Effect of some phyto-flavonoids and terpenoid on proline metabolism of Vibrio parahaemolyticus: Inhibitory mechanism and interaction with molecular docking simulation

Vietnam Journal of Science and Technology 58 (6A) (2020) 189-198 doi:10.15625/2525-2518/58/6A/15526 EFFECT OF SOME PHYTO-FLAVONOIDS AND TERPENOID ON PROLINE METABOLISM OF VIBRIO PARAHAEMOLYTICUS: INHIBITORY MECHANISM AND INTERACTION WITH MOLECULAR DOCKING SIMULATION Tran Thi Hoai Van 1, 2, 3 , Pham Thi Hong Minh 1, 3, * , Pham Quoc Long 1, 3 , Do Tien Lam 1, 3 , Ha Viet Hai 1 , Le Thi Thuy Huong 1,3 , Le Duc Anh 4 , Pham Minh Quan 1, 3, * 1 Institute of Natural Products Chemistry, Vietnam Academy of Science and Technology (VAST), 18 Hoang Quoc Viet, Cau Giay, Ha Noi, Viet Nam 2 Vietnam University of Traditional Medicine, Ministry of Health, 2 Tran Phu, Ha Noi, Viet Nam 3 Graduate University of Science and Technology, VAST, 18 Hoang Quoc Viet, Cau Giay, Ha Noi, Viet Nam 4 HUS High School for Gifted Students, Vietnam National University, 182 Luong The Vinh, Ha Noi, Viet Nam * Emails: pham-minh.quan@inpc.vn; minhhcsh@gmail.com Received: 20 September 2020; Accepted for publication: 7 January 2021 Abstract. Proline dehydrogenase (PDH) plays an important role in protein self-organization through regulating the proline accumulation. Recently, the inhibition of PDH enzyme has been attracting research interest as a novel therapy for drug development with anti-bacterial activities. Four phyto-flavonoids and terpenoids were tested for inhibiting effect against Vibrio parahaemolyticus. All studied compounds exhibited promising anti-bacterial effect in which compound 4 proved to have the highest inhibitory percentage (82.5 %). Molecular docking analysis shed light on the predictive mechanism of action of tested compounds through interacting with key residues of PDH enzyme within the active site. High correlation between dock score and experimental data (R 2 = 0.8014) suggested that this model could be used for further study in functional prediction of potential bioactive compounds. Keywords: Vibrio parahaemolyticus, proline metabolism, anti-microbial, molecular docking. Classification numbers: 1.2.1, 1.2.4. 1. INTRODUCTION Since it first appeared in 2009, acute hepatopancreatic necrosis disease (AHPND) has caused enormous losses to shrimp farms around the world. However, there is a confusion in equating the definition of early mortality syndrome (EMS) as acute hepatopancreatic necrosis Tran Thi Hoai Van, et al. 190 disease (AHPND). EMS was first named by Asian shrimp farmers in 2009 to describe early mortality syndrome in shrimp with unexplained causes, that cause high mortality in their farming ponds during the first 30-40 days of feed. It is not considered as a disease but a syndrome due to a collection of signs and symptoms that frequently appear without knowing the cause of shrimp death very quickly after feeding [1]. By mid-2011, Lightner et al. identified a new histopathological marker in some EMS shrimp that was characterized by desquamation of hepatopancreatic tubular epithelial cells, thus, it was called acute hepatopancreatic necrosis syndrome (AHPNS) [2], then in 2013, Dr. Tran Huu Loc et al. discovered strains of Vibrio parahaemolyticus that are pathogens of AHPNS [3]. The name of the disease was then changed to acute hepatopancreatic necrosis disease (AHPND). Vibrio parahaemolyticus strains contain a toxic plasmid consisting of the virulence genes pirA and B (pirAB). Recently, AHPND has been reported to be caused by other Vibrio species such as V. harveyi, V. campbellii and V. owensii, which have also been found to contain virulent plasmids similar to the pirAB of V. parahaemolyticus [4]. Phyto-flavonoids and terpenoids are widely known to play an important role in human health [5]. There have been many publications reporting their bioactivities against strains of bacteria such as Escherichia coli, Staphylococcus aureus and Vibrio parahaemolyticus [6]. Howerver, the mechanisms by which these compounds control bacterial growth are complex and lack of research. One of the most common inhibitory mechanisms is the destruction of the cytoplasmic membrane due to perforation and/or reduction of membrane fluidity [7]. Bioactive flavonoids and terpenoids cause direct or indirect damage through autolysis/weakening of the cell wall by altering membrane fluidity, thereby, releasing some intracellular components such as enzymes, proteins, ions and nucleotides. Many researches have confirmed this mechanism of action [8]. In addition to the cell membrane damage mechanism, some other flavonoids and terpenoids activities have been identified including inhibition of microbial protein or genetic material (DNA or RNA) synthesis, disturbance in bacterial energy metabolism and proline metabolism [6]. Due to the binding nature of proteins, studies of the interaction of flavonoids/terpenoids with serum albumin [9], trypsin [10], xanthine oxyase [11], a-amylase [12] and so on have been attracting increasing interest in the field of biochemistry. These interactions can provide useful information regarding the mechanism of action of bioactive compounds against biological targets at the molecular level. However, the interacting mechanism of these compounds toward proline dehydrogenase (PDH), an important protein for proline metabolism, has not received attention from scientists. PDH is an important regulating and rate-limiting enzyme in proline accumulation and metabolism, which is widely recognized to play an important role in protein self-organization [13]. The absence of proline can lead to structural protein disturbances [13]. There have been many studies proving that proline is the main regulator of many biochemical and physiological processes in microbial cells [14]. Proline supplementation may decrease the inhibitory effect of phenolic/terpenoid compounds in Listeria monocytogenes [15], Helicobacter pylori [16] and S. aureus [17]. The mechanism of action is assumed to be based on the control and modification of proline oxidation caused by PDH, a key enzyme in proline degradation [17]. Scientists have demonstrated that proline can be replaced by phyto-phenolic compounds as stimulants [17]. However, the correlation between structural properties and antibacterial activity of flavonoid and terpenoid compounds in interacting with PDH is yet to be explored and need further study to clarify. Effect of some phyto flavonoid and terpenoid on proline metabolism of 191 In this study, we tested anti-bacterial effects of Vibrio parahaemolyticus of some phyto- flavonoids and terpenoids. In addition, the mechanism of action of the compounds were analyzed using a molecular docking method between studied compounds and the PDH enzyme target. 2. MATERIALS AND METHODS 2.1. Bacteria strain Vibrio parahaemolyticus ST8T strain (isolated from diseased shrimp samples at farms in Soc Trang province), has been verified by experimental pathogenicity to confirm the ability to cause AHPND, was provided by Southern monitoring center for aquaculture environment and epidemic, Research Institute for Aquaculture No.2. 2.2. Culturing method and biochemical identification of Vibrio parahaemolyticus Vibrio parahaemolyticus strain was grown on thiosulfate citrate bile salts sucrose agar (TCBS agar) plate. One colony of V. parahaemolyticus was cultured and shaken at 280 o C for 18 h to obtain sufficient amount of bacteria for the experiment. Bacterial density was determined by optical density (OD) method at λ = 600 nm, rechecked by dilution and quantitative methods on agar plates. The number of bacteria (colony forming unit-CFU) was determined as 10 8 CFU/ml. 2.3. Anti-bacterial activity assay Anti-bacterial activity assay was conducted by diluting studied compounds directly in a liquid medium according to Boonsri et al. [18]. 0.01 g of tested compound was diluted in 1 ml absolute alcohol to obtain a solution of 10 mg/ml. Added 0.1 ml of stock solution to a test tube consist of 0.89 ml of ISB medium (ISO-SENSITESTTM Broth) plus 0.01 ml of bacterial culture solution of approximately 10 8 CFU/ml to achieve a final bacterial density in the test tube of about 10 6 CFU/ml. Test tube was incubated at 30 o C for 24 hours, then checked for bacterial growth by aspirating 0.1 ml of culture solution and then diluting 10 to 10 -5 steps, spread 0.1 ml of each of the 10 -4 and 10 -5 dilutions on three TCBS plates. Incubated at 30 °C for 24 hours, choose a dilution with a number of colonies between 30 and 300 to calculate the density of bacteria and percentage of bacterial inhibition. Control treatments consisted of one control with bacteria only and one control treated bacteria with the dilute solvent (absolute alcohol). 2.4. Protein and ligand preparation The crystal structure of proline dehydrogenase (PDB ID: 2EKG) was obtained from the Protein Data Bank database [19]. The three-dimensional structures of studied compounds were prepared using MarvinSketch 19.27.0 and PyMOL 2.2.2 (Figure 1) [20]. The energy minimization was carried out using Gabedit 2.5.0 [21]. Naucleidinal, a common PDH inhibitor, was chosen as reference inhibitor. 2.5. Molecular docking studies The molecular docking study utilizes AutoDock 4.2.6 with Lamarckian genetic algorithm (LGA) for searching the optimum dock pose together with scoring function to calculate the binding affinity. AutoDock Tools (ADT) was employed to set up and performed docking Tran Thi Hoai Van, et al. 192 calculation [22]. PHD enzyme model (PDB ID: 2EKG) was prepared for docking simulations by assigning of partial charges, solvation parameters and hydrogens to the receptor molecule. Water molecules and reference inhibitor were removed from the protein molecule to make it a free receptor. Atomic solvation parameters were assigned to the receptor using default parameters. Since ligands are not peptides, Gasteiger charge was assigned and then nonpolar hydrogens were merged. The assignment of rigid roots to the ligand was carried out automatically by the ADT software. All the AutoDock docking runs were performed in Intel ® Core TM i7-9700K CPU @ 3.60 GHz, with 32 GB DDR4 RAM. AutoDock 4.2.6 was compiled and run under Ubuntu- Linux 14.04.6 LTS operating system. The outputs from AutoDock modelling studies were analyzed using PyMOL, Discovery Studio Visualizer, LigPlus and Maestro (Schrödinger). PyMOL was used to calculate the distances of hydrogen bonds as measured between the hydrogen and its assumed binding partner. ent-1α-axetoxy-7,14α-dihydroxykaur-16-en-15-on (1) ent-18-axetoxy-7-hydroxykaur-16-en-15-on (2) ent-18α-axetoxy-7α,14-dihydroxykaur-16-en-15-on (3) quercetin-3-O-β-D-glucopyranoside (4) Naucleidinal Figure 1. Structure of studied compounds. 3. RESULTS AND DISCUSSION 3.1. Anti-bacterial activity The ability to inhibit bacteria of studied compounds were tested by diluting compounds directly into the ISB liquid medium containing 1.45 × 10 6 CFU/ml. Obtained results were presented in Table 1. Effect of some phyto flavonoid and terpenoid on proline metabolism of 193 The results showed that V. parahaemolyticus in two control treatments (only V. parahaemolyticus + ISB medium and V. parahaemolyticus + absolute alcohol + ISB medium) proliferated to a density of 1.47 ± 0.09 × 10 8 CFU/ml and 1.37 ± 0.08 × 10 8 after 24 hours, respectively. Meanwhile, V. parahaemolyticus density in the plates treated with studied compounds only increased to 10 7 CFU / ml. Table 1. Density of V. parahaemolyticus (CFU/ml) after treated for 24 hours. Sample Density (CFU/ml) V. parahaemolyticus density original (VP) 1.45 ± 0.11 x 10 6 Compound 1 + VP + ISB 7.6 ± 1.7 x 10 7 Compound 2 + VP + ISB 4.0 ± 0.6 x 10 7 Compound 3 + VP + ISB 6.8 ± 1.0 x 10 7 Compound 4 + VP + ISB 2.4 ± 1.5 x 10 7 Positive control Naucleidinal + VP + ISB 8.9 ± 0.5 x 10 7 Control VP + ISB 1.47 ± 0.09 x 10 8 Absolute alcohol + VP + ISB 1.37 ± 0.08 x 10 8 The highest density was recorded for treatment with Naucleidinal (8.9 ± 0.5 × 10 7 CFU/ml), followed by compound 1 (7.6 ± 10 7 CFU/ml). Compound 4 exhibited the most anti-bacterial activity toward V. parahaemolyticus (2.4 ± 1.5 10 7 CFU/ml). Statistical analysis results proved that the density of bacteria in two control treatments did not have a statistical difference (P> 0.05) with a significance level of 95 %, which suggest that absolute alcohol solvent does not affect the growth of V. parahaemolyticus. Meanwhile, all bacteria density after 24 hours treated with four compounds displayed a statistically difference with a significance level of 95 % compared to the positive control (P <0.05). Table 2. Inhibitory effects on V. parahaemolyticus (VP) growth after 24 h. Sample Bacterial inhibition percentage after 24h Compound 1 + VP + ISB 44.5 % Compound 2 + VP + ISB 70.8 % Compound 3 + VP + ISB 50.4 % Compound 4 + VP + ISB 82.5 % Naucleidinal + VP + ISB 35.0 % Absolute alcohol + VP + ISB Data from Table 2 show that the inhibition rate of V. parahaemolyticus in the treatment with compound 4 reached up to 82.5 %, following up by treatment with compound 2 (70.8). The inhibition percentage of bacteria obtained in the treatment with compound 3 and 1 were 50.4 % and 44.5 %, respectively. These results suggest that at concentration 0.1 %, compound 4 and 2 exhibited significant inhibition effect against the growth of V. parahaemolyticus. 3.2. Molecular docking studies Tran Thi Hoai Van, et al. 194 The simulated interaction of potential compounds in the active site of the enzyme proline dehydrogenase are presented in Table 3. According to the algorithm in Autodock 4.2.6, the compound with the more negative dock score means that the binding affinity of the compound toward the target is better. Considering the criteria mentioned above, all four compounds after the simulation showed better binding affinity at the active site of PDH than reference inhibitor, naucleidinal, in which compound 4 showed the highest binding affinity (-11.5900 kcal/mol) and compound 1 exhibited the lowest binding affinity (-9.9100 kcal/mol). Table 3. Dock score and formed interaction between studied compounds with PDH. Compound Dock score (kcal/mol) No. of Hydrogen bonds Interacting residues Compound 1 -9.9100 2 Gly64; Asp281 Compound 2 -10.8500 2 Gly64; Gln102 Compound 3 -10.3400 3 Gly64; Asp281; Arg289 Compound 4 -11.5900 8 Asp61; Leu62; Gly64; Leu98; Leu100; Gln102 ; Arg288 ; Arg289 Naucleidinal -7.8200 2 Gly64; Arg289 In addition, these initial results show a high correlation between dock score and the experimental inhibition rate with R 2 = 0.8014 (Figure 2). It suggests that this computational model could be useful in the prediction of potential compounds with inhibition activity against V. parahaemolyticus. Figure 2. The correlation between dock score and V. parahaemolyticus inhibition percentage of tested compounds. Figure 3 shows hydrogen bonds and hydrophobic bonds between enzyme PDH and potential bioactive compounds. In 2017, Ding. et al. [23] reported a list of amino acids which play an important role in the active site of PDH including Gly64, Tyr285, Arg288, Arg289 and Glu292. In this study, the known inhibitor naucleidinal formed two hydrogen bonds with Gly64 and Arg289 proving the reliable of docking method. R² = 0.8014 -13 -12 -11 -10 -9 -8 -7 -6 30 40 50 60 70 80 90 D o ck s co re ( k ca l/ m o l) Bacterial inhibition percentage (%) Effect of some phyto flavonoid and terpenoid on proline metabolism of 195 Compound 4 docked within the PDH active site with the highest docking score. Binding orientation analysis exhibited Asp61, Leu62, Gly64, Leu98, Leu100, Gln102, Arg288, Arg 289 initiating hydrogen interaction, which contribute to the strong binding affinity between compound 4 and the targeted enzyme, in addition, the interaction is further stabilized through hydrophobic interaction with Asp61, Leu62, Leu63, Phe76, Lys99, Gln102. Compound 2 formed two hydrogen bonds with Gly64 and Gln102 meanwhile Asp61, Leu62, Leu63, Ph76, Asp281, Pro284, Tyr285 and Arg 288 were the key residues involved in hydrophobic interaction. The binding site analysis of compound 3 revealed that Gly64, Asp281 and Arg289 were the key residues involved in hydrogen bond formation and an array of hydrophobic interactions was observed as contributed by Leu63, Met66, Lys99, Gln102, Tyr285 and Arg288. Key PDH residues involved in stabilizing compound 1 through weak interactions were Gly64 and Asp281 for H-bonds and Leu63, Lys99, Gln102, Tyr285, Arg288 for hydrophobic interactions. B) A) Tran Thi Hoai Van, et al. 196 Figure 3. 2D docking pose of studied compounds with PHD enzyme model (PDB ID: 2EKG). (A) Compound 1; (B) Compound 2; (C) Compound 3; (D) Compound 4; (E) Naucleidinal; Hydrogen bond - green dashed brick; Hydrophobic bond - dashed red. 4. CONCLUSIONS In this study, four phyto-flavonoids and terpenoids were screened for antibacteria activity and analyzed for proline metabolism effect using molecular docking method. The inhibitory effect of studied compounds against V. parahaemolyticus were 82.5 %, 70.8 %, 50.4 % and 44.5 % for compound 4, 2, 3 and 1, respectively. The high correlation between dock score and C) D) E) Effect of some phyto flavonoid and terpenoid on proline metabolism of 197 experimental inhibition data proved the reliability of the simulation tool in predicting potential bioactive compounds. In general, all four compounds form interaction with key residues within the active site of PDH enzyme, suggesting a reasonable explanation for their mechanism of antibacterial activity. Acknowledgement: This research is funded in part by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 108.06-2017.18 and Research projects granted by Ministry of Agriculture & Rural Development (Code: 04/HĐ-KHCN). Author contribution statement:All authors contributed equally to this work. 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