown that C-terminal amino acid Phe may stabilize ACE inhibitory peptides (Wu et al., 2016). Additionally, FGR and MIR included the same amino acid Arg residues at the C-terminus. Several studies have also demonstrated that peptides have a hydrophilic Arg residue at the C-terminus, such as YR, IR (Ko et al., 2017), VSQLTR (Ji, Zhang, & Ji, 2017), IPALLKR and AQQLAAQLPAMCR (Asoodeh et al., 2014), which exert potent ACE inhibitory activity. In summary, specialized amino acids and their particular sequences likely enhanced the ACE inhibitory peptide activity. In short, peptides ADF, CDR, MIR, FGR, FK, and FYQ had lower docking scores, demonstrating that they had higher-binding affinities with ACE. ADF, CDR, MIR, FGR, and FK all interacted with the ACE active sites, Lys511 and His353. However, FYQ was not connected to the active site, His353. Therefore, ADF, CDR, MIR, FGR, and FK could be used in subsequent ACE inhibitory activity assay. The CDOCKERENERGY values of the peptides ADF, MIR, and FGR were lower than those of the positive control, fosinopril, suggesting that these peptides may have higher ACE inhibitory activity than that of fosinopril and that an in silico screening method was available.
3.3. Prediction of DPP-IV inhibitory activity of the di- and tripeptides Peptides CDR, ADF, FGR, MIR, and FK, which showed better scores in the previous docking with ACE, were used for molecular docking in the CDOCKER program (shown in Table 2). DPP-IV (PDB: 5J3J) was treated as the target to screen peptides that bound tightly with DPP-IV. Peptides were drawn in DS 2017. Molecular docking was conducted using the CDOCKER protocol in DS 2017. The best result was based on the CDOCKER score outcome. Fig. 3 showed the DPP-IV docking positions with the tripeptides ADF, MIR and FGR. The CDOCKER-ENERGY values of ADF, MIR and FGR were −80.2084, −77.2295 and −78.7061 kcal/mol, respectively (as shown in Table 2). ADF formed 3 salt bridges with amino acid residue Glu205, Glu206, and Arg125 at 2.02 Å, 1.89 Å, and 2.71 Å, respectively. Further, two carbon hydrogen bonds and one attractive charge interaction with Glu205 (OE2), Glu206 (OE1), and Arg358 (NH1) were also predicted (Fig. 3a). ADF (O21) also established conventional carbon hydrogen bond with Arg358 (HH22). Phe357 formed a pi-pi T-shaped interaction bond with ADF.
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Fig. 3b showed the optimal three-dimensional structure of MIR docking with DPP-IV. Arg125 (NH1) of DPP-IV formed an unfavorable positive-positive interaction with MIR (N55). Phe357 formed a pi-donor hydrogen bond with MIR (H40), and Arg669 (NH1) and Glu206 (OE1) of DPP-IV formed attractive charge interactions with atoms O63 and H3 of MIR, respectively. Glu205 (OE2), Glu206 (OE2) and Glu206 (OE1) of
DPP-IV formed three salt bridges with MIR. Five conventional carbon hydrogen bonds were observed in the complex; four were Tyr662, Tyr666, Trp659, and Tyr631 with C14 of MIR, and the last was Tyr666 with N1 of MIR. An unfavorable negative-negative interaction occurred between Glu205 (OE2) with MIR (O63). Additionally, a carbon hydrogen bond formed between MIR (H6) and Glu205 (OE2). In the
Fig. 2. Molecular interactions of the tripeptides Asn-Thr-Phe (NTF) (a), Cys-Asp-Arg (CDR) (b), Gln-Gly-Phe (QGF) (c), Asn-Ala-Phe (NAF) (d), Phe-Lys (FK) (e), GlnGly-Leu (QGL) (f), Phe-Tyr-Gln (FYQ) (g) into the active site of ACE. In (a), green color represents conventional hydrogen bond and carbon hydrogen bond, the orange color represents salt bridge and pi-anion, and red color represents unfavorable positive-positive. In (b), green color represents conventional hydrogen bond, pi-donor hydrogen bond and carbon hydrogen bond, orange color represents salt bridge and attractive charge, and red color represents unfavorable acceptoracceptor. In (c), green color represents conventional hydrogen bond, pi-donor hydrogen bond, and carbon hydrogen bond, orange color represents attractive charge, gray color represents metal-acceptor, and red color represents unfavorable positive-positive. In (d), green color represents conventional hydrogen bond and carbon hydrogen bond, and orange color represents salt bridge and pi-anion. In (e), green color represents conventional hydrogen bond and carbon hydrogen bond, and orange color represents attractive charge and salt bridge. In (f), green color represents conventional hydrogen bond and carbon hydrogen bond, orange color represents salt bridge, red color represents unfavorable positive-positive, and pink color represents alkyl. In (g), green color represents conventional hydrogen bond and carbon hydrogen bond, orange color represents attractive charge, pi-anion, and salt bridge, and pink color represents pi-pi T-shaped. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
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Fig. 2. (continued)
complex, His126 (NE2), Arg669 (HH12), Arg669 (HH22), Glu205 (O), and Tyr662 (OH) formed conventional hydrogen bonds with MIR. Tyr666 formed a pi-cation interaction with MIR (N1), and a pi-sulfur interaction was found between Tyr631 and MIR (S13). Val656 was involved in an alkyl interaction with C14 of MIR. Tyr662 (OH), Glu205 (O), Glu206 (OE1), Arg358 (HH22), and Tyr547 (OH) formed conventional hydrogen bonds with FGR (Fig. 3c). One carbon hydrogen bond was observed between Glu205 of DPP-IV with the hydrogen atom H6 of FGR. Tyr662 and His740 established two pi-pi stacked interactions with FGR. Next, FGR interacted with Glu205 (OE2) and Arg358 (HH12) via two salt bridges. OD2 and OE2 of the residues Asp663 and Glu206 of DPP-IV formed attractive charge interactions with N1 of FGR. FGR formed a pi-pi T-shaped interaction with Tyr666. One pi-anion interaction was observed between Phe357 and O54 of FGR. The position of saxagliptin interacting with DPP-IV was shown in Fig. 3d. The CDOCKER-ENERGY value was −37.5099 kcal/mol. Saxagliptin interacted with Tyr666, Arg125, Ser209, Glu206, Glu205 and
Phe357 of 5J3J. Therefore, the residues Glu205, Glu206, and Phe357 of DPP-IV may be involved in DPP-IV binding and may be important screening indicators. The DPP-IV structure had three active pockets: S1, S2 and S3. S1 contained Tyr547, Ser630, Tyr631, Val656, Trp659, Tyr662, Tyr666, Asn710, Val711 and His740. Glu205, Glu206, and Tyr662 constituted the S2 pocket, and Ser209, Arg358, and Phe357 constituted the S3 pocket (Kim et al., 2018). Saxagliptin interacted with the DPP-IV active sites, containing three binding pockets, forming two pi-alkyl interactions with Tyr666 of S1 and combining with Glu205 and Glu206 of S2. Two pi-alkyl interactions and a carbon hydrogen bond were found between Phe357 and Ser209 of S3 in DPP-IV. All important interactions with the critical residues (Phe357, Glu205, Glu206) were observed. The current work indicates that C-terminal Phe and Arg may influence DPPIV inhibitory activity of peptides. ADF contained the amino acid Phe of the C-terminus. Research on the C-terminal amino acid Phe, (e.g., Ala-Pro-Phe, Phe-Pro-Ile and PhePro-Phe) (Nongonierma & FitzGerald, 2018) indicated that Phe may 6
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Fig. 3. Molecular interactions of the tripeptides Ala-Asp-Phe (ADF) (a), Met-Ile-Arg (MIR) (b), Phe-Gly-Arg (FGR) (c), saxagliptin (d) into the active site of DPP-IV. In (a), green color represents conventional hydrogen bond and carbon hydrogen bond, the orange color represents salt bridge and attractive charge, and pink color represents pi-pi T-shaped. In (b), green color represents conventional hydrogen bond, pi-donor hydrogen bond and carbon hydrogen bond, orange color represents salt bridge, pi-cation, pi-sulfur, and attractive charge, red color represents unfavorable positive-positive, and pink color represents alkyl and pi-alkyl. In (c), green color represents conventional hydrogen bond and carbon hydrogen bond, orange color represents salt bridge, pi-anion, and attractive charge, pink color represents pi-pi stacked and pi-pi T-shaped. In (d), green color represents conventional hydrogen bond and carbon hydrogen bond, pink color represents pi-alkyl. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
strengthen DPP-IV inhibitory peptides. Similarly, FGR and MIR had the same Arg at the C-terminus. Several studies have been conducted on peptides with the hydrophilic residue Arg impacting potent DPP-IV inhibition, for example, Ala-Pro-Arg (Nongonierma et al., 2018), TrpArg (Nongonierma & FitzGerald, 2015), and Cys-Ala-Tyr-Gln-Trp- GlnArg-Pro-Val-Asp-Arg-Ile-Arg (Huang, Jao, Ho, & Hsu, 2012). Thus,
amino acids located at specific positions of peptides may be important for inhibiting DPP-IV. ADF, CDR, MIR, FGR, and FK had lower docking scores demonstrating that they had high-binding abilities with DPP-IV and all of them connected to Glu205 and Glu206. ADF, MIR, and FGR connected with the active sites Glu205, Glu206, and Phe357. This study aimed to
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discover peptides with excellent ACE and DPP-IV inhibition. Thus, ADF, CDR, MIR, FGR, and FK, which had high ACE and DPP-IV inhibitory activities, were used in the subsequent DPP-IV inhibitory activity assay. The CDOCKER-ENERGY values of ADF, MIR, and FGR were lower than those of the positive control saxagliptin, and thus ADF, MIR, and FGR may have higher DPP-IV inhibitory activity than that of saxagliptin. This demonstrated the feasibility of the virtual screening method.
inhibitory activity. Many studies on deriving ACE inhibitory peptides from food proteins have focused on in silico methods, for example, with pea and whey proteins (Vermeirssen, van der Bent, Van Camp, van Amerongen, & Verstraete, 2004) and milk casein (Lin et al., 2018). Some studies have also explored the potential of alternatives such as oat proteins (Bleakley et al., 2017; Cheung, Nakayama, Hsu, Samaranayaka, & Li-Chan, 2009), crude barley protein (Gangopadhyay et al., 2016), and giant grouper (Panjaitan, Gomez, & Chang, 2018). Therefore, virtual screening methods are excellent for screening ACE inhibitory peptides.
3.4. In vitro ACE inhibitory activity of promising peptides In vitro ACE inhibition was tested to verify the matching degree between the ACE inhibition predicted by the virtual screening and the actual experimental outcome. The purity and molecular masses of the synthetic peptides ADF, MIR, FGR, FK, and CDR were shown in Fig. 4, respectively. The IC50 values of the ACE inhibitory activities of ADF, MIR and FGR tested via HPLC were 27.75 ± 0.90 mM, 24.97 ± 0.80 mM, and 66.98 ± 1.40 µM, respectively. For MIR and ADF from myosin, the ACE inhibitory rate of MIR (IC50 = 24.97 ± 0.80 mM) was higher than that of ADF (IC50 = 27.75 ± 0.90 mM) and of FGR (IC50 = 66.98 ± 1.40 µM) from lysozyme. FGR had a stronger ACE inhibition than did FK (IC50 = 34.70 mM) from ovalbumin. Peptide CDR lacked ACE
3.5. In vitro DPP-IV inhibitory activity of promising peptides An in vitro DPP-IV inhibition assay was designed to test the matching between the predictive DPP-IV inhibition of the virtual screening and real experiments. The IC50 values of the DPP-IV inhibitory activity of ADF, CDR, MIR, and FGR tested via a fluorescence spectrophotometer were 16.83 mM, 24.49 mM, 4.86 mM, and 46.22 mM, respectively. DPP-IV inhibitory activities of MIR (IC50 = 4.86 mM) and ADF (IC50 = 16.83 mM) identified from myosin were higher than that of CDR (IC50 = 24.49 mM) from ovotransferrin. CDR had higher DPP-IV
Fig. 4. The purity and molecular masses of the synthetic peptides. The HPLC (a) and mass spectrometry (b) results of ADF. The HPLC (c) and mass spectrometry (d) results of MIR. The HPLC (e) and mass spectrometry (f) results of FGR. The HPLC (g) and mass spectrometry (h) results of FK. The HPLC (i) and mass spectrometry (j) results of CDR.
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Fig. 4. (continued)
inhibition than did FGR (IC50 = 46.22 mM) from lysozyme. FK screening from ovalbumin lacked DPP-IV inhibition. Peptides that inhibit DPP-IV have been obtained from numerous food protein sources via molecular docking, including milk (Nongonierma et al., 2018), Ruditapes (Liu et al., 2017), Antarctic krill (Ji et al., 2017), and soy (Lammi, Zanoni, Arnoldi, & Vistoli, 2016). Similarly, molecular docking can distinguish peptides capable of inhibiting DPP-IV from food proteins.
methods, virtual screening is more time-saving and effective. Wherefore, virtual screening was a dependable method of screening latent ACE and DPP-IV inhibitory peptides. The results showed that the IC50 values of ADF, MIR, and FGR against ACE were 27.75 ± 0.90 mM, 24.97 ± 0.80 mM, and 66.98 ± 1.40 μM, respectively, while those against DPP-IV were 16.83 mM, 4.86 mM, and 46.22 mM. Molecular docking simulation demonstrated that tripeptide activities against ACE and DPP-IV may be due to the hydrogen bond interactions. Overall, these tripeptides were useful as natural inhibitors of ACE and DPP-IV for controlling hyperglycemia and hypertension, respectively. However, docking may only provide guidance for enzyme sites. More in vivo animal experiments were needed to verify the virtual screening results.
4. Conclusions In this work, three new ACE and DPP-IV membrane peptidase inhibitory peptides, ADF, MIR, and FGR, were identified from myosin and lysozyme of hen eggs via virtual screening. Compared with traditional 9
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ultrafiltration. Food Chemistry, 239, 453–463. https://doi.org/10.1016/j.foodchem. 2017.06.112. Asoodeh, A., Haghighi, L., Chamani, J., Ansari-Ogholbeyk, M. A., Mojallal-Tabatabaei, Z., & Lagzian, M. (2014). Potential angiotensin I converting enzyme inhibitory peptides from gluten hydrolysate: Biochemical characterization and molecular docking study. Journal of Cereal Science, 60(1), 92–98. https://doi.org/10.1016/j.jcs.2014.01.019. Bleakley, S., Hayes, M., O’Shea, N., Gallagher, E., & Lafarga, T. (2017). Predicted release and analysis of novel ACE-I, renin, and DPP-IV inhibitory peptides from common oat (Avena sativa) protein hydrolysates using in silico analysis. Foods, 6(12), https://doi. org/10.3390/foods6120108. Cheung, I. W., Nakayama, S., Hsu, M. N., Samaranayaka, A. G., & Li-Chan, E. C. (2009). Angiotensin-I converting enzyme inhibitory activity of hydrolysates from oat (Avena sativa) proteins by in silico and in vitro analyses. Journal of Agriculture and Food Chemistry, 57(19), 9234–9242. https://doi.org/10.1021/jf9018245. Conarello, S. L., Li, Z. H., Ronan, J., Roy, R. S., Zhu, L., Jiang, G. Q., ... Zhang, B. B. (2003). Mice lacking dipeptidyl peptidase IV are protected against obesity and insulin resistance. Proceedings of the National Academy of Sciences of the United States of America, 100(11), 6825–6830. https://doi.org/10.1073/pnas.0631828100. Erdmann, K., Cheung, B. W. Y., & Schroder, H. (2008). The possible roles of food-derived bioactive peptides in reducing the risk of cardiovascular disease. Journal of Nutritional Biochemistry, 19(10), 643–654. https://doi.org/10.1016/j.jnutbio.2007.11.010. Fan, H., Wang, J., Liao, W., Jiang, X., & Wu, J. (2019). Identification and characterization of gastrointestinal-resistant angiotensin-converting enzyme inhibitory peptides from egg white proteins. Journal of Agriculture and Food Chemistry, 67(25), 7147–7156. https://doi.org/10.1021/acs.jafc.9b01071. Fu, Y., Young, J. F., Lokke, M. M., Lametsch, R., Aluko, R. E., & Therkildsen, M. (2016). Revalorisation of bovine collagen as a potential precursor of angiotensin 1-converting enzyme (ACE) inhibitory peptides based on in silico and in vitro protein digestions. Journal of Functional Foods, 24, 196–206. https://doi.org/10.1016/j.jff.2016.03.026. Gangopadhyay, N., Wynne, K., O'Connor, P., Gallagher, E., Brunton, N. P., Rai, D. K., & Hayes, M. (2016). In silico and in vitro analyses of the angiotensin-I converting enzyme inhibitory activity of hydrolysates generated from crude barley (Hordeum vulgare) protein concentrates. Food Chemistry, 203, 367–374. https://doi.org/10. 1016/j.foodchem.2016.02.097. Howell, S., Kenny, A. J., & Turner, A. J. (1992). A survey of membrane peptidases in two human colonic cell lines, Caco-2 and HT-29. The Biochemical Journal, 284(Pt 2), 595–601. https://doi.org/10.1042/bj2840595. Huang, S. L., Jao, C. L., Ho, K. P., & Hsu, K. C. (2012). Dipeptidyl-peptidase IV inhibitory activity of peptides derived from tuna cooking juice hydrolysates. Peptides, 35(1), 114–121. https://doi.org/10.1016/j.peptides.2012.03.006. Ji, W., Zhang, C., & Ji, H. (2017). Purification, identification and molecular mechanism of two dipeptidyl peptidase IV (DPP-IV) inhibitory peptides from Antarctic krill (Euphausia superba) protein hydrolysate. Journal of Chromatography B Analytical Technologies in the Biomedical and Life Sciences, 1064, 56–61. https://doi.org/10. 1016/j.jchromb.2017.09.001. Ke, Z., Su, Z., Zhang, X., Cao, Z., Ding, Y., Cao, L., ... Xiao, W. (2017). Discovery of a potent angiotensin converting enzyme inhibitor via virtual screening. Bioorganic & Medicinal Chemistry Letters, 27(16), 3688–3692. https://doi.org/10.1016/j.bmcl. 2017.07.016. Kim, B. R., Kim, H. Y., Choi, I., Kim, J. B., Jin, C. H., & Han, A. R. (2018). DPP-IV inhibitory potentials of flavonol glycosides isolated from the seeds of Lens culinaris. In vitro and molecular docking analyses. Molecules, 23(8), https://doi.org/10.3390/ molecules23081998. Ko, S. C., Jang, J. Y., Ye, B. R., Kim, M. S., Choi, I. W., Park, W. S., ... Jung, W. K. (2017). Purification and molecular docking study of angiotensin I-converting enzyme (ACE) inhibitory peptides from hydrolysates of marine sponge Stylotella aurantium. Process Biochemistry, 54, 180–187. https://doi.org/10.1016/j.procbio.2016.12.023. Lafarga, T., O'Connor, P., & Hayes, M. (2015). In silico methods to identify meat-derived prolyl endopeptidase inhibitors. Food Chemistry, 175, 337–343. https://doi.org/10. 1016/j.foodchem.2014.11.150. Lammi, C., Zanoni, C., Arnoldi, A., & Vistoli, G. (2016). Peptides derived from soy and lupin protein as dipeptidyl-peptidase IV inhibitors. In vitro biochemical screening and in silico molecular modeling study. Journal of Agriculture and Food Chemistry, 64(51), 9601–9606. https://doi.org/10.1021/acs.jafc.6b04041. Lin, K., Zhang, L. W., Han, X., Xin, L., Meng, Z. X., Gong, P. M., & Cheng, D. Y. (2018). Yak milk casein as potential precursor of angiotensin I-converting enzyme inhibitory peptides based on in silico proteolysis. Food Chemistry, 254, 340–347. https://doi. org/10.1016/j.foodchem.2018.02.051. Liu, R., Zhou, L., Zhang, Y., Sheng, N. J., Wang, Z. K., Wu, T. Z., ... Wu, H. (2017). Rapid identification of dipeptidyl peptidase-IV (DPP-IV) inhibitory peptides from Ruditapes philippinarum hydrolysate. Molecules, 22(10), https://doi.org/10.3390/ molecules22101714. Minkiewicz, P., Dziuba, J., Iwaniak, A., Dziuba, M., & Darewicz, M. (2008). BIOPEP database and other programs for processing bioactive peptide sequences. Journal of AOAC International, 91(4), 965–980. Moller, N. P., Scholz-Ahrens, K. E., Roos, N., & Schrezenmeir, J. (2008). Bioactive peptides and proteins from foods: Indication for health effects. European Journal of Nutrition, 47(4), 171–182. https://doi.org/10.1007/s00394-008-0710-2. Mooney, C., Haslam, N. J., Pollastri, G., & Shields, D. C. (2012). Towards the improved discovery and design of functional peptides: common features of diverse classes permit generalized prediction of bioactivity. PLoS ONE, 7(10), https://doi.org/10. 1371/journal.pone.0045012. Nongonierma, A. B., & FitzGerald, R. J. (2018). Enhancing bioactive peptide release and identification using targeted enzymatic hydrolysis of milk proteins. Analytical and Bioanalytical Chemistry, 410(15), 3407–3423. https://doi.org/10.1007/s00216-0170793-9.
Fig. 4. (continued)
5. Ethics statements file Our research did not include any human subjects and animal experiments. Declaration of Competing Interest The authors declared that there is no conflict of interest. Acknowledgements This work was supported by the National Key Research and Development Program of China (2018YFD0400301). Appendix A. Supplementary material Supplementary data to this article can be found online at https:// doi.org/10.1016/j.jff.2019.103649. References Abdelhedi, O., Nasri, R., Mora, L., Jridi, M., Toldra, F., & Nasri, M. (2018). In silico analysis and molecular docking study of angiotensin I-converting enzyme inhibitory peptides from smooth-hound viscera protein hydrolysates fractionated by
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W. Zhao, et al. Nongonierma, A. B., Dellafiora, L., Paolella, S., Galaverna, G., Cozzini, P., & FitzGerald, R. J. (2018). In Silico approaches applied to the study of peptide analogs of Ile-Pro-Ile in relation to their dipeptidyl peptidase IV inhibitory properties. Front Endocrinol (Lausanne), 9(329), https://doi.org/10.3389/fendo.2018.00329. Nongonierma, A. B., & FitzGerald, R. J. (2015). Utilisation of the isobole methodology to study dietary peptide-drug and peptide-peptide interactive effects on dipeptidyl peptidase IV (DPP-IV) inhibition. Food & Function, 6(1), 313–320. https://doi.org/10. 1039/c4fo00883a. Panjaitan, F. C. A., Gomez, H. L. R., & Chang, Y. W. (2018). In silico analysis of bioactive peptides released from giant grouper (Epinephelus lanceolatus) roe proteins identified by proteomics approach. Molecules, 23(11), https://doi.org/10.3390/ molecules23112910. Patil, P., Mandal, S., Tomar, S. K., & Anand, S. (2015). Food protein-derived bioactive peptides in management of type 2 diabetes. European Journal of Nutrition, 54(6), 863–880. https://doi.org/10.1007/s00394-015-0974-2. Rohit, A. C., Sathisha, K., & Aparna, H. S. (2012). A variant peptide of buffalo colostrum beta-lactoglobulin inhibits angiotensin I-converting enzyme activity. European Journal of Medicinal Chemistry, 53, 211–219. https://doi.org/10.1016/j.ejmech.2012. 03.057. Sayd, T., Dufour, C., Chambon, C., Buffiere, C., Remond, D., & Sante-Lhoutellier, V. (2018). Combined in vivo and in silico approaches for predicting the release of bioactive peptides from meat digestion. Food chemistry, 249, 111–118. https://doi. org/10.1016/j.foodchem.2018.01.013. Solanki, D., Hati, S., & Sakure, A. (2017). in silico and in vitro analysis of novel angiotensin I-converting enzyme (ACE) inhibitory bioactive peptides derived from fermented camel milk (Camelus dromedarius). International Journal of Peptide Research and Therapeutics, 23(4), 441–459. https://doi.org/10.1007/s10989-017-9577-5. Vercruysse, L., Smagghe, G., Matsui, T., & Van Camp, J. (2008). Purification and
identification of an angiotensin I converting enzyme (ACE) inhibitory peptide from the gastrointestinal hydrolysate of the cotton leafworm, Spodoptera littoralis. Process Biochemistry, 43(8), 900–904. Vermeirssen, V., van der Bent, A., Van Camp, J., van Amerongen, A., & Verstraete, W. (2004). A quantitative in silico analysis calculates the angiotensin I converting enzyme (ACE) inhibitory activity in pea and whey protein digests. Biochimie, 86(3), 231–239. https://doi.org/10.1016/j.biochi.2004.01.003. Wang, B., & Li, B. (2017). Effect of molecular weight on the transepithelial transport and peptidase degradation of casein-derived peptides by using Caco-2 cell model. Food Chemistry, 218, 1–8. https://doi.org/10.1016/j.foodchem.2016.08.106. Wang, X. M., Chen, H. X., Fu, X. G., Li, S. Q., & Wei, J. (2017). A novel antioxidant and ACE inhibitory peptide from rice bran protein: Biochemical characterization and molecular docking study. LWT-Food Science and Technology, 75, 93–99. https://doi. org/10.1016/j.lwt.2016.08.047. Wu, Q., Du, J., Jia, J., & Kuang, C. (2016). Production of ACE inhibitory peptides from sweet sorghum grain protein using alcalase: Hydrolysis kinetic, purification and molecular docking study. Food Chemistry, 199, 140–149. https://doi.org/10.1016/j. foodchem.2015.12.012. Yu, Z. P., Liu, B. Q., Zhao, W. Z., Yin, Y. G., Liu, J. B., & Chen, F. (2012). Primary and secondary structure of novel ACE-inhibitory peptides from egg white protein. Food Chemistry, 133(2), 315–322. https://doi.org/10.1016/j.foodchem.2012.01.032. Yu, Z. P., Wu, S. J., Zhao, W. Z., Ding, L., Shiuan, D., Chen, F., ... Liu, J. B. (2018). Identification and the molecular mechanism of a novel myosin-derived ACE inhibitory peptide. Food & Function, 9(1), 364–370. https://doi.org/10.1039/ c7fo01558e. Zhao, Y., Chen, Z. Y., Li, J. K., Xu, M. S., Shao, Y. Y., & Tu, Y. G. (2016). Formation mechanism of ovalbumin gel induced by alkali. Food Hydrocolloids, 61, 390–398.
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Novel membrane peptidase inhibitory peptides with activity against angiotensin converting enzyme and dipeptidyl peptidase IV identified from hen eggs Wenzhu Zhaoa, Dan Zhanga, Zhipeng Yua, , Long Dingb, Jingbo Liuc ⁎
a
College of Food Science and Engineering, Bohai University, Jinzhou 121013, PR China College of Food Science and Engineering, Northwest A&F University, Yangling 712100, PR China c Lab of Nutrition and Functional Food, Jilin University, Changchun 130062, PR China b
ARTICLE INFO
ABSTRACT
Keywords: Angiotensin converting enzyme inhibitory peptides Dipeptidyl peptidase IV inhibitory peptides Virtual screening Molecular docking
Angiotensin converting enzyme (ACE) and dipeptidyl peptidase IV (DPP-IV) are important membrane peptidases. The inhibition of ACE and DPP-IV enzymes has become a key therapeutic target for the treatment of hypertension and diabetes. This study was conducted to discover membrane peptidase inhibitory peptides that inhibit ACE and DPP-IV. Egg proteins were cleaved by pepsin and trypsin in silico. The potential activity, solubility, absorption, distribution, metabolism, excretion, and toxicity of the peptides were then predicted online. Finally, ACE and DPP-IV were applied as molecular docking targets for the potential peptides. After simulating gastrointestinal digestion, the IC50 values of ADF, MIR, and FGR against ACE activity were 27.75 ± 0.90 mM, 24.97 ± 0.80 mM, and 66.98 ± 1.40 μM, against DPP-IV activity were 16.83 mM, 4.86 mM, and 46.22 mM, respectively. The ACE and DPP-IV inhibitory peptides identified from hen egg proteins can be used as functional food ingredients for controlling hypertension and diabetes.
1. Introduction Bioactive peptides are inactivated amino acid sequences in food proteins, which are released and activated by enzymes during gastrointestinal digestion (Moller, Scholz-Ahrens, Roos, & Schrezenmeir, 2008). These peptides regulate biological activity and human health (Patil, Mandal, Tomar, & Anand, 2015) and exist in food sources such as soybean, eggs, and milk (Erdmann, Cheung, & Schroder, 2008). In addition, egg proteins are excellent sources of bioactive peptides (Fan, Wang, Liao, Jiang, & Wu, 2019). The potential roles of bioactive peptides rely on their ability to be absorbed into the blood circulation after entering the human body and transported to the target organ in the active form and in a sufficient amount, wherein the gastrointestinal tract (GIT) is a major absorption channel (Sayd et al., 2018). GITmembrane peptidases may alter the structures of peptides, thereby affecting their biological activity (Bleakley, Hayes, O’Shea, Gallagher, & Lafarga, 2017; Wang & Li, 2017). The human colon cell line, Caco-2, has been widely studied because it can differentiate into intestinal cell-
like cells and express characteristics of mature small intestinal cells. Eight membrane peptidases have been identified from Caco-2, i.e., dipeptidyl peptidase IV (DPP-IV), peptidyl dipeptidase A (angiotensin converting enzyme; ACE), amino peptidase N (AP-N), aminopeptidase P (AP-P), aminopeptidase W (AP-W), endopeptidase-24.11 (E-24.11), γglutamyl transpeptidase (γ-GT) and membrane dipeptidase (MDP). The activities of these membrane peptidases differ (Howell, Kenny, & Turner, 1992). ACE and DPP-IV are important membrane peptidases. Bioactive peptides with both ACE and DPP-IV inhibitory activity are more stable in vivo because they are resistant to membrane peptidase degradation and can enter the cell as active molecules. Peptides with dual ACE and DPP-IV inhibitory activities are also important functional bioactive peptides and can inhibit ACE and DPP-IV activity in vitro, thereby helping to lower blood pressure (Gangopadhyay et al., 2016) and exerting antihyperglycemic effects (Conarello et al., 2003). Isolating and purifying bioactive peptides is time-consuming and expensive; however, the process can be advanced by multistep virtual screening methods and in silico GI digestion (Vercruysse, Smagghe,
Abbreviations: ACE, angiotensin converting enzyme; DPP-IV, dipeptidyl peptidase IV; GIT, gastrointestinal tract; AP-N, amino peptidase N; AP-P, aminopeptidase P; AP-W, aminopeptidase W; E-24.11, endopeptidase-24.11; γ-GT, γ-glutamyl transpeptidase; MDP, membrane dipeptidase; HHL, hippuryl-histidyl-leucine; ADMET, absorption, distribution, metabolism, excretion, toxicity; DS, Discovery Studio ⁎ Corresponding author at: Jinzhou City, Liaoning Province, PR China. E-mail address: [email protected] (Z. Yu). https://doi.org/10.1016/j.jff.2019.103649 Received 11 April 2019; Received in revised form 15 October 2019; Accepted 21 October 2019 1756-4646/ © 2019 Elsevier Ltd. All rights reserved.
Please cite this article as: Wenzhu Zhao, et al., Journal of Functional Foods, https://doi.org/10.1016/j.jff.2019.103649
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peptide structures were drawn in Discovery Studio (DS) 2017 client software. The CDOCKER protocol of DS 2017 was used for molecular docking. The docking was conducted with coordinates x: 42.007562, y: 33.97662, and z: 45.631287 and x: 39.239388, y: −7.930548, and z: 94.02401, with a radius of 9 Å. The best pose was output based on the CDOCKER score.
Matsui, & Van Camp, 2008). Computer analysis of bioactive peptides released after food proteolysis is useful, and this technique complements experimental procedures. Many studies have confirmed the reliability of in silico screening methods, which can be considered valid alternatives to classic enzymatic methods (Fu et al., 2016). The main objective of this study was to reveal membrane peptidase inhibitory di- and tripeptides that can overcome GIT degradation and inhibit both ACE and DPP-IV activity using multistep virtual screening methods. Besides, this study also verified whether peptides with ACE and DPP-IV inhibitory activity could resist gastrointestinal degradation via in vitro simulated GIT digestion experiments. The egg protein sequences were searched from the NCBI database and hydrolyzed in silico using pepsin (pH 1.3, EC 3.4.23.1) and trypsin (EC 3.4.21.4). All di- and tripeptides were screened for activity scores. The studied peptide sequences were searched in the BIOPEP-UWM, the database of antihypertensive peptides (AHTPDB) and PepBank, and the peptides have been reported was excluded. The remaining dipeptides and tripeptides were synthesized using the solid-phase method. In addition, potent ACE and DPP-IV inhibitory peptides were docked with ACE and DPP-IV to discover ACE and DPP-IV inhibitory peptides with anti-GIT digestion properties from egg proteins.
2.4. Solid-phase peptide synthesis Hen egg protein-derived peptides, i.e., ADF, MIR, FGR, FK, and CDR, were synthesized using standard Fmoc solid-phase peptide conditions on an AAPPTEC Apex 396 peptide synthesizer as previously described (Yu et al., 2012). The molecular mass and purity of the synthetic peptides were tested via high performance liquid chromatography-electrospray ionization-quadrupole-mass spectrometer (Shimadzu CO., LTD, Beijing, China). 2.5. ACE inhibitory activity assay The ACE inhibitory activity in vitro was determined per the HPLC method of Yu et al. (2018). Thirty microliters of HHL solution and 10 μL of the peptide were added and mixed uniformly, then incubated at 37 °C for 5 min. ACE solution (20 μL) was added and mixed thoroughly. After incubating at 37 °C for 30 min, the reaction solution was obtained and analyzed via HPLC. Data were expressed as means ± SD and subjected to one-way analysis of variance (ANOVA).
2. Materials and methods 2.1. Materials and reagents ACE (protease from rabbit lungs), hippuryl-histidyl-leucine (HHL), and the DPP-IV Inhibitor Screening Kit were obtained from SigmaAldrich Co. (St. Louis, MO, USA). Trifluoroacetic acid, acetonitrile, and methanol were acquired from Fisher Scientific Co. (Waltham, MA, USA) and were chromatographic grade. All other reagents and chemicals used were analytical grade. All synthetic peptides used were supplied by Shanghai Top Peptide Biological Technology Corporation (Shanghai, China).
2.6. DPP-IV inhibition assay In vitro DPP-IV inhibition assay of the peptides isolated from eight egg proteins was performed per the manufacturer’s instructions (DPP-IV Inhibitor Screening Assay Kit, Sigma-Aldrich Co, St. Louis, MO, USA). Two solutions were required for the assay. For the enzyme control solution (uninhibited enzyme), DPP-IV assay buffer was used to substitute the sample inhibitor. First, 25 µL of DPP-IV assay buffer was added to 50 µL diluted DPP-IV enzyme buffer, mixed well using a Vortex Mixer XW-80A, and incubated at 37 °C for 10 min in the dark. Next, 25 µL of diluted DPP-IV substrate buffer was added to the sample and mixed well. The sample inhibitor differed only at the first step, in which 25 µL of peptide was added at 10 mg/mL. Fluorescence was read with excitation wavelengths of 360 nm and emission wavelengths of 460 nm using a fluorescence spectrophotometer (PerkinElmer, Waltham, Massachusetts, USA). The percentage inhibition was computed using the following equation:
2.2. In silico digestion Two representative proteases of pepsin (pH 1.3, EC 3.4.23.1) and trypsin (EC 3.4.21.4) were chosen in the present study. Pepsin and trypsin are two typical enzymes in the gastrointestinal tract and are currently industrialized. The program ExPASy PeptideCutter (http:// web.expasy.org/peptide_cutter/) (Zhao et al., 2016) was used to hydrolyze the peptide sequences released from eight proteins (ovotransferrin, myosin-10, ovomucoid, lysozyme, ovomacroglobulin, avidin, phosvitin, and ovalbumin) of hen eggs. PeptideRanker was used to predict whether the peptides were biologically active and express the theoretical biological activity as a calculated score (http://bioware.ucd. ie/~compass/biowareweb/Serverpages/peptideranker.php) (Mooney, Haslam, Pollastri, & Shields, 2012). Peptides were obtained and compared with known ACE and DPP-IV inhibitory peptides in BIOPEPUWM database (http://www.uwm.edu.pl/biochemia/index.php/en/ biopep) (Minkiewicz, Dziuba, Iwaniak, Dziuba, & Darewicz, 2008), AHTPDB (http://crdd.osdd.net/raghava/ahtpdb/pep.php) and PepBank (http://pepbank.mgh.harvard.edu/) (Solanki, Hati, & Sakure, 2017) after screening. The peptide property calculator (http://www. innovagen.com/) was used to estimate the solubility (Lafarga, O'Connor, & Hayes, 2015). Subsequently, unknown di- and tripeptides were selected, and their water solubility and absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties were predicted.
% Relative Inhibition = (Slope EC
Slope SM)/Slope EC × 100%
Slope SM = slope of the sample inhibitor Slope EC = slope of the enzyme control 3. Results and discussion 3.1. In silico GIT digestion of egg proteins The amino acid sequences of eight egg proteins were chosen from the NCBI database (Table 1). Two typical proteases, pepsin (pH 1.3, EC 3.4.23.1) and trypsin (EC 3.4.21.4), were selected for the study. ExPASy PeptideCutter was used to generate in silico peptide sequences from eight egg proteins. PeptideRanker results were ranked based on active scores. Typically, PeptideRanker training peptides above 0.5 thresholds are considered biologically active. Peptides at 0.5 or more may be biologically active. Peptides were obtained and compared with known ACE and DPP-IV inhibitory peptides in BIOPEP-UWM, AHTPDB and PepBank. Unknown di- and tripeptides were subsequently selected. Besides, water solubility influenced the degree of absorption of the bioactive peptides. The ADMET properties of human intestinal
2.3. Molecular docking The crystal structures of ACE (PDB: 1O86) and DPP-IV (PDB: 5J3J) were selected for molecular docking with peptides. Both ACE and DPPIV were prepared by removing water and adding hydrogen atoms. The 2
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In the docked complex, Glu411 (OE1), Glu384 (OE2), Lys511 (HZ1), Asp453 (OD1), and Glu376 (OE2) formed attractive charge interactions with N55, N55, O63, N1, and H4 of MIR, at distances of 4.94 Å, 4.84 Å, 1.79 Å, 4.09 Å and 1.84 Å, respectively (shown in Fig. 1b). Furthermore, one alkyl interaction between Val380 of ACE and the carbon atom (C14) of MIR (4.33 Å) was observed. Besides, His353 and His383 established two pi-alkyl interactions with MIR at 4.06 Å and 4.48 Å, respectively. MIR interacted with the amino acids Tyr523 (OH), Ala354 (O), His513 (NE2), Glu384 (OE2), Gln281 (HE21), Lys511 (HZ1), Lys511 (HZ3), Asn277 (HD22), Thr282 (HG1), and Thr282 (OG1) via eleven conventional carbon hydrogen bonds. Atoms OE2 and OE2 of Glu376 and Glu384 of ACE formed attractive charge interactions with N46 and N1 of FGR, generating lengths of 5.26 Å and 4.2 Å, respectively (Fig. 1c). Tyr523 (OH), His353 (HE1), and His513 (HE1) of ACE also formed carbon hydrogen bonds with atoms H6, O53, and O54 of FGR at 2.63 Å, 2.43 Å, and 2.62 Å, respectively. FGR formed a pi-alkyl interaction with Val518 (5.03 Å). Three salt bridges were observed in the complex; the first involved the oxygen atom OD1 of Asp377 with the hydrogen atom H48 of FGR (2.62 Å), the second involved OE2 of Glu162 with the hydrogen atom H47 of FGR (2.37 Å), and the third involved the hydrogen atom HZ1 of Lys511 with the oxygen atom O54 of FGR (1.83 Å). Additionally, six conventional carbon hydrogen bonds were involved with Glu376, Asp377, Ala354, Lys511, His353, and Tyr520 of ACE. The interaction of fosinopril with ACE was shown in Fig. 1d, the CDOCKER-ENERGY value was −61.8988 kcal/mol. Fosinopril interacted with ACE at Glu162, Asp377, Val380, Val518, Ala354, His513, Ser355, His353, Ala356, His387, Lys511, Trp279, Gln281, Tyr523, Phe457, and ZN701. Therefore, His353, His513, and Lys511 of ACE may play major roles in ACE binding and may be important screening indicators. The interaction of NTF, CDR, QGF, NAF, FK, QGL, and FYQ with ACE were shown in Fig. 2, respectively. The ACE active sites were composed of three pockets: S1 (Ala354, Glu384, and Tyr523), S2 (Gln281, His353, His513, Lys511, and Tyr520) and S1′ (Glu162) (Abdelhedi et al., 2018; Ko et al., 2017; Rohit, Sathisha, & Aparna, 2012; Wang, Chen, Fu, Li, & Wei, 2017). And the Cterminal Phe of ADF was linked to His513 and His353 forming carbonhydrogen bonds and a conventional hydrogen bond and an attractive charge interaction with Lys511. The results were confirmed using docking analysis. Besides, an ADF and Zn701 interaction was identified. The Arg residue of FGR included two conventional hydrogen bonds with Lys511 and His353 and two carbon hydrogen bonds with His353 and His513. No reaction occurred between FGR and Zn701. Analogous to FGR, the C-terminal Arg generated conventional hydrogen bonds with Lys511 and His513 and displayed an interaction between His353 and MIR. The current research suggested that the C-terminal Phe and Arg may enhance ACE inhibitory activity of peptides. Molecular docking studies showed that the formation of hydrogen bonding interactions caused the firm interaction between ACE active sites and peptides (Wu, Du, Jia, & Kuang, 2016). In this study, ADF contained Phe at the C-terminus. Furthermore,
Table 1 Proteins searched from NCBI in egg. Protein
Accession
Amino Acid Length
Ovotransferrin myosin-10 Ovomucoid Lysozyme Ovomacroglobulin Avidin Phosvitin Ovalbumin
CAA26040 NP_990805 ACJ04729 ACL81750 CAA55385 CAC34569 P67869 0705172A
705 aa 2007 aa 210 aa 147 aa 1454 aa 152 aa 215 aa 385 aa
absorption, Caco-2 permeability, and metabolic parameters were predicted using ADMET in Discovery Studio (DS) 2017. After combining GIT digestion, 10 unknown di- and tripeptides (as shown in Table 2) were selected for solubility and ADMET property prediction; the results showed that they were all nontoxic. The screening of the polypeptides throughout the process was shown in the supporting materials (Tables S1–S3). Moreover, the peptides CDR, ADF, FGR, MIR and FK showed good water solubility, while others showed poor water solubility. 3.2. Prediction of ACE inhibitory activity of the di- and tripeptides Peptides NTF, CDR, QGF, ADF, NAF, FGR, MIR, FK, QGL, and FYQ meeting the requirements of the previous GI screening were subjected to molecular docking using CDOCKER (shown in Table 2). The ACE crystal structure (PDB: 1O86) was treated as the target for screening peptides that bound tightly with ACE (Ke et al., 2017). ACE was prepared by removing water and adding hydrogen atoms. Peptides were drawn in Discovery Studio (DS) 2017 client software. Molecular docking was conducted using CDOCKER protocol in DS 2017. The best position was based on the CDOCKER score output. Fig. 1 showed that the ACE docking postures of the tripeptides, ADF, MIR and FGR. The CDOCKER-ENERGY values of tripeptides ADF, MIR and FGR were −96.527, −93.3993 and −93.3051 kcal/mol, respectively (as shown in Table 2). A lower 'CDOCKER -ENERGY' score indicates a more favorable combination. Val518 of ACE formed a pi-alkyl interaction with the ADF, generating lengths of 5.29 Å (Fig. 1a). The hydrogen atom (H28) of ADF formed a carbon hydrogen bond with OH of the residue TYR523 (2.51 Å). Moreover, His513 (HE1) and His353 (HE1) of ACE also formed carbon hydrogen bonds with atoms O24 and O22 of ADF at distances of 2.76 Å and 2.54 Å, respectively. Asp377 (OD1), Zn701 and Lys511 (HZ3) of ACE formed attractive charge interactions with ADF (N1), ADF (O45) and ADF (O22) generating lengths of 5.24 Å, 2.22 Å and 2.57 Å, respectively. Two conventional carbon hydrogen bonds were also observed in the complex, with the first involving the hydrogen atom (HZ1) of Lys511 with the oxygen atom (O21) of ADF (1.85 Å). The second was Tyr520 (HH) with the oxygen atom (O21) of ADF (2.29 Å). Salt bridges formed between ADF (H2) and Glu162 (OE2) at 1.95 Å. Additionally, a pi-donor hydrogen bond formed between ADF (H14) and His353 at 2.71 Å.
Table 2 PeptideRanker score, Docking score, predicted solubility, and ADMET properties of selected peptides using in silico hydrolysis with pepsin and trypsin. Peptide
PeptideRanker score
Docking score with ACE (-CDOCKER ENERGY)
Docking score with DPP-IV (-CDOCKER ENERGY)
Water Solubility
ADMET/Toxicity
NTF CDR QGF ADF NAF FGR MIR FK QGL FYQ
0.52 0.6 0.94 0.81 0.77 0.97 0.66 0.86 0.53 0.8
90.9827 97.4362 91.5552 96.527 91.1912 93.3051 93.3993 86.6082 88.9634 102.046
81.979 81.3713 81.061 80.2084 78.7809 78.7061 77.2295 75.3097 74.103 73.7114
POOR GOOD POOR GOOD POOR GOOD GOOD GOOD POOR POOR
Non-toxin Non-toxin Non-toxin Non-toxin Non-toxin Non-toxin Non-toxin Non-toxin Non-toxin Non-toxin
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Fig. 1. Molecular interactions of the tripeptides Ala-Asp-Phe (ADF) (a), Met-Ile-Arg (MIR) (b), Phe-Gly-Arg (FGR) (c), fosinopril (d) into the active site of ACE. In (a), green color represents conventional hydrogen bond, carbon hydrogen bond and pi-donor hydrogen bond, the orange color represents salt bridge and attractive charge, and pink color represents pi-alkyl. In (b), green color represents conventional hydrogen bond and carbon hydrogen bond, orange color represents salt bridge and attractive charge, and pink color represents alkyl and pi-alkyl. In (c), green color represents conventional hydrogen bond and carbon hydrogen bond, orange color represents salt bridge and attractive charge, pink color represents pi-alkyl. In (d), green color represents conventional hydrogen bond and carbon hydrogen bond, orange color represents pi-anion, pink color represents pi-alkyl and alkyl, gray color represents metal-acceptor. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
many studies have shown that C-terminal amino acid Phe may stabilize ACE inhibitory peptides (Wu et al., 2016). Additionally, FGR and MIR included the same amino acid Arg residues at the C-terminus. Several studies have also demonstrated that peptides have a hydrophilic Arg residue at the C-terminus, such as YR, IR (Ko et al., 2017), VSQLTR (Ji, Zhang, & Ji, 2017), IPALLKR and AQQLAAQLPAMCR (Asoodeh et al., 2014), which exert potent ACE inhibitory activity. In summary, specialized amino acids and their particular sequences likely enhanced the ACE inhibitory peptide activity. In short, peptides ADF, CDR, MIR, FGR, FK, and FYQ had lower docking scores, demonstrating that they had higher-binding affinities with ACE. ADF, CDR, MIR, FGR, and FK all interacted with the ACE active sites, Lys511 and His353. However, FYQ was not connected to the active site, His353. Therefore, ADF, CDR, MIR, FGR, and FK could be used in subsequent ACE inhibitory activity assay. The CDOCKERENERGY values of the peptides ADF, MIR, and FGR were lower than those of the positive control, fosinopril, suggesting that these peptides may have higher ACE inhibitory activity than that of fosinopril and that an in silico screening method was available.
3.3. Prediction of DPP-IV inhibitory activity of the di- and tripeptides Peptides CDR, ADF, FGR, MIR, and FK, which showed better scores in the previous docking with ACE, were used for molecular docking in the CDOCKER program (shown in Table 2). DPP-IV (PDB: 5J3J) was treated as the target to screen peptides that bound tightly with DPP-IV. Peptides were drawn in DS 2017. Molecular docking was conducted using the CDOCKER protocol in DS 2017. The best result was based on the CDOCKER score outcome. Fig. 3 showed the DPP-IV docking positions with the tripeptides ADF, MIR and FGR. The CDOCKER-ENERGY values of ADF, MIR and FGR were −80.2084, −77.2295 and −78.7061 kcal/mol, respectively (as shown in Table 2). ADF formed 3 salt bridges with amino acid residue Glu205, Glu206, and Arg125 at 2.02 Å, 1.89 Å, and 2.71 Å, respectively. Further, two carbon hydrogen bonds and one attractive charge interaction with Glu205 (OE2), Glu206 (OE1), and Arg358 (NH1) were also predicted (Fig. 3a). ADF (O21) also established conventional carbon hydrogen bond with Arg358 (HH22). Phe357 formed a pi-pi T-shaped interaction bond with ADF.
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Fig. 3b showed the optimal three-dimensional structure of MIR docking with DPP-IV. Arg125 (NH1) of DPP-IV formed an unfavorable positive-positive interaction with MIR (N55). Phe357 formed a pi-donor hydrogen bond with MIR (H40), and Arg669 (NH1) and Glu206 (OE1) of DPP-IV formed attractive charge interactions with atoms O63 and H3 of MIR, respectively. Glu205 (OE2), Glu206 (OE2) and Glu206 (OE1) of
DPP-IV formed three salt bridges with MIR. Five conventional carbon hydrogen bonds were observed in the complex; four were Tyr662, Tyr666, Trp659, and Tyr631 with C14 of MIR, and the last was Tyr666 with N1 of MIR. An unfavorable negative-negative interaction occurred between Glu205 (OE2) with MIR (O63). Additionally, a carbon hydrogen bond formed between MIR (H6) and Glu205 (OE2). In the
Fig. 2. Molecular interactions of the tripeptides Asn-Thr-Phe (NTF) (a), Cys-Asp-Arg (CDR) (b), Gln-Gly-Phe (QGF) (c), Asn-Ala-Phe (NAF) (d), Phe-Lys (FK) (e), GlnGly-Leu (QGL) (f), Phe-Tyr-Gln (FYQ) (g) into the active site of ACE. In (a), green color represents conventional hydrogen bond and carbon hydrogen bond, the orange color represents salt bridge and pi-anion, and red color represents unfavorable positive-positive. In (b), green color represents conventional hydrogen bond, pi-donor hydrogen bond and carbon hydrogen bond, orange color represents salt bridge and attractive charge, and red color represents unfavorable acceptoracceptor. In (c), green color represents conventional hydrogen bond, pi-donor hydrogen bond, and carbon hydrogen bond, orange color represents attractive charge, gray color represents metal-acceptor, and red color represents unfavorable positive-positive. In (d), green color represents conventional hydrogen bond and carbon hydrogen bond, and orange color represents salt bridge and pi-anion. In (e), green color represents conventional hydrogen bond and carbon hydrogen bond, and orange color represents attractive charge and salt bridge. In (f), green color represents conventional hydrogen bond and carbon hydrogen bond, orange color represents salt bridge, red color represents unfavorable positive-positive, and pink color represents alkyl. In (g), green color represents conventional hydrogen bond and carbon hydrogen bond, orange color represents attractive charge, pi-anion, and salt bridge, and pink color represents pi-pi T-shaped. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
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Fig. 2. (continued)
complex, His126 (NE2), Arg669 (HH12), Arg669 (HH22), Glu205 (O), and Tyr662 (OH) formed conventional hydrogen bonds with MIR. Tyr666 formed a pi-cation interaction with MIR (N1), and a pi-sulfur interaction was found between Tyr631 and MIR (S13). Val656 was involved in an alkyl interaction with C14 of MIR. Tyr662 (OH), Glu205 (O), Glu206 (OE1), Arg358 (HH22), and Tyr547 (OH) formed conventional hydrogen bonds with FGR (Fig. 3c). One carbon hydrogen bond was observed between Glu205 of DPP-IV with the hydrogen atom H6 of FGR. Tyr662 and His740 established two pi-pi stacked interactions with FGR. Next, FGR interacted with Glu205 (OE2) and Arg358 (HH12) via two salt bridges. OD2 and OE2 of the residues Asp663 and Glu206 of DPP-IV formed attractive charge interactions with N1 of FGR. FGR formed a pi-pi T-shaped interaction with Tyr666. One pi-anion interaction was observed between Phe357 and O54 of FGR. The position of saxagliptin interacting with DPP-IV was shown in Fig. 3d. The CDOCKER-ENERGY value was −37.5099 kcal/mol. Saxagliptin interacted with Tyr666, Arg125, Ser209, Glu206, Glu205 and
Phe357 of 5J3J. Therefore, the residues Glu205, Glu206, and Phe357 of DPP-IV may be involved in DPP-IV binding and may be important screening indicators. The DPP-IV structure had three active pockets: S1, S2 and S3. S1 contained Tyr547, Ser630, Tyr631, Val656, Trp659, Tyr662, Tyr666, Asn710, Val711 and His740. Glu205, Glu206, and Tyr662 constituted the S2 pocket, and Ser209, Arg358, and Phe357 constituted the S3 pocket (Kim et al., 2018). Saxagliptin interacted with the DPP-IV active sites, containing three binding pockets, forming two pi-alkyl interactions with Tyr666 of S1 and combining with Glu205 and Glu206 of S2. Two pi-alkyl interactions and a carbon hydrogen bond were found between Phe357 and Ser209 of S3 in DPP-IV. All important interactions with the critical residues (Phe357, Glu205, Glu206) were observed. The current work indicates that C-terminal Phe and Arg may influence DPPIV inhibitory activity of peptides. ADF contained the amino acid Phe of the C-terminus. Research on the C-terminal amino acid Phe, (e.g., Ala-Pro-Phe, Phe-Pro-Ile and PhePro-Phe) (Nongonierma & FitzGerald, 2018) indicated that Phe may 6
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Fig. 3. Molecular interactions of the tripeptides Ala-Asp-Phe (ADF) (a), Met-Ile-Arg (MIR) (b), Phe-Gly-Arg (FGR) (c), saxagliptin (d) into the active site of DPP-IV. In (a), green color represents conventional hydrogen bond and carbon hydrogen bond, the orange color represents salt bridge and attractive charge, and pink color represents pi-pi T-shaped. In (b), green color represents conventional hydrogen bond, pi-donor hydrogen bond and carbon hydrogen bond, orange color represents salt bridge, pi-cation, pi-sulfur, and attractive charge, red color represents unfavorable positive-positive, and pink color represents alkyl and pi-alkyl. In (c), green color represents conventional hydrogen bond and carbon hydrogen bond, orange color represents salt bridge, pi-anion, and attractive charge, pink color represents pi-pi stacked and pi-pi T-shaped. In (d), green color represents conventional hydrogen bond and carbon hydrogen bond, pink color represents pi-alkyl. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
strengthen DPP-IV inhibitory peptides. Similarly, FGR and MIR had the same Arg at the C-terminus. Several studies have been conducted on peptides with the hydrophilic residue Arg impacting potent DPP-IV inhibition, for example, Ala-Pro-Arg (Nongonierma et al., 2018), TrpArg (Nongonierma & FitzGerald, 2015), and Cys-Ala-Tyr-Gln-Trp- GlnArg-Pro-Val-Asp-Arg-Ile-Arg (Huang, Jao, Ho, & Hsu, 2012). Thus,
amino acids located at specific positions of peptides may be important for inhibiting DPP-IV. ADF, CDR, MIR, FGR, and FK had lower docking scores demonstrating that they had high-binding abilities with DPP-IV and all of them connected to Glu205 and Glu206. ADF, MIR, and FGR connected with the active sites Glu205, Glu206, and Phe357. This study aimed to
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discover peptides with excellent ACE and DPP-IV inhibition. Thus, ADF, CDR, MIR, FGR, and FK, which had high ACE and DPP-IV inhibitory activities, were used in the subsequent DPP-IV inhibitory activity assay. The CDOCKER-ENERGY values of ADF, MIR, and FGR were lower than those of the positive control saxagliptin, and thus ADF, MIR, and FGR may have higher DPP-IV inhibitory activity than that of saxagliptin. This demonstrated the feasibility of the virtual screening method.
inhibitory activity. Many studies on deriving ACE inhibitory peptides from food proteins have focused on in silico methods, for example, with pea and whey proteins (Vermeirssen, van der Bent, Van Camp, van Amerongen, & Verstraete, 2004) and milk casein (Lin et al., 2018). Some studies have also explored the potential of alternatives such as oat proteins (Bleakley et al., 2017; Cheung, Nakayama, Hsu, Samaranayaka, & Li-Chan, 2009), crude barley protein (Gangopadhyay et al., 2016), and giant grouper (Panjaitan, Gomez, & Chang, 2018). Therefore, virtual screening methods are excellent for screening ACE inhibitory peptides.
3.4. In vitro ACE inhibitory activity of promising peptides In vitro ACE inhibition was tested to verify the matching degree between the ACE inhibition predicted by the virtual screening and the actual experimental outcome. The purity and molecular masses of the synthetic peptides ADF, MIR, FGR, FK, and CDR were shown in Fig. 4, respectively. The IC50 values of the ACE inhibitory activities of ADF, MIR and FGR tested via HPLC were 27.75 ± 0.90 mM, 24.97 ± 0.80 mM, and 66.98 ± 1.40 µM, respectively. For MIR and ADF from myosin, the ACE inhibitory rate of MIR (IC50 = 24.97 ± 0.80 mM) was higher than that of ADF (IC50 = 27.75 ± 0.90 mM) and of FGR (IC50 = 66.98 ± 1.40 µM) from lysozyme. FGR had a stronger ACE inhibition than did FK (IC50 = 34.70 mM) from ovalbumin. Peptide CDR lacked ACE
3.5. In vitro DPP-IV inhibitory activity of promising peptides An in vitro DPP-IV inhibition assay was designed to test the matching between the predictive DPP-IV inhibition of the virtual screening and real experiments. The IC50 values of the DPP-IV inhibitory activity of ADF, CDR, MIR, and FGR tested via a fluorescence spectrophotometer were 16.83 mM, 24.49 mM, 4.86 mM, and 46.22 mM, respectively. DPP-IV inhibitory activities of MIR (IC50 = 4.86 mM) and ADF (IC50 = 16.83 mM) identified from myosin were higher than that of CDR (IC50 = 24.49 mM) from ovotransferrin. CDR had higher DPP-IV
Fig. 4. The purity and molecular masses of the synthetic peptides. The HPLC (a) and mass spectrometry (b) results of ADF. The HPLC (c) and mass spectrometry (d) results of MIR. The HPLC (e) and mass spectrometry (f) results of FGR. The HPLC (g) and mass spectrometry (h) results of FK. The HPLC (i) and mass spectrometry (j) results of CDR.
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Fig. 4. (continued)
inhibition than did FGR (IC50 = 46.22 mM) from lysozyme. FK screening from ovalbumin lacked DPP-IV inhibition. Peptides that inhibit DPP-IV have been obtained from numerous food protein sources via molecular docking, including milk (Nongonierma et al., 2018), Ruditapes (Liu et al., 2017), Antarctic krill (Ji et al., 2017), and soy (Lammi, Zanoni, Arnoldi, & Vistoli, 2016). Similarly, molecular docking can distinguish peptides capable of inhibiting DPP-IV from food proteins.
methods, virtual screening is more time-saving and effective. Wherefore, virtual screening was a dependable method of screening latent ACE and DPP-IV inhibitory peptides. The results showed that the IC50 values of ADF, MIR, and FGR against ACE were 27.75 ± 0.90 mM, 24.97 ± 0.80 mM, and 66.98 ± 1.40 μM, respectively, while those against DPP-IV were 16.83 mM, 4.86 mM, and 46.22 mM. Molecular docking simulation demonstrated that tripeptide activities against ACE and DPP-IV may be due to the hydrogen bond interactions. Overall, these tripeptides were useful as natural inhibitors of ACE and DPP-IV for controlling hyperglycemia and hypertension, respectively. However, docking may only provide guidance for enzyme sites. More in vivo animal experiments were needed to verify the virtual screening results.
4. Conclusions In this work, three new ACE and DPP-IV membrane peptidase inhibitory peptides, ADF, MIR, and FGR, were identified from myosin and lysozyme of hen eggs via virtual screening. Compared with traditional 9
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ultrafiltration. Food Chemistry, 239, 453–463. https://doi.org/10.1016/j.foodchem. 2017.06.112. Asoodeh, A., Haghighi, L., Chamani, J., Ansari-Ogholbeyk, M. A., Mojallal-Tabatabaei, Z., & Lagzian, M. (2014). Potential angiotensin I converting enzyme inhibitory peptides from gluten hydrolysate: Biochemical characterization and molecular docking study. Journal of Cereal Science, 60(1), 92–98. https://doi.org/10.1016/j.jcs.2014.01.019. Bleakley, S., Hayes, M., O’Shea, N., Gallagher, E., & Lafarga, T. (2017). Predicted release and analysis of novel ACE-I, renin, and DPP-IV inhibitory peptides from common oat (Avena sativa) protein hydrolysates using in silico analysis. Foods, 6(12), https://doi. org/10.3390/foods6120108. Cheung, I. W., Nakayama, S., Hsu, M. N., Samaranayaka, A. G., & Li-Chan, E. C. (2009). Angiotensin-I converting enzyme inhibitory activity of hydrolysates from oat (Avena sativa) proteins by in silico and in vitro analyses. Journal of Agriculture and Food Chemistry, 57(19), 9234–9242. https://doi.org/10.1021/jf9018245. Conarello, S. L., Li, Z. H., Ronan, J., Roy, R. S., Zhu, L., Jiang, G. Q., ... Zhang, B. B. (2003). Mice lacking dipeptidyl peptidase IV are protected against obesity and insulin resistance. Proceedings of the National Academy of Sciences of the United States of America, 100(11), 6825–6830. https://doi.org/10.1073/pnas.0631828100. Erdmann, K., Cheung, B. W. Y., & Schroder, H. (2008). The possible roles of food-derived bioactive peptides in reducing the risk of cardiovascular disease. Journal of Nutritional Biochemistry, 19(10), 643–654. https://doi.org/10.1016/j.jnutbio.2007.11.010. Fan, H., Wang, J., Liao, W., Jiang, X., & Wu, J. (2019). Identification and characterization of gastrointestinal-resistant angiotensin-converting enzyme inhibitory peptides from egg white proteins. Journal of Agriculture and Food Chemistry, 67(25), 7147–7156. https://doi.org/10.1021/acs.jafc.9b01071. Fu, Y., Young, J. F., Lokke, M. M., Lametsch, R., Aluko, R. E., & Therkildsen, M. (2016). Revalorisation of bovine collagen as a potential precursor of angiotensin 1-converting enzyme (ACE) inhibitory peptides based on in silico and in vitro protein digestions. Journal of Functional Foods, 24, 196–206. https://doi.org/10.1016/j.jff.2016.03.026. Gangopadhyay, N., Wynne, K., O'Connor, P., Gallagher, E., Brunton, N. P., Rai, D. K., & Hayes, M. (2016). In silico and in vitro analyses of the angiotensin-I converting enzyme inhibitory activity of hydrolysates generated from crude barley (Hordeum vulgare) protein concentrates. Food Chemistry, 203, 367–374. https://doi.org/10. 1016/j.foodchem.2016.02.097. Howell, S., Kenny, A. J., & Turner, A. J. (1992). A survey of membrane peptidases in two human colonic cell lines, Caco-2 and HT-29. The Biochemical Journal, 284(Pt 2), 595–601. https://doi.org/10.1042/bj2840595. Huang, S. L., Jao, C. L., Ho, K. P., & Hsu, K. C. (2012). Dipeptidyl-peptidase IV inhibitory activity of peptides derived from tuna cooking juice hydrolysates. Peptides, 35(1), 114–121. https://doi.org/10.1016/j.peptides.2012.03.006. Ji, W., Zhang, C., & Ji, H. (2017). Purification, identification and molecular mechanism of two dipeptidyl peptidase IV (DPP-IV) inhibitory peptides from Antarctic krill (Euphausia superba) protein hydrolysate. Journal of Chromatography B Analytical Technologies in the Biomedical and Life Sciences, 1064, 56–61. https://doi.org/10. 1016/j.jchromb.2017.09.001. Ke, Z., Su, Z., Zhang, X., Cao, Z., Ding, Y., Cao, L., ... Xiao, W. (2017). Discovery of a potent angiotensin converting enzyme inhibitor via virtual screening. Bioorganic & Medicinal Chemistry Letters, 27(16), 3688–3692. https://doi.org/10.1016/j.bmcl. 2017.07.016. Kim, B. R., Kim, H. Y., Choi, I., Kim, J. B., Jin, C. H., & Han, A. R. (2018). DPP-IV inhibitory potentials of flavonol glycosides isolated from the seeds of Lens culinaris. In vitro and molecular docking analyses. Molecules, 23(8), https://doi.org/10.3390/ molecules23081998. Ko, S. C., Jang, J. Y., Ye, B. R., Kim, M. S., Choi, I. W., Park, W. S., ... Jung, W. K. (2017). Purification and molecular docking study of angiotensin I-converting enzyme (ACE) inhibitory peptides from hydrolysates of marine sponge Stylotella aurantium. Process Biochemistry, 54, 180–187. https://doi.org/10.1016/j.procbio.2016.12.023. Lafarga, T., O'Connor, P., & Hayes, M. (2015). In silico methods to identify meat-derived prolyl endopeptidase inhibitors. Food Chemistry, 175, 337–343. https://doi.org/10. 1016/j.foodchem.2014.11.150. Lammi, C., Zanoni, C., Arnoldi, A., & Vistoli, G. (2016). Peptides derived from soy and lupin protein as dipeptidyl-peptidase IV inhibitors. In vitro biochemical screening and in silico molecular modeling study. Journal of Agriculture and Food Chemistry, 64(51), 9601–9606. https://doi.org/10.1021/acs.jafc.6b04041. Lin, K., Zhang, L. W., Han, X., Xin, L., Meng, Z. X., Gong, P. M., & Cheng, D. Y. (2018). Yak milk casein as potential precursor of angiotensin I-converting enzyme inhibitory peptides based on in silico proteolysis. Food Chemistry, 254, 340–347. https://doi. org/10.1016/j.foodchem.2018.02.051. Liu, R., Zhou, L., Zhang, Y., Sheng, N. J., Wang, Z. K., Wu, T. Z., ... Wu, H. (2017). Rapid identification of dipeptidyl peptidase-IV (DPP-IV) inhibitory peptides from Ruditapes philippinarum hydrolysate. Molecules, 22(10), https://doi.org/10.3390/ molecules22101714. Minkiewicz, P., Dziuba, J., Iwaniak, A., Dziuba, M., & Darewicz, M. (2008). BIOPEP database and other programs for processing bioactive peptide sequences. Journal of AOAC International, 91(4), 965–980. Moller, N. P., Scholz-Ahrens, K. E., Roos, N., & Schrezenmeir, J. (2008). Bioactive peptides and proteins from foods: Indication for health effects. European Journal of Nutrition, 47(4), 171–182. https://doi.org/10.1007/s00394-008-0710-2. Mooney, C., Haslam, N. J., Pollastri, G., & Shields, D. C. (2012). Towards the improved discovery and design of functional peptides: common features of diverse classes permit generalized prediction of bioactivity. PLoS ONE, 7(10), https://doi.org/10. 1371/journal.pone.0045012. Nongonierma, A. B., & FitzGerald, R. J. (2018). Enhancing bioactive peptide release and identification using targeted enzymatic hydrolysis of milk proteins. Analytical and Bioanalytical Chemistry, 410(15), 3407–3423. https://doi.org/10.1007/s00216-0170793-9.
Fig. 4. (continued)
5. Ethics statements file Our research did not include any human subjects and animal experiments. Declaration of Competing Interest The authors declared that there is no conflict of interest. Acknowledgements This work was supported by the National Key Research and Development Program of China (2018YFD0400301). Appendix A. Supplementary material Supplementary data to this article can be found online at https:// doi.org/10.1016/j.jff.2019.103649. References Abdelhedi, O., Nasri, R., Mora, L., Jridi, M., Toldra, F., & Nasri, M. (2018). In silico analysis and molecular docking study of angiotensin I-converting enzyme inhibitory peptides from smooth-hound viscera protein hydrolysates fractionated by
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W. Zhao, et al. Nongonierma, A. B., Dellafiora, L., Paolella, S., Galaverna, G., Cozzini, P., & FitzGerald, R. J. (2018). In Silico approaches applied to the study of peptide analogs of Ile-Pro-Ile in relation to their dipeptidyl peptidase IV inhibitory properties. Front Endocrinol (Lausanne), 9(329), https://doi.org/10.3389/fendo.2018.00329. Nongonierma, A. B., & FitzGerald, R. J. (2015). Utilisation of the isobole methodology to study dietary peptide-drug and peptide-peptide interactive effects on dipeptidyl peptidase IV (DPP-IV) inhibition. Food & Function, 6(1), 313–320. https://doi.org/10. 1039/c4fo00883a. Panjaitan, F. C. A., Gomez, H. L. R., & Chang, Y. W. (2018). In silico analysis of bioactive peptides released from giant grouper (Epinephelus lanceolatus) roe proteins identified by proteomics approach. Molecules, 23(11), https://doi.org/10.3390/ molecules23112910. Patil, P., Mandal, S., Tomar, S. K., & Anand, S. (2015). Food protein-derived bioactive peptides in management of type 2 diabetes. European Journal of Nutrition, 54(6), 863–880. https://doi.org/10.1007/s00394-015-0974-2. Rohit, A. C., Sathisha, K., & Aparna, H. S. (2012). A variant peptide of buffalo colostrum beta-lactoglobulin inhibits angiotensin I-converting enzyme activity. European Journal of Medicinal Chemistry, 53, 211–219. https://doi.org/10.1016/j.ejmech.2012. 03.057. Sayd, T., Dufour, C., Chambon, C., Buffiere, C., Remond, D., & Sante-Lhoutellier, V. (2018). Combined in vivo and in silico approaches for predicting the release of bioactive peptides from meat digestion. Food chemistry, 249, 111–118. https://doi. org/10.1016/j.foodchem.2018.01.013. Solanki, D., Hati, S., & Sakure, A. (2017). in silico and in vitro analysis of novel angiotensin I-converting enzyme (ACE) inhibitory bioactive peptides derived from fermented camel milk (Camelus dromedarius). International Journal of Peptide Research and Therapeutics, 23(4), 441–459. https://doi.org/10.1007/s10989-017-9577-5. Vercruysse, L., Smagghe, G., Matsui, T., & Van Camp, J. (2008). Purification and
identification of an angiotensin I converting enzyme (ACE) inhibitory peptide from the gastrointestinal hydrolysate of the cotton leafworm, Spodoptera littoralis. Process Biochemistry, 43(8), 900–904. Vermeirssen, V., van der Bent, A., Van Camp, J., van Amerongen, A., & Verstraete, W. (2004). A quantitative in silico analysis calculates the angiotensin I converting enzyme (ACE) inhibitory activity in pea and whey protein digests. Biochimie, 86(3), 231–239. https://doi.org/10.1016/j.biochi.2004.01.003. Wang, B., & Li, B. (2017). Effect of molecular weight on the transepithelial transport and peptidase degradation of casein-derived peptides by using Caco-2 cell model. Food Chemistry, 218, 1–8. https://doi.org/10.1016/j.foodchem.2016.08.106. Wang, X. M., Chen, H. X., Fu, X. G., Li, S. Q., & Wei, J. (2017). A novel antioxidant and ACE inhibitory peptide from rice bran protein: Biochemical characterization and molecular docking study. LWT-Food Science and Technology, 75, 93–99. https://doi. org/10.1016/j.lwt.2016.08.047. Wu, Q., Du, J., Jia, J., & Kuang, C. (2016). Production of ACE inhibitory peptides from sweet sorghum grain protein using alcalase: Hydrolysis kinetic, purification and molecular docking study. Food Chemistry, 199, 140–149. https://doi.org/10.1016/j. foodchem.2015.12.012. Yu, Z. P., Liu, B. Q., Zhao, W. Z., Yin, Y. G., Liu, J. B., & Chen, F. (2012). Primary and secondary structure of novel ACE-inhibitory peptides from egg white protein. Food Chemistry, 133(2), 315–322. https://doi.org/10.1016/j.foodchem.2012.01.032. Yu, Z. P., Wu, S. J., Zhao, W. Z., Ding, L., Shiuan, D., Chen, F., ... Liu, J. B. (2018). Identification and the molecular mechanism of a novel myosin-derived ACE inhibitory peptide. Food & Function, 9(1), 364–370. https://doi.org/10.1039/ c7fo01558e. Zhao, Y., Chen, Z. Y., Li, J. K., Xu, M. S., Shao, Y. Y., & Tu, Y. G. (2016). Formation mechanism of ovalbumin gel induced by alkali. Food Hydrocolloids, 61, 390–398.
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