ISSN: 0973-7510
E-ISSN: 2581-690X
, Putu Angga Wiradana2, Anak Agung Ayu Putri Permatasari2, I Gede Widhiantara2, Novaria Sari Dewi Panjaitan3, Arif Nur Muhammad Ansori4, Komang Januartha Putra Pinatih5, I Made Jawi6 and Ketut Suastika7Red ginger rhizome (Zingiber officinale var. Rubrum) and avocado leaves (Persea americana Mill.) are empirically known as one of the medicinal plants used in Taro Village, Gianyar Regency, Bali which have great potential in treating infectious diseases caused by antibiotic resistance, such as MRSA. This study aims to analyze the phytoconstituents and anti-MRSA potential contained in red ginger rhizome and avocado leaves extracts by assessing their inhibitory effects on three proteins related to MRSA resistance and virulence (PBAP2a, transglycosylase, and glycosyltransferase). Phytoconstituents of avocado leaf and red ginger extracts were analyzed using GC-MS. Molecular docking was performed in silico to determine the similarity properties of predicted drugs, bioactivity, toxicity, identification of active sites and validation of protein structures, and docking simulations were performed between compounds found in the extract and their target proteins. Phytoconstituent analysis revealed that avocado leaves and red ginger extracts as a whole have 43 types of compounds and 10 bioactive compounds each with beneficial drug-like properties. The compound 6,11-hexadecadien-1-ol from avocado leaves extracts was predicted to have hepatotoxic properties. There were at least 3 compounds, namely beta-bisabolene from avocado leaves extract, zingiberenol and gamma-curcumene from red ginger rhizome extract, showing the lowest binding affinity for the target protein. Red ginger rhizome and avocado leaves extracts showed valuable potential as anti-MRSA agents through the mechanism of inhibition of three resistance-related proteins, as predicted by in silico analysis.
Antimicrobial Resistance, Penicillin-binding Protein-2a, Transglycosylase, Glycosyltransferase, MRSA
Antimicrobial resistance is one of the most significant public health issues facing the globe today (AMR). Antimicrobial resistance (AMR) is expected to cause significant clinical losses, severe economic consequences, and the loss of 10 million lives annually by 2050, according to the highly cited review on antimicrobial resistance.1 According to a recent systematic investigation, AMR bacteria were responsible for 4.95 million deaths in 2019, and 1.27 million of them were directly related to AMR.2 Based on the results of the Global Burden of Disease, Injuries, and Risk Factors (GBD) research, AMR was reported as the third most common cause of death after ischemic heart disease and stroke.3 The stages of the process of bacterial resistance to antibiotics include; (i) genetic mutations in bacteria; (ii) overuse of broad-spectrum antibiotics; and (iii) bacteria form a biofilm which functions as a protector so that the bacteria are resistant to antibacterials.4-6
Methicillin-resistant Staphylococcus aureus (MRSA) is the second most common cause of antibiotic-resistant bacterial infections in many European countries,7 America,8 Africa,9 Australia7 to Asian countries10 and including in the Southeast Asian region such as Indonesia.11-13 The prevalence of MRSA infection in the world varies from 1% to 50% in each country. Asian countries have the highest prevalence of MRSA in the world, with about 50% of these bacteria causing circulatory infections.4 Research conducted in the Asia-Pacific region shows that the population with MRSA carriers reaches 23.5%.15 The prevalence of MRSA infection in Indonesia was reported around 0.3%-51% with the highest prevalence found in Aceh (50%)16 and Jakarta reaching 47%.11
MRSA can survive and develop well after being captured by phagocytic cells.17 The invading cells actually protect the bacteria from the bactericidal action of commercial antibiotics, thus causing resistance to infection. The current problem is that the treatment of intracellular infections requires long-term and intensive administration of antibiotics, however, most antibiotics are reported to fail to kill intracellular bacteria due to low intracellular accumulation, short retention, or reduced antibacterial action in cells. Interestingly, MRSA is also capable of producing a series of virulence factors that trigger infection, such as the penicillin-binding protein 2a (PBP2a) receptor, transglycosylase and glycosyltransferase. These receptors are known to have an important role as an inhibitor of the activity of b-lactam antibiotics in the resistance mechanism of MRSA bacteria.18
Natural antibacterial drugs have emerged as a replacement solution for conventional antibiotics in the treatment of drug-resistant intracellular bacteria. Natural bactericides have the advantage of being easily accessible and having a wider range of use than standard antibiotics.19,20 It should be noted that natural antibacterials exhibit bactericidal effects through multiple pathways, making the development of resistance an interesting challenge to be further studied through in silico studies on these virulence factor-associated proteins in MRSA. Gingerol, is an important component of red ginger rhizome extract which is popular as a natural antibacterial compound. Gingerol has high biocompatibility as a “green” bactericide and its antibacterial activity had been documented.21 Several previous studies stated that gingerol specifically inhibited the expression of several pore-forming toxins which are important components of bacterial virulence factors. However, the single antibacterial activity exerted by red ginger rhizome extracts is lower than other popular antibiotics, thereby reducing its practical use and efficacy.
The combination of traditional Balinese medicine (Usaddha) to prevent and treat infectious diseases has recently attracted increasing attention. Therapy using a combination of natural ingredients was known as polyherbal therapy which had a tendency to produce synergistic therapeutic effects,22 which was caused by the action between the active ingredients contained in each ingredient.23 The ingredients stated refers to natural ingredients that have been used traditionally by people in Indonesia, especially in Taro Village, Gianyar Regency, Bali Province, whom for generations have used red ginger infusion combined with boiled avocado leaves which can empirically be effective in providing a therapeutic effect. The extracts of avocado leaves contain active antibacterial compounds such as alkaloids, saponins and flavonoids.24
However, there are still no reports that reveal the phytoconstituent components of red ginger and avocado leaves and the effectiveness of their active compounds in inhibiting proteins that produce virulence factors in MRSA. Molecular docking using an in silico approach is a computational method used for the discovery of new drug candidates.25 This makes it possible to discover and identify key compounds with therapeutic potential, namely evaluation of effectiveness, prediction of molecular interactions, and drug toxicity.26 Some in silico studies have reported the effectiveness of certain traditional medicines, such as Stachytarpheta jamaicensis which could be found in Indonesia, as traditional plants with antibacterial active compounds. Based on previous report, docking in silico using Autodock Vina integrated with PyRx 8.0 showed that S. jamaicensis, a wild plant from the Verbenanceae, has the best binding affinity with luteolin-G1mS complex. Therefore, in this study, the extracts of red ginger rhizome and avocado leaves were used to screen their phytoconstituent composition using GC-MS and several phytochemicals were selected for in silico screening and evaluated for their interactions on the penicillin-binding protein 2a (PBAP2a), transglycosylase and glycosyltransferase receptors in MRSA. This research is very useful for revealing new phytochemicals from local plants that can play a role in the development of natural antibacterials through inhibitor mechanisms.
Plant sample extraction and phytoconstituent profiling
The red ginger and avocado leaves used in this research came from the Satya Kencana Banjar Tebuana Farmers Group Garden, Taro Village, Tegalalang District, Gianyar Regency, Bali Province. The voucher specimens were preserved in the “Eka Karya” Bali-BRIN Botanical Garden Characteristics Laboratory (accession no: ELSA 35877 and ELSA 35901). Fresh red ginger rhizomes and avocado leaves were washed with clean water to remove foreign contaminants or organic matter. The samples were dried at room temperature to remove water before being dried for 24 hours in a 50°C oven. To obtain powder preparations, the dried samples (simplisia) were pulverized using a grinder and sieved with a 20-mesh sieve. The extraction process was carried out using a maceration method using ethanol 96% in a ratio of 1:10 w/v (200 grams of simplicia powder with 2000 mL of solvent) for 3 × 24 hours. It was evaporated using a vacuum rotary evaporator until a thick extract was produced,27 which was then combined.
The phytoconstituent profile of red ginger rhizome and avocado leaves extracts was evaluated using GC-MS (QP 2010, Shimadzu). The bioactive compounds contained in the extract were identified by comparing the retention time and patterns of mass peak with reference to the database of the National Institute of Standards and Technology (NIST) and the Wiley Registry of Mass Spectral Data, New York.28 Compounds were identified by comparing sample MS spectra with the WILEY229 Library and the NIST62 database.29,30
In Silico analysis
Ligand preparation
The chemical compounds used in this research came from the results of chromatography with ethanol solvent on avocado leaves consisting of benzene, 1-(1,5-dimethyl-4-hexenyl)-4-methyl- (CAS), zingiberene- (CAS), E,E-alpha-farnese, beta-bisabolene- (CAS), beta-sesquiphellandrene- (CAS), neophytadiene, tetradecanoic acid, ethyl ester- (CAS), 6,11-hexadecadien-1-ol, 9,12-octadecadienoic acid, methyl ester, (E,E)- (CAS), and ethyl oleate. Meanwhile, red ginger rhizome extracts consist of octanal (CAS), endo-borneol, decanal-(CAS), 2,6-octadienal, 3,7-dimethyl-, (Z)-, geraniol, gamma-curcumene, widdrene, zingiberenol, d-nerolidol, and trans-6-shogaol. Ligand sample preparation was carried out through the PubChem database (https://pubchem.ncbi.nlm.nih.gov/) to obtain several information such as CID, compound link, and 3D structure with structure data format (sdf) files.31
Protein preparation
The targets in this research are several proteins from MRSA consisting of penicillin-binding protein 2a (PBP2a) (RCSB ID: 5M18), transglycosylase (RCSB ID: 3VMT), and glycosyltransferase (RCSB: 6FTB). PBP2a in MRSA has an important role as an inhibitor of β-lactam antibiotic activity in the resistance mechanism. The activity of transglycosylase and glycosyltransferase enzymes plays a role in cell wall synthesis in MRSA, both of which have a relationship in the resistance mechanism, which triggers bacteria to adapt to various environments including antibiotics.32 The 3D structure of each target was obtained from RCSB PDB (https://www.rcsb.org/) with pdb files.
Drug-likeness assay
The similarity of the activity of the query compound with the drug molecule is predicted via the SCFBio server (http://www.scfbio-iitd.res.in/software/drugdesign/lipinski.jsp) using the Lipinski Rule of Five’s method. These rules refer to physicochemical parameters consisting of molecular mass, lipophilicity, donor-acceptor hydrogen bonds, and molar refractivity. Compounds with positive prediction results are categorized as drug-like molecule.33
Prediction of bioactivity and toxicity probabilities
The bioactivity test in this study refers to the probability of being antibacterial, the test was carried out via the PASS Online server (http://www.pharmaexpert.ru/passonline/). This prediction refers to an activation probability Pa ≥ 0.3 to trigger the emergence of antibacterial activity of the query compound and the Pa value must be greater than the inhibition probability (Pi).34 Toxicity predictions for compounds with antibacterial activity values, namely Pa ≥ 0.3, are carried out via the ProTox-II server (http://tox.charite.de/protox_II/), the toxicity prediction results obtained are the possible carcinogenicity, hepatoxicity and LD50 values of the query compounds.35
Molecular docking simulation
Molecular docking simulation Ligands in sdf format were minimized for increased structural flexibility and conversion of sdf files into protein databank format (PDB) via OpenBabel v2.3.2 software. The energy minimization process is included in the preparation stage for molecular docking simulations with specific targets. Sterilization of target proteins was carried out in this study using PyMOL v.2.5.2 software (Schrodinger, Inc., USA) with an academic license. Sterilization of 3D structures refers to the removal of water molecules on the target for preparation and optimization of molecular docking. Docking analysis aims to identify the inhibitory activity of the ligand on its target. This refers to the binding affinity value. The increasingly negative binding affinity value triggers an increase in the binding strength of the ligand to the target. This research uses PyRx v1.0.0 software (Scripps Research, USA) with an academic license for molecular docking simulations carried out with a grid position covering all targets at the XYZ center position and dimensions.36
Chemical bond interactions
Identification of the position and type of chemical bond interactions in the ligand-protein complex was carried out using LigPlot +v.2.2 software. Weak bonds such as hydrogen and hydrophobic can be formed when a ligand binds to the target domain, this aims to trigger a biological response such as inhibition of activity. The existence of these bonds can affect the stability of drug candidates.37
Visualization of 3D structure
The 3D structure from the molecular docking simulation results is displayed in the form of cartoons, transparent surfaces, and sticks with color selection using PyMOL v.2.5.2 software (Schrodinger, Inc., USA) with an academic license. Molecular visualization aims to display the 3D structure of ligand-protein with a representative appearance through structural and color selection methods with publication standards.38 Table 1 below shows the detailed identification and reported concentrations of chemicals in each red ginger and avocado leaves extract solvent.
Table (1):
Phytoconstituents of red ginger rhizome and avocado leaf extracts were identified by GC-MS analysis
| No. | Chemical compound | Retention Time | Peak Area (%) | Formula | |||||
|---|---|---|---|---|---|---|---|---|---|
| Red Ginger | Avocado leave | ||||||||
| 1 | Octanal (CAS) | 6.120
6.111 |
2.01
– |
–
– |
C8H16O | ||||
| 2 | endo-Borneol | 9.765 | 1.19 | – | C10H18O | ||||
| 3 | Decanal (CAS) | 10.441 | 4.51 | – | C10H20O | ||||
| 4 | 2,6-Octadienal, 3,7-dimethyl-, (Z)- | 11.436 | 1.26 | – | C10H16O | ||||
| 5 | GERANIOL | 11.958 | 2.41 | – | C10H18O | ||||
| 6 | 2,6-Octadien-1-ol, 3,7-dimethyl-, acetate (CAS) | 15.147 | 1.85 | – | C12H20O2 | ||||
| 7 | gamma-curcumene | 17.790 17.775 |
2.10 | – | C15H24 | ||||
| 8 | Benzene, 1-(1,5-dimethyl-4-hexenyl)-4-methyl- | 17.971 | 6.67 | 3.38 | C15H22 | ||||
| 9 | trans-Caryophyllene | 18.390 | 13.75 | – | C15H24 | ||||
| 10 | Thujopsene | 18.594 | 8.46 | – | C15H24 | ||||
| 11 | alpha-Himachalene | 18.668 | 3.28 | – | C15H24 | ||||
| 12 | (+)-Aromadendrene | 19.112 | 10.84 | – | C15H24 | ||||
| 13 | Elemol | 19.841 | 0.63 | – | C15H26O | ||||
| 14 | d-Nerolidol | 20.751 | 1.54 | – | C15H26O | ||||
| 15 | zingiberenol | 21.345 | 1.15 | – | C15H26O | ||||
| 16 | 1,2-diethoxy-4-ethylbenzene | 22.887 | 20.93 | – | C12H18O2 | ||||
| 17 | alpha-Bisabolol | 23.263 | 1.47 | – | C15H26O | ||||
| 18 | 6,10-Dodecadien-1-yn-3-ol, 3,7,11-trimethyl- (CAS) | 23.480 | 0.99 | – | C15H24O | ||||
| 19 | Campherenone | 26.153 | 1.32 | – | C15H24O | ||||
| 20 | 9,10-Dimethyltricyclo[4.2.1.1(2,5)]decane-9,10-diol | 27.525 | 1.10 | – | C12H20O2 | ||||
| 21 | Ethyl myristate | 29.444 | 2.34 | – | C16H32O2 | ||||
| 22 | Oleic acid | 32.839 | 3.54 | – | C20H38O2 | ||||
| 23 | (E)-4-(2′,6′,6′-Trimethyl-1′,2′-epoxycyclohexyl)-3-penten-2-one | 34.356 | 1.82 | – | C14H22O2 | ||||
| 24 | Shogaol | 35.669 | 2.77 | – | C17H24O3 | ||||
| 24 | Zingiberene (CAS) | 18.156 | – | 3.33 | C15H24 | ||||
| 26 | Alpha-Faresenne | 18.405 | – | 1.03 | C15H24 | ||||
| 27 | beta-Bisabolene (CAS) | 18.487 | – | 1.66 | C15H24 | ||||
| 28 | beta-Sesquiphellandrene (CAS) | 18.922 | – | 2.67 | C15H24 | ||||
| 29 | Neophytadiene | 26.139 | – | 0.54 | C20H38 | ||||
| 30 | Tetradecanoic acid, ethyl ester (CAS) | 29.464 | – | 29.12 | C16H32O2 | ||||
| 31 | 6,11-Hexadecadien-1-ol | 31.096 | – | 3.12 | C16H30O | ||||
| 32 | 9,12-Octadecadienoic acid, methyl ester, (E,E)- (CAS) | 32.727 | – | 3.84 | C19H34O2 | ||||
| 33 | Ethyl Oleate | 32.864 | – | 36.28 | C20H38O2 | ||||
| 34 | Dicyclohexyl-4,4′-diol | 33.102 | – | 0.49 | C12H22O2 | ||||
| 35 | Heptadecanoic acid, ethyl ester (CAS) | 33.303 | – | 4.27 | C19H38O2 | ||||
| 36 | 2,5-Furandione, 3-(dodecenyl)dihydro- | 34.372 | – | 1.26 | C16H26O2 | ||||
| 37 | Hexadecadienoic acid, methyl ester (CAS) | 34.500 | – | 1.22 | C17H30O2 | ||||
| 38 | Hexadecanoic acid, 2-hydroxy-1,3-propanediyl ester (CAS) | 35.240 | – | 1.78 | C35H68O5 | ||||
| 39 | Hexadecanoic acid, ethyl ester (CAS) | 36.850 | – | 0.90 | C18H36O2 | ||||
| 40 | D-Mannitol | 36.885 | – | 0.55 | C28H58O12 | ||||
| 41 | cis-9-Hexadecenal | 37.559 | – | 0.65 | C16H30O | ||||
| 42 | 13-Octadecenal, (Z)- | 38.319 | – | 2.79 | C18H34O | ||||
| 43 | 9-Eicosynee | 39.369 | – | 1.09 | C20H38 | ||||
In this research, the extraction was carried out using ethanol solvent to evaluate the impact of solvent polarity on the bioactivity produced from each extract. GC-MS analysis was used to determine the bioactive compound profile of each extract. In general, 43 chemical components were found with the following phytochemical content of red ginger rhizome extract: 1,2-diethoxy-4-ethylbenzene (20.93%), trans-caryophyllene (13.75%), (+)-aromadendrene (10.84%), thujopsene (8.46%), benzene, 1-(1,5-dimethyl-4-hexenyl)-4-methyl- (6.67%), decanal (4.51%), oleic acid (zingiberenol (1.15%)) and gamma-curcumin (2.10%). Meanwhile, in the extracts of avocado leaves, the main elemental composition is ethyl oleate (36.28%), tetradecanoic acid, ethyl ester (29.12%), 9,12-octadecadienoic acid, methyl ester, (E,E)- (3.84%), and benzene, 1-(1,5-dimethyl-4-hexenyl)-4-methyl- (3.38%).
The inclusion criteria for phytochemical compounds used as bioactive compounds must meet pharmacological and pharmacodynamic criteria. Based on their similarities as candidate medicinal ingredients, there are ten compounds each that meet the criteria of avocado leaves and red ginger rhizome extracts (Table 2). The target proteins used in this study were PBP2a (RCSB ID: 5M18), Transglycosylase (RCSB ID: 3VMT), and Glycosyltransferase (RCSB: 6FTB). 3D structure rendered via PyMOL v.2.5.2 (Schrodinger, Inc., USA) with an academic license with ster (Figure 1).
Table (2):
Ligand samples of red ginger rhizome and avocado leaves accessed from the PubChem database
| Sample name | Compounds | PubChem CID | Link |
|---|---|---|---|
| Avocado leaves | Benzene, 1-(1,5-dimethyl-4-hexenyl)-4-methyl- (CAS) | 577053 | https://pubchem.ncbi.nlm.nih.gov/compound/577053 |
| Zingiberene (CAS) | 92776 | https://pubchem.ncbi.nlm.nih.gov/compound/92776 | |
| E,E-Alpha-Farnesene | 5281516 | https://pubchem.ncbi.nlm.nih.gov/compound/5281516 | |
| beta-Bisabolene (CAS) | 10104370 | https://pubchem.ncbi.nlm.nih.gov/compound/beta-Bisabolene | |
| beta-Sesquiphellandrene (CAS) | 519764 | https://pubchem.ncbi.nlm.nih.gov/compound/beta-Sesquiphellandrene | |
| Neophytadiene | 10446 | https://pubchem.ncbi.nlm.nih.gov/compound/Neophytadiene | |
| Tetradecanoic acid, ethyl ester (CAS) | 31283 | https://pubchem.ncbi.nlm.nih.gov/compound/31283 | |
| 6,11-Hexadecadien-1-ol | 6440740 | https://pubchem.ncbi.nlm.nih.gov/compound/6440740 | |
| 9,12-Octadecadienoic acid, methyl ester, (E,E)- (CAS) | 3931 | https://pubchem.ncbi.nlm.nih.gov/compound/9_12-Octadecadienoic-acid | |
| Ethyl Oleate | 5363269 | https://pubchem.ncbi.nlm.nih.gov/compound/Ethyl-oleate | |
| Red Ginger | Octanal (CAS) | 454 | https://pubchem.ncbi.nlm.nih.gov/compound/454 |
| endo-Borneol | 6552009 | https://pubchem.ncbi.nlm.nih.gov/compound/6552009 | |
| Decanal (CAS) | 8175 | https://pubchem.ncbi.nlm.nih.gov/compound/8175 | |
| 2,6-Octadienal, 3,7-dimethyl-, (Z)- | 8843 | https://pubchem.ncbi.nlm.nih.gov/compound/8843 | |
| Geraniol | 637566 | https://pubchem.ncbi.nlm.nih.gov/compound/637566 | |
| gamma-curcumene | 12304273 | https://pubchem.ncbi.nlm.nih.gov/compound/12304273 | |
| Widdrene | 442402 | https://pubchem.ncbi.nlm.nih.gov/compound/442402 | |
| Zingiberenol | 13213649 | https://pubchem.ncbi.nlm.nih.gov/compound/13213649 | |
| d-Nerolidol | 5356544 | https://pubchem.ncbi.nlm.nih.gov/compound/5356544 | |
| trans-6-shogaol | 11152 | https://pubchem.ncbi.nlm.nih.gov/compound/11152 |
Figure 1. Visualization of target 3D structures in MRSA bacteria. (A) PBAP2a; (B) Transglycosylase; (C) Glycosyltransferase
Lipinski Rule’s of Five plays a role in identifying the similarity of query compounds with drug molecules through physicochemical parameters. These rules state that a query compound that is categorized as a drug-like molecule must fulfill at least two rules of five. These rules refer to the molecular mass must be below 500 Daltons, the high lipophilicity (LogP) must have a value smaller than 5, the number of donor hydrogen bonds must be less than 5 and the molar refractivity must have a value between 40-130.33 The drug-likeness prediction results for query ligands from avocado leaves and red ginger show that all chemical compound samples are drug-like molecules because they fulfill at least two rules in the Lipinski Rule’s of Five (Table 3).
Table (3):
The results of druglikeness prediction
| Source | Compounds | MM (<500 Dalton) | LogP (<5) | HBD (<5) | HBA (<10) | MR (40-130) | Probable |
|---|---|---|---|---|---|---|---|
| Avocado leaves | Benzene, 1-(1,5-dimethyl-4-hexenyl)-4-methyl- (CAS) | 204.000 | 4.924 | 0 | 0 | 68.282 | Drug-like molecule |
| Zingiberene (CAS) | 204.000 | 4.891 | 0 | 0 | 68.832 | Drug-like molecule | |
| E,E-ALPHA-FARNESENE | 204.000 | 5.201 | 0 | 0 | 70.992 | Drug-like molecule | |
| beta-Bisabolene (CAS) | 204.000 | 5.035 | 0 | 0 | 68.902 | Drug-like molecule | |
| beta-Sesquiphellandrene (CAS) | 204.000 | 4.891 | 0 | 0 | 68.832 | Drug-like molecule | |
| Neophytadiene | 278.000 | 7.167 | 0 | 0 | 94.055 | Drug-like molecule | |
| Tetradecanoic acid, ethyl ester (CAS) | 256.000 | 5.250 | 0 | 2 | 77.710 | Drug-like molecule | |
| 6,11-Hexadecadien-1-ol | 280.000 | 5.582 | 0 | 2 | 86.756 | Drug-like molecule | |
| 9,12-Octadecadienoic acid, methyl ester, (E,E)- (CAS) | 280.000 | 5.884 | 1 | 2 | 86.993 | Drug-like molecule | |
| Ethyl Oleate | 310.000 | 5.705 | 0 | 2 | 108.268 | Drug-like molecule | |
| Red Ginger | Octanal (CAS) | 128.000 | 2.545 | 0 | 1 | 39.439 | Drug-like molecule |
| endo-Borneol | 154.000 | 2.193 | 1 | 1 | 45.235 | Drug-like molecule | |
| Decanal (CAS) | 156.000 | 3.325 | 0 | 1 | 48.673 | Drug-like molecule | |
| 2,6-Octadienal, 3,7-dimethyl-, (Z)- | 152.000 | 2.877 | 0 | 1 | 48.485 | Drug-like molecule | |
| GERANIOL | 154.000 | 2.671 | 1 | 1 | 49.507 | Drug-like molecule | |
| gamma-curcumene | 204.000 | 5.035 | 0 | 0 | 68.902 | Drug-like molecule | |
| Widdrene | 204.000 | 4.559 | 0 | 0 | 64.652 | Drug-like molecule | |
| Zingiberenol | 222.000 | 4.086 | 1 | 1 | 70.316 | Drug-like molecule | |
| d-Nerolidol | 222.000 | 4.396 | 1 | 1 | 72.476 | Drug-like molecule | |
| trans-6-shogaol | 276.000 | 4.038 | 1 | 3 | 81.268 | Drug-like molecule |
Bioactivity prediction in this study refers to the probability level of antibacterial activity ability of the query compound which is indicated by the values of Pa dan Pi.34 Compounds with values of Pa ≥ 0.3 and Pa ≥ Pi show computationally proven antibacterial capabilities. The results of identifying bioactivity and toxicity in compounds from avocado leaves showed zingiberene (CAS), E,E-alpha-farnesene, beta-bisabolene (CAS), beta-sesquiphellandrene (CAS), neophytadiene, 9,12-octadecadienoic acid, methyl ester, (E,E)- (CAS), and compounds from red ginger extracts such as 2,6-octadienal, 3,7-dimethyl-, (Z)-, geraniol, gamma-curcumene, zingiberenol, and d-nerolidol have antibacterial activity and do not have carcinogenicity and hepatoxicity type toxins. The compound 6,11-hexadecadien-1-ol from the extract of avocado leaves was actually antibacterial but not used for further analysis because it had hepatoxicity type toxin activity (Table 4).
Table (4):
Bioactivity and toxicity prediction results
| Source | Compound | Antibacterial Activity | Toxicity Information | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Pa |
Pi |
Carcinogenicity | Hepatoxicity | LD50 (mg/kg) | ||||||
| Avocado leaves extracts | Benzene, 1-(1,5-dimethyl-4-hexenyl)-4-methyl- (CAS) | – | – | – | – | – | ||||
| Zingiberene (CAS) | 0.416 | 0.026 | Inactive | Inactive | 1680 | |||||
| E,E-Alpha-Farnesene | 0.459 | 0.021 | Inactive | Inactive | 3650 | |||||
| beta-Bisabolene (CAS) | 0.413 | 0.027 | Inactive | Inactive | 4440 | |||||
| beta-Sesquiphellandrene (CAS) | 0.441 | 0.023 | Inactive | Inactive | 5000 | |||||
| Neophytadiene | 0.363 | 0.040 | Inactive | Inactive | 5050 | |||||
| Tetradecanoic acid, ethyl ester (CAS) | – | – | – | – | – | |||||
| 6,11-Hexadecadien-1-ol | 0.310 | 0.056 | Inactive | Active | 1190 | |||||
| 9,12-Octadecadienoic acid, methyl ester, (E,E)- (CAS) | 0.335 | 0.047 | Inactive | Inactive | 10000 | |||||
| Ethyl Oleate | – | – | – | – | – | |||||
| Red ginger extracts | Octanal (CAS) | – | – | – | – | – | ||||
| endo-Borneol | – | – | – | – | – | |||||
| Decanal (CAS) | – | – | – | – | – | |||||
| 2,6-Octadienal, 3,7-dimethyl-, (Z)- | 0.371 | 0.038 | Inactive | Inactive | 500 | |||||
| Geraniol | 0.424 | 0.025 | Inactive | Inactive | 2100 | |||||
| gamma-curcumene | 0.367 | 0.039 | Inactive | Inactive | 1680 | |||||
| Widdrene | – | – | – | – | – | |||||
| Zingiberenol | 0.463 | 0.020 | Inactive | Inactive | 2340 | |||||
| d-Nerolidol | 0.462 | 0.020 | Inactive | Inactive | 5000 | |||||
| trans-6-shogaol | – | – | – | – | – | |||||
The molecular docking method used in this research is a blind type, ignoring the active site to screen for other potential binding sites on the target. Ligand activity is shown through the binding affinity value. Binding affinity refers to the negative binding energy formed in a ligand-protein complex. This energy works based on Gibbs’ law, namely, the more negative it is, the stronger the bonding interactions will trigger and trigger stability in the molecular complex formed. Ligands with the most negative binding affinity values can trigger inhibitory activity on targets.39,40 Grid docking plays a role in directing ligand binding to the target; the grid position in this study consists of PBP2a center (Å) X: 6.162 Y: -13.287 Z: -50.318 Dimension (Å) X: 115.233 Y: 92.017 Z: 134.318, transglycosylase center (Å) X: -22.275 Y: -2.201 Z: -3.133 Dimension (Å) X: 76.625 Y: 82.946 Z: 109.053 and glycosyltransferase center (Å) X: -35.030 Y: -27.001 Z: 62.281 Dimension (Å) X: 47.826 Y: 52.426 Z: 51.292.
Visualization of ligand-target protein interactions is displayed by staining proteins with different ligands. The chemical bond interactions formed in the complex resulting from docking are weak bonds such as hydrogen and hydrophobic which play a role in triggering biological responses, for example target inhibitory activity by ligands.41,42 The results of the research show that all antibiotic candidate compounds from the extracts of avocado leaves and red ginger, namely beta-bisabolene (CAS), zingiberenol, and gamma-curcumene can form weak bonds such as hydrogen and hydrophobic; this triggers inhibitory activity at the target receptor on MRSA (Figure 2).
Figure 2. 2D visualization of molecular interactions of ligands with targets. (A) PBAP2a_beta-bisabolene (CAS); (B) Transglycosylase_beta-bisabolene (CAS); (C) Glycosyltransferase_beta-bisabolene (CAS); (D) PBAP2a_zingiberenol; (E) Transglycosylase_zingiberenol; (F) Glycosyltransferase_gamma-curcumene
Several chemicals found in high concentrations in each extract material can be investigated for their potential as compound identities in an effort to standardize materials through the use of finding compound identity markers. Several compounds from each extract were screened to determine their effectiveness in silico in inhibiting receptors that generate virulence factors in MRSA. Several results of previous studies reported something similar to these results. Monoterpene and sesquiterpene hydrocarbon compounds were found to dominate the chemical composition of wild ginger extract.43
The bioactive compounds, including geranial, zingiberene, and -sesquiterpene, have been shown to be the main components in ginger plants, ranging from 10-60%.44,45 Apart from avocado leaves extracts, previous research also revealed that the bioactive compounds extracted from avocado seed powder are mostly terpenes and fatty acid derivative esters which have been proven to have bioactivity to alleviate nephrotoxicity and hepatoprotective properties induced by cyclosporine-A (CsA).46,47 The marker compound for avocado seed extract is known to be flavon C-glycoside based on its metabolite characteristics. Naringenin is one of the main flavanones detected together with its glycosides and is a unique marker with anti-MRSA activity. Both red ginger rhizomes and avocado leaves have potential uses as herbal components or standardized herbal therapies, according to the results of this study.
The selection of these proteins was based on their potential in MRSA physiology in producing virulence factors and resistance to antimicrobial agents. PPB2A is a peptidoglycan transpeptidase that works together with the PBP2 transglycosylase domain from S. aureus, which accelerates cell wall production in the presence of b-lactam antibiotics, thereby allowing the bacteria to survive and develop. Transglycosylase is an important cleavage enzyme involved in the peptidoglycan turnover of Gram-negative bacteria.48 This enzyme belongs to the glycoside hydrolase family, catalyzing the non-hydrolytic cleavage of the glycosidic linkage between MurNAc and GlcNAc in peptidoglycan, producing muropeptide 1,6-anhydromuramyl disaccharide.49 Furthermore, glycosyltransferase is a component of cell wall biosynthetic enzymes that has been studied to play an important role in the final phase of bacterial peptidoglycan synthesis.50 Glycosyltransferases are responsible for the elongation of glycan strands using lipid-linked disaccharides-pentapeptides as substrates. A group of bifunctional high molecular weight penicillin-binding proteins possessing glycosyltransferase activity has been identified in S. aureus.51
The drug-likeness prediction results in this study certainly have a greater number of compounds that have the potential to be medicinal compounds when compared to similar studies. Garcinia atroviridis phytochemical compounds were screened in silico as anti-Dengue Virus (DENV) agents based on drug similarities, only six of the 24 compounds met the criteria, including dodecanoic acid, atroviridin, naringenin, kaempherol, quercetin, and gentisein.52 Similar research also revealed in silico studies of herbal extracts (basil, thyme, rosemary, and eucalyptus) on their inhibition of b-lactamase of S. aureus which showed that all the chemical compounds used met the Lipinski Rule’s of Five criteria of not finding negative results in ADMET analysis.53
Related studies have reported on the use of computational techniques to predict the toxicity of several traditional Chinese medicine (TCM) formulations and most of the studies are concerned with the prediction of hepatotoxicity. This may be related to the fact that hepatotoxicity data are more widely available in public databases than other toxicity categories. However, here we add predictions of the toxicity of ligand compounds to their possible carcinogenic properties and LD50. There are also several other toxicities that still need to be discussed, including cardiotoxicity, hemolytic toxicity, and nephrotoxicity.54-56
The results of the molecular docking simulation show that the compound beta-bisabolene (CAS) from avocado leaves extract has the most negative binding affinity for the three targets, then from red ginger extract, zingiberenol, has the most negative binding affinity for PBP2a and transglycosylase, and gamma-curcumene on glycosyltransferase (Table 5). The lowest or most negative binding affinity is needed to support the stability of interactions during cellular processes and has activity as an inhibitor on target receptors.57 However, inhibition of this compound is still needed through in vitro and in vivo assays in future research. Potential compounds as antibiotic candidates from the extracts of avocado leaves and ginger rhizomes which act as target inhibitors consist of beta-bisabolene (CAS), zingiberenol, and gamma-curcumene. The molecular complex resulting from docking of the ligand-protein complex with the most negative binding affinity is displayed through the structure transparent surfaces, cartoons, and sticks (Figure 3).
Table (5):
Molecular docking results of avocado leaves extract and red ginger rhizome compounds against PBP2a, transglycosylase and glycosyltransferase receptors in MRSA
| Source | CID | Compounds | Binding Affinity (kcal/mol) | ||
|---|---|---|---|---|---|
| PBP2a | Transglycosylase | Glycosyltransferase | |||
| Avocado leaves extracts | 92776 | Zingiberene (CAS) | -5.6 | -5.4 | -5.4 |
| 5281516 | E,E-alpha-farnese | -5.5 | -5.0 | -5.4 | |
| 10104370 | beta-bisabolene (CAS) | -5.7 | -5.7 | -5.9 | |
| 519764 | beta-sesquiphellandrene (CAS) | -5.5 | -5.5 | -5.2 | |
| 10446 | Neophytadiene | -5.4 | -4.5 | -4.1 | |
| 3931 | 9,12-octadecadienoic acid, methyl ester, (E,E)- (CAS) | -5.2 | -4.6 | -5.3 | |
| Red ginger extracts | 8843 | 2,6-Octadienal, 3,7-dimethyl-, (Z)- | -5.2 | -5.0 | -4.9 |
| 637566 | Geraniol | -5.0 | -5.0 | -5.0 | |
| 12304273 | gamma-curcumene | -6.0 | -5.3 | -5.9 | |
| 13213649 | Zingiberenol | -6.2 | -6.0 | -5.5 | |
| 5356544 | d-Nerolidol | -5.8 | -5.2 | -5.0 | |
Figure 3. 3D structure resulting from docking of the ligand with the target. Ligands from avocado leaves extracts (green) and red ginger rhizome extracts (magenta). (A) PBAP2a_beta-bisabolene (CAS); (B) Transglycosylase_beta-bisabolene (CAS); (C) Glycosyltransferase_beta-bisabolene (CAS); (D) PBAP2a_zingiberenol; (E) Transglycosylase_zingiberenol; (F) Glycosyltransferase_gamma-curcumene
The compound beta-bisabolene is commonly found in essential oils of medicinal plants with natural antimicrobial and antioxidant activity. Apart from the avocado leaves extracts in this study, the compound beta-bisabolene can also be found in carrots, lemons, cubes, oranges and oregano and is generally used as a natural flavoring in beverage products.58 The Zingiberenol compound was reported to be found in the GC-MS results of Chinese ginger essential oil extract at RT 29.409 and 29.830.59 The zingiberenol compound significantly inhibited the effects of nitric oxide production in RAW 264.7 macrophages induced with LPS, indicating the immunomodulatory activity of this extract.60 The compound curcumene was reportedly identified in the essential oil of the rhizome of Curcuma longa, C. aeruginosa, and C. longa. In addition, in vitro and in silico testing of this compound showed anti-dengue fever activity by inhibiting DENV-2 NS2B-NS3.61 This report may be the first to report the compounds beta-bisabolene (avocado leaves) and zingiberenol and gamma-curcumene (red ginger rhizomes) in inhibiting the virulence factors of MRSA in silico.
The total phytoconstituents obtained from the extracts of avocado leaves and red ginger rhizome were 43 types of compounds. Prediction of bioactivity results show in our study show that the compound 6,11-hexadecadien-1-ol from avocado leaves extracts has computationally hepatotoxic properties. There are at least three compounds, namely beta-bisabolene, from avocado leaves extract, zingiberenol and gamma-curcumene, from red ginger rhizome extracts which are able to bind to the active site of MRSA resistance-related proteins (PBAP2a, transglycosylase and glycosyltransferase) with lower binding affinity values than inhibitors. By observing the in silico data and the potential active compounds contained in avocado leaves and red ginger rhizome extracts, a promising antibacterial agent could possibly be obtained from these traditional plants to be utilized against MRSA. The mechanism of action played by each compound is through inhibition of three proteins related to antibiotic resistance controlled by MRSA. Further researches using in vitro and in vivo approaches are very important and recommended to ensure the synergistic effect of these two extracts against MRSA infections.
ACKNOWLEDGMENTS
The authors would like to thank the Institute for Research and Community Service (LPPM) at Universitas Dhyana Pura for supporting the implementation of this research. The authors also thank all those who have helped carry out the research, such as students, workers at the Science and Health Laboratory, Universitas Dhyana Pura, and ASCAdemia who have provided proofreading services for this manuscript.
CONFLICT OF INTEREST
The authors declare that there is no conflict of interest.
AUTHORS’ CONTRIBUTION
All authors listed have made a substantial, direct, and intellectual contribution to the work and approved the final manuscript for publication.
FUNDING
This research was funded by the Institute for Research and Community Service (LPPM) Universitas Dhyana Pura through the Higher Education Excellence Research Scheme Research Funding Grant Program in 2022 with Contract Number: 02/UNDHIRA-LPPM/Lit./2022.
DATA AVAILABILITY
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
ETHICS STATEMENT
Not applicable.
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