Enhanced Allicin Cytotoxicity on HEPG-2 Cells Using Glycyrrhetinic Acid Surface-Decorated Gelatin Nanoparticles.

The cytotoxic potential of allicin was evaluated on different cancer cell lines, particularly, hepatic (HepG-2), breast (MCF-7), lung (A-549), and prostatic (PC-3), where allicin scored an IC50 score of 19.26 μM on HepG-2. In order to increase the cell uptake, optimized allicin-loaded gelatin nanoparticles (GNPs) were prepared where the optimum formulation was surface-conjugated to glycyrrhetinic acid. GNPs were optimized using a D-optimal design. The optimum formulation had a particle size of 370.7 ± 6.78 nm and polydispersity index of 0.0363 ± 0.009 and 39.13 ± 2.38% of drug entrapment. The conjugation of the ligand, glycyrrhetinic acid with allicin-loaded GNPs, was confirmed utilizing 1H NMR. Drug release profiles in the presence/absence of collagenase were obtained. Finally, a cytotoxicity study on HepG-2 was performed for the unconjugated and conjugated allicin-loaded GNPs scoring IC50 of 10.95 and 5.046 μM, revealing two- and fourfold enhancements in allicin cytotoxicity, respectively. To our knowledge, the ligand-carrier pair, glycyrrhetinic acid-gelatin, was not explored before, and the developed system poses a successful liver cancer therapy.

Introduction

Applying the combined approach of passive targeting and ligand surface-decorated drug delivery systems in cancer treatment has the advantage that these delivery systems have the ability for more internalization at the specific cancerous cell sites. In return, this will lead to more enhanced therapies with less side and adverse effects.[1] Through modification of the polyfunctional surface of gelatin nanoparticles (GNPs) by conjugation with a targeting ligand, this approach could be tackled. Glycyrrhetinic acid, the aglycon released from the hydrolysis of glycyrrhizin extracted from licorice (Glycyrrhiza glabra) roots, is believed to possess a highly specific binding site in rat liver[2] and is a potential ligand to the asialoglyco protein receptors (ASGPRs) abundant in the liver. Additionally, glycyrrhetinic acid itself has antihepatitis and hepatoprotective activities.[3] Gelatin is a denatured protein obtained by acidic or alkaline hydrolysis of collagen which is plentifully found in many animal tissues. Regarding nanoparticulate drug delivery systems, gelatin, unlike synthetic polymers, is considered to have a good safety profile. In addition of being GRAS by the FDA, gelatin shows low antigenicity because of being a denatured protein.[4] The accessibility of its functional groups helps for many chemical modifications, of which developing a targeted nanovehicle is of great importance.[5]

In many research studies, allicin showed promising anticancer and anti-metastatic activity through various mechanisms.[6] It has the ability to inhibit lymph angiogenesis which is a key cellular process in metastasis of tumor cells. In addition, it was found to suppress capillary formation, cell migration, and phosphorylation of vascular endothelial growth factor receptor 2.[7] Also, the antioxidant property of allicin, by prompting the cellular phase II detoxification system, contributes to its anticancer activity.[8] Other mechanisms including inhibition of cell proliferation due to its microtubule-disrupting properties[9] and induction of apoptosis and cell-cycle arrest[10] were also investigated.

Therefore, the aim of this work is to formulate optimized allicin-loaded GNPs. Conjugation of the optimized drug-loaded GNPs with glycyrrhetinic acid was also investigated aiming at achieving safe and effective delivery of the drug allicin to hepatic cancer cells via intratumor injection. Additionally, the ligand–receptor interaction was assessed using molecular docking.

Results and Discussion

Cytotoxicity Screening of Allicin on Different Human Cancer Cell Lines

Allicin, as a drug of choice, was evaluated regarding its cytotoxicity using MTT assay that relies on the mitochondrial activity of the active viable cells. The cytotoxic potential of allicin on different human cancer cell lines, namely, human hepatocellular cancer cell line HepG-2, human breast cancer cell line MCF-7, human lung cancer cell line A-549, and human prostatic cancer cell line PC-3 is shown in Figure , where allicin scored IC50 of 19.26, 28.51, 36, and 77.92 μM, respectively. It is observed that allicin exerts its most inhibitory effect on hepatic cancer cells, making it a promising natural substance that could be used in the treatment of liver cancer cases.

Figure 1

Evaluation of the cytotoxic potential of allicin on: (A) human hepatocellular cancer cell line HepG-2, (B) human breast cancer cell line MCF-7, (C) human lung cancer cell line, and (D) human prostatic cancer cell line.

Accordingly, the HepG-2 cell lines were selected for further investigations in this work. In order to enhance the allicin cytotoxic effect, it was loaded in GNPs as nanocarriers, afterward the allicin-loaded GNPs were conjugated with glycyrrhetinic acid to promote the active hepatocellular uptake. As will be shown later, both conjugated and unconjugated allicin-loaded GNPs were investigated on HEPG-2 cell line to evaluate the effect of nanonization[11] and conjugation on IC50 of allicin.

Practical Yield of Plain GNPs

The percentage yield of the plain GNPs relative to the initial amount of gelatin used was 16.16 ± 0.3%. On the other hand, the percentage yield relative to the obtained gel-like precipitate [representing the actual mass of high molecular weight (HMW) gelatin, i.e., capable of forming the nanoparticles] after the first desolvation step was found to be 23.488 ± 0.44%. This data goes with accordance to that explained by Zwiorek.[5]

Particle Size and PDI Measurements of the Plain GNPs

Both particle size and polydispersity index (PDI) are key determinants in the implication of nanotechnology in the development of drug delivery systems as they directly affect the biodistribution, destiny, targeting properties, and toxicity of such nanodelivery systems.[12]

The results displayed in Table indicate that increasing gluteraldehyde (GA) % leads generally to a decrease in particle size. Concerning the cross-linking time, the opposite was observed. This finding can be indicated by giving enough time for interparticular amide bridging between different GNPs because of the symmetric cross-linking effect of GA leading to particle growth as a result of GNP aggregation.[13] On the other hand, the effect of stirring speed on the resultant particle size stays unclear, so, further data analysis was employed to explore its effect. Consequently, the optimum formulation (run #12) in terms of particle size (370.7 ± 6.78) and PDI (0.0363 ± 0.009), which was selected for completing the rest of the study experiments, was prepared at the highest experimented gelatin[NH/GA[CHO] ratio of 1:2 (i.e., 66.67%) and the lowest of the cross-linking time (4 h). Despite the high GA % used, the particle size produced was the smallest among the whole design. This could be attributed to the fact that high GA % would provide enough amount of cross-linking to achieve sufficient intraparticular amide bonding within the GNPs in order to be satisfactorily hardened and shrunken but the short cross-linking time avoids chances of formation of interparticular bridging and particle aggregation.[14]

Table 1

Optimization of GNPs Using the D-Optimal Experimental Design

run	GA %	CLT (h)	stirring speed (rpm)	mean P.S. (nm) ± SD	mean PDI ± SD
1	33.30	16.00	1000.00	786.1 ± 100.4	0.1785 ± 0.005
2	66.70	16.00	700.00	629.75 ± 4.74	0.307 ± 0.034
3	66.70	4.00	700.00	389.85 ± 2.89	0.057 ± 0.033
4	50.00	7.00	1150.00	402.22 ± 2.83	0.1635 ± 0.013
5	33.30	4.00	1000.00	663.55 ± 8.69	0.535 ± 0.069
6	33.30	16.00	700.00	740.45 ± 1.2	0.3645 ± 0.036
7	66.70	16.00	1300.00	566.7 ± 0.14	0.2515 ± 0.043
8	66.70	16.00	700.00	622.4 ± 0.85	0.1115 ± 0.153
9	50.00	10.00	850.00	416.84 ± 8.88	0.3215 ± 0.027
10	33.30	4.00	1300.00	431.5 ± 2.12	0.148 ± 0.132
11	33.30	10.00	1300.00	385.5 ± 21.25	0.3895 ± 0.062
12	66.70	4.00	700.00	370.7 ± 6.78	0.0363 ± 0.009
13	33.30	4.00	700.00	478.25 ± 3.04	0.473 ± 0.0255
14	50.00	16.00	1300.00	378.8 ± 1.55	0.122 ± 0.029
15	66.70	4.00	1300.00	547.65 ± 12.79	0.129 ± 0.0594
16	33.30	10.00	1300.00	388 ± 2.98	0.405 ± 0.064

Regarding the PDIs, it ranged from 0.0363 ± 0.009 to 0.535 ± 0.069. It is noticeable that PDIs are relatively low, indicating narrow particle size distribution. This could prove the efficiency of the double desolvation method in producing uniform particle size owing to the process of discarding the low and intermediate molecular weight gelatin which is not involved in the formation of nanoparticles in the first desolvation step as discussed in the previous section.[15] The data statistical analyses, 3D and contour plots, and the generated model diagnostics and validation are found in the Supporting Information, Table S1 and Figures S1–S4.

Allicin-Loaded GNPs

Entrapment Efficiency of Allicin-Loaded GNPs

Allicin was entrapped in the optimized gelatin nanospheres with an average entrapment efficiency of 39.13 ± 2.38%. This moderate efficiency could be attributed to the hydrophilic nature of allicin that may lead to its easy leakage in the aqueous environment during or after the preparation of the nanoparticles.[16,17]

Particle Size and PDI Measurement

The results of allicin-loaded optimized formulation were insignificantly different at P < 0.05 compared to its plain counterpart where the results of particle size and PDI measurements were 371.9 ± 5.54 and 0.0313 ± 0.007, respectively. This indicates the efficient and homogeneous incorporation of allicin throughout the matrix of the produced nanospheres being both hydrophilic in nature.

Transmission Electron Microscopy

Transmission electron microscopy (TEM) morphological examination for the prepared allicin-loaded GNPs revealed that particles were spherical and homogeneous with the absence of any aggregates (Figure ). Moreover, the indicated particle size for the GNPs showed a good correlation with particle size measurements obtained by the dynamic light scattering (DLS) method except that the latter method provided slightly larger particle size as DLS measures the hydrodynamic diameter of the particles and on an intensity-based manner so that the latter method is relatively sensitive to the formation of aggregates and is biased toward the larger particles.[15]

Figure 2

TEM images for the prepared allicin-loaded GNPs at a magnification power of 50 000× for (A,C) and 25 000× for (B).

Confirming Glycyrrhetinic Acid Conjugation Using 1H NMR Spectroscopy

Glycyrrhetinic acid showed the carboxylic OH peak at 11 ppm (the most deshielded), the peak of the allylic double bond in the cyclohexene at 5.4 ppm, and the aliphatic region at 0.5–2.5 ppm as illustrated in the Supporting Information, Figure S5A. Referring to the Supporting Information, Figure S5B, it displayed the unconjugated allicin-loaded GNPs. The chemical conjugation of glycyrrhetinic acid to allicin-loaded GNPs was confirmed by the Supporting Information, Figure S5C where the disappearance of the peak for the carboxylic OH proton of glycyrrhetinic acid (11 ppm) proved the formation of the amide bond between the carboxylic OH of glycyrrhetinic acid and the amino groups of gelatin. Also, the presence of the allylic double bond peak in the cyclohexene (5.4 ppm) and the aliphatic region (0.5–2.5 ppm) emphasizes this conjugation as clearly depicted in the Supporting Information, Figure S5D.

In Vitro Release Study of Allicin-Loaded GNPs

Enzymatic degradation of GNPs within the body can occur inside the cell after internalization of the particles or outside the cell by other extracellular proteases at neutral or acidic pH.[18]

After 24 h incubation in phosphate-buffered saline (PBS) of pH 7.4 in the presence of collagenase, GNPs showed a cumulative percent released for allicin of 96.04 ± 2.2%, whereas after the same time interval in the absence of collagenase, GNPs appeared to be more stable with only 46.61 ± 3.55% of cumulative allicin percent released. Thus, in the presence of collagenase, almost all of the allicin were resolved after 24 h. Both release profiles are biphasic with similar release behavior, exhibiting a relatively rapid release within the first 8 h, then a more sustained release pattern evidenced until the end of the experiment (24 h). This behavior can be explained by the distribution of allicin within the GNPs. Being a denaturated protein, gelatin is built up of amino acid backbone. Accordingly, proteolytic enzymes are expected to play a pivotal role in the release of the entrapped drugs from the gelatin matrix when used as a drug delivery system.[19] This enzymatic degradation of GNPs within the body can occur inside the cell after internalization of the particles or outside the cell by other extracellular proteases at neutral or acidic pH.[18] Allicin release from the prepared optimized GNPs was believed to be governed by three concomitant mechanisms, namely, the release of the surface-electrically bound allicin, the diffusion of allicin from the GNP matrix to the release medium, and the erosion of the gelatin matrix due to dissolution in the aqueous release medium or/and digestion via proteolysis.[20] Considering these overlapping mechanisms, allicin in vitro release was evaluated in both the presence and absence of collagenase enzyme.

It is obvious that both release profiles (Figure ) are biphasic with the same release behavior, exhibiting a relatively rapid release within the first 8 h followed by a more retarded release pattern evidenced until the end of the experiment (24 h). This behavior can be explained by the dual distribution of allicin within the GNPs, adsorbed electrostatically to the surface and entrapped throughout the gelatin matrix. In the presence of collagenase enzyme, release occurred owing to combined mechanisms of drug diffusion and matrix erosion because of both dissolution of gelatin in the aqueous medium and proteolytic activity of collagenase.

Figure 3

In vitro release profiles of allicin from the prepared GNPs in PBS of pH 7.4 with and without collagenase.

During the first 2 h, ∼20% of allicin was released because of the fast liberation of the surface-bound allicin together with the digestion of the gelatin matrix. PBS of pH 7.4 serves as an alkaline medium for the GNPs (IEP of ∼5.7); hence, the surface positive charge decreases because of the suppressed protonation of the amino groups and facilitates the release of the surface-bound negatively charged allicin.[21]

Subsequently, from 2 to 4 h, the rate of release was decreased as it was limited by the slow diffusion of allicin from the cross-linked gelatin matrix in addition to the digestion of this matrix. Moreover, the deterioration of the matrix by the action of collagenase enzyme substantially increased the rate of allicin release during the period from 4 to 8 h. Therefore, the release of ≈80% was achieved during the first 8 h. Afterward, the inner collapsed core of the gelatin matrix retarded the release of the remaining allicin in a sustained slow manner.

In the case of absence of collagenase, the same behavior was evidenced except for the lack of the proteolytic effect on digesting the gelatin matrix. Initially, a rapid release of only ≈40% was evidenced during the first 8 h. However, nearly another 5% was released for the end of 24 h where the release of allicin depended only on its diffusion and the slow dissolution of the cross-linked gelatin matrix.

Accordingly, after 24 h incubation in PBS of pH 7.4 in the presence of collagenase, GNPs showed a cumulative percent release for allicin of 97.71 ± 2.02%, whereas after the same time interval in the absence of collagenase, only 51.74 ± 1.27% of cumulative allicin percent was released.

In vivo, being in the systemic circulation, GNPs were reported to distribute rapidly into the liver and the spleen and phagocytozed by liver Kupffer cells.[22] Synergistically, in the case of hepatocellular carcinoma, GNPs would passively accumulate in the hepatic tissue by the enhanced permeability and retention effect.[23,24] Following endocytosis of A-GNPs, allicin release would be augmented via the intracellular lysozymes and the hyperenzyme activity of the over expressed matrix metalloproteases inside hepatic cancer cells.[25,26]

Cytotoxicity of the Conjugated and Unconjugated Allicin-Loaded GNPs on HEPG-2 Cells

MTT assay was employed to measure the viability of HepG-2 hepatocellular cancer cells after 24 h incubation of different concentrations of both unconjugated and conjugated allicin-loaded GNPs. Both showed significantly enhanced cytotoxic effect where the IC50 of the unconjugated particles was 10.95 μM, whereas that of the conjugated particles was 5.046 μM. Compared to native allicin (IC50 of 19.29 μM), the cytotoxic potential was improved by approximately twofold for the unconjugated allicin-loaded GNPs and by fourfold for the conjugated allicin-loaded GNPs (Figure ). This improvement can be ascribed to the encouraged passive endocytosis occurred because of the formulation of allicin in a nanocarrier for the unconjugated nanoparticles.[27] Regarding the conjugated nanoparticle, the cytotoxic ability of allicin was further improved because of the presence of glycyrrhetinic acid molecules which actively increase the internalization of the nanocarriers inside the hepatic cells as a result of a highly specific interaction between glycyrrhetinic acid and its receptors displayed on the surface of the hepatic cell, namely, ASGPR.[2,15] Glycyrrhetinic acid was previously reported to increase the uptake of nanoparticles by liver cells.[28] Hence, allicin exerted the same inhibitory effect at a much lower molar concentration.[29] Moreover, glycyrrhetinic acid and its related compounds were found to induce G1 arrest and apoptosis in HepG-2 cell lines, in addition to its hepatoprotective effect.[30]

Figure 4

Cytotoxicity of unconjugated and conjugated allicin-loaded GNPs on HepG-2 cells.

Interaction of Glycyrrhetinic Acid with Hepatic ASGPRs Illustrated Using Molecular Docking Studies

The docking of glycyrrhetinic acid on the carbohydrate part of the liver ASGPR (lectin) was successful, scoring a binding energy of −11.53 ± 0.50 kcal/mol indicating a good ligand–receptor interaction. Figure demonstrates the successful fitting of glycyrrhetinic acid on the protein receptor and explains the type of interaction as hydrogen bonding between the hydroxyl group of glycyrrhetinic acid and the arginine residue of the ASGPR. These results boast the explanation of the decreased IC50 scores because of better internalization of the glycyrrhetinic acid-conjugated particles as a direct result of this type of carbohydrate–lectin interaction.

Figure 5

Interaction of glycyrrhetinic acid with the ASGPR. Molecular docking displayed in (A) 2D and (B) 3D images.

Conclusions

Glycyrrhetinic acid-conjugated allicin-loaded GNPs pose a successful, safe, and economic remedy for hepatocellular carcinoma that can be rapidly processed to animal and human studies. The development of this new remedy from completely natural components (drug + carrier + targeting moiety) is an additional asset.

Experimental Section

Materials

Gelatin type A from porcine skin (bloom 300), GA (25% solution in water), glycine, 1-ethyl-3-(3-dimethyl-aminopropyl)carbodiimidehydrochloride (EDC), diethylpyrocarbonate, glycyrrhetinic acid, and collagenase from Clostridium histolyticum in addition to the chemicals that were used in the cytotoxicity studies: dimethyl sulfoxide (DMSO), MTT, and trypan blue dye were purchased from Sigma, St. Louis, Mo., USA. Acetone was purchased from Labscan, Dublin, Ireland. Allicin was purchased from Jiangsu chiataiqingjiang Pharmaceutical Co., Ltd., China. Spectra/Por dialysis membrane, 12 000–14 000 molecular weight cutoff, was purchased from Spectrum Laboratories Inc., Rancho Dominguez, Canada.

Methods

Preliminary Screening of Different Human Cancer Cell Lines for Allicin Cytotoxicity

In order to evaluate the cytotoxic effects of allicin, different human cancer cell lines were used, specifically, human hepatocellular cancer cell line (HepG-2), human prostate cancer cell line (PC-3), human lung cancer cell line (A-549), and human breast cancer cell line (MCF-7).

The cells were grown on the RPMI-1640 medium supplemented with 10% inactivated fetal calf serum and 50 μg/mL gentamycin. The cells were maintained at 37 °C in a humidified atmosphere with 5% CO2 and were subcultured two to three times a week. The cytotoxicity was evaluated using viability assay and using MTT test. The used technique is detailed in the Supporting Information.

Experimental Design and Preparation of Plain GNPs

GNPs were prepared using the method of double desolvation. Minor changes were made to the procedure which is described in the literature by Coester and his colleagues.[31] In addition, the D-optimal experimental design was applied to optimize the independent factors of the method, namely, the amount of the used cross-linker (GA), cross-linking times (4, 10, and 16 h), and stirring speeds (700, 1000, and 1300 rpm). The amount of GA added was expressed either as percentages (33.3, 50, and 66.7% w/w) or as gelatin[NH/GA[CHO] molar ratios (1:0.5, 1:1, and 1:2, respectively). Briefly, 1.25 g of gelatin A (bloom 300) was dispersed in 25 mL of purified deionized water under continuous mechanical stirring at 500 rpm, and the temperature was kept at 40–45 °C. The first desolvation step is then performed to precipitate the HMW gelatin chains which will be then used in the formation of the nanospheres. As a desolvating agent, 25 mL of acetone was added to the gelatin dispersion and shortly incubated for 1 min to ensure complete precipitation of HMW gelatin. The supernatant was discarded, and the precipitate was redispersed in another 25 mL of purified deionized water at 40–45 °C using mild stirring. The gelatin dispersion was then retained acidic to pH 2.5 using 2–3 drops of 5 M HCl. The second desolvation step is the key step in forming the nanoparticles where the gelatin dispersion was titrated with 75 mL of acetone dropwise at 40–45 °C under stirring speeds that were adjusted according to the design. For stiffening of the GNPs, different amounts of the cross-linker GA (25% v/v) were added to the nanoparticle dispersion for different time intervals to initiate intraparticular cross-linking. To stop the action of GA at the end of a given time interval, the glycine solution (751 mg/100 mL) was added to block its carboxylic groups. The mixture was stirred at 500 rpm for 1 h. Eventually, the GNPs were purified by triplicate centrifugation/redispersion cycles in purified deionized water.

Determination of the Practical Yield of the Prepared Plain GNPs

The optimum formulation of plain GNPs was used for the determination of the practical amount of the produced GNPs by the adopted double desolvation method where the GNPs were prepared at the gelatin[NH/GA[CHO] ratio equals 1:2, stirring rate of 700 rpm, and 4 h of cross-linking. The produced nanoparticle dispersion was then lyophilized (Eyela FDU-2100, Japan), and the weight of the lyophilizate was determined. During the preparation of the GNPs and after the precipitation of the HMW gelatin in the first desolvation step, the formed gel-like precipitate was left to dry in the desiccator under vacuum for 48 h and then was also weighed.

The percentage yield of the produced nanoparticles was calculated in relation to both the weight of the initial added amount of gelatin (1.25 g) and to the weight of the gel-like precipitate containing the HMW gelatin. Thus, the following equations were applied

Particle Size and PDI Measurements for the Prepared Plain GNPs

Plain GNPs were subjected to the DLS technique in order to determine their hydrodynamic diameters using a Malvern Zetasizer (Nano ZS, Malvern, Worcestershire, UK). The parameters of the measurement were adjusted so that the viscosity of pure water was 0.8872 cP at 25 °C. Data of the particle size were described as an average mean size. PDIs were measured using the same instrument under the same conditions. All readings were in triplicates.

Preparation and Characterization of Allicin-Loaded GNPs

The preparation of allicin-loaded GNPs was achieved by using the optimized formula (stirring rate of 700 rpm, gelatin[NH/GA[CHO] ratio of 1:2 and 4 h cross-linking time). Incorporation of allicin to GNPs was achieved by adding 50 mg of allicin powder to the 25 mL of purified deionized water which was used for the redispersion of the gel-like precipitate formed after the first desolvation step. Before the addition of allicin solution, the solution was filtered in a 25 mL volumetric flask using a filter paper of pore size 90 mm. Afterward, the volume of the solution was adjusted to 25 mL. The absorbance of allicin solution was then measured spectrophotometrically using the spectrophotometer (Jasco—V-630, Japan) at λmax of 282.1 nm and compared to a preconstructed calibration curve of allicin in deionized water to get the actual amount of allicin used.

Entrapment Efficiency Calculation for Allicin-Loaded GNPs

For the determination of entrapment efficiency (% EE), the prepared allicin-loaded nanoparticles were centrifuged at 15 000 rpm at room temperature for 45 min using the freeze centrifuge (Sigma—2-16 KL, Germany). The supernatant was discarded, and the formed nanoparticle cake was digested in 100 mL of 0.1 N HCl so as to release the entrapped allicin where its amount was also determined spectrophotometrically using the same instrument (Jasco—V-630, Japan) against a preconstructed calibration curve of allicin in 0.1 N HCl at λmax of 282.4 nm. At the end, the entrapment efficiency was calculated as percentage drug entrapped using the following equation

Particle Size and PDI Measurements for Allicin-Loaded GNPs

Particle size and PDI was measured for the prepared allicin-loaded GNPs similarly to those for the plain GNPs explained in Section 2.2.3.

Transmission Electron Microscopy

TEM JEM-1400 (JEOL, Tokyo, Japan) was used to investigate the morphology and homogeneity of the prepared allicin-loaded GNPs at 80 kV voltage. The sample of GNP suspension was prepared by mounting on a carbon-coated copper grid and left for air drying at room temperature before imaging.

Conjugation of Allicin-Loaded Nanoparticles with Glycyrrhetinic Acid for the Enhanced Hepatocellular Uptake

As a preparatory step, the optimized allicin-loaded GNP dispersion was purified using a dialysis membrane (12 000–14 000 molecular weight cutoff) in a dialyzing medium consisting of distilled water for 96 h with mild stirring. The dialysis medium was replaced every 2 h.

To 50 mL of the purified allicin-loaded GNP dispersion, glycyrrhetinic acid was added in a ratio of 1:10 by weight glycyrrhetinic acid/GNPs. For ionization of the carboxylic groups of glycyrrhetinic acid, the medium was rendered alkaline at pH 9 using 5 M NaOH. The mixture was vigorously stirred till complete dissolution of glycyrrhetinic acid; then, EDC was added in amount equal to that of glycyrrhetinic acid. EDC was used as a carboxyl activating agent for the coupling of primary amines of gelatin amino acids to yield amide bonds with carboxylic groups of glycyrrhetinic acid.[29,32] Stirring was continued for 3 h at room temperature, and then the produced conjugated allicin-loaded GNP dispersion was purified by dialysis as previously explained.

1H NMR Spectroscopy for the Conjugated Allicin-Loaded GNPs

1H NMR spectroscopy was performed for each of glycyrrhetinic acid, bare allicin-loaded GNPs (unconjugated), and conjugated allicin-loaded nanoparticles. All liquid samples were lyophilized (Eyela FDU-2100, Japan) and then dissolved in a mixture of deuterated acetic acid and DMSO, and their NMR spectra were recorded on a 400 MHz NMR spectrometer (Bruker AVANCE III Switzerland). The produced charts were compared to confirm the conjugation of glycyrrhetinic acid molecules with the GNPs.

In Vitro Release Study of the Conjugated Allicin-Loaded GNPs

The release behavior of allicin from the conjugated GNPs in PBS of pH 7.4 was investigated in both the presence and the absence of collagenase enzyme. For different time intervals (2, 4, 6, 8, and 24 h), 2 mL of the conjugated allicin-loaded GNP dispersion was incubated in an Eppendorf tube at 37 ± 1 °C in 1 mL of PBS pH 7.4 with or without 2 μg/mL collagenase under continuous shaking at 100–120 rpm. At the end of each time interval, the suspension was centrifuged at 12 000 rpm for 30 min. The amount of allicin in the supernatant was determined spectrophotometrically (Jasco—V-630, Japan) at λmax of 283.2 nm, and the percent released was calculated.

Cytotoxicity Study of the Conjugated and Unconjugated GNPs on the HepG-2 Cell Line

Evaluation of the cytotoxic effect of both conjugated and unconjugated allicin-loaded GNPs on the human hepatocellular cancer cell line (HepG-2)[33] was conducted following the same method described in Section . The purpose of this final cytotoxicity study was to explore the enhanced antitumor potential of allicin in unconjugated and conjugated GNPs compared to native allicin, that is, the effect of nanonization and ligand–receptor binding on drug internalization, cellular uptake, and the consequent antitumor effect.

Investigating Glycyrrhetinic Acid–ASPGR Interaction Using Molecular Docking Studies

The crystal structure of the carbohydrate recognition domain of the H1 subunit of the ASGPR was obtained from the RCSB protein data bank (https://www.rcsb.org/) with a code of 1DV8. The isomeric SMILES corresponding to the chemical structure of the studied ligand (carbohydrate); glycyrrhetinic acid was obtained using PubChem. The corresponding 3D chemical structures were generated using the builder function of MOE version 2014.0901 (Chemical Computing Group Inc., Montreal, Canada). Further, energy minimization was performed using MMFF94x forcefield of the same software.[34−36] The docking analysis was employed using MOE version 2014.0901 (Chemical Computing Group Inc., Montreal, Canada). The pdb file of the protein nanoparticle matrix was imported to MOE where the identification of the binding sites was performed using the MOE’s “Site finder” tool[37] to be ready for docking using the “triangle matcher” as a placement method. This software creates dummy atoms around the docking target atoms. These dummy atoms are considered the docking positions. The software-integrated London score was utilized for calculating the binding energy scoring value.[38−41]