Phytochemical profile, antimicrobial, and anti-quorum sensing properties of fruit stalks of Prunus avium L

E. Onem¨ 1 , H.C. Sarısu2 , A.G. Ozaydın¨ 3 , M.T. Muhammed1 and A. Ak4

Abstract

The aim of this study is to investigate the phytochemical contents and antibacterial properties of 2-year Prunus avium L. standard cultivars [Cristalina (Cr), 0900 Ziraat (Zr)] and to elucidate the mechanism of action of the extracts on the quorum sensing (QS) system by using homology modelling and molecular docking. Phenolic contents of methanol extract of Cr and Zr stalks were detected by HPLC. As a result, catechin hydrate (636467–812793 µg g−1) and chlorogenic acid (99881–12734 µg g−1) were found to be the highest in stalk extracts in the two varieties in 2017. All extracts had inhibitory effect on Gram-positive bacteria. Stalk extract of Zr showed higher inhibition rate (86%) on swarming motility. Stalk samples of Zr collected in 2017 and 2018 also reduced biofilm formation by 75 and 73%, respectively. The computational analysis revealed that one of the major component of the extracts, chlorogenic acid, was able to bind to the QS system receptors, LasR, RhlR, and PqsR. Therefore, the mechanism of decreasing the production of virulence factors by the extracts might be through inhibiting these receptors and thus interfering with the QS system.

Significance and Impact of the Study: Increasing antibiotic resistance has created the necessity to develop effective new strategies to combat bacteria. The findings showed that extracts from stalks of Prunus avium L., which are considered as waste materials, may be used as new antibacterial agent and these extracts may be utilized as quorum sensing inhibitors.

Keywords
bioactive compounds, biofilm, molecular modelling, stalk, swarming, sweet cherry extract.

Introduction

Resistance to antimicrobial drugs is one of the most important problems encountered to public health in the 21st century (Malik and Bhattacharyya 2019). Infections caused by biofilms are conditions that increase mortality and morbidity in patients with weak immune systems. As a matter of fact, while new antibiotic discoveries have been slowing down in recent years, multiple antibiotic resistance microorganisms have emerged and antibiotics have begun to lose their efficacy to a great extent (Akis¸ogˇlu et al. 2019). Therefore, it has become necessary to employ new strategies against bacteria. In addition to researches to develop new antibiotics, studies on the promising even better than discovering new antibiotics. The communication system used in many bacteria is known as quorum sensing (QS). Targeting this system is an effective way in controlling bacteria biomass, biofilm formation, movement, and expression of virulence genes (Gonzalez and Keshavan 2006). The basis of this commu-´ nication between bacteria is based on the ability of bacteria to synthesize signal molecules in their environment, to detect the density of these syntheses, and consequently the expression of specific genes (Lerat and Moran 2004). Many studies have shown that biofilm formation is under the control of the QS system. Furthermore, bacteria in biofilm are less sensitive to antibiotics than planktonic bacteria. In addition, they are resistant to heavy metals, salinity, acidity, and phagocytosis (Lebeaux et al. 2014; Meesilp and Mesil 2019). Studies have shown that antibiotic resistance can be overcome by blocking their signals (Hong et al. 2012; Jiang et al. 2019). Many studies focused on the suppression of the system with special emphasis on phytochemicals.
The origin of sweet cherry (Prunus avium L.) is the Southern Caucasus, the Caspian Sea, and the NorthEastern Anatolia. This species has spread from these areas to the rest of the world and covers a wide area in the world (Webster and Looney 1996). As with many herbal products, cherries also have an impact on human nutrition and health. Since the early 1900s, hundreds of cherry varieties have been cultivated by breeding studies (Kappel 2005). In the recent years, it is known that cherry stalk (Stipites cerasorum) has been used as a decoction or infusion in the treatment of cough, cold, abdominal and stomach aches, digestive, and kidney problems in several countries. In addition, it has been noted that it has a diuretic activity for kidney inflammation and kidney stones as an herbal drug and it is preferred by boiling (Kendir and Koro¨ glu 2019).˘
In this study, the antibacterial effects of stalk extracts of two cherry species on some Gram-positive and Gramnegative bacteria and their potential as inhibitors of QS against PA01 were investigated. In addition, phenolic content was determined by HPLC analysis. Moreover, molecular modelling analysis was performed to elucidate the possible interactions of the major component with LasR, RhlR, and PqsR receptor protein of Pseudomonas aeruginosa PA01.

Results and Discussion

Biochemical compound of plant extracts

The phenolic compounds of methanol extracts of Cr and Zr stalk collected in 2017 and 2018 are shown in Table 1. Chlorogenic acid, caffeic acid, epicatechin and rutin were detected in all samples for 2 years. Other components varied depending on varieties and years. Biochemical contents, phenolic components, organic acid, and/or sugar contents of cherry fruit have been investigated in previous studies (Prvulovic et al. 2011; Martini et al. 2017; Afonso et al. 2020). However, there are very few studies about phenolic components of cherry stalks, which are considered as waste materials. Phenolic content of Zr fruits was studied and amounts of catechin, epicatechin, and chlorogenic acid were found to be 292, 995, and 433 µg g−1, respectively (Kelebek and Selli 2011). In another study, 64 phenolic compounds were examined in the fruits of five different cherry varieties and epicatechin was high in all the varieties (Martini et al. 2017). It is also reported that plants grown in different climates and in different geographies also differ in terms of their phenolic content such as hydroxycinnamic derivatives primarily neochlorogenic, caffeoylquinic, p-coumaroylquinic, and chlorogenic acids (Blando and Oomah 2019). In our study, epicatechin and chlorogenic acid were detected to be the major components in the fruit stalks. In a study conducted with cherry leaf, extracts prepared by using different solvents may have different phenolic matter and it was found that the extract prepared with methanol had the highest value as total phenolic matter (Kutlu et al. 2014).

Antibacterial activity

Antibacterial effects of the extracts used in the study were determined primarily by measuring zone diameters using agar well diffusion method. For this purpose, five Grampositive and four Gram-negative bacteria were used. As a result, antibacterial effect was observed on Gram-positive bacteria and no effect was observed on Gram-negative bacteria. As seen in Table 2, fruit stalk extracts showed a high inhibition effect on bacterial growth except for the extracts of Cr collected for 2 years on Enterococcus faecalis. Extracts showed significant antimicrobial activity with different MIC values. The MIC values of the extracts ranged from 75 to 270 µg ml−1. Cr and Zr stalk extracts (2017) showed very strong activity against Bacillus cereus with the lowest MIC value of 27 and 10 µg ml−1, respectively.
Bactericidal effects of plants on bacteria are known to occur through many mechanisms of action due to the flavonoids, either by inhibiting nucleic acid biosynthesis or by different molecular processes (Cushnie and Lamb 2005; Baba and Malik 2015; Slobodn´ıkova´ et al. 2016). Phenolic compounds generally show antimicrobial effects at the membrane level. For example, phenol modifies cell membrane functions by influencing protein fat content, and promoting the outflow of potassium ions. Catechins and epigallocatechin gallate also affect the lipid layer, by causing the disintegration of the membrane and causing cell deterioration resulting in death (Hashimoto et al. 1999; Yucel and Yucel 2015). In this study, high amount of catechin hydrate (383322–812793 µg g−1) was detected in methanol extracts of stalk of two cherry species for 2 years and chlorogenic acid, caffeic acid, epicatechin were the other major components detected in stalk extracts (Table 1). Previous studies have shown that chlorogenic acid, caffeic acid, and epicatechin have antibacterial properties (Masika et al. 2004; Kabir et al. 2014). Similarly, it was found that methanol extracts prepared with stalk of both cherry varieties had more antibacterial effect on Gram-positive bacteria and this dif- was observed that catechin hydrate had antibacterial effect ference was thought to be from catechin hydrate which is on Gram-positive bacteria, and showed a synergistic effect seen in high rate of stalk extract. In a previous study, it with antibiotics such as erythromycin and clindamycin, and decreased MIC significantly (Miklasinska´ et al. 2016). In another study, quercetin and chlorogenic acid have antibacterial effect on mutant Escherichia coli CM 851, which does not have DNA repair mechanism, while they have no effects on E. coli 50 with DNA repair mechanism. Thus, it was determined that these substances showed antibacterial effect by causing DNA damage (PuupponenPimia¨ et al. 2001).
In this study, although the amount of chlorogenic acid was high in the stalk extracts, the antibacterial effect was not observed on the tested Gram-negative bacteria. This can be explained by the fact that the isolated plant contents are pure and the amounts are different. In the recent years, in addition to the antibacterial properties, anti-quorum sensing properties of plants have been the focus of studies, particularly on resistant bacteria.

Anti-swarming, anti-biofilm activity of stalk extracts

The data obtained with the anti-quorum sensing properties of the extracts are important since no similar study was found in the literature review. Therefore, the inhibition effect of cherry extracts on PA01 QS especially biofilm formation and swarming, detected in this study, would fill this gap.Swarming motility is one of the effective virulence factors in early biofilm formation (Ugurlu et al. 2016; Donmez and¨ Onem 2018). Swarming bacteria act in mul-¨ ticellular groups and are mostly multidrug resistant (Butler et al. 2010).
Previous studies showed that some phenolic acids like gallic, ferulic and ellagic acids had the potential to inhibit swarming motility (Lister et al. 2009; John et al. 2017). Although there were no gallic acid and ferulic acid in the cherry stalks we studied, high inhibition was observed. We can conclude that total phenolic compounds may be effective in the inhibition of swarming and/or other phenolic compounds may also be effective. In this study, both varieties showed significant inhibition effects on swarming when compared with control in stalk samples of 2 years.
According to our results, which were evaluated by measuring the spread from the center to the wall on the medium, control PA01 showed 67 mm spread, while extracts prepared with stalk samples of Zr showed results ranging from 11 to 14 mm at 11–15 µg ml−1 concentration, respectively. These results showed that extracts of the stalk have a significant inhibition effect on swarming motility of PA01 between 78 and 86%.
Inhibition effects of extracts on biofilm formation were compared statistically with control for both years (Fig. 1c, d). Fruit stalk extracts decreased biofilm formation levels in both varieties and it was statistically significant (P < 001**) in same concentration. It was determined that fruit stalk samples reduced significantly the formation of biofilm regardless of year and variety.
Pseudomonas aeruginosa is highly successful in developing resistance to antibiotics (Stein 2005). Lipopolysaccharides in the outer membrane structure that cause lifethreatening biofilms, create a natural barrier and prevent the penetration of most antibiotics (Sabarinathan et al. 2020).
The biofilm layer protects the bacteria against antimicrobial agents and the host immune system. It also plays an active role in the permanent colonization of the bacteria in the host and complicates the healing process of the host (Donlan and Costerton 2002; Roy et al. 2018). Many studies have shown that biofilm formation is under the control of the QS system and it is shown that the resistance to antibiotics can be reduced by blocking the signals that provide communication between bacteria and by preventing biofilm formation (Hong et al. 2012; Jiang et al. 2019). Therefore, prevention of biofilm formation is important in preventing infections and nowadays biofilm elimination strategies are one of the most important research fields. Inhibition of biofilms by plant polyphenols occurs by inhibiting communication between bacteria without inhibiting bacterial growth (Slobodn´ıkova´ et al. 2016). The QS plays a critical role in the formation of biofilm in Gram-negative and positive species and a variety of molecules derived from natural plants or medicinal herbs extract have anti-biofilm properties (Lu et al. 2019).When the effects of different cherry fruit stalk extracts on biofilm formation were examined, it was seen that stalk extracts of both varieties significantly prevented biofilm formation. Specifically, stalk extracts of Zr collected in 2017 and 2018 showed a high inhibition rate of 75% and 73%, respectively.

Homology Modeling

In the experimental study, it was determined that fruit stalk samples significantly reduced the formation of biofilm regardless of year and variety. So, it is crucial to analyze the binding of molecules to the receptor protein to explain the inhibitory effect on virulence production. Chlorogenic acid was one of the major components of the extracts in this study. Therefore, possible interactions of chlorogenic acid with the LasR, RhlR, and PqsR receptor protein of P. aeruginosa were determined and then compared with the binding mode of the natural ligands.
The 3D structure of RhlR was estimated by homology modeling. Homology modeling is considered to be the most accurate one among the computational structure prediction methods (Cavasotto and Phatak 2009; Muhammed and Aki-Yalcin 2019). According to the verification and validation results obtained, the 3D model built was reliable (Fig. 2). The molecular docking result obtained by using the model was found to be comparable with its reference ligand, BHL (N-butanoyl-L-homoserine lactone).
Homology modeling was used to predict the 3D structure of RhlR. Verification and validation of the best model generated was performed by SAVES. The results obtained revealed that the model is reliable. Verify 3D value and ERRAT quality factor of the model were found to be 9258 and 9386%, respectively (Fig. 2a,b). The Ramachandran plot developed demonstrated that 9958% of the residues were found to be in the allowed region. In addition to this, 9253% of the residues were in the most favored region (Fig. 2c). The binding site of the protein was also estimated with CASTp (Fig. 2e). The GRID map was arranged in a way that includes the residues in the binding site of the model (Fig. 2d). 

Molecular Docking

The experimental results revealed that cherry extracts contain molecules that decrease the production of the virulence factors by interfering with the QS system of P. aeruginosa. The interference of the extracts in QS might be through the inhibition of the three main QS system receptors, LasR, RhlR, and PqsR. Molecular docking was performed against these receptors to elucidate the mechanism of action. For this purpose, chlorogenic acid, which is one of the major constituents of the extract, was used as a ligand. In each case, results with the best binding energy and RMSD values were used for further investigations. The molecular docking results demonstrated that chlorogenic acid had a good interaction pattern with these receptors (Fig. 2). The binding energy of chlorogenic acid with LasR, RhlR and PqsR was found to be −105, −67, and −77 kcal mol−1, respectively. Thus, chlorogenic acid has the best interaction with LasR in docking binding energy measurement. Furthermore, the molecular docking results of LasR, RhlR, and PqsR by docking of them with their reference ligands was found to be similar to the docking result of chlorogenic acid (Table 3).
In an experimental study, the natural agonist of LasR, OdDHL (N-3-Oxo-Dodecanoyl-L-Homoserine Lactone) was found to have hydrogen bonds at Asp73 and Ser129. In the same study, the analogs of the natural ligand that are QS inhibitors were found to have various interactions at Ala38, Asp73, Tyr93, and Leu110 positions (Bottomley et al. 2007). In another experimental work, the interaction at Leu125 was found to be one of the important residues for the binding of a ligand to the L3 loop of LasR(O’Reilly et al. 2018). In the molecular docking hydrogen bonds at Gly38, Tyr93, Leu125, Ser129 and various other interactions at Asp73, Trp88, Phe101, Ala105, and Leu110 were detected (Fig. 2f). These data illustrated the high similarity between the computational results obtained in this work and the experimental results from the literature. Similarly, chlorogenic acid was found to have interactions with PqsR at Gln194, Leu197, Ile236, Tyr258, and Ile263 positions in the computational analysis (Fig. 2h). In a previous experimental analysis, PqsR was found to have interactions with NHQ (2-nonyl-4-hydroxyquinoline) at all of the positions detected in this work except Leu97 (Ilangovan et al. 2013). In short, the computational results reported here are in line with the experimental works available. Furthermore, the molecular docking results of LasR and PqsR with redocking of them with the bound ligands in their PDB structures was similar to the docking result of chlorogenic acid. As a result, the computational results are consistent in both experimental and theoretical standards. To sum up, the computational results exhibited that chlorogenic acid had good interactions with LasR, RhlR, and PqsR. Among of the three QS receptors, chlorogenic acid had the best interaction with LasR and exhibited the highest similarity with the interaction of its natural ligand, OdDHL (Table 3).
The computational analysis revealed that chlorogenic acid can bind to all the three QS receptors, LasR, RhlR, and PqsR. The binding of chlorogenic acid to these receptors has QS inhibiting effect by interfering with the binding of the natural inducers to their respective receptors. A recent experimental study showed that the gene expression of lasR, rhlR, and pqsA was downregulated by chlorogenic acid treatment. The result in this last study was supported by molecular modeling (Kelebek and Selli 2011). In another study, chlorogenic acid was screened as one of the LasR and RhlR inhibitors through virtual screening. Further in vitro experiments in the same study approved its potential QS inhibiting effect (Martini et al. 2017). These studies supported the results obtained in this work. So, the computational results of this study indicated that the QS inhibition activity of the tested extracts might result from the inhibition of this system by the binding of their major component, chlorogenic acid, with the QS receptors. This study was conducted using experimental (wet lab) and computational methods. Extensive molecular modeling was performed with chlorogenic acid and three different receptors in QS. Since contemporary tools were applied, the results were unique from similar studies (Wang et al. 2019). The difference was apparent in the detected high degree of similarity with the references.
It was determined that catechin (flavan-3-ol) isolated from Azadirachta indica has strong antibiofilm effect on the dental plaque caused by P. gingivalis and Alcaligenes faecalis in vitro, catechin was further docked with quorum sensing LuxS protein (PDB ID: 6SLI) which also showed considerable interaction (Lahiri et al. 2021). In another study, both of in vitro and in silico studies were done to prove the anti-quorum sensing potential of Senegalia nigrescens by selected phytochemicals and suggested that the S. nigrescens extracts and phytochemicals such as melanoxetin and quercetin-3-O-methyl ether, have ability to reduce virulence and pathogenicity of drug-resistant bacteria in vivo (Bodede et al. 2018).
In this study, the anti-quorum sensing activity of the cherry species was studied for the first time. In the light of the data obtained, in future studies components contained in the cherry stalk should be purified and the effects of each component should be investigated on the mechanisms involved in biofilm formation separately. In addition, while investigating antibacterial activity of cherry waste on different resistant species, combinations of major components with antibiotics can be tried to investigate their synergistic effects. Furthermore, the expression level can be determined by choosing the most relevant receptor used in modeling. QS plays an important role in the virulence and pathogenicity of invasive pathogens due to the expression of genes encoding virulence factors in bacteria. Although the mechanism of QS is not yet fully elucidated, therapeutic agents targeting this system are thought to be an alternative to antibiotics in the treatment of infectious diseases in the future. For this reason, many natural or synthetic substances are investigated on the inhibition of the QS system. Due to its low cost and fewer side effects, people now have an interest in the use of traditional medicines. So, the study suggests the suitability of cherry stalks as a potential prospective anti-quorum sensing inhibitor.

Materials and Methods

Plant material

In the study, fruit stalks of Cr and Zr on Gisela 6 rootstock which is semi-dwarf rootstock (Hrotko and Rozpara 2017) planted in 2012 were used as plant material. Planting area is in the Egirdir˘ Fruit Research Institute (37°4901797″N; 30°5202244″E). Common growing methods and integrated pest management methods in the orchard were used, and trees were irrigated with drip irrigation system (Sarısu et al. 2016). Cristalina is heartshaped with dark red-to-black skin and firm, dark flesh. Sweet and moderately large on long thick stalks. The tree of the 0900 Ziraat grows vigorously and widely. Its fruit is thin-long stemmed, hard, crisp, wide heart-shaped, bright red and dark red color and resistant to cracking. It is an important variety subject to the world cherry trade. Both varieties were vegetative propagated standard clones. Fruit stalks were collected on June 1, 2017, and May 17, 2018, for Cr variety and on June 30, 2017, and June 14, 2018, for 0900 Ziraat. The stalk samples were dried under shade in laboratory conditions and grinded.

HPLC-DAD analysis

Phenolic compounds were evaluated by reversed phasehigh performance liquid chromatography (RP-HPLC, Shimadzu Scientific Instruments, Tokyo, Japan) with direct injection. An HPLC equipped with an SCL-10Avp System controller, an SIL–10AD vp Autosampler, an LC-10AD vp pump, a DGU-14a degasser, a CTO-10 A vp column heater, and a diode array detector (DAD) with wavelengths set at 278 nm. A gradient solvent system was used for separation of phenolic compounds, solvent A: 30% acetic acid in distilled water and solvent B: pure methanol. A 90-min linear gradient was programmed as follows: 0– 010 min, 0–7% B; 010–20 min, 7–28% B; 20–28 min, 28–25% B; 28–35 min, 25–30% B; 35–50 min, 30 B; 50– 60 min, 30–33% B; 60–62 min, 33–42% B; 62–70 min, 42–50% B; 70–73 min, 50–70% B; 73–75 min, 70–80% B; 75–80 min, 80–100% B; 80–90 min, 100–7% B. The flow rate was 08 ml min−1, samples of 20 µl were injected into the reversed-phase C18 column (Agilent Eclipse XDB C18 (250 mm × 46 mm length, 5 μm). The column temperature was set at 30°C (Caponio et al. 2001).

Bacterial strains and antibacterial activity

It was carried out on antibacterial activity with Grampositive (Staphylococcus aureus ATCC 25923, Methicillinresistant S. aureus ATCC 43300, B. cereus ATCC 11778, E. faecalis 29212) and Gram-negative (E. coli ATCC 25922, P. aeruginosa ATCC 27853, P. aeruginosa PA01) bacteria. The antibacterial effect of extracts was determined using the agar well diffusion method (Holder and Boyce 1994). At the end of the study, which was performed in three replications, the average of the results was calculated with standard deviations and antibacterial effects were evaluated.

Minimum inhibitory concentration

Minimum inhibitory concentrations (MIC) of the extracts were determined using a 96-well plate with the tube dilution method (Wiegand et al. 2008). A hundred microliter of each extract was added to the wells containing 100 µl of Muller Hinton Broth and twofold serial dilutions were made. Ten microliters of 1 × 108 CFU bacteria suspension was added to each well and incubated at 37°C/35°C for 18–24 h. The lowest concentration without growth at the end of incubation was measured as the MIC value.

Biofilm formation assay

The effect of methanol extracts of cherry stalks on bacterial biofilm was investigated according to the crystal violet (CV) test (O’Toole 2011). Different concentrations of the extracts were added to the LB broth medium located in the wells and 5 µl of overnight PA01 culture was added in wells. After incubation at 37°C for 48 h, the plate contents were poured and washed with 3–5 times to remove planktonic bacteria. CV was added 01% concentration to the wells and it was washed again with pure water 3–5 times after 30 min. It was left to stand for 15 min by adding 95% ethanol. OD (Optical Density) values (Epoch Microplate Spectrophotometer) were recorded at 570 nm. The inhibition rate of extracts on biofilm formation was calculated according to formula: Inhibition rate ð%Þ ¼ ½ðOD in control OD in treatmentÞ 100 OD in control

Swarming motility assay

Pseudomonas aeruginosa PA01 was produced overnight in LBB medium with a shaking incubator at 37°C. At the end of the incubation, it was taken into a sterile tube and centrifuged at 4500 rev min−1 for 5 min. Swarm medium contains 8 g l−1 nutrient broth, 5 g l−1 bacto agar and 05% (w/v) glucose. Two hundred microliters of these extracts by mixing with 20 ml swarm medium was poured into petri-dishes. Five microliter of the bacterial supernatant was inoculated to the center of each petridish and allowed to dry for 10–15 min, then incubated at 37°C for 16–18 h (Rashid et al. 2000). The swarming motility was tested by measuring the diameter of the spread from the point of inoculation to the outward. The results were evaluated by comparing PA01 strain in control medium. The swarm tests were repeated three times and the results were averaged.

Homology modeling

The 3D structure of RhlR has not been determined yet. Thus, its 3D structure was generated by homology modeling. The amino acid sequence of the protein was retrieved from UniProt (accession number: P54292) (Apweiler 2009). PSI-BLAST (Position specific iteration-basic local alignment search tool) search was performed using this sequence against PDB database to find the template structures that are used in the modeling (Altschul et al. 1997). Homology modeling was undertaken by SWISS-MODEL (Waterhouse et al. 2018), I-TASSER (Zhang 2008) and MODELLER (Kuntal et al. 2010) to get the most reliable model. Then, the models generated by these methods were compared with each other. Among of these models the best one in the verification criteria was selected. Verification and validation of the model was performed with SAVES (Colovos and Yeates 1993). The binding site of the model was predicted by CASTp (Dundas et al. 2006). Molecular docking of RhlR was then performed with consideration of the binding site predicted.

Molecular docking

The 3D structures of LasR (PDB ID: 6D6L) (O’Reilly et al. 2018) and PqsR (PDB ID: 4JVC) (Ilangovan et al. 2013) were retrieved from the Protein Data Bank (PDB). On the other hand, the 3D structure of RhlR was generated by homology modeling. The structure of chlorogenic acid was drawn with ChemDraw ultra 12.0 (Cousins 2011). Molecular docking was carried out with AutoDock Vina (Trott and Olson 2009). Prior to docking, GRID map of each protein that covers the binding region and its surrounding residues was determined. The targets were prepared by adding polar hydrogens and assigning Gasteiger charges. The ligand was prepared by minimizing its energy, adding polar hydrogens and assigning Gasteiger charges. After assigning the receptor, the ligand and the size as well as the center of the GRID map, the command prompt of AutoDock Vina was run (Trott and Olson 2009). The receptor–ligand interactions of the docking results were visualized and analyzed by using Discovery Studio 3.5 (Barnum et al. 1996).

Statistical evaluation

The experiments subject to statistical evaluation were carried out according to the random parcels trial design with in three replications, cultivars, and control factors in two consecutive years. Data were subjected to analysis of variance with JUMP software and the differences between the averages of the results were compared with letters according to the LSD multiple comparison test.

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