Introduction

Pumpkin (Cucurbita moschata) seeds are one of the major oilseeds in the world, especially in China, which is one of the largest pumpkin producers. The primarily used of pumpkin seeds (almost 90%) is for edible oil extraction, producing a large quantity of by-products, which is pumpkin seed meal that contains 60–70% of protein [1]. The high protein content makes pumpkin seeds an attractive and promising source of plant proteins. However, as major components of by-products after oil extraction process, these pumpkin seed proteins are usually discarded or utilized as animal feeds.

In recent years, pumpkin seed proteins have attracted great attention not only due to its nutritional value but also its important role as a good source of bioactive peptides. Many studies have suggested that pumpkin seed protein hydrolysates exhibit various biological activities, such as antioxidant, antidiabetic, and hepatoprotective activity [2,3,4,5]. Moreover, a recent study demonstrated that the essential amino acids (EAA) composition of pumpkin seed proteins met the requirements that specified by FAO/WHO for pre-school children and adults [6]. Consequently, pumpkin seed proteins with desirable nutritionally properties can be recognized as an innovative source of bioactive peptides.

The inhibition of ACE (EC 3.4.15.1) is an effective target for the control of hypertension, which is a serious public health problem worldwide. Food proteins-derived ACE inhibitory peptides, because of their easy absorption and importantly without undesirable adverse effects, thus could serve as an alternative of commercial antihypertensive drugs for the prevention of hypertension [7]. A previous study by Vaštag et al. reported that pumpkin seed proteins hydrolyzed by alcalase (EC 3.4.21.62) were found to show higher ACE inhibitory activity than by flavourzyme and the combined use of them [2]. As a commercially protease, alcalase has been extensively used in the production of ACE inhibitory peptides from diverse food proteins [8]. Hence, it can be hypothesized that alcalase is suitable for the generation of ACE inhibitory peptides from pumpkin seed proteins. 12S globulin and 2S albumin are two major fraction of pumpkin seed proteins [9]. However, the potential of pumpkin seed proteins hydrolyzed with alcalase to release bioactive peptides has not been studied systematically. Hence, efforts are needed to explore potent ACE inhibitory peptides from pumpkin seed proteins.

The traditional method to screen novel bioactive peptides contains a complex series of steps, which makes it time consuming and low efficiency [10]. Recently, in silico approach, as a result of the development of bioinformatic tools, such as BIOPEP-UWM database, SwissADME webtool, molecular docking and molecular dynamic simulation techniques, is emerging as a cost-effective, useful and valid tool [11, 12]. In silico approach has been widely used to predict and discover novel ACE inhibitory peptides released from various food proteins, such as rice bran protein [13], milk protein [14], and quinoa protein [15]. The aim of the present study was to predict and screen novel ACE inhibitory peptides from pumpkin seed proteins using the in silico approach and further to elucidate the underlying inhibition mechanism of ACE.

Materials and methods

Materials and reagents

ACE (A6778), N-[3-(2-furyl)acryloyl]-Phe-Gly-Gly (FAPGG, F7131) and 4-(2-hydroxyethyl)-1-piperazine ethanesulfonic acid (HEPES) were purchased from Sigma-Aldrich (St. Louis, MO, USA).

Evaluation of pumpkin seed proteins as precursors of bioactive peptides

Two sequences of pumpkin seed proteins, namely 11S globulin subunit beta (P13744) and 2S albumin (Q39649) (supplementary information (SI) Table S1), were retrieved from the UniProt Knowledgebase (http://www.uniprot.org/). Their potential to be the source of bioactive peptides were evaluated using the “Profiles of potential biological activity” of BIOPEP-UWM database (http://www.uwm.edu.pl/biochemia/index.php/pl/biopep). Then the occurrence frequency of peptide fragments with a given bioactivity in a protein sequence (A) is calculated based on the following equation:

$$ A = a/N, $$
(1)

where a represents the number of fragments with a given bioactivity activity in a protein sequence, and N represents the number of amino acid resides in the protein.

In silico digestion of pumpkin seed proteins by alcalase

The “ENZYME(S) ACTION” tool in the BIOPEP-UWM database was used to hydrolyze the two pumpkin seed proteins by alcalase. The release frequency (AE) of ACE inhibitory peptides and its relative release frequency (W) are calculated according to the following equations, respectively. Subsequently, di- and tripeptides without known ACE inhibitory activities were selected for the following study:

$$ A_{{\text{E}}} = d/N, $$
(2)
$$ W = A_{{\text{E}}} /A, $$
(3)

where d represents the number of peptide fragments with a given bioactivity activity released from the select protein sequence by alcalase, and N represents the number of amino acid resides in the protein.

Molecular docking

The structure of selected peptides was drawn by Molecular Operating Environment (MOE) software and their energies were minimized. The 3D structure of ACE in complex with lisinopril (PDB ID: 1O86, 2.00 Å) was download from the Protein Data Bank (https://www.rcsb.org). All water molecules in the crystal structure were removed and then subjected to structure preparation program of MOE. The redocking of lisinopril and the docking of peptides were performed with the followed parameters: Placement: Triangle matcher; rescoring 1: London dG; Refinement: Induced fit; and rescoring 2: GBVI/WSA dG.

The prediction of ADME properties and toxicity

The online tools SwissADME (http://www.swissadme.ch/) and ToxinPred (http://crdd.osdd.net/raghava//toxinpred/) were used to predict the human gastrointestinal absorption (HIA) properties and the toxicity of these selected peptides.

Synthesis of peptide IAF

The peptide IAF (purity > 95%) was synthesized by Bankpeptide Biological Technology Co., Ltd. (Hefei, China) and was stored at − 20 °C until use.

Assay for ACE inhibitory activity

ACE inhibitory activity of IAF was determined according to the method described by Uraipong et al. [16] with modifications. Briefly, 10 μL of ACE solution (0.1 unit/mL in 80 mM HEPES) and 40 μL different concentrations of IAF were mixed in a 96-well microplate. The plate was incubated at 37 °C for 10 min and then 50 μL of 1.0 mM FAPGG was added into each well to start the reaction. The absorbance was monitored for 30 min at 340 nm. ACE inhibitory activity is calculated according to the following equation:

$$ {\text{ACE}} (\% ) = \left[ {1 - \left( {{\raise0.7ex\hbox{$R$} \!\mathord{\left/ {\vphantom {R {R_{0} }}}\right.\kern-\nulldelimiterspace} \!\lower0.7ex\hbox{${R_{0} }$}}} \right)} \right] \times 100, $$
(4)

where R and R0 are the slopes of IAF and control, respectively.

MD simulations

MD simulations were performed using Amber99SB-ILDN force field of GROMACS software package version 2019.5 [17]. Each system (ACE–IAF complex and ACE protein) was solvated in SPC216 water in a dodecahedron box, with a minimum distance of 1.0 nm among the protein surfaces and the box edges. Na+ ions were added to neutralize the system. The Particle Mesh Ewald (PME) method was used to evaluate the electrostatic interaction and the cutoff value for van der Waals interaction was set to 1.0 nm. Followed energy minimization using steepest descent method, 100 ps NVT and NPT equilibration were performed to reach the set temperature (300 K) and pressure (1 bar). 30 ns MD simulations of each system with a time step of 2 fs were performed.

Statistical analysis

Origin 8.0 and SPSS 13.0 were utilized for the data processing. Statistical significance was set at P < 0.05.

Results and discussions

Biological activity profiles of pumpkin seed proteins and ACE inhibitory peptides released after in silico proteolysis by alcalase

To evaluate the potential of pumpkin seed proteins as precursors of bioactive peptides, two predominant protein sequences including 11S globulin and 2S albumin were selected to determine the A values by BIOPEP-UWM database. As shown in SI table S2, fragments with 17 known bioactivity activities in total were found in pumpkin seed protein. The results were in agreement with some previous studies that have reported several biological activities of pumpkin seed protein hydrolysate, including antioxidant activity and ACE inhibitory activity [2, 18, 19]. Moreover, as shown in table S2, the frequency of ACE inhibitory peptides occurrence in 11S globulin (A = 0.4662) and 2S albumin (A = 0.3616) were higher than that of others except dipeptidyl peptidase IV inhibitory peptides. According to a previous study by Iwaniak et al. [20], the moderated A values in our study implied that pumpkin seed proteins could be considered as a source of various bioactive peptides, especially ACE inhibitors with a high potential. AE is one important parameter that can be used to evaluate the release frequency of the bioactive fragments with a given bioactivity from a protein by selected enzymes. As shown in Table 1, the AE value of 11S globulin was higher than that of 2S albumin, as a result of its high A value, suggesting that more ACE inhibitory peptides could be released by alcalase. According to the previous study [20], the AE and W in the study suggested that alcalase might be suitable to release ACE inhibitory peptides from pumpkin seed proteins. The results is also in agreement with the experimental study by Vaštag et al. [2].

Table 1 In silico proteolysis of pumpkin seed proteins by alcalase
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A total of 111 peptides (SI Fig. S1) in total can be released from the two protein sequences after in silico digestion with alcalase, and among which 16 peptides with known ACE inhibitory activities are listed in Table 1. ACE inhibitory peptide-derived food proteins have been extensively studied. To exert an inhibitory activity, it is necessary that peptides are absorbed, and reach the target tissue in an active form. Small molecular peptides, especially di-/tripeptides, were found to more likely to penetrate through intestinal membranes in their intact forms [21]. Thus, 47 peptides (shown in Table 2), including 20 tripeptides and 27 dipeptides, were selected for further screening study.

Table 2 Docking scores and toxicity prediction of 47 peptides
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Virtual screening for novel ACE inhibitory peptides

To screen potential ACE inhibitory peptides, 47 peptides were docked to ACE using MOE software. First, the initial ligand, lisinopril, was extracted and re-docked into ACE to validate the accuracy of the docking algorithm. The root mean square deviation (RMSD) value between the re-docked ligand and the native ligand conformation was 0.83 Å (SI Fig. S2), which is less than 2 Å, indicating that the docking parameters to be used were reliable [22]. Table 2 shows the rank of S values of the 47 peptides. Peptides with lower docking score (S value) could be considered to be more potent ACE inhibitors. Results in Table 2 revealed that the docking scores of 15 peptides (S < − 11.5), among the 47 selected peptides, were lower or comparable than the score of the origin inhibitor lisinopril (− 12.6746). Our results suggested that these peptides exhibited stronger binding affinity with ACE compared to the rest, hence, might be potential candidate for ACE inhibitors.

Many promising inhibitors fail to exhibit ACE inhibitory activities due to their unfavorable bioavailability characteristics [23]. Thus, the HIA properties of the top 15 scoring peptides were evaluated by SwissADME. According to the BOILED-Egg model (Fig. 1A), small molecules that presented in the white zone could passive absorption by the gastrointestinal tract with high likelihood, and that drawn by red circles cannot efflux by P-Glycoprotein (P-gp) [24]. Accordingly, only IAF (molecule 14 in Fig. 2A) was predicted to exhibit acceptable HIA properties, and to be not a PGP substrate (PGP-). Moreover, the bioavailability radar (Fig. 1B) shows that IAF has good physiochemical properties required for oral bioavailability [24]. Bioactive peptides with good bioavailability were presumed to exhibit high bioactivity [25]. Collectively, the above in silico results imply that IAF (structure shown in Fig. 1C) can be considered to be potential ACE inhibitors with good bioavailability. Therefore, the tripeptide IAF was selected for further study.

Fig. 1
figure 1

ADME properties of 15 peptides. A The EGG-BOILED model for selected peptides. B The bioavailability radar of IAF. The pink area represents the most favorable area for six physicochemical properties including INSATU (unsaturation), INSOLU (insolubility), FLEX (rotatable bonds), LIPO (lipophilicity), SIZE (molecular weight) and POLAR (polar surface area). C Molecular structure of IAF

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Fig. 2
figure 2

Inhibitory activity and interaction mechanism of IAF. A In vitro inhibitory activity of ACE by IAF. B 2D interactions of IAF with the residues in the active site of ACE. C Interactions between IAF and Zn2+ in the active site of ACE

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ACE inhibitory activity and mechanisms of IAF

Based on the above virtual screening results, IAF was chemically synthesized and its ACE inhibitory activity was evaluated by in vitro assay. According to the in vitro results (Fig. 2A), the IC50 value of IAF was 19.87 ± 0.50 μM. Obviously, the ACE inhibitory activity of IAF was higher than that of several previous identified, such as Ala-Phe (AF, IC50 = 165.3 μM) and Ile-Phe (IF, IC50 = 65.8 μM) from salt-free soy sauce [26], Val-Val-Leu-Tyr-Lys (VVLYK, IC50 = 533.9 μM) from oil palm kernel glutelin-2 [27], and Ala-Gly-Ser (AGS, IC50 = 527.9 μm) from cuttlefish (Sepia officinalis) muscle proteins [28]. Thus, the novel tripeptide IAF obtained in the study is one promising ACE inhibitor.

The active site of ACE consists of three major pockets: S1 (Ala354, Glu384 and Tyr523), S2′ (Gln281, Tyr520, Lys511, His513 and His353), and S1′ (Glu162) [29]. Further, molecular docking was conducted to investigate the binding mode between IAF and ACE. As shown in Fig. 2B, IAF formed hydrogen bonds with five key residues of ACE enzyme, including Tyr523, Glu384, Ala354 of S1, Glu162 of S1′ and His387. In addition, it can be seen that O2 and O3 atoms of IAF interacted with Zn ion (Zn2+) at the active site (Fig. 2B, C). The distances between the oxygen atoms and Zn ion were 1.96 and 1.97 Å, respectively. This favors their interactions with Zn ion, which play significant roles in the inhibition of ACE enzyme [30]. This indicated that IAF can effectively interact with key residues at the active site of ACE.

Stability of ACE–IAF complex

To better understand the interaction molecular mechanisms between IAF and ACE, the 30 ns MD simulation of ACE–IAF complex was carried out using Gromacs software package. ACE–IAF complex with low binding energy was selected as starting structure to perform MD simulation. In addition, MD simulation of ACE without inhibitor IAF was also performed to compare with ACE–IAF complex. RMSD is a key parameter to reflect the stability of the simulation system, and its lower value indicates higher stability [31]. As shown in Fig. 3A, RMSD values of ACE and ACE–IAF complex tends to be stable after 5 ns, floating around 0.1785 and 0.1685 nm, respectively. Both of them were less than 0.2 nm reveal that the two simulation systems achieved equilibrium [17]. It can be observed that RMSD value of ACE without IAF was higher than that of ACE–IAF complex, suggesting that ACE combined with the inhibitor was more stable than that without. Moreover, the motion trajectory of IAF was analyzed and the results is presented in Fig. 3B. Together with the RMSD value of IAF shown in Fig. 3A, the results suggested that IAF did not escape from the docking cavity of ACE during the 30 ns simulation. In addition, the radius of gyration (Rg) values, as an indicator for structural change in a protein, was calculated to evaluate structural changes of ACE. The average Rg values after 5 ns simulation are 2.3990 nm for ACE and 2.3944 nm for ACE–IAF complex, respectively (Fig. 3C). Similarly, as shown in Fig. 3D, the binding of IAF to ACE does not induce a remark change in the solvent-accessible surface area (SASA) of ACE. As depicted, the change of Rg and SASA is less than 0.2%, indicating that the overall structure of ACE remained stable during simulation.

Fig. 3
figure 3

Stability of ACE–IAF complex. The RMSD (A), Rg (C), SASA (D), and RMSF (E) values of ACE and IAF (blue line in A) during the 30 ns MD simulation. F Molecular surface of ACE in simulation. The last frame was used to calculate. B The motion trajectory of IAF (line in blue) in the binding cavity over the 30 ns MD simulation

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The root mean square fluctuation (RMSF) is an important indicator of the average fluctuations of every amino acid residue [17]. Thus, RMSF was further calculate to investigate the freedom of motion for per residue of ACE protein. Figure 3E, F displays the RMSF values of the two systems during the 30 ns simulation and the location of flexible resides (His153-Gly156, Phe293-Asp300 and Ser435-Gly438) on ACE protein. As expected, these residues belonging to loops mostly fluctuated during two simulations on the surface of ACE. The amino acid residues at the active site of ACE did not exhibit a high RMSF value. Taken together, the above results indicate that the overall conformation of ACE protein was stable over the simulation time when the peptide IAF is bound, and therefore, ACE–IAF was able to form stable conformation at the active site of ACE.

Interactions of IAF with ACE

It is well known that the non-covalent interactions between ACE and its inhibitory peptides were essential factors contributed to the inhibition of ACE. The last frame of MD was used to analysis the non-covalent interactions between IAF and ACE. As shown in Fig. 4A, B, IAF formed four hydrogen bonds with residues Ala354, Arg522, Glu162 and His513 after 30 ns simulation, which is different form the molecular docking results. It was reported that a hydrogen bond is considered to be stable when its occupancy rate is higher than 50% [32]. Therefore, the hydrogen bond occupancy of IAF and ACE were calculated to evaluate the strength and stability of hydrogen bonds. As summarized in Table 3, three hydrogen bonds were found to be remain stable during the simulation for their occupancy were higher than 50%. In consistently, it can be seen that ACE–IAF complex were mainly stabilized by 3 ∼ 5 hydrogen bonding after 5 ns simulation (Fig. 4C), indicating that continuous hydrogen bonds formed between ACE and IAF. Based on Fig. 4D, it can be implied that the interactions between IAF and His513 and Glu162 play more important roles among the three hydrogen bonds listed in Table 3 for their distances are more stable during the simulation. Meanwhile, IAF can formed hydrophobic interactions with His353, Ser355, Val518, Pro519, Tyr523, His383, Val380, Glu384, Glu411 and Gln369 (Fig. 4B). Many of these interacted amino acids has been demonstrated to be key residues in ACE active site which interact with ACE inhibitor lisinopril such as His383, Glu411, Tyr523 and Glu384 [33]. These results indicate that IAF can effectively interact with ACE at the active site through hydrogen bonds and hydrophobic interactions, which can partly explain the ACE inhibitory activity of IAF.

Fig. 4
figure 4

Interactions of IAF with ACE. A Orientation of IAF at the active site of ACE. B Hydrogen bonding interactions between IAF and ACE resides obtained from the last frame of simulation. C Hydrogen bond numbers in ACE–IAF simulation system. D Distances between atoms of IAF and key residues of ACE

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Table 3 List of hydrogen bonds observed between the IAF with ACE during the simulation
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Interactions of IAF with Zn2+ in ACE

An increasing number of studies have confirmed that the interactions between ACE inhibitors and Zn2+ exhibits significant influence on the inhibition of ACE [17, 34]. The interaction between Zn2+ in ACE and IAF is shown in Fig. 5A. As shown, the Zn2+ is surrounded by three residues, namely Glu411, Glu384 of ACE and Phe of IAF. The crucial roles of Glu411 and Glu384 for the inhibition of ACE has been reported in previous studies [35, 36]. Different with the molecular docking (Fig. 2B, C), the metal carboxylic coordination bond between O2 atom of IAF was found to be broken after 30 ns simulation. It is known that a shorter distance or closer proximity is essential for forming ligand–Zn2+ interaction [34]. Thus, the distance between the oxygen atoms, including O2 and O3 of IAF, OE1 and OE2 of Glu411, and OE2 of Glu384 and Zn2+, were further calculate. As shown in Fig. 5B–D, the average mean values of distance between four oxygen atoms and Zn2+ after 5 ns simulation were 0.3284, 0.1776, 0.1879, 0.1837 and 0.1843 nm, respectively. Except the distance between O2 atom of IAF and Zn2+, three of them were less than 0.214 nm which is the sum of radius of oxygen atom (0.14 nm) and Zn2+ (0.074 nm). Therefore, in consistent with Fig. 5A, the Zn2+ and carboxyl groups are capable of forming four metal carboxylic coordination bonds, which play important roles for the stability of ACE–IAF complex [30]. According to a previous report by Natesh et al. [37], the formation of metal carbonyl bond between Zn2+ and enalapril, a commercial antihypertensive drug, brings about the observed ACE inhibiting behavior. Moreover, it is difficult to break the chelation interactions because of the higher energy than other interaction forces [30]. Our results show that the average distance value between Zn2+ and O3 atom of IAF favors the formation of chelation interaction during the 30 ns simulation. Consequently, we can infer that its chelation with Zn2+ in the active site plays an important role in the ACE inhibition by IAF.

Fig. 5
figure 5

The intermolecular interaction mechanisms between IAF and ACE. A Binding mode between Zn2+ and IAF and ACE resides (Glu384 and Glu411). B The distance between Zn2+ and O3 of IAF with time dependence. C The distance between Zn2+ and OE1 and OE2 of Glu411 with time dependence. D The distance between Zn2+ and OE2 of Glu384 with time dependence

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Conclusions

The novel ACE inhibitory peptide IAF was successfully identified from pumpkin seed proteins in this study. IAF exhibited potent in vitro ACE inhibitory ability with an IC50 of 19.87 ± 0.50 μM. MD simulations suggest that ACE–IAF complex reached stable after 5 ns and the structure of ACE protein remain stable when the inhibitor IAF is bounded. Hydrogen bond interactions between IAF and key residues (His513 and Glu162) of ACE including, in particular, the formation of metal carboxylic coordination bond between O3 atom of IAF and Zn2+ were considered to play critical roles in the stabilization of ACE–IAF complex, which may be partly explain the considerable inhibition of ACE by IAF. Further studies including ex vivo and in vivo experiments would be necessary to investigate the efficacy of IAF for controlling blood pressure and hypertension.