茶叶多肽对血管紧张素转化酶的抑制机理

Inhibitory mechanism of angiotensin-converting enzyme inhibitory peptides from black tea 茶叶多肽对血管紧张素转化酶的抑制机理 1 first-author 1 1 1 2 1 1 corresp Xiaochang WANG, xcwang@zju.edu.cn Xiaochang WANG, xcwang@zju.edu.cn xcwang@zju.edu.cn https://orcid.org/0000-0002-9278-9867 Tea Research Institute, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou310058, China Tea Research Institute, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou310058, China Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo113-8657, Japan Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo113-8657, Japan The aim of this work is to discover the inhibitory mechanism of tea peptides and to analyse the affinities between the peptides and the angiotensin-converting enzyme (ACE) as well as the stability of the complexes using in vitro and in silico methods. Four peptide sequences identified from tea, namely peptides I, II, III, and IV, were used to examine ACE inhibition and kinetics. The half maximal inhibitory concentration (IC 50 ) values of the four peptides were (210.03±18.29), (178.91±5.18), (196.31±2.87), and (121.11±3.38) μmol/L, respectively. The results of Lineweaver-Burk plots showed that peptides I, II, and IV inhibited ACE activity in an uncompetitive manner, which requires the presence of substrate. Peptide III inhibited ACE in a non-competitive manner, for which the presence of substrate is not necessary. The docking simulations showed that the four peptides did not bind to the active sites of ACE, indicating that the four peptides are allosteric inhibitors. The binding free energies calculated from molecular dynamic (MD) simulation were -72.47, -42.20, -52.10, and -67.14 kcal/mol (1 kcal=4.186 kJ), respectively. The lower IC 50 value of peptide IV may be attributed to its stability when docking with ACE and changes in the flexibility and unfolding of ACE. These four bioactive peptides with ACE inhibitory ability can be incorporated into novel functional ingredients of black tea. 目的 2 探究红茶中分离的茶叶多肽与血管紧张素转化酶（ACE）的结合关系以及结合稳定性，从而发现红茶多肽对ACE的抑制机理。 创新点 2 ACE是哺乳动物调节血压的关键酶，越来越多的研究着力于从食物蛋白中发现天然无副作用的ACE抑制剂。计算机模拟技术具有高效、低成本、高通量等优点，本研究从体外实验和计算机模拟两个维度来分析多肽与ACE之间的相互作用，并使用了分子对接和分子动力学模拟两种计算机模拟方法，使结果更加可靠。 方法 2 用体外酶抑制实验获取茶叶多肽（红茶中分离）对ACE的半抑制浓度（IC 50 ）；用酶动力学实验探究红茶多肽对ACE的抑制类型；通过分子对接技术预测茶叶多肽在ACE蛋白中的结合位置；通过100 ns的分子动力学模拟实验评价各多肽对ACE蛋白自由度和展开度的影响以及多肽-蛋白结合物的稳定性。 结论 2 四条茶叶多肽都表现出较高的体外ACE抑制活性（IC 50 值分别为(210.03±18.29)、(178.91±5.18)、(196.31±2.87)和(121.11±3.38)µmol/L），酶动力学实验表明多肽I、II和IV对ACE的抑制类型为反竞争性抑制（即需要底物先与酶结合才能发挥作用），多肽III为非竞争性抑制（即不管底物是否与酶结合都能发挥作用）。分子对接结果显示四条多肽都对接在远离ACE活性口袋的空腔中，分子动力学模拟结果揭示多肽的ACE抑制能力与其对ACE蛋白残基自由度和蛋白展开度的影响存在相关性，多肽IV体外抑制能力最强同时对ACE蛋白的影响最大。本研究说明四条茶叶多肽是通过改变ACE蛋白结构来达到抑制作用，符合变构抑制剂的作用原理。 Black tea Angiotensin-1-converting enzyme (ACE) inhibitory peptide Kinetic study Molecular docking Molecular dynamic (MD) simulation 红茶 血管紧张素转化酶（ACE）抑制肽 动力学研究 分子对接 分子动力学模拟 1 Introduction 1 Hypertension is the leading preventable cause of premature death worldwide because of its high prevalence and resulting complications ( Mills et al., 2016 Mills et al., 2016 ). Long-term high blood pressure is normally considered a major risk factor for cardiovascular diseases (CVDs) such as atherosclerosis, coronary heart disease, stroke, and heart failure ( Daskaya-Dikmen et al., 2017 Daskaya-Dikmen et al., 2017 ). It has been indicated that treatments that lower blood pressure can significantly reduce the risk of CVDs ( Ettehad et al., 2016 Ettehad et al., 2016 ). Currently, angiotensin-converting enzyme (ACE; EC 3.4.15.1) is thought to perform a crucial function in controlling blood pressure ( Hanif et al., 2010 Hanif et al., 2010 ). ACE is a key component of the renin angiotensin system (RAS), an essential hormone system responsible for the homeostasis of blood pressure in mammals. It removes the C-terminal dipeptide from its substrate precursor peptide angiotensin I (AngI) to produce AngII, which is a potent vasoconstrictor and blocks the vasodilating properties of bradykinin, ultimately causing an increase in blood pressure ( Harrison and Acharya, 2014 Harrison and Acharya, 2014 ). The first ACE inhibitors were found from the snake venom of Bothrops jararaca ( Ferreira, 1965 Ferreira, 1965 ). Thereafter many synthetic ACE inhibitors, including captopril, enalapril, and lisinopril, were developed as effective antihypertensive drugs. However, they may cause certain adverse effects, including coughing, allergic reactions, taste disturbances, and skin rashes ( Bougatef et al., 2008 Bougatef et al., 2008 ). People suffering from prehypertension (resting blood pressures between 120 mmHg/80 mmHg and 139 mmHg/89 mmHg (1 mmHg=0.133 kPa)) usually do not accept drug treatment because of the side effects and costs. However, lifestyle change including doing more exercise and taking healthy nutrients is urgently needed ( Collier and Landram, 2012 Collier and Landram, 2012 ; Tao C et al., 2017 Tao C et al., 2017 ). Thus, there is a growing interest in discovering ACE inhibitors in natural products as alternatives or as co-adjuvant to synthetic drugs. The identification of bioactive ACE inhibitory peptides derived from food proteins has become popular in recent years because of the excellent efficacy and safety of these peptides. They are inactive within the parent protein but exert positive physiological effects on systems of the body when released ( Lafarga and Hayes, 2017 Lafarga and Hayes, 2017 ). A large number of bioactive peptides have been isolated from bacteria, fungi, plants, animals, and even human bodies ( Gu et al., 2011 Gu et al., 2011 ). The online database BIOPEP-UWM ( http://www.uwm.edu.pl/biochemia http://www.uwm.edu.pl/biochemia ) contains fundamental information about sequence databases and tools for the evaluation of proteins as the precursors of bioactive peptides. Over nine hundred bioactive peptides have been reported as ACE inhibitors in the BIOPEP database thus far. Most are from food sources, such as milk ( Li et al., 2015 Li et al., 2015 ), chicken muscle, tuna, soy, garlic, wheat, and olive seeds ( Minkiewicz et al., 2008 Minkiewicz et al., 2008 ). Several studies have also reported in vivo ACE inhibitory activity of peptides ( Escudero et al., 2013 Escudero et al., 2013 ; Majumder et al., 2015 Majumder et al., 2015 ). Therefore, ACE inhibitory peptides derived from food have received greater recognition and have been studied closely as potent natural and healthier alternatives to ACE inhibitor drugs. More recently, in order to circumvent some challenges of the classical approach and interpret the mechanisms of action of novel ACE inhibitory peptides, in silico approaches have been widely used. For example, molecular docking has been applied to study the active mechanisms by which certain food-derived peptides inhibit ACE activity ( Sornwatana et al., 2015 Sornwatana et al., 2015 ). Molecular dynamic (MD) simulation has been used to further explore the interactions between inhibitors and receptors from a metabolic perspective ( Guan et al., 2016 Guan et al., 2016 ). Tea is a traditional health beverage in China, and its antioxidant ( Satoh et al., 2005 Satoh et al., 2005 ), antidiabetic ( Wang et al., 2010 Wang et al., 2010 ; Zhang et al., 2010 Zhang et al., 2010 ), and anti-hypertensive ( Li et al., 2019 Li et al., 2019 ) functions have been confirmed. In our previous studies, black tea was examined as a source of bioactive peptides for its special manufactory process such as fermentation, and four peptides (QTDEYGNPPR, AGFAGDDAPR, IDESLR, and IQDKEGIPPDQQR) with dipeptidyl-peptidase IV (DPP-IV) inhibitory activity were purified and identified using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and liquid chromatography tandem mass spectrometer (LC-MS/MS) technologies ( Lu et al., 2019 Lu et al., 2019 ). Certain peptides have been reported that are capable of exerting multiple types of physiological activity ( Patil et al., 2015 Patil et al., 2015 ). For example, GYGGVSLPEW and LKPTPEGDLE derived from whey protein were reported as effective at inhibiting both ACE (half maximal inhibitory concentration (IC 50 )=2 μmol/L) and DPP-IV (IC 50 =42 μmol/L) ( Lacroix et al., 2016 Lacroix et al., 2016 ). Diabetes and hypertension are believed to share a common pathway and a person with diabetes is more likely to suffer high blood pressure ( Cheung and Li, 2012 Cheung and Li, 2012 ). Thus, in this study, we plan to investigate the ACE inhibitory activity of black tea peptides in vitro and to explore their inhibition patterns and mechanisms using the classic Lineweaver-Burk model as well as molecular docking/dynamic simulation. This study may provide a theoretical basis and experimental evidence for peptides in black tea as novel bioactive components and provide further evidence for black tea as a type of functional food. 2 Materials and methods 1 2.1 Materials 2 N -‍[3-‍(2-furyl)acryloyl]‍-L-phenylalanyl-glycyl-glycine (FAPGG; Lot: F7131), ACE (EC 3.4.15.1) from rabbit lung (Lot: A6778), and captopril (Lot: C8856) were purchased from Sigma-Aldrich (St. Louis, MO, USA). Black tea derived peptide sequences (QTDEYGNPPR, AGFAGDDAPR, IDESLR, and IQDKEGIPPDQQR) were synthesized by the Chinese Peptide Company (Hangzhou, China) with a purity of 96%‒97%. 2.2 Assay for ACE inhibitory activity 2 ACE inhibitory activity was measured according to the method described by Shalaby et al. (2006) Shalaby et al. (2006) with minor modifications. Briefly, 10 μL of the ACE solution (final activity of 12.5 U/L) was mixed with 40 μL of the peptide solution (final concentrations were 100 to 700 μg/mL, dissolved in ultrapure water) in the wells of a 96-well microtiter plate at room temperature. Then, 150 μL of 0.88 mmol/L FAPGG (dissolved in 50 mmol/L Tris-HCl buffer containing 0.3 mol/L NaCl, pH 7.5, preheated at 37 ℃, for 15 min) was added to each well in less than 1 min. Next, the microtiter plate was immediately transferred to the microplate reader (Synergy H1, BioTek Instruments Inc., Vermont, USA). The rate of the decrease in absorbance at 345 nm was recorded for 30 min in 1-min intervals at 37 ℃. For control groups, 40 μL of buffer (50 mmol/L Tris-HCl buffer with 0.3 mol/L NaCl, pH 7.5) was used instead of the peptide solution. ACE activity was expressed as the slope of the decrease in absorbance ( ρA ), and the inhibitory activity was calculated according to the formula: <math display="block" id="M1"><mi mathvariant="normal">A</mi><mi mathvariant="normal">C</mi><mi mathvariant="normal">E</mi><mtext> </mtext><mi mathvariant="normal">i</mi><mi mathvariant="normal">n</mi><mi mathvariant="normal">h</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">b</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">t</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">o</mi><mi mathvariant="normal">n</mi><mo>=</mo><mo stretchy="false">(</mo><mn mathvariant="normal">1</mn><mo>-</mo><mi>ρ</mi><msub><mrow><mi>A</mi></mrow><mrow><mi mathvariant="normal">i</mi><mi mathvariant="normal">n</mi><mi mathvariant="normal">h</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">b</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">t</mi><mi mathvariant="normal">o</mi><mi mathvariant="normal">r</mi></mrow></msub><mo>/</mo><mi>ρ</mi><msub><mrow><mi>A</mi></mrow><mrow><mi mathvariant="normal">c</mi><mi mathvariant="normal">o</mi><mi mathvariant="normal">n</mi><mi mathvariant="normal">t</mi><mi mathvariant="normal">r</mi><mi mathvariant="normal">o</mi><mi mathvariant="normal">l</mi></mrow></msub><mo stretchy="false">)</mo><mo>×</mo><mn mathvariant="normal">100</mn><mi mathvariant="normal">%</mi><mo>,</mo></math> http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=27610348&type= http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=27610331&type= 71.03533173 4.48733330 where ρA inhibitor and ρA control are the slopes obtained in the presence and absence of peptides, respectively. The IC 50 values of tested samples were determined by the plot of ACE inhibition (%) against lg(sample concentration). To determine the modes of ACE inhibition, the experiment was carried out with a set of concentrations of FAPGG substrate (0.88, 0.44, 0.22, and 0.11 mmol/L). V 0 is defined as the amount of FAPGG hydrolysed by ACE in 1 min at 37 ℃. The values of V 0 were measured in the absence and presence of peptide I (0.255 and 0.340 μmol/L), peptide II (0.205 and 0.307 μmol/L), peptide III (0.273 and 0.410 μmol/L), and peptide IV (0.273 and 0.410 μmol/L). The inhibition patterns of peptides were determined by Lineweaver-Burk plots. Non-competitive inhibitor, which does not necessarily need the presence of substrate, will change both the slope and the y -intercept. Uncompetitive inhibitor, which requires the presence of substrate, changes the y -intercept but not the slope. Competitive inhibitor changes the slope but not the y -intercept. 2.3 Molecular docking simulation 2 The structures of the peptides were obtained using the PEP-FOLD peptide structure prediction server ( Shen et al., 2014 Shen et al., 2014 ). The crystal structures of ACE and captopril were obtained from the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB; ACE was obtained from PDB structure 4APH and captopril was obtained from PDB structure 1UZF). The structure of FAPGG was obtained from the PubChem database. The structure removing glycyl-glycine (GG) from FAPGG was used as the structure of N -[3-(2-furyl)acryloyl]‍-L-phenylalanyl (FAP). The ACE protein was prepared by removing water molecules and co-crystal ligands. Molecular docking was performed using AutoDock Vina Version 1.1.2 ( Trott and Olson, 2010 Trott and Olson, 2010 ), A grid of 40×40×40 points in the x- , y- , and z -axis directions was built with a grid spacing of 1 Å. Docking FAPGG to ACE was performed before the docking of peptides I, II, and IV because they were uncompetitive inhibitors. The mode with the lowest affinity value was chosen as the final docking result. 2.4 Molecular dynamic simulation 2 All the complex systems were subjected to MD simulation using the Amber 17 project ( Case et al., 2005 Case et al., 2005 ). Each complex was solvated in an octahedral box full of TIP3P water molecules. Sodium ions were placed to keep the whole system neutral and at minimum energy. The leaprc.protein.ff14SB force field was used to perform the 100 ns MD simulation. The coordinate bonds between Zn (II) and its surroundings were treated by the Metal Center Parameter Builder (MCPB) method ( Yu et al., 2019 Yu et al., 2019 ). The MD simulations at 300 K were performed for 100 ns, and the MD time step was taken as 0.02 s; thus 5000 conformations were obtained in each MD simulation. 2.5 Binding free energy and ligand‒residue interaction decomposition calculation 2 After simulation, the binding free energies were calculated using the molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) approach in Amber 17. This is suitable for various molecular systems. The concepts and the practical procedures of this approach have been described in detail elsewhere ( Homeyer and Gohlke, 2012 Homeyer and Gohlke, 2012 ). A total of 100 snapshots were extracted from the 5000 MD trajectories (100 ns) equably for calculation, and the interval was 50 trajectories. The interactions between each ligand (peptide) and every residue in the ACE protein were analysed using the MM-PBSA decomposition process applied in the MM-PBSA module in Amber 17. The snapshots extracted from this procedure were the same as those in the binding free energy calculations. 2.6 Statistical analysis 2 The assays of ACE inhibitory activity were carried out with three replications and data were presented as mean±standard deviation (SD). Significant differences of ACE inhibitory activity were analysed using Ryan-Einot-Gabriel-Welsch multiple range (REGWQ) test ( P < 0.05) in Statistical Analysis System (SAS) University Edition (Institute Inc., Cary, NC, USA). 3 Results 1 3.1 ACE inhibitory activity of tea peptides 2 Four synthetic peptides identified in black tea were tested for ACE inhibitory activity at concentrations ranging from 100 to 700 μg/mL. The unit of concentration was converted to μmol/L according to the peptide molecular weights. The IC 50 values for four peptides are presented in Table 1 Table 1 . Tridecapeptide IQDKEGIPPDQQR (peptide IV) exhibited the strongest inhibitory capacity with the lowest IC 50 value of (121.11±3.38) μmol/L, compared to AGFAGDDAPR (peptide II, (178.91±5.18) μmol/L), the hexapeptide IDESLR (peptide III, (196.31±2.87) μmol/L), and decapeptide QTDEYGNPPR (peptide I, (210.03±18.29) μmol/L). The IC 50 value of captopril (positive control) was (21.78±1.10) nmol/L, which was consistent with the IC 50 range obtained by others (7–22 nmol/L) ( Shalaby et al., 2006 Shalaby et al., 2006 ). The IC 50 values are expressed as mean±standard deviation (SD), n =3. Means with the same letters (a, b, c) are not significantly different ( P > 0.05). 1 kcal=4.186 kJ. Sample Peptide sequence Molecular mass (Da) IC 50 Binding free energy (kcal/mol) Peptide I QTDEYGNPPR 1176 (210.03±18.29) a μmol/L -72.47 Peptide II AGFAGDDAPR 976 (178.91±5.18) b μmol/L -42.20 Peptide III IDESLR 731 (196.31±2.87) ab μmol/L -52.10 Peptide IV IQDKEGIPPDQQR 1523 (121.11±3.38) c μmol/L -67.14 Captopril 217 (21.78±1.10) nmol/L -24.20 3.2 Kinetics of ACE inhibition activity 2 The ACE inhibition patterns of the four peptides were evaluated by Lineweaver-Burk plots. The regression curves of different peptide concentrations were parallel for peptides I, II, and IV, exhibiting uncompetitive inhibition (Figs. 1a 1a , 1b 1b , and 1d). The regression curves of different concentrations of peptide III intersected at the 1/[ S ] axis, indicating that the inhibition was non-competitive ( Fig. 1 Fig. 1 c). 3.3 Molecular docking of tea peptides and ACE 2 The different IC 50 values and inhibition patterns among the four peptides indicated that these peptides inhibit ACE through different mechanisms. Therefore, molecular docking was performed to further investigate the interactions and to predict the preferred orientations of these four peptides when they bind to ACE. The best docking modes with the lowest affinity values are shown in Fig. 2 Fig. 2 . Peptides I, II, III, and IV were all located in a long cleft in ACE away from the active pockets. The interactions of ACE with four peptide ligands were detected and plotted using the LigPlot+ program ( Laskowski and Swindells, 2011 Laskowski and Swindells, 2011 ). The results presented in Fig. 3 Fig. 3 show that interactions including hydrogen bonds, hydrophobic forces, and van der Waals contacts can be observed. Fifteen hydrogen bonds were formed between amino acids of peptide I and residues of ACE ( Fig. 3 Fig. 3 a). Six hydrogen bonds were found between amino acids of peptide II and residues of ACE in Fig. 3 Fig. 3 b. Only two hydrogen bonds were formed between peptide III and ACE ( Fig. 3 Fig. 3 c), while peptide IV was surrounded by an extensive network of interactive residues from ACE ( Fig. 3 Fig. 3 d). The carbonyl oxygen atoms and amidogen hydrogen atoms of Gln2 IV contributed four hydrogen bonds, Ile1 IV , Pro9 IV , and Asp10 IV contributed two hydrogen bonds each. Lys4 IV and Arg13 IV were stabilized with residues Thr92 ACE and Lys118 ACE by one hydrogen bond interaction. On the other sides, captopril was docked in the cavity near the active pockets and formed hydrogen bonds with Tyr520 ACE and Gln281 ACE ( Fig. 2 Fig. 2 ). 3.4 Molecular dynamic simulation of tea peptides and ACE 2 The conformations selected from molecular docking were performed with dynamic simulation to further validate their interaction mechanisms. Total binding free energies and contributions of residues surrounding peptides were calculated by the MM-PBSA approach. The binding free energy of peptide I was the lowest (‍-‍72.47 kcal/mol, 1 kcal=4.186 kJ), followed by peptide IV (-67.14 kcal/mol) and peptide III (-52.10 kcal/mol), and the value of peptide II was the highest (-42.20 kcal/mol) ( Table 1 Table 1 ). The van der Waals (Δ E vdw ), electrostatic (Δ E ele ), polar solvation (Δ E sol ), and total (Δ E total ) contributions of the residues to the binding free energy of the ACE‒peptide complex were also calculated by the MM-PBSA method. Electrostatic interactions play an important part in the formation of hydrogen bonds; in the presence of strong electrostatic interactions, several hydrogen bonds can easily form ( Guan et al., 2016 Guan et al., 2016 ). Arg124 ACE contributes the most electrostatic energy to the peptide I–ACE complex ( Fig. 4 Fig. 4 a). Trp59 ACE and Arg124 ACE both contributed remarkable total energy to the combinations of peptide II‍–‍ACE ( Fig. 4 Fig. 4 b). Arg124 ACE , Lys368 ACE , and Arg522 ACE all contributed both electrostatic and total energies ( Fig. 4 Fig. 4 c). Trp59 ACE , Tyr62 ACE , Glu143 ACE , Trp357 ACE , and Ser516 ACE show clear total energy values in Fig. 4 Fig. 4 d. In addition, Lys118 ACE , Asp121 ACE , and Arg522 ACE make significant electrostatic contributions. The initial binding orientations of peptides may change at different phases during simulation. Thus, the numbers of hydrogen bonds between ACE and inhibitory peptides were further confirmed by the results of MD simulations ( Fig. 5 Fig. 5 ). Peptide I can form more hydrogen bonds with ACE than can the other three peptides. Over ten hydrogen bonds can be constantly observed during the entire MD process, and the maximum number of hydrogen bonds formed was 25. The number of hydrogen bonds with ACE of peptide IV was fewer than that of peptide I but more than those of peptides II and III. The probabilities and details of occurrence of hydrogen bonds are shown in Table 2 Table 2 . Peptide I can form hydrogen bonds with 19 residues of ACE. Peptide II can form hydrogen bonds with 15 residues of ACE. However, the most presence of hydrogen bonds during MD simulation between peptide II and ACE was only 45.56%. Ser355 ACE , Arg522 ACE , Asn66 ACE , Trp357 ACE , Arg124 ACE , Glu384 ACE , Lys368 ACE , Glu403 ACE , and Hie513 ACE might form hydrogen bonds with peptide III. Peptide IV has a probability of occurrence of hydrogen bonding with 14 residues of ACE, including Asn66 ACE , Asn85 ACE , Lys118 ACE , Glu123 ACE , Arg124 ACE , Tyr135 ACE , Leu139 ACE , Glu143 ACE , Ser355 ACE , Ala356 ACE , Glu403 ACE , Gly404 ACE , Ser516 ACE , and Arg522 ACE . Acceptor Donor Presence (%) Acceptor Donor Presence (%) Peptide I  Glu4 I OE2 Ala125N 7.68  Arg10 I O Arg522NH2 86.32  Arg10 I OXT Tyr523OH 7.54  Glu4 I OE1 Arg124NH2 69.46  Asp3 I O Arg124NH2 5.42  Arg10 I O Arg522NH1 68.30 Peptide II  Asn70OD1 Arg10 I NH2 64.40  Asp6 II OD2 Arg124NH2 45.56  Ser517O Tyr5 I OH 59.00  Asp7 II O Asn85ND2 40.08  Asp3 I OD2 Tyr360OH 56.28  Glu403OE2 Phe3 II N 38.82  Ser516OG Arg10 I NE 54.20  Glu403OE1 Gly2 II N 38.06  Glu143OE1 Arg10 I NH2 46.94  Asp6 II O Arg124NE 33.52  Tyr5 I O TyR62OH 46.22  Leu122O Asp6 II N 29.72  Arg10 I O Tyr523OH 44.92  Asp6 II HB3 Ala125N 27.26  Glu4 I OE1 Arg124NE 44.48  Ser516O Arg10 II NH1 23.72  Glu143OE2 Arg10 I NH2 44.38  Asp7 II OD1 Tyr62OH 21.66  Asn70OD1 Arg10 I NH1 42.02  Arg10 II O Asn66ND2 18.64  Glu4 I OE2 Thr92OG1 41.38  Arg10 II OXT Ser355OG 18.62  Asp3 I OD1 Tyr360OH 41.04  Asp6 II OD2 Asn85ND2 18.06  Arg10 I OXT Hie353NE2 40.16  Asp7 II O Arg124NH1 17.56  Ser517OG Tyr5 I OH 29.20  Arg10 II O Trp357NE1 17.06  Ser516HG Arg10 I NE 27.28  Arg10 II OXT Asn66ND2 16.64  Asn7 I OD1 Ser517OG 25.54  Asp7 II O Arg124NH2 16.42  Glu4 I OE1 Thr92OG1 25.06  Glu403OE2 Gly2 II N 14.76  Glu4 I OE2 Arg124NE 24.94  Asp6 II OD1 Arg124NH2 14.24  Leu139O Asn7 I ND2 24.00  Arg10 II OXT Trp357NE1 13.84  Arg402O Gln1 I N 22.34  Asp358OD1 Ala1 II N 13.14  Arg402O Gln1 I N 22.00  Gly2 II O Tyr360OH 13.12  Glu143OE1 Asn7 I ND2 21.64  Arg10 II O Ser355OG 12.90  Tyr5 I OH Tyr200OH 21.02  Asp6 II O Arg124N 12.88  Arg402O Gln1 I N 20.70  Ala1 II O Tyr360OH 12.78  Glu143OE2 Asn7 I ND2 19.84  Asp358OD1 Ala1 II N 12.54  Arg10 I OXT Hie513NE2 18.60  Asp358OD1 Ala1 II N 12.42  Ser516OG Asn7 I ND2 18.30  Phe3 II O Lys118NZ 11.22  Asp3 I O Trp59NE1 15.92  Phe3 II O Lys118NZ 10.04  Glu403OE1 Gln1 I N 15.02  Phe3 II O Lys118NZ 10.04  Glu403OE1 Gln1 I N 14.76  Arg402O Ala1 II N 7.34  Glu403OE1 Gln1 I N 13.34  Arg10 II OXT Lys368NZ 6.90  Asp3 I OD1 Lys118NZ 13.02  Arg402O Ala1 II N 6.80  Asp3 I OD1 Lys118NZ 10.20  Arg10 II O Asn70ND2 6.76  Asp3 I OD1 Lys118NZ 9.82  Arg10 II OXT Lys368NZ 6.48  Tyr62OH Thr2 I OG1 9.72  Arg402O Ala1 II N 6.44  Arg10 II OXT Lys368NZ 5.82  Gln2 IV O Arg124NH1 38.26  Ser516O Arg10 II NH2 5.62  Glu123OE1 Arg13 IV NH2 34.76  Arg10 II O Lys368NZ 5.06  Glu143OE1 Gln2 IV NE2 31.94 Peptide III  Glu123OE2 Arg13 IV NH2 31.10  Arg6 III O Ser355OG 98.94  Glu403OE2 Gln11 IV NE2 29.98  Glu3 III OE2 Arg522NH1 65.20  Glu143OE2 Gln2 IV NE2 29.04  Ser4 III O Asn66ND2 62.36  Asp3 IV O Arg124NH1 25.42  Arg6 III O Trp357NE1 59.90  Asp10 IV OD1 Arg522NH2 17.86  Glu3 III OE1 Arg522NH2 59.24  Glu143OE1 Ile1 IV N 17.16  Asp2 III OD2 Arg124NH2 58.94  Asp10 IV OD1 Arg522NH1 17.14  Glu384OE2 Arg6 III NH2 39.58  Glu143OE2 Ile1 IV N 15.98  Arg6 III O Lys368NZ 28.68  Glu143OE1 Ile1 IV N 15.96  Glu384OE1 Arg6 III NH2 49.50  Glu143OE1 Ile1 IV N 15.52  Asp2 III OD1 Arg124NH1 45.90  Glu403OE1 Gln11 IV NE2 15.20  Glu384OE2 Arg6 III NH1 42.26  Glu143OE2 Ile1 IV N 15.08  Glu384OE1 Arg6 III NH1 42.20  Gln11 IV O Arg522NH2 15.04  Glu403OE2 Ile1 III N 15.04  Asn66OD1 Gln2 IV NE2 14.64  Glu403OE1 Ile1 III N 14.20  Asp10 IV OD2 Ser355OG 13.94  Asp2 III OD2 Arg124NH1 9.02  Gln11 IV OE1 Gly404N 11.64  Arg6 III OXT Lys368NZ 7.02  Asp3 IV OD2 Tyr135OH 11.34  Arg6 III O Lys368NZ 28.46  Glu143OE2 Ile1 IV N 10.88  Arg6 III O Lys368NZ 22.70  Arg13 IV O Lys118NZ 9.88  Glu3 III OE1 Arg522NH1 19.96  Asp10 IV O Arg522NH2 9.68  Glu403OE1 Ile1 III N 15.08  Gln2 IV OE1 Tyr62OH 9.28  Arg6 III OXT Lys368NZ 6.94  Arg13 IV O Lys118NZ 7.88  Leu5 III O Hie513NE2 6.40  Glu123OE1 Lys4 IV NZ 7.84  Arg6 III OXT Lys368NZ 6.06  Gly6 IV O Tyr360OH 7.68  Arg6 III OXT Hie513NE2 5.78  Arg13 IV O Lys118NZ 7.60  Glu403OE1 Ile1 III N 13.70  Glu123OE2 Arg13 IV NH1 7.60  Glu403OE2 Ile1 III N 12.44  Ser516O Ile1 IV N 7.22  Glu403OE2 Ile1 III N 11.04  Ser516O Ile1 IV N 7.18  Glu3 III OE2 Arg522NH2 9.78  Arg13 IV OXT Lys118NZ 6.78  Asp2 III OD1 Arg124NH2 5.66  Ala356O Asp10 IV N 6.72 Peptide IV  Ser516O Ile1 IV N 6.68  Asp10 IV O Arg522NH1 71.60  Ser516OG Ile1 IV N 6.08  Gln2 IV O Arg124NH2 67.92  Arg13 IV OXT Lys118NZ 5.90  Gly404O Gln11 IV NE2 60.88  Arg13 IV OXT Lys118NZ 5.80  Gln11 IV O Arg522NH2 58.74  Leu139O Gln2 IV NE2 5.64  Gln2 IV OE1 Asn85ND2 47.36  Asn66OD1 Gln2 IV N 5.32 The stability of the ACE protein/peptide complexes during their binding processes was predicted using root mean square deviation (RMSD) analysis. Five thousand trajectories obtained from the 100-ns dynamic simulation were used in this analysis. The RMSD of ACE increased after inhibitors (peptides and captopril) bound to it ( Fig. 6 Fig. 6 a). However, the RMSD of ACE combined with captopril rose and fluctuated very slightly. The RMSD of ACE combined with peptide IV increased to a higher level than that with captopril but lower than those with the other three peptides. The fluctuation of RMSD of peptide IV was most stable of the four peptides when coupled to ACE ( Fig. 6 Fig. 6 b). Generally, the radius of gyration ( R g ) was used to describe the degree of unfolding of a protein to its native state ( Wang et al., 2016 Wang et al., 2016 ). The variations in R g indicated that all four peptides and the captopril were able to loosen ACE after binding. The tightness of ACE changed least after binding with peptide I. Peptide II had the strongest effect on the unfolding of ACE and peptide IV had a similar effect with captopril ( Fig. 6 Fig. 6 c). The average distance between the C-terminal carboxylic oxygen of each peptide and the zinc atom is shown in Fig. 6 Fig. 6 d. When the system of the dynamics process reached balance after 60 ns, the distance between the C-terminal carboxylic oxygen of peptide IV and the zinc atom was the longest of the four peptides followed by peptides II, III, and I in sequence. The root mean square fluctuation (RMSF) values reflect the fluctuations of individual residues; a lower RMSF value indicates greater stability ( Ning et al., 2018 Ning et al., 2018 ). Both peptides and captopril can make ACE more flexible ( Fig. 7 Fig. 7 ). After binding, in regions 40‒204, 305‍‒‍390, 465‍‒‍485, captopril does not significantly change the RMSF value of ACE, but the value is evidently increased by four peptides at different time (Figs. 2 2 and 7 7 ). 4 Discussion 1 Food-derived ACE inhibitory peptides are diverse in source, sequence length, amino acid constitution, and IC 50 values. Studies of the structure–activity relationship of ACE inhibitory peptides showed the presence of tyrosine (Y), phenylalanine (F), tryptophan (W), proline (P), lysine (K), isoleucine (I), valine (V), leucine (L), and arginine (R) in the peptides and amino acids with positive charges at the C-terminus exerting a strong influence on ACE binding ( Daskaya-Dikmen et al., 2017 Daskaya-Dikmen et al., 2017 ). Kumar et al. (2015) Kumar et al. (2015) identified 1745 antihypertensive peptides (AHTPs) from the literature and publicly available datasets and obtained random fragments from the Swiss-Prot proteins as a negative database to build a platform for predicting, screening, and designing AHTPs. They reported that residue P is highly abundant in AHTPs but amino acids such as aspartic acid (D) and serine (S) are less frequent in most AHTPs in comparison to non-AHTPs. In our study, peptides I, II, and IV all include P in their sequences, which may help to improve their inhibitory capacity. On the other hand, peptide III does not contain P but includes both D and S in its sequence, which may weaken its inhibitory potency. Using Kumar's platform ( Kumar et al., 2015 Kumar et al., 2015 ), the four peptides in our study obtained scores of 0.12, 0.24, -1.07, and 1.00, respectively. These results were consistent with their IC 50 values obtained from the in vitro experiments. Thus, amino acid composition could have an important effect on antihypertensive potency. Moreover, judging from hydrogen bond occupancies for ACE–peptide complexes during the MD process, R of the four peptides all contribute most to the formation of hydrogen bonds for the stabilization of the complex ( Table 2 Table 2 ). This indicates that R is of great importance in the inhibition of ACE. Most food-derived peptides inhibit ACE in a competitive or non-competitive manner ( Puchalska et al., 2015 Puchalska et al., 2015 ). The peptides with competitive inhibition mode usually bind with the active site of ACE via hydrogen bonds ( Chamata et al., 2020 Chamata et al., 2020 ; Zheng et al., 2020 Zheng et al., 2020 ), and even coordinate with Zn (II) of ACE ( Tao ML et al., 2017 Tao ML et al., 2017 ). ACE has three main active site pockets: S1, S2, and S1'. S1 pocket includes Ala354, Glu384, and Tyr523 residues; S2 pocket includes Gln281, His353, Lys511, His513, and Tyr520 residues; and S1' includes Glu162 residue ( Zheng et al., 2019 Zheng et al., 2019 ). The result of molecular docking of captopril (a competitive positive control) in our study showed that captopril binds to the S2 pocket and forms hydrogen bonds with Tyr520 and Gln281. Peptides with a non-competitive inhibition pattern can work with or without the substrate present. Although it has been reported that a non-competitive inhibitory peptide YLVR could bind with certain amino acids in the ACE active site through cation–pi interactions ( Liu et al., 2018 Liu et al., 2018 ), they usually cannot form hydrogen bonds with crucial amino acid residues in the active site of ACE ( Zhao et al., 2019 Zhao et al., 2019 ). As in our study, peptide III acted as a non-competitive inhibitor that does not bind the active sites of ACE. Peptides with competitive inhibition mode can have interactions with the active site pockets of ACE, but this does not mean that they certainly have better inhibitory activity. For example, ASL (IC 50 =102.15 μmol/L), AFKDETEEVPFR (IC 50 =80.20 μmol/L), and CRQNTLGHNTQTSIAQ (IC 50 =80.00 μmol/L) present competitive, non-competitive, and uncompetitive inhibition patterns, respectively. Among these three peptides, the competitive inhibitory peptide (ASL) does not show stronger inhibitory activity than the others ( Tanzadehpanah et al., 2013 Tanzadehpanah et al., 2013 ; Wu et al., 2015 Wu et al., 2015 ; Forghani et al., 2016 Forghani et al., 2016 ). Therefore, the ACE inhibitory potency of peptides in different inhibition modes cannot be directly compared. As far as we know, only a few peptides are reported to exhibit uncompetitive inhibition, in which the peptide only binds to the enzyme–substrate complex and the inhibitor does not compete with the substrate, such as CRQNTLGHNTQTSIAQ from Stichopus horrens ( Forghani et al., 2016 Forghani et al., 2016 ) and FESNFNTQATNR from lysozyme hydrolysate ( Asoodeh et al., 2012 Asoodeh et al., 2012 ). Thus, the inhibition mechanism of uncompetitive inhibitory peptides has not been clearly illustrated. In our research, interestingly, peptides I, II, and IV all showed an uncompetitive mode of inhibition. The in vitro ACE inhibitory activity of peptide IV was higher than that of peptides II and I. The RMSD value of peptide IV was the lowest, which means that the stability of peptide IV was the highest, although the hydrogen bond number between ACE and peptide I was higher than that of peptide IV during MD simulation. In addition, the RMSF of ACE was enhanced most by peptide IV. The R g of peptide IV was higher than that of peptide I, which means peptide IV could significantly change the structure of ACE. Thus, our peptides may inhibit the activity of ACE by changing its conformation. After FAPGG (the ACE substrate) binds to ACE, it is hydrolysed to FAP. Our black tea peptides are located at the exit channel of the cavity where FAP is docked ( Fig. 2 Fig. 2 ). Our peptides with uncompetitive inhibitory mode may also block the dissociation of hydrolysis product of the substrate, and finally the hydrolysis will also act as an inhibitor of ACE. The inhibitory peptides with the same inhibiton mode could be affected by the distance between the C-terminal carboxylic oxygen of peptide and the zinc atom of ACE ( Gunalan et al., 2020 Gunalan et al., 2020 ). In our study, results of MD simulation showed that the distance between peptide IV and the zinc atom of ACE is longer than those of peptides II and I. In vitro inhibitory activity is a requirement for natural peptides to be a blood pressure-lowering material, and the in vivo biostability and bioavailability of peptides must also be considered. First of all, peptides should remain stable against gastrointestinal enzymes, because oral administration is considered to be the main intake route. Peptides could be digested by internal proteases in vivo and consequently alter their ACE inhibitory activity, compared to the ACE inhibitory activity of the peptides in vitro. For example, the ACE inhibitory activity of the peptide LVLPGELAK is enhanced twofold after simulated digestion, compared to the original value as in vitro ( Dang et al., 2019 Dang et al., 2019 ). However, peptide YGGY (IC 50 =3.4 μmol/L) loses its inhibitory activity after simulated digestion ( Saito et al., 1994 Saito et al., 1994 ). Some peptides could retain their activity after gastrointestinal enzyme digestion peptides such as RGQVIYVL, ASPKPSSA, and QFLLAGR isolated from quinoa branalbumin ( Zheng et al., 2019 Zheng et al., 2019 ) and SSYYPFK isolated from naked oat globulin ( Zheng et al., 2020 Zheng et al., 2020 ). It has been mentioned that the sequence and position of the amino acids of peptides determine their ability against gastrointestinal enzymes ( Martin and Deussen, 2019 Martin and Deussen, 2019 ). Sharma et al. (2014) Sharma et al. (2014) developed a web sever "HLP" ( http://crdd.osdd.net/raghava/hlp crdd.osdd.net/raghava/hlp ) to predict the half-life of peptides in an intestine-like environment and it can be used to predict the susceptibility of peptides towards protease degradation. The results analyzed by this server showed that peptides II, III, and IV presented high stability and peptide I presented normal stability. We noticed that peptide IV may be a substrate of trypsin. However, peptides containing Lys resisting gastrointestinal digestion have been reported both in vitro and in vivo ( García-Mora et al., 2017 García-Mora et al., 2017 ; Fan et al., 2019 Fan et al., 2019 ). First, the small intestinal epithelium plays a crucial role in the absorption of nutrients and it is also a barrier against unfavourable substances in food. Second, peptides should be efficiently absorbed by the intestinal epithelium. Di- and tri-peptides are mainly transported via specific oligopeptide transporter proteins (peptide-transporters 1 (PEPT1)) of the absorptive cells ( Shimizu, 1999 Shimizu, 1999 ; Groneberg et al., 2001 Groneberg et al., 2001 ). Paracellular pathways and transcytosis can help oligopeptides, with amino acid residues ranging from three to more, to transport ( Miner-Williams et al., 2014 Miner-Williams et al., 2014 ). For example, the Caco-2 cell monolayer model is often used in simulated intestinal transport experiments in vitro. QIGLF (IC 50 =75.00 μmol/L) derived from egg white ovalbumin can be absorbed intactly through Caco-2 cell monolayers via a paracellular pathway ( Ding et al., 2014 Ding et al., 2014 ). Peptide QAGLSPVR (IC 50 =68.35 μmol/L), which has proven clear ACE inhibitory potency in vitro and on spontaneously hypertensive rats, can transport through the Caco-2 cell monolayer via the paracellular pathway ( Sun et al., 2019 Sun et al., 2019 ). However, two corn gluten-derived peptides YFCLT and GLLLPH transport across Caco-2 cell monolayers via both energy-dependent transcytosis and the paracellular pathway ( Ding et al., 2018 Ding et al., 2018 ). A long-residue peptide (YQEPALGPVRGPFPIIV) from milk can transport through the Caco‐2 cell monolayer involved in transcytosis transport ( Regazzo et al., 2010 Regazzo et al., 2010 ). So peptides in our study might be absorded via transcytosis or the paracellular pathway. 5 Conclusions 1 Food-derived multi-target peptides could be used as resources to explore the inhibition mechanisms of ACE inhibitory peptides. We examined four black tea peptides all located in a cavity away from the active site pocket of ACE. The peptides in this study were identified from black tea without any treatment of exogenous enzymes. The stability and bioavailability of black tea peptides in vivo still require further investigation. We endeavoured to find more bioactive peptides from tea in many different ways. The ACE inhibitory peptides discovered from black tea have potential for antihypertension and will contribute to a new conception of black tea consumption. References Asoodeh A , Yazdi MM , Chamani J , 2012 . Purification and characterisation of angiotensin I converting enzyme inhibitory peptides from lysozyme hydrolysates . 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Isolation of novel ACE-inhibitory peptide from naked oat globulin hydrolysates in silico approach: molecular docking, in vivo antihypertension and effects on renin and intracellular endothelin-1 . J Food Sci , 85 ( 4 ): 1328 - 1337 . https://doi.org/10.1111/1750-3841.15115 https://doi.org/10.1111/1750-3841.15115 Isolation of novel ACE-inhibitory peptide from naked oat globulin hydrolysates in silico approach: molecular docking, in vivo antihypertension and effects on renin and intracellular endothelin-1 Yating LU performed the experimental research and data analysis, and wrote and edited the manuscript. Yu WANG, Danyi HUANG, and Dongmei FAN performed the data analysis. Zhuang BIAN performed the experimental research. Peng LU reviewed and edited the manuscript. Xiaochang WANG supervised the research, and reviewed and edited the manuscript. All authors have read and approved the final manuscript and, therefore, have full access to all the data in the study and take responsibility for the integrity and security of the data. The research was supported by the National Key Research and Development Program of China (No. 2016YFD0200900) and the Science Technology Department of Zhejiang Province (No. 2016C02053-8), China. 10.1631/jzus.B2000520 1673-1581（2021）07-0575-15 2020-09-02 2021-02-21 2021-07-15 2022-05-09 2021-05-12 © Zhejiang University Press 2021 Yating LU, Yu WANG, Danyi HUANG, Zhuang BIAN, Peng LU, Dongmei FAN, and Xiaochang WANG declare that they have no conflict of interest. This article does not contain any studies with human or animal subjects performed by any of the authors. Compliance with ethics guidelines 浙江大学学报（英文版）（B辑：生物医学和生物技术） 7 22