ANTIBACTERIAL ACTIVITY, PHARMACOKINETICS AND MOLECULAR DOCKING OF PHYTOCHEMICALS FROM RICINUS COMMUNIS` LEAF EXTRACT

ANTIBACTERIAL ACTIVITY, PHARMACOKINETICS AND MOLECULAR DOCKING OF PHYTOCHEMICALS FROM RICINUS COMMUNIS` LEAF EXTRACT

Tsolanku Sidney Maliehe *, Sandile Nduduzo Mboyazi, Mduduzi Innocent Nqotheni, Sbongiseni Buthelezi and Jabulani Siyabonga Shandu

Department of Biochemistry and Microbiology, University of Zululand, Kwa Dlangezwa, South Africa.

ABSTRACT: To evaluate the antibacterial activity, pharmacokinetics and molecular interaction of the compounds from Ricinus communis` leaf extract. Antibacterial activity was assessed by using the micro-dilution method. The chemical constituents of the methanolic leaf extract were assessed by using gas chromatography-mass spectrophotometry (GC-MS). The drug-like and toxicity properties of the phytocompounds were predicted by SwissADME and ADMET lab tools. AutoDock Vina was employed to investigate the binding strength of the ligand-receptor complexes. The extract displayed antibacterial activity with the lowest minimum inhibitory concentration of 1.56 mg/mL on Bacillus spizizenii (ATCC 6633). The GC-MS showed volatile compounds, namely hexadecanoic acid, methyl ester (0.62%), tridecanoic acid (0.76%), pentafluoro propionic acid, nonyl ester (0.85%), 10-octadecanoic acid, methyl ester (2.93%) and cis-vaccenic acid (94.84%). The compounds did not inhibit isomers of cytochrome P450 (CPY) (CYP 2D6 and CYP 3A4). They were all predicted to have drug-like properties as they adhered to the Lipinski Ro5. The compounds did not show to induce any hepatotoxic effects. The compounds revealed the docking scores in the range of -4.4 to -5.7 kcal/mol. R. communis has the potential to be utilized as a source of therapeutic drug-like compounds.

Keywords: Ricinus communis, Antibacterial activity, Pharmacokinetics, Toxicity, Molecular docking

INTRODUCTION: There is remarkable progress made towards reducing morbidity and mortality rates due to infectious diseases in most parts of the world. However, the emergence of new antimicrobial resistance mechanisms among pathogenic microorganisms does threaten human health ¹.

Major reasons for resistance to antimicrobials are an inappropriate use of antimicrobials, intake of improper dosages and excessive use of antimicrobials ². Microorganisms resist drug effects through enzymatic inactivation of the drug molecules, modification of target sites and extrusion by efflux pump ³. Moreover, most of the allopathic drugs are costly and turn to induce adverse side effects ⁴. Confronted with these challenges, it is imperative to search for new compounds with inhibitory activities characterized by high potency, improved mechanisms of action and less side effects. Medicinal plants are the predominantly used natural sources of pharmacologically active compounds in modern-day drug discoveries ⁵. The plant-based molecules are recognized for their broad spectrum of pharmacological activities that include antimicrobial and immune-suppressant effects, among others ⁶. Their pharmacotherapeutic activities are due to their diverse bioactive compounds, including alkaloids, tannins, saponins, glycosides and flavonoids ⁷. Nevertheless, many of the newly discovered compounds are banned at the clinical stages of drug discovery processes. This is mainly due to the poor pharmacokinetic properties and toxicity displayed by most of these compounds ⁸. The pharmacokinetic properties of molecules describe their absorption, distribution, metabolism, and excretion characteristics. These parameters are summed up by the term ADME or better ADMET when toxicity profiles are included ⁹. The evaluation of the ADMET parameters at the early stages of drug discovery and development can decrease the pharmacokinetic-related fiascos and financial losses. Although conventional methods are used to evaluate pharmacokinetics, they take a considerable length of time and are costly ¹⁰. Recently, computational methods are considered the important primary step in the evaluation of suitable drug-like compounds and prevention of time wastage and expenses on drug candidates that would have undesirable effects ¹¹. Moreover, these computational tools are widely used in the analysis of the binding energetics, molecular interactions, and conformational changes ¹². Molecular docking is widely used to predict the conformation of ligands within the receptor proteins with a significant degree of certainty ¹³.

Ricinus communis is a medicinal plant from the Eurphobiceae family ¹⁴. It is recognized for its therapeutic properties, including antimicrobial, anti-inflammatory, antioxidant, and wound healing properties ¹⁵. The phytochemical screening has revealed the presence of different classes of compounds that include flavanols, alkaloids, glycosides, flavonoids, steroid and saponin in different parts ¹⁶. Although many studies are documenting its pharmacological properties that include antimicrobial activity, there are limited studies on assessing pharmacokinetic properties and molecular interactions with its phytochemicals.

The study aimed to evaluate the antibacterial activity, ADMET properties and molecular interactions of phytochemicals from Ricinus communis` leaf extract with the target protein. The chemical constituents were identified using the standard biochemical techniques and gas chromatography-mass spectrophotometry (GC-MS). The in-vitro antibacterial activity was assessed by using the dilution method. Lastly, the ADMET properties of the identified phytochemicals and their molecular interaction with the target protein were investigated using SwissADME, ADMET lab and AutoDock Vina tools.

EXPERIMENTAL:

Study Area: The study was conducted in the Department of Biochemistry and Microbiology at the University of Zululand, KwaZulu-Natal, South Africa, from July 2019 to the end of February.

Chemicals and Media: The chemicals and media that were used in this study were of analytical grades. They were procured from Merck (Ltd) Pty and Sigma Aldrich Co. Ltd (Steinem, Germany).

Sample Preparation and Extraction: Ricinus communis` leaves were collected from Felix ton, Empangeni in KwaZulu-Natal, South Africa. The sample was transported to the University of Zululand, South Africa. The leaves were authenticated by Dr. Ntuliat, the University Herbarium. The plant was allocated the specimen voucher SNM01. Thereafter, the leaves were washed, dried at room temperature and milled to powder. Ten grams of the powdered material was extracted with methanol (100 mL) for 72 hours at the shaking incubator at 25°C, 110 rpm.  The extract was filtered by Whatman no. 1 filter paper and evaporated under a stream of air at room temperature ¹⁷.

Antibacterial Activity: The minimum inhibitory concentration (MIC) of the extract was evaluated by serial microdilution using 96-well microplate ¹⁸. The wells in row A were pipetted with 50 µL of Mueller-Hinton Broth (MHB) and had 50 µL of 50 mg/mL of the extract. Rows B through H was filled with 50 µL of MHB. A serial dilution was carried out with corresponding final concentration of 0.39 mg/mL. Thereafter, the wells were added with 50 µL of fresh bacterial suspension (10⁶cfu/mL). The bacterial strains were Proteus mirabilis (ATCC 25933) and Bacillus spizizenii (ATCC 6633). Ciprofloxacin was used as positive control, while 10% dimethyl sulfoxide served as a negative control. The plate was sealed with parafilm and incubated at 37°C overnight. After incubation, the wells were added with 30 µL p-iodonitrotetrazolium violet (4 mg/mL). The MIC was taken as the lowest concentration that displayed clear wells, indicative of the absence of bacterial growth.

Phytochemical Analysis: The phytochemical screening of the crude extract was done for the detection of different classes of phytocompounds ²⁰. The evaluation of volatile phytochemicals was performed by using gas chromatography-mass spectrometry (THERMO Gas Chromatography TRACE ULTRA VER: 5.0, Germiston, SA). The helium gas flow rate was set to 1 mL per minute, with a spit ratio of 1:50. The temperature of the injection port was set to 250°C with the temperature of the detector put at 280°C. The column temperature was put at 40 °C for 1 min and then raised from 40 - 120°C. After that, 2 µL of the extract was injected for investigation. The mass spectra required in the scan mode were 70 eV. The identification of the phytochemicals was confirmed based on the retention indexes and mass spectra that were compared to those attained from the libraries. The evaluation was performed two times ¹⁵.

Physicochemical and Pharmacokinetic Pro-perties: The SwissADME tool was used to evaluate the physicochemical and pharmacokinetic properties of the identified compounds. The simplified molecular-input line-entry system (SMILES) of each compound was obtained from Pub Chem and inserted into the SwissADME tool. Thereafter, the physicochemical properties such as the molecular weight (MW), number of hydrogen bond acceptors (N_HBA), hydrogen bond donors (N_HBD) and rotatable bonds (N_RB). The lipophilicity was evaluated using consensus logP (cLogP) estimation. The solubility (LogS) was investigated using three models, namely ESOL, Ali and SILICOS-IT. The pharmacokinetic properties such as human intestinal absorption (HIA), penetration of the blood-brain barrier (BBB), the interaction of compounds with P-glycoprotein (P-gp) and metabolism were predicted ^{20, 21}.

Drug-Likeness Prediction: The drug-likeness of the compounds was investigated in accordance with the Lipinski rule of five (Ro5) using Swiss ADME tool ²¹. According to Ro5, drug-like molecules ought to have MV ≤ 500 Da, log P-value≤ 5, N_HBD ≤ 5, and N_HBA must be ≤ 10. In addition, the N_RB ought to be ≤ 10 and compounds must not violate more than one of the Ro5 ²². The bioavailability scores of the phytochemicals were computed based on their MV, cLogP, N_HBD and N_HBA^{21, 22}.

Bioactivity Score: Bioactivity scores of the compounds were predicted using the software Molin spiration score online. The bioactive scores were evaluated against G protein-coupled receptors (GPCR ligand), ion channel modulator, a kinase inhibitor, nuclear receptor ligand, protease inhibitor, and enzyme inhibitor ^{23, 24}.

Toxicological study: The toxicological properties were calculated using the online server ADMET lab online tool. The simplified molecular-input line-entry system (SMILES) for each compound was procured from Pub Chem and inserted into ADMET lab. Thereafter, the human hepatotoxicity (HHT) and skin sensitivity (Skin Sen) of the compounds were evaluated ²⁵.

Molecular Docking: Retrieval and Preparation of The Receptors: The three-dimensional structures of the three target receptor proteins were retrieved from the Protein Data Bank (PDB). The receptor protein was FtsZ (PDB ID 4DDQ), a protein that plays an important role in bacterial cell division ²⁶.

The structures were loaded into the Bio via Discovery Studio 4.1 Visualizer. The water molecules, heteroatoms and ligands were deleted. Thereafter, polar hydrogen atoms were added to the protein ²⁷.

Ligand Preparation: The structures of the identified compounds were procured from the National Centre for Biotechnology Information (NCBI) PubChem compound database. The ligands were energy minimized using Chimera 1.14. Thereafter, the PDB files of the structures were converted to PDBQT files using Auto Dock tools.

Molecular Docking and Visualisation of the Complexes: The docking of the target protein with the ligands was done using AutoDock Vina ²⁸. Docking was performed to get a set of possible conformations and orientations for the ligand at the binding site. The ligand displaying the lowest binding affinity was chosen as the best conformation. The docked protein-ligand complexes were visualized using Bio via Discovery Studio 4.1 Visualizer. For analyzing the interaction in the complexes, surfaces were created close to the ligand and the hydrogen and other interactions were evaluated ²⁷.

Statistical Analysis: The experiments were performed in triplicates and the data was reported as mean ± standard deviation. The analyses were done by one-way analysis of variance and regarded to be significantly different at p < 0.05.

RESULTS AND DISCUSSION:

Antibacterial Activity: The antibacterial activity of the extract is shown in Table 1. B. spizizenii (ATCC 6633) was more susceptible to the antibacterial effect of the extract, presenting a lower MIC of inhibition 1.56 mg/mL as compared to the MIC of P. mirabilis (ATCC 25933), which was 6.25 mg/mL.

It is generally accepted that Gram-negative bacteria are less susceptible to antimicrobials in comparison to the Gram-positive bacteria. The difference is associated with the properties of the outer membrane of the Gram-negative bacteria that have a surface with strong hydrophilicity that acts as a robust permeability barrier ²⁹.

TABLE 1: MINIMUM INHIBITORY CONCENTRATION (mg/mL) OF THE EXTRACT

Phytochemical Classes from the Methanol Extract: The screening of different classes of the compounds in the leaf material was performed and the results are illustrated in Table 2. The presence of all classes (alkaloids, flavonoids, glycosides, saponins, steroids, tannins, and terpenoids) evaluated was observed. The screened phytochemicals are reported to possess pharmacologically important properties that include antibacterial and cytotoxic activities ³⁰. The antibacterial activity is owed to the presence of these phytochemicals.

TABLE 2: PRELIMINARY PHYTOCHEMICAL SCREENING OF THE LEAF MATERIAL

Key: +: weakly positive; ++: moderately positive; +++: strongly positive

Volatile Compounds from the Extract: The methanolic extract under GC-MS chromatogram gave a yield of 5 volatile compounds Table 3. Hexadecenoic acid, methyl ester (0.62%), tridecanoic acid (0.76%), pentafluoro propionic acid, nonyl ester (0.85%), 10-octadecanoic acid, methyl ester (2.93%) and cis-vaccenic acid (94.84%) as the major component. Previous studies have reported all of these compounds to possess antimicrobial activity ^{31, 32}. Thus, the antimicrobial activity observed in this study was attributed to the presence of these compounds ³⁵.

TABLE 3: THE CHEMICAL CONSTITUENTS OF THE EXTRACT

Molecular Weight (MV) of the Compounds: The permeability and bioavailability of drug molecules are influenced by the molecular property called molecular weight (MV). The weightier the molecule (greater than 500 g/mol), the lower the permeability and bioavailability are and vice versa ¹⁸. The molecular weights of the compounds are shown in Table 4. It was observed that all compounds have less than 500 g/mol, implying the potential for good bioavailability.

N_hba and N_hbd of the Compounds: Hydrogen bonds are recognized for their important role in membrane permeation and absorption of molecules in the gastro-intestines ³⁶. In addition, hydrogen bond interactions have an influence on the ligand-receptor binding affinity. Hydrogen bond strength in the molecules was estimated by calculating the N_HBD (sum of OHs and NHs) and N_HBA (sum of Os and Ns) and the results are presented in Table 4. Molecules with N_HBD ≤ 5 and N_HBA ≤ 10 have high probabilities of membrane permeability and bioavailability ³⁷. This means that all compounds evaluated in this study have the potential to be bioavailable as they have N_HBD ≤ 5 and N_HBA ≤ 10.

TABLE 4: THE PHYSICOCHEMICAL PROPERTIES AND LIPOPHILICITY OF IDENTIFIED COMPOUNDS

N_RB of the Compounds: Rotatable bonds are defined as single bonds that are not found in aromatic rings but bound to nonterminal heavy atoms. The N_RB contributes to molecular rigidity or flexibility, which directly affects oral bio-availability and the strength of intermolecular interactions ³⁸. The N_RB were counted, and the results are shown in Table 4. The compounds had the N_RB in the range of 11 to16. According to ³⁹, compounds with N_RB greater than 10 turns to display poor drug bioavailability. A high N_RB (greater than 10) enhance high flexibility, consequently leading to poor bioavailability.

Lipophilicity (cLogP) of the compounds: Lipophilicity (expressed as cLogP) is an important parameter that influences drug absorption in the body. High cLogP-values (5≤ LogP) is associated with poor absorption and vice versa ⁴⁰. The cLogP-values of the compounds are displayed in Table 4. Tridecanoic acid and pentafluoro propionic acid, nonyl ester were found to have a cLog P-value less than 5. This means these compounds have a high probability of being absorbed and bioavailable. Hexadecenoic acid, methyl ester, 10-octadecenoic acid methyl ester and cis-vaccenic acid have cLogP-value greater than 5, indicative of the likelihood of these compounds to have problematic permeability and bioavailability ⁴¹.

Aqueous Solubility of the Compounds: Aqueous solubility measures the compounds’ solubility in water at the temperature of 25°C. Low solubility turns to be a limiting factor in drug discovery and development ¹¹. The solubility of the compounds was predicted and the results are shown in Table 5.

The results reveal the phytochemicals to be poorly soluble to soluble depending on the Log’s prediction model used. Thus, the compounds have the potential to be bioavailable in the body as they are all soluble to some degree ⁴².

TABLE 5: SOLUBILITY PREDICTIONS OF IDENTIFIED COMPOUNDS

Gastrointestinal Absorption (GIA) of the Compounds: Gastrointestinal absorption (GIA) is a vital property for the drug molecules that are orally administered.

It depicts the absorption of molecules administered from the gastro-intestine into the bloodstream. All compounds except pentafluoro propionic acid, nonyl ester are predicted to be absorbed in the gastrointestinal tract Table 6. Since, most of the drug molecules are orally administered, they are required to be highly absorbed in the intestinal tissue ⁴².

Interestingly, all tested compounds except pentafluoro propionic acid, nonyl ester, can be easily absorbed in the intestines upon oral administration.

Blood-Brain Barrier (BBB) Permeability: The BBB is the endothelial cell layer found in the brain and is responsible for separating the brain from the blood ⁴⁴. The ability of the compounds to cross BBB was assessed and the results are shown in Table 6. Hexadecenoic acid, methyl ester and tridecanoic acid are presumed to permeate BBB, whereas pentafluoro propionic acid, nonyl ester, 10-octadecenoic acid methyl ester and cis-vaccenic acid are not able to cross BBB. BBB is important for drug molecules that target mainly the brain cells ⁴⁵. This implies that the three compounds that could cross the BBB can be effectively administered and used to treat brain-related disorders.

TABLE 6: PHARMACOKINETIC PARAMETER OF IDENTIFIED COMPOUNDS

P-Glycoprotein (P-Gp) Substrates: P-gp in the cell membrane is responsible for drug transportation out of the cells ⁴⁶. The ability of the identified phytocompounds to act as substrates were predicted and the results were presented in Table 6. The five identified compounds were found not to be P-gp substrates. The efflux action of P-gp turns to render most cells resistant to the effect of drug molecules as it pumps them out of the cells and lowers their concentration, consequently their efficacy⁴⁷. Since all compounds are P-gp substrates, it is highly possible that their pharmacologic effects can drastically be reduced the efflux action of P-gp.

Metabolism of the Compounds: There are a group of enzymes in the liver called cytochrome P450 (CPY) family that are responsible for drug metabolism of drugs and their excretion through bile or urine. Out of the 17 families of CYP enzymes, CYP 1, 2 and 3 are mainly responsible for metabolising drug molecules ⁴⁸. The effects of compounds on CYP 1A2, CYP 2C19, CYP 2C9, CYP 2D6 and CYP 3A4 are shown in Table 6.  All compounds except pentafluoro propionic acid, nonyl ester were predicted inhibitors of CYP 1A2. However, they did not show the potential to inhibit CYP 2D6 and CYP 3A4. CYP 2C19 was only inhibited by pentafluoro propionic acid, nonyl ester cis-Vaccenic acid showed potential to inhibit CYP 2C9. The inhibition of these enzymes would affect the biodegradation of the compounds, consequently leading to adverse side effects⁴⁹.

Drug-Likeness of the Compounds: Drug-likeness is a concept that assesses the relationship between the structural, physicochemical and pharmaco-kinetic properties of the compounds ⁵⁰. The drug-likeness of the compounds was assessed using the Lipinski Ro5. The Lipinski Ro5 states that the drug-like compounds should have the MV, cLogP, nHBA, and n HBD of the compounds should be no more than 500 g/mol, 5, 10 and 5, respectively. Moreover, the compounds ought not to violate more than one of the Ro5 ²². The drug-like properties of the identified compounds are displayed in Table 7. All compounds adhere to the Lipinski Ro5. This means that all compounds can be categorized as drug-like molecules.

TABLE 7: DRUG-LIKENESS AND BIOAVAILABILITY SCORES OF THE COMPOUNDS

Bioavailability Scores of the Compounds: The bioavailability score defines the permeability and bioavailability characteristics of possible drug candidates ⁵¹. All compounds showed a bio-availability score of 0.55 and 0.56 Table 7. Many factors that control the entry of drug molecules from the gastrointestinal tract to the blood system often reduce the amounts of the bioavailable drugs. However, the tested compounds have desirable bioavailability scores (≥ 0.50).

Bioactivity Scores of the Compounds: Bioactivity scores the compounds as the nuclear receptor ligand; kinase inhibitor and protease inhibitor were predicted by using Molinspiration. The predicted bioactivity scores are given in Table 8. The drug-like molecules are esteemed as active when the scores are greater than 0, moderately active when the scores are in the range of -5.0 - 0.0, and inactive when the scores are less than -5.0 ⁵².

All compounds showed to be moderately active as the kinase inhibitors. This implies that all compounds can be used to treat adverse conditions caused by hyperactive protein kinases. Pentafluoro propionic acid, nonyl ester and is-vaccenic acid were found to be active nuclear receptors and protease inhibitors, whereas the other ligands were moderately active. In accordance with the results, the compounds can reduce the hyper-active protease effects to some degree, which can lead to the managed biological homeostasis. Moreover, nuclear receptor molecules are used to regulate some metabolic disorders such as cancer ⁵³. Thus, the compounds have the potential to be utilized as therapeutic agents against such diseases.

TABLE 8: BIOACTIVITY SCORES OF THE IDENTIFIED COMPOUNDS

Toxicological Properties of the Compounds: Toxicity is a measure of adverse effects induced by compounds on living organisms and their ecosystem ¹¹. The human liver is the central site of drug metabolism and is thus exposed to the adverse effects that may be induced by various drug-like compounds ⁵⁴. The human hepatotoxicity (HHT) of the compounds was evaluated, and the results are demonstrated in Table 9. The compounds are all predicted to be non-hepatotoxic. This implies that the compounds have biosafety and the inability to cause liver dysfunction and failure.

TABLE 9: TOXICOLOGICAL PROPERTIES OF THE COMPOUNDS

Skin reactions such as sensitization and irritation are widely known hazards of chemicals. Skin sensitization is a fatal reaction triggered by the repetitive exposure of the skin to the sensitizing compound ⁵⁵. The skin sensitivity to the identified phytochemicals was predicted and the results are shown in Table 9. Tridecanoic acid is the only compound found as non-skin sensitizer, whereas other compounds are skin sensitizers. This implies that only safety measures that include skin protectors ought to be considered upon the use of these compounds except when tridecanoic acid.

Binding Scores of the Compounds: Molecular docking uses scoring algorithms to predict the likelihood of ligands to bind to target proteins. The ligand-protein binding ability occurs spontaneously when the free energy charge is negative ⁵⁶. The binding scores of the ligand-receptor complexes are presented in Table 10.  Pentafluoro propionic acid, nonyl ester-Fts Z interaction had the largest negative free energy values of -5.7kcal/mol followed by hexadecenoic acid, methyl ester-FtsZ (-4.77kcal/mol), cis-vaccenic acid-FtsZ (-4.77kcal/ mol), tridecanoic acid-FtsZ (-4.57kcal/mol) and 10-octadecanoic acid, methyl ester-FtsZ (-4.47 kcal/mol) interactions.

The observed results suggested that all the tested ligands have the potential to form stable complexes with the target protein, consequently resulting in the inhibition of the bacteria. However, the drug used as a control cipro ofloxacin had the highest negative free energy (-7.5 kcal/mol), indicative of better binding ability in comparison to the test ligands.

TABLE 10: MOLECULAR DOCKING SCORES AND INTERMOLECULAR MOLECULAR INTERACTIONS BETWEEN THE LIGANDS AND THE RECEPTOR

FIG 1: THE 2D STRUCTURES OF DOCKED COMPLEXES. (A) HEXADECANOIC ACID, METHYL ESTER-FTSZ, (B) TRIDECANOIC ACID-FTSZ, (C) PENTAFLUOROPROPIONIC ACID, NONYL ESTER-FTSZ, (D) 10-OCTADECANOIC ACID, METHYL ESTER-RECEPTOR, CIS-VACCENIC ACID-FTSZ, AND (F) CIPROFLOXACIN-FTSZ

Molecular Bonds of the Ligand-Receptor Complexes: The binding energy values of the ligand-receptor complexes are the results of the different types of molecular bonds formed. The various ligand-receptor interactions are displayed in Table 10, Fig. 1 and Fig. 2. Hexadecenoic acid, methyl ester demonstrated four hydrogen bonds with different amino acid residues (GLY A:21, THR A:109, GLY A:108, and GLY A:110). The compound also formed van der Waals, carbon-hydrogen bonds and alkyl bonds. Tridecanoic acid interacted with FtsZ protein via five hydrogen bonds with GLY A: 108, GLY A: 110, GLY A: 104, GLY A:21 and THR A:109. It also showed pi-alkyl interaction with PHE A: 183 and van der Waals interactions with other amino acid residues. Pentafluoro propionic acid, nonyl ester formed eight hydrogen bonds, the residues GLY A: 21, GLY A:108, GLY A:110, and THR A:109. This ligand-receptor complex also formed van der Waals, carbon-hydrogen bond, alkyl, and pi-alkyl bonds. The10-Octadecanoic acid, methyl ester has two H- bonds with ARG A:143 and GLY A:1082, van der Waal interactions, and pi-alkyl bonds (PHE A: 183). the cis-Vaccenic acid-FtsZ complex is supported by four hydrogen bonds at residues GLY A:22, VAL A:19, THR A:109 and GLY A:110, van der Waals interactions, carbon-hydrogen bond, and pi-alkyl bonds. Ciprofloxacin formed four hydrogen bonds with GLY A: 104, GLY A:23, GLY A:110 and GLY A:21, van der Waal interactions, carbon-hydrogen bond, pi-alkyl bond (PHE A:183), pi-cation bonds (ARG A:143), and unfavorable bonds. The ligand-receptor complexes were steadied by hydrogen bonds that include O-H and C=O groups. The test ligands served as donors and acceptors. It was concluded that the ligands revealed antibacterial activity by interacting with the functional groups of the FtsZ protein ⁵⁷.

FIG 2: THE 3D STRUCTURES OF DOCKED LIGANDS INSIDE THE BINDING POCKET OF THE RECEPTOR. (A) HEXADECENOIC ACID, METHYL ESTER-FTSZ, (B) TRIDECANOIC ACID-FTSZ, (C) PENTAFLUORO PROPIONIC ACID, NONYL ESTER-FTSZ, (D) 10-OCTADECANOIC ACID, METHYL ESTER-FTSZ, CIS-VACCENIC ACID-FTSZ, AND (F) CIPROFLOXACIN-FTSZ

CONCLUSION: B. spizizenii (ATCC 6633) was more susceptible to the antibacterial effect of the extract with the lowest MIC value of 1.56 mg/ml. The volatile compounds obtained were hexadecenoic acid, methyl ester, tridecanoic acid, pentafluoro propionic acid, nonyl ester, 10-octadecanoic acid, methyl ester and cis-vaccenic acid, which are all reported to have antimicrobial activity.

All compounds were predicted to be bioavailable and were also found to have drug-like properties. These compounds do not display any hepatotoxic effects. The ligands were predicted to demonstrate antibacterial activity by interacting with the functional groups of the FtsZ protein. For future studies, the in vitro and in vivo studies of the identified volatile phytocompounds are recommended.

ACKNOWLEDGEMENT: The authors acknowledge the Department of Biochemistry and Microbiology, University of Zululand and National Research Foundation of South Africa (Grant number: SFH 180531338367) facilities and funds to conduct this research.

CONFLICTS OF INTEREST: No conflict of interest associated with this work.

CONTRIBUTION OF AUTHORS: We declare that this work was done by the authors named in this article and the authors will bear all liabilities about claims relating to the content of this article.

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    How to cite this article:

    Maliehe TS, Mboyazi SN, Nqotheni MI, Buthelezi S and Shandu JS: Antibacterial activity, pharmacokinetics and molecular docking of phytochemicals from Ricinus communis` leaf extract. Int J Pharm Sci & Res 2021; 12(10): 5308-18. doi: 10.13040/IJPSR.0975-8232.12(10).5308-18.

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