METABOLIC PROFILING, IN SILICO DOCKING AND ANTIBACTERIAL POTENTIAL OF PHYTOCONSTITUENTS FROM Phyllanthus muellerianus LEAVES

Global increase in the level of antimicrobial resistance among bacterial pathogens has prompted the search for alternative treatment from medicinal plants. Phyllanthus muellerianus (PM) leaves has been used traditionally against microorganisms of medical importance, hence the need to evaluate the pharmacological pathways and mode of actions using in vitro and in silico approaches. Clinical isolates of eight (8) microorganisms associated with urinary tract infections (UTIs) were obtained and identified using morphological and biochemical methods. Phyllanthus muellerianus (PM) leaves were extracted and purified by solvent partitioning. Ethyl acetate fraction of PM had the highest yield and zone diameter range from 13.5±1.00mm to 28±1.53mm. The rate of protein leakage per time interval of Staphylococcus aureus increased from 9.29 μg/ml at 0 minute to 17.43 μg/ml at 120 minutes while leakage in Candida albicans also increased from 8.57 μg/ml at 0 minute to 70.43 μg/ml at 120 minutes. GCMS fingerprints, pharmacodynamics and pharmacokinetic studies revealed the active agent as quindoline, an azaindoles and isoteres of indoles having a binding energy of -9.1 kcal/mol. Analyses of the structural and atomic orientations of quindoline, and superimposition on ciprofloxacin, a common antibiotic revealed an interesting comparison, effecting a stronger binding affinity of Quindoline-HMG-CoA complex.


Minimum Inhibitory and Minimum Bactericidal Concentration
The Minimum inhibitory concentration (MIC) of the ethyl acetate fraction was also determined and the result indicated that 37.5% had a MIC of 6.25mg/ml while others except Klebsiella pneumoniae had a concentration of 12.5mg/ml. Further analysis into the MBC revealed all test organisms except Klebsiella pneumoniae had MBC of 25mg/ml. Table 1 shows the MIC and MBC value for all the organisms by Ethyl acetate fraction of Phyllanthus muellerianus. Enterobacter sp. 6. 25 25 Antibiotic sensitivity of all test organisms The result of the antibiotics sensitivity test as shown in table 2 and 3 indicates that Proteus mirabilis was resistant to 7 of the antibiotics used, Citrobacter sp. was resistant to 5 antibiotics, Staphylococcus aureus, Enterobacter sp. and Candida albicans were resistant to 4 of the antibiotics while Klebsiella pneumoniae and Escherichia coli was resistant to only 3 antibiotics. However, 75% of the organisms tested were resistant to the penicillin and cephalosporin group of antibiotics, 62.5% were resistant to Chloramphenicol and Sulphamethoxazole/ Trimetoprim. In addition, the Aminoglycosides were shown to possess great antimicrobial activity against all isolates tested. Also, with the exception of Proteus mirabilis, all organisms were sensitive to the Fluoroquinolones.

Rate of kill of the ethyl acetate fraction of Phyllanthus muellerianus
The time rate of kill of the extract as depicted in figure 2 and 3 indicates a continuous decrease in the cell population as the time of exposure increases. For Staphylococcus aureus, at MIC x 1, the colony forming unit (cfu) counted at 0 min was 62 x 10 6 cfu/ml which progressively decreases to 1 x 10 3 cfu/ml at 120min. Similarly at MIC x 2, 51 x 10 6 cfu/ml was recorded at 0min while at 120mins, 3 x 10 2 cfu/ml was observed. Furthermore, Candida albicans experienced continuous decrease in cell population as the exposure time increases. At MIC x 1, the cell population was 39 x 10 7 cfu/ml at 0mins whereas at 120mins, 1 x 10 2 cfu/ml was observed. MIC x 2 on the other hand, had a sharp decrease in cell population from 31 x 10 6 cfu/ml at 0min to 1 x 10 1 cfu/ml at 120min. However, both controls did not exhibit significant decrease or increase in cell population.

Mechanism of action of the ethyl acetate fraction of Phyllanthus muellerianus
The mechanism of action of the extract through nucleotide leakage indicates that as the exposure time increases, the rate of leakage also increases. Figure 4 shows the steady increase in the absorbance value of Staphylococcus aureus at MIC x 1 and MIC x 2 as time increases whereas, the control did not exhibit any significant change in the absorbance value. This is also same in Figure 5 which shows the nucleotide leakage of Candida albicans at both MIC 1 and MIC 2.
In addition, the rate of protein leakage per time interval of Staphylococcus aureus was determined and the result in figure 6 shows a steady increase in protein concentration as exposure time increases. At 0 minute, 9.29μg/ml was observed and this increased up to 11.86 μg/ml at 120minutes for MIC x 1 while MIC x 2 had a steady increase from 10.14 μg/ml at 0minute to 17.43 μg/ml at 120mins. Candida albicans in figure 7 also exhibited this continuous increase in protein leakage at MIC x 1 and MIC x 2.
At 0minutes, 8.57 μg/ml was observed for MIC x 1 while MIC x 2 had 23.14 μg/ml whereas at 120 minutes 52.57 μg/ml and 70.43 μg/ml was recorded for MIC x 1 and MIC x 2 respectively. The control for both organisms did not show significant change in concentration.       In silico studies The GC -MS analysis of the components (ligands) of Phyllanthus muellerianus showed the presence of 8,11,14-eicosatrienoic acid, 9,12,15-octadecatrienoic acid, 2 -Methoxyl -4vinylglycine, Bis (2ethylhexyl)phthalate, 2methoxy -4-vinyl phenol, 2-(1-Adamantyl) -Nbenzylglycine, alpha -D -Galactopyranoside, Quindoline, Benzofuran, 1,2,3, -Benzetriol, and Phytol. In addition, the results of the pharmacokinetics and pharmacodynamics properties of profiled ligands from Phyllanthus muellerianus are presented in Table 5-10. All the ligands passed the Lipinski rule of five except for 8,11,14-eicosatrienoic acid, 9,12,15-octadecatrienoic acid, bis (2-ethylhexyl) phthalate and phytol which has log P values above 5 as seen in Table 5. The distribution of a substance in phases of different lipophilicities is measured as the partition coefficient P (log P). Lipophilicity plays a vital role in the assessment of the therapeutic suitability of a drug. It is a substitute to in vivo studies which are important complements in drug discovery. With the exception of substances that are taken up via a transporter, the absorption is usually better when the compounds are more lipophilic as in the case of quindoline and (1-adamantyl) benzylglycine with log P values of 3.8693 and 3.4458 respectively. This advantage is limited by the solubility in aqueous phases, which decreases severely as the lipophilicity increases. As seen in Table 6, water solubility (log mol/L) decreases proportionately for all the ligands. However, a negative log P value for b-Dglucopyranose means the ligand is a hydrophilic drug whose intake could negatively impact permeability. The excretion path also depends on the lipophilicity of the ligand. Our study shows that extremely lipophilic substances are more quickly metabolized (as seen in Table 7), but are also toxicologically worrisome (Table 8). Only quindoline and 2-methoxyl-4-vinylglycine are substrates of renal organic cation transporter while other drugs are possibly cleared through other available routes such as bile, breath, faces and sweat.  We discovered from our study that Bis (2-ethylhexyl) phthalate and phytol exerted an inhibitory effect on hERG II but none of the ligands interacted with hERG I. Adeoye et al. (2020) has earlier reported that administration of lopinavir, remdesivir, and chloroquine could result in delayed ventricular repolarisation through inhibition of the hERG potassium channel leading to normal cardiac function compromise and disruption of hepatic functions [10]. However, none of this compound was observed to trigger hepatotoxicity. Instead, only (1-adamantyl) benzylglycine, 9,12,15-octadecatrienoic acid and ciprofloxacin (standard drug) were observed to induce hepatotoxicity but no inhibitory effect on hERG I or II (Table 8).
Predictive appraisal of the drugs' distribution through the nervous system showed that lipophilicity of the drugs correlates significantly with the tendency to permeate the blood-brain barrier (log BB) and the central nervous system (log PS). Quindoline, benzofuran, (1-adamantyl) benzylglycine, 2methoxyl-4-vinylglycine and phytol showed favourable penetration through the blood-brain barrier while all the ligands were quite unfavourable towards CNS-penetration (Table 10). Klebe 2013 reported that the optimum lipophilicity required for a drug to cross the blood-brain barrier is in the range of log P = 1.5-2.5 while for CNS-active substances, an optimal lipophilicity around log P = 2 should be aimed for in order to facilitate penetration across the blood-brain barrier. Also, the predicted steadystate volume of distribution (VDss) showed that (1-adamantyl) benzylglycine, 8,11,14-eicosatrienoic acid, 9,12,15-octadecatrienoic acid and ciprofloxacin had lower theoretical dose required for uniform distribution in the plasma.  The in silico study predicted the molecular interaction between profiled ligands from Phyllanthus muellerianus and 3hydroxyl -3methylglutaryl CoA (HMG-CoA) reductase, (a mevalonate synthetase which is the enzyme responsible for the synthesis of peptidoglycan in Staphylococcus aureus and as such its inhibition leads to its inactivity), and showed that all the ligands exhibited relatively good interaction with the enzyme as predicted by their docking scores ( Figure 8 ). However, quindoline was selected for further molecular investigation after considering its pharmacodynamics and pharmacokinetic predictions, in addition to its docking score of -9.1 kcal/mol. This indicated a higher binding affinity to the pocket site of HMG-CoA when compared to ciprofloxacin, a common antibiotic used in the treatment of gram-positive microorganisms has -7.7 kcal/mol and Acetoacetyl CoA which is the natural substrate it binds with. Figure 9 shows the interaction of quindoline and the residues at the site of HMG-CoA and their corresponding orientations while Figure 10 depicts Ciprofloxacin (CIP) binding orientation with residues of at site of HMG-CoA and their corresponding orientations. Superimposition of Quindoline on ciprofloxacin (figure 11c) reveals interesting comparison between the two ligands, predicting our ligand as a drug-lead agent against HMG-CoA inhibition. Analysing the structural and atomic orientations of quindoline (15C, 2N, 10H), we observed the presence of azaindole backbone (4-azaindole moiety ring). Azaindoles are heterocyclic aromatic organic compounds, consisting of a pyrole ring fused to a pyridine ring [12]. As isoteres of indoles, they exhibit excellent potential for biological activity. This structural conformation may have increased the stability of the ligand, effecting a stronger binding affinity of Quindoline-HMG-CoA complex. As earlier proposed by Taylor et al. (2002), binding affinity is a function of the stability of the ligand-target complex, conversely optimizing new bonds and increasing the biological activity of a complex molecule [13].

DISCUSSION
This study has been able to show that Phyllanthus muellerianus leaves extract exhibited high potency against the organisms used in this study which conforms with the reports of Doughari and Sunday (2008) who also reported the potency of Phyllanthus muellerianus leaf extract [1]. Furthermore, Assob et al. (2011) have shown that the methanol and ethyl acetate stem bark and aqueous leaf extract of Phyllanthus muellerianus, possess antibacterial activity and this support the findings of our study [14]. With further purification of the crude extract of Phyllanthus muellerianus, Dichloromethane (DCM) and Ethyl acetate fraction had the highest zones of inhibition. This could be because DCM and ethyl acetate are able to leach out more flavonoids from the crude extract and these flavonoids account for the high antimicrobial activity [15]. The rate of kill of the ethyl acetate fraction of Phyllanthus muellerianus extract as depicted in this study indicates a continuous decrease in the cell population as the time of exposure increases for both concentrations of the MIC used. This is in line with the reports of Boakye et. al.,(2016b) who reported a gradual decrease in cell population for the first three hours [5]. However, the rate of cell population decrease was faster in MIC x 2 than in MIC x 1, this result conforms to the popular assertion that says the higher the concentration, the higher the antimicrobial effect of the agent against organisms [16]. The mechanism of action of the ethyl acetate fraction of Phyllanthus muellerianus in this study revealed that there was an increase in nucleotide and protein leakage as the exposure time increases. Stojkovic et al., (2013) posited that this is an indication that nucleotide materials (such as purine and pyrimidine bases) had been lost through a damaged cytoplasmic membrane since membrane integrity can be determined through the detection of absorbance at 260nm because nucleotides have strong ultraviolet absorption at that wavelength [17]. The protein leakages on Staphylococcus aureus and Candida albicans could be due to an induced cell lysis by the components of Phyllanthus muellerianus thus damaging the cell wall and membrane [18]. The high antioxidant activities of Phyllanthus muellerianus obtained in this study is in line with the findings of Boakye et. al.,(2016c) who reported high FRAP values similar to this study. Higher FRAP values give higher antioxidant capacity because FRAP value is based on reducing ferric ion, where antioxidants are the reducing agents [19]. The reducing power might be due to hydrogen donating ability, and is generally associated with the presence of reductones [20]. High antioxidant activity of the plant extracts may be due to the high tannin content since the antioxidant activity of tannins is mediated through reducing power and scavenging activity [21] [22]. Khan et. al.,(2012) also reported that many flavonoids and related polyphenols contribute significantly to the antioxidant activity of medicinal plants [23]. It must be noted that the reagent used for total phenolic content in the study does not react exclusively with phenolics, but also with other reducing agents; for example, ascorbic acid [24] [25]. Hence, results of this test therefore reflect the total antioxidant activity of the plant extracts used in this study. The physicochemical analysis of Phyllanthus muellerianus revealed the presence of quite a number of components which is in consonance with the reports of Boakye et. al.,(2016a) [26]. Saleem (2009) also isolated bis (2-ethyloctyl) phthalate, bis (2-ethylicosyl) phthalate, 3-friedelanone, methylgallate, αsitosterol which were also components isolated in this study [27]. It is however pertinent to point out that there were slight differences in the percentage abundance of the components obtained in this study as compared with the findings of Saleem (2009) and Boakye et al.,(2016a). This could be due to variation in ecological factors, climate, geographical location, time of harvesting and age of plants. The rule of five has been established by Lipinski et al. (1997) to predict favourable ADME properties using computer models [28]. For an active substance to be considered, it should not violate more than two of the rule of five: Molecular weight ≤ 500 Da, Partition coefficient log P ≤ 5, No more than 5 Hbond donor groups, No more than 10 H-bond acceptor groups. These simple rules (as a factor of five) were derived from experience and are almost exclusively used to preselect compounds for screening. Usually the more lipophilic a compound is, the better it will be absorbed and consequently, the stronger the biological activity; however, limited solubility in the aqueous phase restricts lipophilicity. Relevant test models have been developed by using thin layers of human colon carcinomas (Caco2). These also allow the absorption by transporters to be studied. As we see in our study (in Table 2), the lipophilicity values corresponds to the Caco2 values and varies directly with human intestinal absorption values. These three parameters are observed to work in tandem; an increase in one predicts an increase in the other. However, we see that lipophilicity again correlates negatively with water solubility as seen with b-D-glucopyranose with log P = -3.2214, water solubility = -1.377, caco2 = 0.249 and human intestinal absorption = 21.51, which is the lowest among all the profiled ligands absorption prediction. Caco2 permeability and human intestinal absorption (HIA) indices are factors that determine the ultimate bioavailability of the drug. Another system that was recently structurally characterized is the membrane-bound glycoprotein GP170, an efflux membrane transporter and a member of the ATP-binding cassette transporter found primarily in epithelial cells. It is a transporter that can expel drugs from the cell. Our study (Table 2) shows that quindoline and ciprofloxacin are substrates of P-glycoprotein and therefore can modulate the physiological functions of P-glycoprotein by regulating the active uptake and the distribution of drugs. Hydrophilic substances and polar metabolites, including those after conjugation with polar groups, are excreted via the kidneys. The excretion of lipophilic substance is usually accomplished hepatically, and subsequently over the intestines. Such substances often undergo oxidative metabolism, with the concomitant possibility of toxic metabolites being produced [9].
The predicted toxicity effect of the drug on Salmonella typhimurium reverse mutation assay showed that quindoline and 2-methoxyl-4-vinylglycine could trigger mutagenic events while others are considered as non-mutagenic agents. However, the toxicities of all the extremely lipophilic ligands in Tetrahymena pyriformis were high ranging from 0.545-1.884, while 2-methoxyl-4-vinylglycine showed the highest toxicity level of all the ligands with a concentration of 0.071 ug/l. Also, these extremely lipophilic ligands namely: 8,11,14-eicosatrienoic acid, 9,12,15-octadecatrienoic acid, bis (2-ethylhexyl) phthalate and phytol induced minnow toxicity with concentrations as low as -1.665, -1.183, -2.266 and -1.504 nM respectively, indicating high cytotoxic effects of the ligands, hence confirming their possible lethal effects on cells. Bis (2-ethylhexyl) phthalate has been linked to increased incidence of hepatocellular carcinomas in animals by the National cancer institute with primary routes of exposure such as inhalation, digestion and dermal contact According to Adeoye et al. (2020), the acute toxicity of a ligand/drug predicts it possible toxicity effects, either mild or severe which could occur within a short time-frame after administration [10]. Quindoline, 1,2,3-benzetriol, 8,11,14-eicosatrienoic acid and 9,12,15-octadecatrienoic acid were shown to elicit a low maximum tolerated dose in humans. Another large group of enzymes worthy of mention are the cytochrome P450 (CYPs) metabolic enzymes. CYPs are the major enzymes involved in drug metabolism. They account for approximately 75% of the total metabolic activity taking place in the organism. Consequently, most drugs undergo deactivation by CYPs, either directly or by facilitated excretion from the body. Also, many substances are biotransformation by CYPs to form their active compounds [29]. Humans have 57 genes and more than 59 pseudogenes divided among18 families of cytochrome P450 genes and 43 subfamilies. CYP 1, 2 and 3 are involved in drug and steroid metabolism. Our study reveals that Quindoline was predicted as the highest CYPs promiscuity by its ability to interact with 6 out of 7 available CYPs on virtual screening by acting as CYP3A4 substrate, CYP1A2 inhibitor, CYP2C19 inhibitor, CYP2C9 inhibitor, CYP2D6 inhibitor and CYP3A4 inhibitor. Ciprofloxacin, b-D-glucopyranose and 1,2,3-benzetriol did not show any interaction with CYPs, either by acting as a substrate or inhibitor as seen in Table 5. However, none of the ligands was predicted as a substrate for CYP2D6, which provides an open field for further study here. Many drugs have been observed to either increase or decrease the activity of various CYP isozymes either by inducing the biosynthesis of an isozyme or by inhibiting the activity of the CYP. This is a major source of adverse drug interactions, since changes in CYP enzyme activity may affect the metabolism and clearance of various drugs [9] [30]. Molecular interaction studies of quindoline binding pocket of HMG-CoA reveals that the inhibitorenzyme relationship is primarily dominated by hydrogen bond and hydrophobic interactions. Panigrahi and Desiraju (2007) have provided comprehensive reports on the contribution of hydrogen bonds to binding affinity of a target-drug, and Patil et al (2010) identified the relevance of hydrophobic interaction on target-drug [31] [32]. A hydrogen bond is characterized by a pronounced distance and angle dependence. It is directional and its geometry is defined within narrow limits. Because of their strength, hydrogen bond interactions are specific, with conserved orientation. However, they are also made and broken rapidly during complexation, conformational change, and folding. This study suggests that the high number of electrostatic hydrogen bond could be responsible for the highest binding affinity exhibited by Quindoline. As revealed by previous studies by Panigrahi and Desiraju (2007), the median H -O distance, d, in a ligand-protein interaction that may affect a ligand binding is ≤ 2.0 A˚ and that the hydrogen bonds are linear, having set the standard H-bonding criteria as d (H -A) ≤ 3.0 A˚ and ϴ (X -H -A) ≤ 90 o [31]. Hydrophobic interactions are created through the close proximity between non-polar amino acid side chains of the protein and lipophilic groups on the ligand. It should be noted that these lipophilic groups are aliphatic or aromatic hydrocarbon groups and also halogen substituents (e.g., chlorine, fluorine) and other heterocycles (e.g thiophene and furan). Usually, all areas that cannot form hydrogen bonds are counted as lipophilic parts of the surface of a protein and ligand. As shown in our study, hydrophobic interactions often afford a significant contribution to the binding affinity for ligands with large lipophilic groups: A:PHE236-:QUIN (pi-pi T-shaped hydrophobic bond, d = 4.99 A 0 ), QUIN-:PRO235:A (pialiky hydrophobic bond, d = 5.43 A 0 , 4.57 A 0 , 4.29 A 0 ). This might have further improved the activity of Quindoline. Teague et al (1999) reported that the average number of hydrophobic atoms in marketed drugs is 16, with one to two donors and three to four acceptors [33]. Hence, we cannot fail to emphasize the importance of hydrophobic interactions in drug designing. Several studies have also revealed that increase in hydrophobic atoms in active site of drug-target interface further increases the biological activity of a drug-lead [34] [35]. Other weak interactions involving halogen atom (both as electrophiles and nucleophiles), p -acceptors and sulphur atom acceptors are also important in the protein-ligand interface. The presence of several pi-pi and pi-alkyl hydrophobic bond appear to affect the binding of quindoline to HMG-CoA. However, previous findings have predicted a distance of d ≤ 3.5 A o and angle ϴ ≤ 100 o . Hence, the distance exhibited by these weak interactions may not favour ligand binding. Furthermore, we observed in our study that pisulphur bond was found to be present, having a distance d of 5.81 A o and 5.21 A o . Although, studies have shown that sulphur atoms are larger and have a more diffuse electron cloud than oxygen and nitrogen and they are still capable of participating in hydrogen bonds. However, a hydrogen bond is presumed to exist if the distance d (H -S) is ≤ 2.9 A˚.

MATERIALS AND METHODS Preparation of Plant Extract:
This was done using the method described by Oluwafemi and Debiri, (2010) with slight modifications [36]. The leaves of Phyllanthus muellerianus were airdried and chopped into small pieces. This was thereafter pulverized using a blender and the powdered mass was kept in an airtight container for further use. Two hundred grammes (200g) of the pulverized leaves were macerated with 2L of 60% methanol and stirred continuously for 72 hours to ensure homogeneity. The mixture was then filtered using Whatman No. 1 filter paper and the filtrate evaporated to semi solid mass using a rotary evaporator and subsequently dried in a petri dish in the dessicator. The crude extracts were purified by solvent partitioning using various solvents in order of their polarity. The dried crude extract obtained was reconstituted with distilled water and poured into the separating funnel after which Nhexane was added and swirled gently to mix. The mixture was left to settle into layers before collecting the N-hexane fraction. This process was repeated until there is no more change in the colour of the Nhexane. Dichloromethane (DCM) was thereafter added to the remaining solution and its fractions were also collected followed by Ethyl Acetate and lastly Butanol. The remaining solution of the extract was taken as the aqueous fraction. The various fractions of the extracts in solution were concentrated to dryness using the rotary evaporator while the aqueous fraction was lyophilized.

Antimicrobial Activity (Agar Well Diffusion Assay)
The purified extracts of Phyllanthus muellerianus were dissolved in sterile water at 50 mg/mL concentration. The test organisms used (Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Citrobacter sp., Proteus mirabilis, Enterobacter sp. Coagulase negative Staphylococcus aureus and Candida albicans) were standardized with sterile saline (NaCl 0.9%), and the turbidity was adjusted to the standard inoculums of a McFarland scale of 0.5 (1.0 x 10 8 colony forming units/mL). Briefly, agar plates containing 20 mL of Mueller Hinton Agar (Oxoid Ltd., Hampshire UK) were inoculated with the bacterial and fungal strains under aseptic conditions and wells (diameter = 8 mm) were filled with 100μ L of the extracts. The experiment was repeated in triplicates and the mean zone of inhibition was recorded after incubating the test organisms at 37 0 C (24 h).

Determination of the Minimum Inhibitory Concentration (MIC)
The fraction that showed higher yield and antibacterial activities was subjected to MIC (minimum inhibitory concentration) assays [37]. Serial dilutions were prepared with concentrations ranging from 0.195 to 100mg/mL. Sterile water was used as a negative control (Blank sterile water). Each prepared concentration (of 2mL) in tubes was mixed with 18mL of sterile nutrient agar (Oxoid Ltd., Hampshire UK) plates that were inoculated with 100 μL each of the 10 8 cfu/mL bacterial and spore suspension from fungal strains. The plates were incubated aerobically at 37 0 C (18-24 h). The MIC values which represent the lowest compound concentration that completely inhibits the growth of microorganisms was recorded. All tests were performed in triplicates.

Determination of Minimum Bactericidal Concentration (MBC)
Based on the MIC results obtained, the concentrations of all extracts that showed no growth were subcultured into sterile nutrient agar plates and incubated for 48 hours. The MBC was taken as the least concentration that did not show any growth on the agar plates. Antibiotic Sensitivity test Kirby Bauer's disk diffusion method was employed to determine the effect of standard antibiotics against the test microorganism. Ten different standard antibiotics (Oxoid Ltd., Hampshire UK) were used for this study. They include: Ciprofloxacin, Gentamicin, Ampicillin, Cefoxitin, Chloramphenicol, Nalidixic acid, Amoxycillin/Clavulanic acid, Sulphamethoxazol/ Trimethoprim, Amikacin and Tetracycline. These antibiotic discs were placed aseptically on the plate already seeded with the test organisms using a pair of sterile forceps. The plates were thereafter incubated at 37 o C for 24 hours. After incubation, zone of growth inhibition was measured and recorded. This experiment was carried out in duplicates. The result obtained was thereafter interpreted using the Clinical and Standard Laboratory Institute (CLSI) chart (CLSI, 2013) and European Committee on Antimicrobial Susceptibility Testing (EUCAST) guidelines [38] [39].

Determination of the rate of kill
The killing rate of the most active extract on the most susceptible bacterial isolate was carried out according to the method described by Odenholt et al., (2001) with little modifications. 0.5ml of the standardized bacterial suspension was first serially diluted using sterile saline to obtain ten dilution factors (10 -1 , 10 -2 , 10 -3 ,10 -4 ,10 -5 ,10 -6 ,10 -7 ,10 -8 , 10 -9 and 10 -10 ) these dilutions were then seeded into nutrient agar plates using the pour plate technique. Heterogeneous plate count was then carried out to determine the viable microbial population count in each dilution factor to serve as reference for the rate of kill [40]. Thereafter, 2ml of the standardized bacterial suspension was added to 18ml of the most active fraction of the extract at a concentration equal to 1x MIC and 2 x MIC values. This mixture was thoroughly shaken together and exactly 0.5ml of the mixture was immediately transferred into 4.5ml of 3% Tween -80 nutrient broth and the suspension was thoroughly mixed. This serve as the portion taken at 0 minute as this was done at 15 minutes interval for 2 hours. Exactly 0.5ml was taken from each suspension and serially diluted up to 10 -6 in 4.5ml sterile normal saline. Then, 0.5ml of the final dilution factor was transferred into labeled pre -sterilized molten nutrient agar plates. This plate was incubated at 37 0 C for 24 hours. The time at which the least number of viable count was obtained was recorded as the time it will take the antimicrobial agent to kill the organism.

Determination of possible mechanism of action by Nucleotide Leakage
The modified method as described by Miksusanti et al., (2008) was used to determine the leakage of nucleotides from the cells of the test organisms. Cells of Staphylococcus aureus and Candida albicans was standardized with saline and treated with various concentration of the extract relative to the MIC at various time intervals for 2 hours. Each suspension was then centrifuged at 10,000rpm and the optical density of the supernatant collected was measured at 595nm wavelength using a Spectrophotometer. Sterile saline inoculated with the same quantity of inoculums was used as control [41].

Determination of possible mechanism of action by Protein Leakage
The leakage of proteins from the cells of the test organisms was also determined. Cells of Staphylococcus aureus and Candida albicans was standardized with saline and treated with various concentration of the extract relative to the MIC at various time intervals for 2 hours. Each suspension was then centrifuged at 10,000rpm and 0.2ml of the supernatant was taken and mixed with 1.4ml of distilled water. 0.4ml Bradford's reagent was thereafter added to the mixture. Normal saline inoculated with the same quantity of inoculums was used as control. Optical Density (OD) of the resulting solution was thereafter taken at 595nm after 5mins. The Concentration of protein leaked was calculated using the Optical density extrapolated from the equation of the best linear regression line obtained from the graph of bovine serum albumin (BSA) standard curve [41].

Antioxidant analysis of Phyllanthus muellerianus Leaf extract
The various extracts were also tested for antioxidant properties. The properties assayed include: Total antioxidant capacity (TAC), Total flavonoids, Total Phenol, Ferric Reducing Antioxidant Power (FRAP).

Physicochemical Analysis
Physicochemical analysis of the extract was performed using Shimadzu GC-MS-QP 2010 Ultra equipped with a SLB-5ms Column fused with silica capillary (0.20mm X 30.0m). The initial temperature was maintained at 40°C for 3 minutes and then heated at a rate of 15°C per minute up to 290°C with a director voltage relative to the tuning result. Carrier gas Helium was used at a rate of 1ml per minute. n-Hexane was first used to flush the columns so as to reduce noise or false peaks. The extract was thereafter introduced into the GC -MS equipment. Different components present were identified with their various peaks and other chemical properties were afterwards obtained.

ADMET Studies
The ADMET (absorption, distribution, metabolism, elimination, and toxicity) studies of profiles compounds obtained from Shimadzu GC-MS-QP 2010 Ultra were carried out using pkCSM tool (http://biosig.unimelb.edu.au/pkcsm/pre-diction) and SwissADME [42] [43]. The profiled compounds were first screened for their physicochemical properties to determine the Pharmaceutical Active Ingredients (PAIs) using Lipinski rule of five (Molecular weight, logarithms of partial coefficient, hydrogen bond donor (HBD) and hydrogen bond acceptor (HBA)) [28]. The canonical SMILES for the molecular structures of each of the compounds were obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov). The compounds with desirable physicochemical properties were further filtered for pharmacokinetic properties.

Ligand preparation
The SDF structure of the ligands was retrieved from the PubChem database (www.pubchem.ncbi.nlm.nih.gov) [44]. The compounds were converted to .pdb chemical format using PYMOL molecular graphics system (1.7.4.5 Edu) [45]. Polar hydrogens were added while non-polar hydrogens were merged with the carbons and the internal degrees of freedom and torsions were set. The ligand molecules were further converted to the dockable .pdbqt format using Autodock vina program.

Enzyme Preparation
The crystal structure of HMG-CoA (1TXT) was retrieved from the protein databank (www.rcsb.org) (Berman et al., 2000). The crystal structure was prepared individually by removing existing ligands and water molecules, while missing hydrogen atoms were added using Autodock vina program, Scripps Research Institute. Thereafter, non-polar hydrogens were merged while polar hydrogen where added to the enzyme. The enzyme was subsequently saved into .pdbqt format in preparation for molecular docking.

Molecular Docking Analysis
The molecular docking analysis was executed to ascertain the binding conformation of the proteinligand complex using AutoDock vina [46]. The binding conformation would aid to reveal the binding energy of the HMG-CoA and Quindoline. The ligands side chain and the torsional bonds kept flexible while the HMG-CoA fixed rigid. All the ligands were docked to the residue involved in catalytic activity with x, y, and z coordinates of 7.000, -7.250 and 68.750 respectively. The grid box was set at 74 Å × 78 Å × 56 Å and with an exhaustiveness of 8. The free binding energy (∆G bind ) was calculated using the sum of van der Waals energy (∆G vdw ), the sum of electrostatic energy (∆G elect ), the sum of hydrogen bond and desolvation energy (∆G hbond ), the sum of final total internal energy (∆G conform ), the sum of torsional free energy (∆G tor ) and the sum unbound system energy (∆G solv ) [47]. The compounds were then ranked by their binding affinity scores. Molecular interactions between the receptors and compounds with most remarkable binding affinities were first viewed with PYMOL after which further graphical analysis was obtained using Discovery Studio Visualizer, BIOVIA, 2016.