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AIMS Biophysics

2020, Volume 7, Issue 4: 323-338. doi: 10.3934/biophy.2020023
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Review Special Issues

Nanoparticle-based delivery platforms for mRNA vaccine development

  • 1.
    Department of Vaccine Technology, Vaccine Institute, Hacettepe University, Ankara, Turkey
  • 2.
    Department of Molecular Neuroscience, Institute of Health Sciences, Üsküdar University, Istanbul, Turkey
  • 3.
    Department of Nutrition and Dietetics, Faculty of Health Sciences, Üsküdar University, Istanbul, Turkey
  • Received: 21 June 2020 Accepted: 16 August 2020 Published: 20 August 2020

  • Conventional vaccines have saved millions of lives, and new vaccines have also been developed; however, an urgent need for an efficient vaccine against SARS-CoV-2 showed us that vaccine development technologies should be improved more to obtain prophylactic agents rapidly during pandemic diseases. One of the next-generation vaccine technologies is utilization of mRNA molecules encoding antigens. The mRNA vaccines offer many advantages compared to conventional and other subunit vaccines. For instance, mRNA vaccines are relatively safe since they do not cause disease and mRNA does not integrate into the genome. mRNA vaccines also provide diverse types of immune responses resulting in the activation of CD4+ and CD8+ T cells. However, utilization of mRNA molecules also has some drawbacks such as degradation by ubiquitous nucleases in vivo. Nanoparticles (NPs) are delivery platforms that carry the desired molecule, a drug or a vaccine agent, to the target cell such as antigen presenting cells in the case of vaccine development. NP platforms also protect mRNA molecules from the degradation by nucleases. Therefore, efficient mRNA vaccines can be obtained via utilization of NPs in the formulation. Although lipid-based NPs are widely preferred in vaccine development due to the nature of cell membrane, there are various types of other NPs used in vaccine formulations, such as virus-like particles (VLPs), polymers, polypeptides, dendrimers or gold NPs. Improvements in the NP delivery technologies will contribute to the development of mRNA vaccines with higher efficiency.

    Citation: Sezer Okay, Öznur Özge Özcan, Mesut Karahan. Nanoparticle-based delivery platforms for mRNA vaccine development[J]. AIMS Biophysics, 2020, 7(4): 323-338. doi: 10.3934/biophy.2020023

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    1.   Introduction

    Nonsteroidal anti-inflammatory drugs (NSAIDs) are one of the most frequently prescribed medicinal classes in old people and children [1],[2]. These medications are typically used to treat inflammatory illnesses and to reduce pain associated with a variety of medical ailments or surgeries [3]. They are used to treat chronic inflammatory disorders such as arthritis, gout, and rheumatoid. NSAIDs work by inhibiting the cyclooxygenase (COX) enzymes, which decrease the production of prostaglandins (PGs), which are believed to be involved in the complicated process of inflammation [4].

    Inflammatory responses caused by the production of histamine, bradykinin, and prostaglandins are part of the host's defense systems. COX are important enzymes in the biosynthesis of prostaglandins, which are the primary mediators of the inflammatory response, pain, and elevated body temperature (hyperpyrexia). The body generates two major isoforms of COX enzymes, namely cyclooxygenases-1 (COX-1) and cyclooxygenases-2 (COX-2). It has been reported that COX-1 is responsible for the production of important biological messengers such as prostaglandins and thromboxanes and is implicated in blood coagulation, pain-causing, and stomach protection, whereas COX-2 is implicated in pain triggered by inflammation and plays a key role in prostaglandin synthesis pathway in inflammatory cells and the nervous system [5],[6]. When COX-1 is blocked, the inflammatory response is decreased, but gastrointestinal lining defense is also reduced. This might result in stomach distress, ulcers, and hemorrhage from the gastrointestinal tract. Whereas COX-2 is normally restricted to inflamed tissue, COX-2 inhibition causes significantly reduced stomach irritation as well as a lower risk of gastric hemorrhage [7]. As a result, selective COX-2 inhibitors such as rofecoxib (Vioxx®) and celecoxib drugs have been designed to alleviate COX-related inflammation [8]. However, Coxib medications have been removed due to an enhanced danger of long-term heart attacks and strokes [9].

    Furthermore, NSAIDs are one of the most popular treatments in the world, however, they are not generally accepted by users, and hence their long-term usage in chronic medical conditions is accompanied with significant undesirable consequences. Long-term NSAIDS medication may cause stomach epithelial injury marked by localized necrosis, bleeding, and in some cases, severe ulceration [10],[11]. The NSAID-induced gastropathy issues that limit the effectiveness of this class of medications are due mainly to the nonselective inhibitory activity of both constitutive (COX-1) and inducible (COX-2) homologs of cyclooxygenase, as well as the existence of corrosive carboxylic acid features and functions in their structure [12].

    As a result, developing effective COX inhibitors from biological compounds is necessary. Medicinal plants, aromatic herbs, and their essential oils (EOs) have lately been recognized to have curative effects and also to have many health benefits. They have been shown to offer a wide range of medicinal benefits, including antibacterial, antifungal, antioxidant, anti-inflammatory, analgesic, and anticancer properties [13]–[15]. Lavender (Lavandula officinalis (Lamiaceae family)) is a popular aromatic plant in the Mediterranean region, including Algeria. Lavender has mostly been employed in medicinal and domestic culinary applications over the world. The EO extracted from lavender aerial parts is the primary contributor to its distinctive perfume and medicinal function [16],[17]. In ethnomedicine, lavender is used as an anti-inflammatory medication [18],[19]. As a result, it is important to describe the molecular docking study of lavender metabolites with COX-1 and COX-2.

    The current study focuses on identifying potential treatment options that will be regarded as successful anti-inflammatory medication therapy. Molecular docking is a vital computational method in drug design and development projects, and it was used to match a small ligand as a guest with a variety of receptor molecules as hosts. This docking-based technology is often used to estimate a compound's attraction for a target protein. In this paper, molecular docking of various potential anti-inflammatory medicines and numerous terpenes discovered in LEO was done in this research to investigate the inhibition likelihood against COX-1 and COX-2 receptors using the DockThor server and BIOVIA Discovery Studio visualizer software. A total of 29 LEO terpene compounds were virtually screened on the COX-1 (PDB ID 3N8Y) and COX-2 (PDB ID 3LN1) enzymes. The binding affinities were compared to those of other anti-inflammatory medications. The docked compounds with the highest binding affinities were also screened for drug-likeness utilizing the SwissADME and PASS platforms, based on physicochemical, pharmacological, and toxicological features.

    2.   Materials and methods

    2.1.   Preparation of COX enzymes

    From the protein data bank, the X-ray crystal structures of COX-1 and COX-2 (PDB codes 3N8Y and 3LN1, respectively) were retrieved (Table 1 and Figure 1). The deletion of ligands, water molecules, as well as other heteroatoms was done using the software BIOVIA Discovery Studio visualizer (Dassault Systèmes Corp., Version 2020). The protein's crystal structure was furthered by the addition of hydrogen after missing and incomplete residues were filled in. The PDB file of the improved receptor was then utilized to simulate docking.

    Table 1.  Protein target data.
    PDB ID COX 1 (PDB ID: 3N8Y) COX-2 (PDB ID: 3LN1)
    Title Structure of aspirin acetylated COX-1 in complex with Diclofenac Structure of celecoxib bound at the COX-2 active site
    DOI 10.2210/pdb3N8Y/pdb 10.2210/pdb3LN1/pdb
    Author(s) Sidhu RS, Lee J, Yuan C, et al. Kiefer JR, Kurumbail RG, Stallings WC, et al.
    Deposited 28-05-2010 01-02-2010
    Resolution 2.60 Å 2.40 Å
    Classification Oxidoreductase Oxidoreductase
    Organism Ovis aries Mus musculus
    Expression system Spodoptera frugiperda Spodoptera frugiperda
    Method X-ray diffraction X-ray diffraction
    Molecule Prostaglandin G/H synthase 1 Prostaglandin G/H synthase 2
    Chains A A, B, C, D
    Sequence length 553 amino acids 587 amino acids
    Total structure weight 134.2 kDa 278.19 kDa
     | Show Table
    DownLoad: CSV
    Figure 1.  Three-dimensional crystal structure of the molecular target, COX-1 enzyme (3N8Y) was represented in (a) solid ribbon (b) without hetatoms (c) chaine A.
    DownLoad: Full-Size Img PowerPoint

    2.2.   Literature survey and selection of ligands

    LEO's total medicinal effect is provided by a diverse array of bioactive terpenes. Based on the percentage concentration in the LEO fraction, a study of the literature was conducted to identify the most important of these bioactive compounds. A literature search was carried out to obtain information about the LEO and its bioactive compounds from electronic databases such as Google scholar, PubMed, ScienceDirect, Wiley, MDPI, Springer, and other online journal publications and dissertations. There has been a lot of difference in the LEO chemical composition among different Lavandula species. We focused our chemical composition analysis on 29 terpenes that make up the bulk of lavender volatile oil. The compounds focused on in this study include limonene, α-terpineol, p-cymene, β-phellandrene, β-ocimene, myrcene, α-bisabolol, geraniol, germacrene D, β-caryophyllene, linalyl acetate, caryophyllene oxide, lavandulol, lavandulyl acetate, bornyl acetate, neryl acetate, cis-linalool oxide, terpinen-4-ol, linalool, eucalyptol, α-pinene, trans-linalool oxide, geranyl acetate, fenchone, β-pinene, camphene, camphor, borneol, β-farnesene. From the PubChem (pubchem.ncbi.nlm.nih.gov) database, the small molecular structures of the significant bioactive LEO constituents were obtained in sdf format. The application BIOVIA Discovery Studio visualizer was used to compute bond lengths, display receptors, ligand structures, and hydrogen bonding connections. After a comprehensive study of the literature, 34 structures of ligand molecules (Figures 2 and 3) were found and obtained from the PubChem database.

    Figure 2.  Chemical structure of selected anti-inflammatory drugs.
    DownLoad: Full-Size Img PowerPoint
    Figure 3.  Chemical structure of all selected ligand terpenes in docking studies.
    DownLoad: Full-Size Img PowerPoint

    2.3.   Molecular docking

    In this research, we used the free DockThor Portal (www.dockthor.lncc.br) created by the Grupo de Modelagem Molecular de Sistemas Biológicos (GMMSB) (www.gmmsb.lncc.br) located at the Laboratório Nacional de Computaço Cientfica (LNCC) in Petrópolis, Brazil, for receptor-ligand dock. The DockThor Portal received the files of the retrieved ligands and receptors for docking simulation. The COX protein's active site with the biggest surface area was chosen for docking when all optimal ligands were applied. The following parameters were included in the docking process: Number of evaluations: 1000000; population size: 750; initial seed: −1985; number of runs: 24; docking: soft; spatial discretization of the energy grid: 0.25 Å; grid points: <1000000. All conformers with the best placements and dock scores for each ligand will be stored in the output folder. The technique additionally emphasizes the ideal conformer positioning for a certain ligand that has the best (minimum) score. The lowest interaction energy for each ligand and COX proteins for the ideal ligand position inside the binding site cavity was discovered once the docking procedure was complete. With the aid of the Discovery Studio visualizer, the interactions of intricate protein-ligand conformations were examined.

    2.4.   In silico ADME-toxicity prediction studies

    Through examination of pharmacokinetic characteristics, a few molecules from the molecular docking analysis were assessed for their drug-like activity. The admetSAR program (http://lmmd.ecust.edu.cn) was used to estimate the pharmacokinetic profile (absorption, distribution, metabolism, excretion, and toxicity (ADMET)), of the LEO terpenes [20]. The topological polar surface area (TPSA), clog P, fragment-based drug-likeness, and drug score values were determined using the OSIRIS property explorer (www.organic-chemistry.org/prog/peo/). By using criteria such as molecular weight ≤ 500, logP ≤ 5, hydrogen bond donor ≤ 5, hydrogen bond acceptor ≤ 10, and TPSA ≤ 500, the ligands were further tested for the Lipinski rule of five. By inputting SMILES structures from PubChem notations or uploading SDF files, the molecules may be evaluated to determine their toxicological qualities. Toxicological modeling can then be used to generate a plethora of data regarding the effects associated with the structure.

    2.5.   PASS computer program

    PASS version, an online system that predicts possible pharmacological effects of a chemical based on its structural information, was used to obtain the biological activity spectra of previously reported LEO phytoconstituents. PASS is a computer-based tool used to predict several types of physiological responses for numerous substances including phytoconstituents. This program compares over 300 pharmacological effects and biochemical pathways of substances and provides probabilities of activity (Pa) and inactivity (Pi). The only constituents deemed to be viable for a certain medical activity are those with Pa greater than Pi [21].

    3.   Results and discussion

    3.1.   Molecular docking studies

    The project that was submitted to the DockThor Portal makes use of the computing resources offered by the Brazilian SINAPAD (Sistema Nacional de Alto Desempenho) system, which has a high-performance platform. The top models were chosen after the DockThor Portal developed a variety of models for each docking operation between the COX receptor site and phytoconstituents. This computational process begins by docking each ligand molecule, followed by scoring. Using the DockThor server and the Discovery Studio software, docking experiments were conducted to examine the molecular interactions between the available active sites of target enzymes and LEO terpenes in order to determine the affinity of the compounds for COX-1 and COX-2. Based on their minimum binding energies associated with the complex formation at the catalytic activity, limonene, α-terpineol, p-cymene, β-phellandrene, β-ocimene, and terpinen-4-ol were rated in terms of their COX inhibitory activity. The docked chemicals' binding energies on COX-1 were determined to be between −8.536 and −8.438 kcal/mol (Table 2). Celecoxib and diclofenac sodium, two common anti-inflammatory medicines, had noticeably greater binding energies for the COX-2 target, showing that all of the chosen chemicals need less energy to block the protein.

    Table 2.  Docking data generated by DockThor server between various ligands molecules of the reference and LEO compounds with COX-1 & COX-2 enzymes.
    Compound name COX-1 binding affinity (kcal/mol) Compound name COX-2 binding affinity (kcal/mol)
    Limonene −8.536 Celecoxib −8.673
    α-Terpineol −8.535 Myrcene −8.495
    p-Cymene −8.515 α-Bisabolol −8.458
    β-Phellandrene −8.486 β-Caryophyllene −8.400
    β-Ocimene −8.463 β-Ocimene −8.353
    Terpinen-4-ol −8.438 Diclofenac sodium −8.313
    Germacrene D −8.413 Geraniol −8.303
    α-Pinene −8.334 Germacrene D −8.271
    Myrcene −8.332 β-Farnesene −8.257
    β-Pinene −8.274 β-Phellandrene −8.179
    Camphene −8.266 p-Cymene −8.018
    Fenchone −8.265 Betamethasone −7.990
    Celecoxib −8.191 Linalyl acetate −7.979
    Betamethasone −8.041 Caryophyllene oxide −7.893
    β-Farnesene −7.894 α-Terpineol −7.868
    Lavandulol −7.888 Lavandulol −7.731
    Diclofenac sodium −7.792 Lavandulyl acetate −7.586
    Caryophyllene oxide −7.760 Bornyl acetate −7.561
    β-Caryophyllene −7.696 Neryl acetate −7.537
    Geranyl acetate −7.661 cis-Linalool oxide −7.522
    Linalool −7.591 Ketoprofen −7.478
    α-Bisabolol −7.427 Terpinen-4-ol −7.228
    Ibuprofen −7.385 Geranyl acetate −7.211
    Bornyl acetate −7.349 Linalool −7.073
    Neryl acetate −7.329 Eucalyptol −6.999
    Lavandulyl acetate −7.224 trans-Linalool oxide −6.992
    Linalyl acetate −7.208 α-Pinene −6.980
    trans-Linalool oxide −7.133 Borneol −6.945
    cis-Linalool oxide −7.018 β-Pinene −6.929
    Ketoprofen −6.878 Ibuprofen −6.929
    Eucalyptol −6.761 Fenchone −6.917
    Borneol −6.727 Camphene −6.913
    Camphor −6.690 Limonene −6.904
    Geraniol −6.575 Camphor −6.835
     | Show Table
    DownLoad: CSV

    The best predicted binding energies for COX-1 and COX-2 were found to be for β-ocimene (Figure 4), with values of −8.463 and −8.353 kcal/mol, respectively, according to the molecular docking data shown in Table 3. Homnan et al. [22] looked at β-ocimene's ability to reduce inflammation. This hydrocarbon monoterpene strongly suppressed COX-2 activity and reduced prostaglandin E2 (PGE2) amounts in a dose-dependent way, with IC50 of 75.64 and much less than 20 g/mL, respectively. Kim et al. [23] studied the anti-inflammatory efficacy of EOs extracted from the Hallabong flower, which contained 11% β-ocimene. The hydro-distilled natural oils from the Hallabong flower (Citrus medica L. var. sarcodactylis) inhibited the lipopolysaccharide (LPS)-induced production of COX-2 enzyme on LPS-stimulated RAW 264.7 cells. Furthermore, it suppressed PGE2 production in a dose-dependent way, with an IC50 value of less than 0.01%. It is clear that the interaction energy of the limonene compound is lower in COX-2 (−6.904) than in COX-1 (−8.536), indicating that it is a selective COX-1 inhibitor. Nevertheless, only hydrophobic linkages between limonene and COX-1 could be seen, even though many amino acid residues are implicated in a specific binding mechanism.

    Table 3.  Summary of binding interactions and top-ranked LEO phytochemicals screened against COX-1 receptor (PDB ID: 3N8Y) binding site.
    PubChem ID Compound name Binding affinity (kcal/mol) Active amino acids residues Distance (Å) Category Type
    22311 Limonene −8.536 LEU353 5.20786 Hydrophobic Alkyl
    VAL318 4.48233
    LEU321 4.09047
    ILE492 4.95029
    VAL318 4.93115
    ILE492 4.84844
    ALA496 3.85553
    LEU321 5.04185
    ALA496 4.71957
    PHE350 5.39045 Hydrophobic Pi-alkyl
    TYR354 4.42773
    TRP356 4.93007
    17100 α-Terpineol −8.535 VAL318 4.16085 Hydrophobic Alkyl
    LEU321 4.26425
    ILE492 5.17717
    VAL318 4.00893
    ALA496 3.92114
    LEU353 4.90529
    LEU321 5.24608
    ALA496 4.62466
    PHE350 5.37118 Hydrophobic Pi-alkyl
    TYR354 4.48363
    TRP356 4.93781
    7463 p-Cymene −8.515 GLY495 4.23719 Hydrophobic Amide-Pi stacked
    VAL318 4.34579 Hydrophobic Alkyl
    LEU353 4.55204
    LEU321 5.16326 Hydrophobic Pi-alkyl
    ALA496 4.90846
    PHE350 5.35724
    TYR354 4.5216
    TRP356 4.93121
    11142 β-Phellandrene −8.486 VAL318 5.09711 Hydrophobic Alkyl
    ILE492 4.24168
    ALA496 4.4928
    LEU353 5.4746
    LEU321 5.43761
    ILE492 5.36154
    ALA496 4.34849
    TYR354 4.54422 Hydrophobic Pi-alkyl
    TRP356 4.96094
    5281553 β-Ocimene −8.463 ALA171 4.33901 Hydrophobic Alkyl
    LEU359 5.24116
    HIS176 4.48699 Hydrophobic Pi-alkyl
    HIS176 4.8897
    HIS176 4.64473
    PHE179 4.52532
    TYR354 5.19321
    HIS355 4.96911
    HIS355 4.2718
    HIS355 4.50183
    HIS357 4.60123
    11230 Terpinen-4-ol −8.438 VAL318 4.4207 Hydrophobic Alkyl
    ALA496 3.96373
    VAL318 4.88286
    ILE492 5.48398
    ALA496 3.53657
    2662 Celecoxib −8.191 GLU316 1.52341 H bond Conventional H bond
    PHE549 2.06864
    SER548 3.10647 H bond Carbon H bond
    GLN319 3.36899 Halogen Halogen (fluorine)
    GLN327 3.53859
    GLU316 4.45539 Electrostatic Pi-Anion
    HIS550 5.08501 Hydrophobic Pi-Pi stacked
    HIS550 4.31237 Hydrophobic Pi-alkyl
    9782 Betamethasone −8.041 HIS355 1.8315 H bond Conventional H bond
    GLU423 1.68056
    HIS357 3.63158 Halogen Halogen (fluorine)
    HIS355 5.48416 Hydrophobic Pi-alkyl
     | Show Table
    DownLoad: CSV
    Figure 4.  Snapshot represents the interaction between some selected ligands and COX-1.
    DownLoad: Full-Size Img PowerPoint

    By inhibiting the production of the inflammatory genes matrix metalloproteinase (MMP)-2 and -9, limonene significantly reduced clinical symptoms and intestinal mucosa destruction in rats with ulcerative colitis (UC). In addition, limonene treatment increased the expression of the proteins COX-2 and inducible nitric oxide synthase (iNOS) as well as antioxidants in UC rats [24]. In order to comprehend the biological and pharmacological effects of limonene on the production of pro-inflammatory mediators and cytokines in macrophage cells, Yoon et al. [25] performed an in vitro study and revealed that limonene prevents LPS from inducing PGE2 and nitric oxide (NO) production in RAW 264.7 cells. The synthesis of the iNOS and COX-2 enzymes was inhibited by limonene in a dose-dependent way. In addition, limonene dose-dependently reduced the production of TNF-α, IL-1β, and IL-6. These findings lead us to suggest that limonene could be a promising anti-inflammatory component.

    Table 4.  Summary of binding interactions and top-ranked LEO phytochemicals screened against COX-2 receptor (PDB ID: 3LN1) binding site.
    PubChem ID Compound name Binding affinity (kcal/mol) Active amino acids residues Distance (Å) Category Type
    2662 Celecoxib −8.673 GLU257 2.19857 Hydrogen bond Conventional H bond
    GLN256 2.02558
    THR179 3.05721
    ASN189 2.64444
    HIS181 3.09038 Pi-donor H bond
    HIS181 4.93934 Hydrophobic Pi-Pi T-shaped
    ILE241 4.7911 Alkyl
    LYS178 5.34418 Pi-alkyl
    VAL258 4.60764
    VAL258 4.75717
    HIS353 5.2587
    31253 Myrcene −8.495 ALA169 4.05042 Hydrophobic Alkyl
    LEU357 5.31713
    LEU358 4.81577
    HIS174 5.05216 Pi-alkyl
    HIS355 4.8889
    HIS174 5.01
    PHE177 4.71421
    HIS353 4.63097
    HIS174 4.97848
    HIS353 4.03611
    HIS355 4.48883
    TRP354 4.65567
    TRP354 4.85802
    10586 α-Bisabolol −8.458 THR179 2.30299 Hydrogen bond Conventional H bond
    HIS181 2.22428
    VAL258 5.14002 Hydrophobic Alkyl
    LYS178 4.15079
    VAL258 5.05092
    VAL258 5.27629
    HIS174 4.48034 Pi-alkyl
    HIS353 4.90952
    HIS181 5.06576
    HIS174 5.19112
    HIS353 3.61505
    5281515 β-Caryophyllene −8.400 VAL258 3.86278 Hydrophobic Alkyl
    HIS174 5.46788 Pi-alkyl
    HIS174 4.71157
    HIS181 4.93027
    HIS174 5.2873
    HIS174 4.58658
    HIS353 4.28092
    5281553 β-Ocimene −8.353 LEU358 4.86083 Hydrophobic Alkyl
    ALA169 4.49891
    LEU357 5.33171
    HIS174 5.05417 Pi-alkyl
    HIS355 4.23129
    HIS174 4.94839
    PHE177 4.929
    HIS353 4.4817
    HIS174 4.89993
    HIS353 4.2914
    5018304 Diclofenac Na −8.313 GLN170 2.90417 Hydrogen bond Conventional H bond
    HIS174 1.4732
    HIS353 4.37635 Hydrophobic Pi-Pi stacked
    HIS355 5.5618 Pi-Pi T-shaped
    HIS174 5.29974 Pi-alkyl
    HIS353 4.33105
    HIS355 3.98766
    VAL414 4.0637
    637566 Geraniol −8.303 TRP354 1.82951 Hydrogen bond Conventional H bond
    HIS355 2.93434 Hydrophobic Pi-sigma
    ALA169 4.25559 Alkyl
    HIS174 4.49101 Pi-alkyl
    HIS174 4.86783
    PHE177 4.76602
    HIS353 4.24043
     | Show Table
    DownLoad: CSV

    Myrcene exhibits the greatest binding affinity for COX-2 (−8.495 kcal/mol) when compared to standard medications and other investigated substances (Table 3), despite binding to COX-2 residues ALA169, LEU357, LEU358, HIS174, HIS353, HIS355, PHE177, and TRP354 (Table 4 and Figure 5). Its lower binding affinity to COX-1 (−8.332 kcal/mol) than that of limonene, α-terpineol, and p-cymene, however, suggests that it is more competitive for the COX-2 enzyme. It interacts with hydrophobic residues of amino acids on COX-2 via associations with alkyl and pi-alkyl groups.

    Figure 5.  Snapshot represents the interaction between some selected ligands and COX-2.
    DownLoad: Full-Size Img PowerPoint

    Additionally, EOs extracted from aromatic herbs and medicinal plants that contain 10% or less of myrcene have been found to have anti-inflammatory benefits. There is evidence that the oil of Eremanthus erythropappus reduces edema and leukocyte extravasation in several organs, including the hind paw and lung [26],[27]. Another myrcene-rich EO reduced the levels of pro-inflammatory cytokines and COX-2 within eight hours in a rat model of severe synovitis [28]. In arthritic human chondrocytes, pure myrcene reduced the expression of iNOS and interfered with the IL-1 signaling pathway [29]. These data demonstrate that myrcene and myrcene-containing EOs have potent anti-inflammatory and analgesic properties.

    3.2.   In silico pharmacokinetic prediction

    Drug-likeness characteristics are important in determining the quality of emerging anti-inflammatory compounds. Based on their structure, early predictions of the pharmacokinetic behavior of prospective plant-derived EO compounds should aid in the identification of more safe and more efficient leads for further preclinical studies. In this research, we examined five of the most relevant pharmacokinetic and ADME indicators for LEO compounds to see if they may be used as drugs. These anticipated results would demonstrate the compounds' potential as drugs and point to the likelihood of them serving as an oral anti-inflammatory substitute.

    Table 5 shows the outcomes of using Osiris Property Explorer to estimate the drug-likeness of compounds based on several chemical descriptors. The majority of substances have partition coefficients (clog P) values less than 5, although others (such as β-caryophyllene) defy the Lipinski rule of five for lipophilicity and may have low oral bioavailability and penetration. The Lipinski rule of five is clearly broken by the most powerful molecule (β-caryophyllene), which has a log P value of 5.49. In contrast, the other five compounds are predicted to be orally active and have log P values ranging from 4.47 to 1.81. Additionally, compounds are attractive drug candidates for additional study and development because of their lower TPSA score (zero), which indicates favorable drug-like properties, and their high drug-likeness score. The ADME properties and toxicological profile of the LEO molecules were also investigated using an online admetSAR cheminformatic system to detect prospective and secure drug candidate(s) and to screen out substances that are most likely to fail in successive stages of the development process due to unfavorable ADMET properties.

    Table 5.  Drug-likeness prediction through OSIRIS property explorer.
    Mutagenic Tumorigenic Irritant Reproductive effect clog P TPSA Solubility Drug likeness Drug score
    Celecoxib - - - - 2.59 86.36 −4.17 −8.11 0.37
    Myrcene - + + + 4.29 0 −2.5 −7.82 0.09
    α-Bisabolol - - + - 4.47 20.23 −3.16 −1.47 0.27
    β-Caryophyllene - - - - 5.49 0 −3.66 −6.48 0.31
    β-Ocimene - - + - 4.23 0 −2.33 −5.46 0.24
    Diclofenac Na - - - - 1.81 52.16 −4.64 2.3 0.71
    Geraniol - - + - 3.49 20.23 −1.89 −3.57 0.27
     | Show Table
    DownLoad: CSV

    Drugs' destiny in vivo, or ADME, has a complete or partial impact on how they behave pharmacologically. The blood/brain partition coefficient (Plog BB), Caco-2 cell permeability (PCaco), human intestinal absorption (log HIA), P glycoprotein nonsubstrate and non-inhibitor (log pGI), and probability of Caco-2 cell permeability (log Papp) are among the in silico projected pharmacokinetic (ADME) attributes of all studied ligands and are shown in Table 6.

    According to the findings in Table 6, the chemical β-caryophyllene is not carcinogenic, whereas myrcene and β-ocimene failed the AMES toxicity test and were therefore found to be carcinogenic. The calculated LD50 dosage (1.4040–1.6722 mol/kg) for the selected terpenes in a rat acute toxicity model appears to be secure enough for research on in vivo anti-inflammatory efficacy. A molecule's degree of intestinal absorption after oral delivery is measured by the HIA score. If the score is below one, the absorption can be quite high. All terpenes in the current investigation had HIA scores that range from 0.9538 to 0.9926, indicating that they will be well assimilated from the gastrointestinal tract [30]. The estimated cell permeability (PCaco-2) of selected terpenes, which ranges from 0.7228 to 0.6327, is also reported to be within the acceptable range (−1 to +1), aiding in the transit of the bioactive compounds to the gut and, thus, improving absorption. It may be deduced from the anticipated log BB score (0.9536–0.9312) that these terpenes have the highest likelihood of crossing the blood-brain barrier and having an effect on the function of the central nervous system.

    Table 6.  ADME prediction for the top-ranked compounds using the admetSAR toolbox.
    Blood-brain barrier Human intestinal absorption Caco-2 permeability P-glycoprotein substrate P-glycoprotein inhibitor Renal organic cation transporter AMES toxicity Carcinogens Caco-2 permeability (LogPapp, cm/s) Rat acute toxicity (LD50, mol/kg)
    Celecoxib BBB+ HIA+ Caco2+ - - - - - 1.0149 2.3719
    0.9713 1 0.8866 0.9287 0.8619 0.8582 0.7185 0.7905
    Myrcene BBB+ HIA+ Caco2+ - - - - + 1.5571 1.404
    0.9478 0.9538 0.7228 0.6521 0.701 0.8183 0.9227 0.5684
    β-Caryophyllene BBB+ HIA+ Caco2+ + - - - - 1.5225 1.4345
    0.9536 0.9926 0.6327 0.5779 0.5989 0.8269 0.9167 0.6863
    β-Ocimene BBB+ HIA+ Caco2+ - - - - + 1.5641 1.6722
    0.9312 0.9764 0.6913 0.6792 0.7425 0.8829 0.8917 0.7261
    Diclofenac Na BBB+ HIA+ Caco2+ - - - - - 1.8481 2.855
    0.9827 0.8998 0.8196 0.8827 0.8557 0.8776 0.8443 0.6747
    Geraniol BBB+ HIA+ Caco2+ - - - - - 1.2481 1.6146
    0.9375 0.9846 0.6445 0.5851 0.8865 0.8179 0.9132 0.5055
     | Show Table
    DownLoad: CSV

    3.3.   PASS predictions biological activity

    The biological activity spectra of previously known phytochemical compounds were obtained using the online PASS version. These predictions were assessed and made available in Table 7 for flexible usage. The range of biological activities that a chemical substance exhibits when it interacts with different types of biological entities is known as its biological activity spectrum. It allows us to combine information from several sources in the same training set, which is required since no one publication covers all of the diverse aspects of a compound's biological action.

    Table 7.  The PASS prediction findings reveal the biological activity spectrum and toxicity of the top-ranked LEO terpenes.
    Compound name Pa Pi Biological activity spectrum predicted by PASS Pa Pi Possible adverse & toxic effects
    Celecoxib 0.955 0.002 Cyclooxygenase 1 inhibitor 0.671 0.016 Pseudoporphyria
    0.859 0.003 Non-steroidal anti-inflammatory agent 0.569 0.013 Ulcer, peptic
    0.809 0.007 Antiarthritic 0.571 0.02 Methemoglobinemia
    Myrcene 0.941 0.004 Mucomembranous protector 0.829 0.004 Skin irritation, high
    0.896 0.005 Antineoplastic 0.786 0.01 Hyperglycemic
    0.836 0.012 Antieczematic 0.791 0.026 Toxic, respiration
    α-Bisabolol 0.847 0.005 Apoptosis agonist 0.862 0.016 Behavioral disturbance
    0.83 0.013 Antieczematic 0.843 0.003 Skin irritation, moderate
    0.727 0.006 Antithrombotic 0.822 0.02 Conjunctivitis
    β-Caryophyllene 0.915 0.005 Antineoplastic 0.836 0.004 Sensitization
    0.897 0.005 Antieczematic 0.788 0.005 Irritation
    0.745 0.011 Antiinflammatory 0.545 0.062 Nephrotoxic
    β-Ocimene 0.928 0.004 Antieczematic 0.82 0.004 Skin irritative effect
    0.806 0.004 Carminative 0.777 0.004 Lacrimal secretion stimulant
    0.91 0.004 Mucomembranous protector 0.816 0.004 Skin irritation, high
    Geraniol 0.953 0.003 Mucomembranous protector 0.951 0.002 Skin irritation, moderate
    0.77 0.004 Antiulcerative 0.925 0.005 Anemia
    0.766 0.001 Antiviral (rhinovirus) 0.878 0.004 Hyperglycemic
    Limonene 0.961 0.001 Carminative 0.856 0.005 Gastrointestinal disturbance
    0.896 0.005 Antieczematic 0.811 0.015 Respiratory failure
    0.812 0.01 Antineoplastic 0.675 0.005 Sedative
    α-Terpineol 0.862 0.005 Respiratory analeptic 0.887 0.011 Euphoria
    0.837 0.003 Carminative 0.839 0.015 Ocular toxicity
    0.825 0.014 Antieczematic 0.838 0.019 Behavioral disturbance
    p-Cymene 0.919 0.004 Mucomembranous protector 0.961 0.009 Toxic, respiration
    0.881 0.002 Carminative 0.928 0.003 Hematemesis
    0.884 0.006 Antieczematic 0.878 0.004 Gastrointestinal hemorrhage
    β-Phellandrene 0.916 0.004 Antieczematic 0.827 0.012 Ulcer, aphthous
    0.883 0.002 Carminative 0.799 0.005 Irritation
    0.83 0.009 Antineoplastic 0.725 0.032 Conjunctivitis
    β-Ocimene 0.928 0.004 Antieczematic 0.82 0.004 Skin irritative effect
    0.91 0.004 Mucomembranous protector 0.777 0.004 Lacrimal secretion stimulant
    0.858 0.005 Apoptosis agonist 0.754 0.01 Hypomagnesemia
    Terpinen-4-ol 0.838 0.011 Antieczematic 0.852 0.007 Hematemesis
    0.829 0.003 Carminative 0.779 0.023 Ulcer, aphthous
    0.796 0.02 Antiseborrheic 0.702 0.015 Optic neuritis
     | Show Table
    DownLoad: CSV

    Pa (probability “to be active”) estimates the chance that the studied compound is belonging to the sub-class of active compounds. Pi (probability “to be inactive”) estimates the chance that the studied compound is belonging to the sub-class of inactive compounds.

    The probable activity (Pa) values were higher than Pa > 0.5, and the probable inactivity (Pi) scores were extremely near to 0, demonstrating that the compound is highly expected to demonstrate these activities. It is also notable that the selected terpenes have very suitable molecular properties and predictable pharmacological activities against COX-1 and COX-2 enzymes.

    A literature survey corroborates the docking finding, revealing that LEO compounds have antibacterial properties [31] and function as antioxidants by reducing lipid peroxidation [32],[33]. As a result, we believe that the chosen phytoconstituents will boost immunity while inhibiting COX enzymes [34]. Anti-inflammatory phytochemical constituents with stronger docking scores, higher binding energies, and better interaction with conserved catalytic residues that may induce inhibition/blockade of the COX protein pathways might be viable preventive and curative options [35],[36].

    4.   Conclusions

    There is a pressing need to create new substances with therapeutic action in order to develop drugs with fewer negative effects. The current work assesses the potential for binding interactions between phytocompounds from LEO and COX enzymes by molecular docking. Molecular docking revealed that limonene has the highest negative binding affinity in complex with COX-1, followed by α-terpineol and p-cymene. Myrcene exhibits the greatest binding affinity for COX-2 when compared to standard medications, followed by α-bisabolol and β-caryophyllene. The LEO's chosen phytochemicals were found to be highly selective, have substantial binding potential, and react strongly with COX-1 and COX-2 receptors by computational screening. Best docking scores, ligand placement at the region of inhibition, interaction profiles with catalytic residues, and appropriate ADMET values all point to the likelihood that myrcene and β-ocimene may be effective COX inhibitors. Based on satisfying Lipinski's rule five, these terpenes can also be identified as prospective therapeutic candidates.



    Conflict of interest


    The authors declare no conflict of interest.

    [1] Sharp PA (2009) The centrality of RNA. Cell 136: 577-580.
    [2] Cooper TA, Wan L, Dreyfuss G (2009) RNA and disease. Cell 136: 777-793.
    [3] Fry LE, Patrício MI, Williams J, et al. (2019) Association of messenger RNA level with phenotype in patients with choroideremia: potential implications for gene therapy dose. JAMA Ophthalmol 138: 128-135.
    [4] Li B, Zhang X, Dong Y (2019) Nanoscale platforms for messenger RNA delivery. Wires Nanomed Nanobi 11: e1530.
    [5] Midoux P, Pichon C (2015) Lipid-based mRNA vaccine delivery systems. Expert Rev Vaccines 14: 221-234.
    [6] Dannull J, Haley NR, Archer G, et al. (2013) Melanoma immunotherapy using mature DCs expressing the constitutive proteasome. J Clin Invest 123: 3135-3145.
    [7] Van Lint S, Heirman C, Thielemans K, et al. (2013) mRNA: From a chemical blueprint for protein production to an off-the-shelf therapeutic. Hum Vacc Immunother 9: 265-274.
    [8] Yang J, Arya S, Lung P, et al. (2019) Hybrid nanovaccine for the co-delivery of the mRNA antigen and adjuvant. Nanoscale 11: 21782-21789.
    [9] Le TT, Andreadakis Z, Kumar A, et al. (2020) The COVID-19 vaccine development landscape. Nat Rev Drug Discov 19: 305-306.
    [10] Geall AJ, Mandl CW, Ulmer JB (2013) RNA: the new revolution in nucleic acid vaccines. Semin Immunol 25: 152-159.
    [11] Pardi N, Hogan MJ, Porter FW, et al. (2018) mRNA vaccines—a new era in vaccinology. Nat Rev Drug Discov 17: 261-279.
    [12] Pascolo S (2015) The messenger's great message for vaccination. Expert Rev Vaccines 14: 153-156.
    [13] Deering RP, Kommareddy S, Ulmer JB, et al. (2014) Nucleic acid vaccines: prospects for non-viral delivery of mRNA vaccines. Expert Opin Drug Deliv 11: 885-899.
    [14] Liu MA (2010) Immunologic basis of vaccine vectors. Immunity 33: 504-515.
    [15] Jäschke A, Helm M (2003) RNA sex. Chem Biol 10: 1148-1150.
    [16] Pollard C, Rejman J, De Haes W, et al. (2013) Type I IFN counteracts the induction of antigen-specific immune responses by lipid-based delivery of mRNA vaccines. Mol Ther 21: 251-259.
    [17] Vallazza B, Petri S, Poleganov MA, et al. (2015) Recombinant messenger RNA technology and its application in cancer immunotherapy, transcript replacement therapies, pluripotent stem cell induction, and beyond. Wiley Interdiscip Rev RNA 6: 471-499.
    [18] Gómez-Aguado I, Rodríguez-Castejón J, Vicente-Pascual M, et al. (2020) Nanomedicines to deliver mRNA: State of the art and future perspectives. Nanomaterials 10: 364.
    [19] Versteeg L, Almutairi MM, Hotez PJ, et al. (2019) Enlisting the mRNA vaccine platform to combat parasitic infections. Vaccines 7: 122.
    [20] Hekele A, Bertholet S, Archer J, et al. (2013) Rapidly produced SAM® vaccine against H7N9 influenza is immunogenic in mice. Emerg Microbes Infect 2: e52.
    [21] Lindgren G, Ols S, Liang F, et al. (2017) Induction of robust B cell responses after influenza mRNA vaccination is accompanied by circulating hemagglutinin-specific ICOS+ PD-1+ CXCR3+ T follicular helper cells. Front Immunol 8: 1539.
    [22] Luo F, Zheng L, Hu Y, et al. (2017) Induction of protective immunity against Toxoplasma gondii in mice by nucleoside triphosphate hydrolase-II (NTPase-II) self-amplifying RNA vaccine encapsulated in lipid nanoparticle (LNP). Front Microbiol 8: 605.
    [23] Michel T, Golombek S, Steinle H, et al. (2019) Efficient reduction of synthetic mRNA induced immune activation by simultaneous delivery of B18R encoding mRNA. J Biol Eng 13: 40.
    [24] Appay V, Douek DC, Price DA (2008) CD8+ T cell efficacy in vaccination and disease. Nat Med 14: 623-628.
    [25] Pardi N, Hogan MJ, Naradikian MS, et al. (2018) Nucleoside-modified mRNA vaccines induce potent T follicular helper and germinal center B cell responses. J Exp Med 215: 1571-1588.
    [26] Zarghampoor F, Azarpira N, Khatami SR, et al. (2019) Improved translation efficiency of therapeutic mRNA. Gene 707: 231-238.
    [27] Kowalski PS, Rudra A, Miao L, et al. (2019) Delivering the messenger: Advances in technologies for therapeutic mRNA delivery. Mol Ther 27: 710-728.
    [28] Reichmuth AM, Oberli MA, Jaklenec A, et al. (2016) mRNA vaccine delivery using lipid nanoparticles. Ther Deliv 7: 319-334.
    [29] Lundstrom K (2009) Alphaviruses in gene therapy. Viruses 1: 13-25.
    [30] Chira S, Jackson CS, Oprea I, et al. (2015) Progresses towards safe and efficient gene therapy vectors. Oncotarget 6: 30675-30703.
    [31] Ku SH, Jo SD, Lee YK, et al. (2016) Chemical and structural modifications of RNAi therapeutics. Adv Drug Deliv Rev 104: 16-28.
    [32] Presnyak V, Alhusaini N, Chen YH, et al. (2015) Codon optimality is a major determinant of mRNA stability. Cell 160: 1111-1124.
    [33] Thess A, Grund S, Mui BL, et al. (2015) Sequence-engineered mRNA without chemical nucleoside modifications enables an effective protein therapy in large animals. Mol Ther 23: 1456-1464.
    [34] Wojtczak BA, Sikorski PJ, Fac-Dabrowska K, et al. (2018) 5′-phosphorothiolate dinucleotide cap analogues: Reagents for messenger RNA modification and potent small-molecular inhibitors of decapping enzymes. J Am Chem Soc 140: 5987-5999.
    [35] Li B, Luo X, Dong Y (2016) Effects of chemically modified messenger RNA on protein expression. Bioconjug Chem 27: 849-853.
    [36] Li M, Zhao M, Fu Y, et al. (2016) Enhanced intranasal delivery of mRNA vaccine by overcoming the nasal epithelial barrier via intra- and paracellular pathways. J Control Release 228: 9-19.
    [37] Svitkin YV, Cheng YM, Chakraborty T, et al. (2017) N1-methyl-pseudouridine in mRNA enhances translation through eIF2a-dependent and independent mechanisms by increasing ribosome density. Nucleic Acids Res 45: 6023-6036.
    [38] Oberg AL, Kennedy RB, Li P, et al. (2011) Systems biology approaches to new vaccine development. Curr Opin Immunol 23: 436-443.
    [39] Auffan M, Rose J, Bottero JY, et al. (2009) Towards a definition of inorganic nanoparticles from an environmental, health and safety perspective. Nat Nanotechnol 4: 634-641.
    [40] Treuel L, Jiang X, Nienhaus GU (2013) New views on cellular uptake and trafficking of manufactured nanoparticles. J R Soc Interface 10: 20120939.
    [41] Ulkoski D, Bak A, Wilson JT, et al. (2019) Recent advances in polymeric materials for the delivery of RNA therapeutics. Expert Opin Drug Deliv 16: 1149-1167.
    [42] Pérez-Ortín JE, Alepuz P, Chávez S, et al. (2013) Eukaryotic mRNA decay: Methodologies, pathways, and links to other stages of gene expression. J Mol Biol 425: 3750-3775.
    [43] Pati R, Shevtsov M, Sonawane A (2018) Nanoparticle vaccines against infectious diseases. Front Immunol 9: 2224.
    [44] Means TK, Hayashi F, Smith KD, et al. (2003) The Toll-like receptor 5 stimulus bacterial flagellin induces maturation and chemokine production in human dendritic cells. J Immunol 170: 5165-5175.
    [45] Boraschi D, Italiani P, Palomba R, et al. (2017) Nanoparticles and innate immunity: new perspectives on host defence. Semin Immunol 34: 33-51.
    [46] Chen YS, Hung YC, Lin WH, et al. (2010) Assessment of gold nanoparticles as a size-dependent vaccine carrier for enhancing the antibody response against synthetic foot-and-mouth disease virus peptide. Nanotechnology 21: 195101.
    [47] Wang T, Zou M, Jiang H, et al. (2011) Synthesis of a novel kind of carbon nanoparticle with large mesopores and macropores and its application as an oral vaccine adjuvant. Eur J Pharm Sci 44: 653-659.
    [48] Xu L, Liu Y, Chen Z, et al. (2012) Surface-engineered gold nanorods: promising DNA vaccine adjuvant for HIV-1 treatment. Nano Lett 12: 2003-2012.
    [49] Tao W, Gill HS (2015) M2e-immobilized gold nanoparticles as influenza A vaccine: role of soluble M2e and longevity of protection. Vaccine 33: 2307-2315.
    [50] Li X, Deng X, Huang Z (2001) In vitro protein release and degradation of poly-d-L-lactide-poly(ethylene glycol) microspheres with entrapped human serum albumin: quantitative evaluation of the factors involved in protein release phases. Pharm Res 18: 117-124.
    [51] Chahal JS, Fang T, Woodham AW, et al. (2017) An RNA nanoparticle vaccine against Zika virus elicits antibody and CD8+ T cell responses in a mouse model. Sci Rep 7: 252.
    [52] Chahal JS, Khan OF, Cooper CL, et al. (2016) Dendrimer-RNA nanoparticles generate protective immunity against lethal Ebola, H1N1 influenza, and toxoplasma gondii challenges with a single dose. Proc Natl Acad Sci U S A 113: E4133-E4142.
    [53] Sharifnia Z, Bandehpour M, Hamishehkar H, et al. (2019) In-vitro transcribed mRNA delivery using PLGA/PEI nanoparticles into human monocyte-derived dendritic cells. Iran J Pharm Res 18: 1659-1675.
    [54] Uchida S, Kinoh H, Ishii T, et al. (2016) Systemic delivery of messenger RNA for the treatment of pancreatic cancer using polyplex nanomicelles with a cholesterol moiety. Biomaterials 82: 221-228.
    [55] Kaczmarek JC, Patel AK, Kauffman KJ, et al. (2016) Polymer-lipid nanoparticles for systemic delivery of mRNA to the lungs. Angew Chem Int Ed Engl 55: 13808-13812.
    [56] Patel AK, Kaczmarek JC, Bose S, et al. (2019) Inhaled nanoformulated mRNA polyplexes for protein production in lung epithelium. Adv Mater 31: e1805116.
    [57] Liu Y, Li Y, Keskin D, et al. (2019) Poly(β-amino esters): Synthesis, formulations, and their biomedical applications. Adv Healthc Mater 8: e1801359.
    [58] Capasso Palmiero U, Kaczmarek JC, Fenton OS, et al. (2018) Poly(β-amino ester)-co-poly(caprolactone) terpolymers as nonviral vectors for mRNA delivery in vitro and in vivo. Adv Healthc Mater 7: e1800249.
    [59] Palamà IE, Cortese B, D'Amone S, et al. (2015) mRNA delivery using non-viral PCL nanoparticles. Biomater Sci 3: 144-151.
    [60] Lacroix C, Humanes A, Coiffier C, et al. (2020) Polylactide-based reactive micelles as a robust platform for mRNA delivery. Pharm Res 37: 30.
    [61] Dong Y, Dorkin JR, Wang W, et al. (2016) Poly(glycoamidoamine) brushes formulated nanomaterials for systemic siRNA and mRNA delivery in vivo. Nano Lett 16: 842-848.
    [62] Palmerston Mendes L, Pan J, Torchilin VP (2017) Dendrimers as nanocarriers for nucleic acid and drug delivery in cancer therapy. Molecules 22: 1401.
    [63] Franiak-Pietryga I, Ziemba B, Messmer B, et al. (2018) Dendrimers as drug nanocarriers: the future of gene therapy and targeted therapies in cancer. Dendrimers: Fundamentals and Applications IntechOpen, 7.
    [64] Islam MA, Xu Y, Tao W, et al. (2018) Restoration of tumour-growth suppression in vivo via systemic nanoparticle-mediated delivery of PTEN mRNA. Nat Biomed Eng 2: 850-864.
    [65] Hajam IA, Senevirathne A, Hewawaduge C, et al. (2020) Intranasally administered protein coated chitosan nanoparticles encapsulating influenza H9N2 HA2 and M2e mRNA molecules elicit protective immunity against avian influenza viruses in chickens. Vet Res 51: 37.
    [66] McCullough KC, Bassi I, Milona P, et al. (2014) Self-replicating replicon-RNA delivery to dendritic cells by chitosan-nanoparticles for translation in vitro and in vivo. Mol Ther Nucleic Acids 3: e173.
    [67] Maiyo F, Singh M (2019) Folate-targeted mRNA delivery using chitosan-functionalized selenium nanoparticles: potential in cancer immunotherapy. Pharmaceuticals (Basel) 12: 164.
    [68] Son S, Nam J, Zenkov I, et al. (2020) Sugar-nanocapsules imprinted with microbial molecular patterns for mRNA vaccination. Nano Lett 20: 1499-1509.
    [69] Siewert C, Haas H, Nawroth T, et al. (2019) Investigation of charge ratio variation in mRNA - DEAE-dextran polyplex delivery systems. Biomaterials 192: 612-620.
    [70] Zeng C, Zhang C, Walker PG, et al. (2020) Formulation and delivery technologies for mRNA vaccines. Current Topics in Microbiology and Immunology Berlin: Springer.
    [71] Scheel B, Teufel R, Probst J, et al. (2005) Toll-like receptor-dependent activation of several human blood cell types by protamine-condensed mRNA. Eur J Immunol 35: 1557-1566.
    [72] Schlake T, Thess A, Fotin-Mleczek M, et al. (2012) Developing mRNA-vaccine technologies. RNA Biol 9: 1319-1330.
    [73] Fotin-Mleczek M, Duchardt KM, Lorenz C, et al. (2011) Messenger RNA-based vaccines with dual activity induce balanced TLR-7 dependent adaptive immune responses and provide antitumor activity. J Immunother 34: 1-15.
    [74] Schnee M, Vogel AB, Voss D, et al. (2016) An mRNA vaccine encoding rabies virus glycoprotein induces protection against lethal infection in mice and correlates of protection in adult and newborn pigs. PLoS Negl Trop Dis 10: e0004746.
    [75] Udhayakumar VK, De Beuckelaer A, McCaffrey J, et al. (2017) Arginine-rich peptide-based mRNA nanocomplexes efficiently instigate cytotoxic T cell immunity dependent on the amphipathic organization of the peptide. Adv Healthc Mater 6: 1601412.
    [76] Coolen AL, Lacroix C, Mercier-Gouy P, et al. (2019) Poly(lactic acid) nanoparticles and cell-penetrating peptide potentiate mRNA-based vaccine expression in dendritic cells triggering their activation. Biomaterials 195: 23-37.
    [77] Jekhmane S, De Haas R, Paulino da Silva Filho O, et al. (2017) Virus-like particles of mRNA with artificial minimal coat proteins: particle formation, stability, and transfection efficiency. Nucleic Acid Ther 27: 159-167.
    [78] Li J, Sun Y, Jia T, et al. (2014) Messenger RNA vaccine based on recombinant MS2 virus-like particles against prostate cancer. Int J Cancer 134: 1683-1694.
    [79] Sun S, Li W, Sun Y, et al. (2011) A new RNA vaccine platform based on MS2 virus-like particles produced in saccharomyces cerevisiae. Biochem Biophys Res Commun 407: 124-128.
    [80] Zhitnyuk Y, Gee P, Lung MSY, et al. (2018) Efficient mRNA delivery system utilizing chimeric VSVG-L7Ae virus-like particles. Biochem Biophys Res Commun 505: 1097-1102.
    [81] Kauffman KJ, Webber MJ, Anderson DG (2016) Materials for non-viral intracellular delivery of messenger RNA therapeutics. J Control Release 240: 227-234.
    [82] Kulkarni JA, Cullis PR, Van Der Meel R (2018) Lipid nanoparticles enabling gene therapies: From concepts to clinical utility. Nucleic Acid Ther 28: 146-157.
    [83] Dimitriadis GJ (1978) Translation of rabbit globin mRNA introduced by liposomes into mouse lymphocytes. Nature 274: 923-924.
    [84] Moon JJ, Suh H, Bershteyn A, et al. (2011) Interbilayer-crosslinked multilamellar vesicles as synthetic vaccines for potent humoral and cellular immune responses. Nat Mater 10: 243-251.
    [85] Tyagi RK, Garg NK, Sahu T (2012) Vaccination strategies against malaria: novel carrier(s) more than a tour de force. J Control Release 162: 242-254.
    [86] Adler-Moore J, Munoz M, Kim H, et al. (2011) Characterization of the murine Th2 response to immunization with liposomal M2e influenza vaccine. Vaccine 29: 4460-4468.
    [87] Monslow MA, Elbashir S, Sullivan NL, et al. (2020) Immunogenicity generated by mRNA vaccine encoding VZV gE antigen is comparable to adjuvanted subunit vaccine and better than live attenuated vaccine in nonhuman primates. Vaccine 38: 5793-5802.
    [88] Erasmus JH, Archer J, Fuerte-Stone J, et al. (2020) Intramuscular delivery of replicon RNA encoding ZIKV-117 human monoclonal antibody protects against Zika virus infection. Mol Ther Methods Clin Dev 18: 402-414.
    [89] Freyn AW, da Silva JR, Rosado VC, et al. (2020) A multi-targeting, nucleoside-modified mRNA influenza virus vaccine provides broad protection in mice. Mol Ther 28: 1569-1584.
    [90] Lo MK, Spengler JR, Welch SR, et al. (2020) Evaluation of a single-dose nucleoside-modified messenger RNA vaccine encoding Hendra virus-soluble glycoprotein against lethal Nipah virus challenge in Syrian hamsters. J Infect Dis 221: S493-S498.
    [91] Yang T, Li C, Wang X, et al. (2020) Efficient hepatic delivery and protein expression enabled by optimized mRNA and ionizable lipid nanoparticle. Bioact Mater 5: 1053-1061.
    [92] Moyo N, Wee EG, Korber B, et al. (2020) Tetravalent immunogen assembled from conserved regions of HIV-1 and delivered as mRNA demonstrates potent preclinical T-cell immunogenicity and breadth. Vaccines (Basel) 8: 360.
    [93] Lou G, Anderluzzi G, Schmidt ST, et al. (2020) Delivery of self-amplifying mRNA vaccines by cationic lipid nanoparticles: The impact of cationic lipid selection. J Control Release 325: 370-379.
    [94] Mai Y, Guo J, Zhao Y, et al. (2020) Intranasal delivery of cationic liposome-protamine complex mRNA vaccine elicits effective anti-tumor immunity. Cell Immunol 354: 104143.
    [95] Eygeris Y, Patel S, Jozic A, et al. (2020) Deconvoluting lipid nanoparticle structure for messenger RNA delivery. Nano Lett 20: 4543-4549.
    [96] Van Hoecke L, Verbeke R, De Vlieger D, et al. (2020) mRNA encoding a bispecific single domain antibody construct protects against influenza A virus infection in mice. Mol Ther Nucleic Acids 20: 777-787.
    [97] Zhong Z, Mc Cafferty S, Combes F, et al. (2018) mRNA therapeutics deliver a hopeful message. Nano Today 23: 16-39.
    [98] Bogers WM, Oostermeijer H, Mooij P, et al. (2015) Potent immune responses in rhesus macaques induced by nonviral delivery of a self-amplifying RNA vaccine expressing HIV type 1 envelope with a cationic nanoemulsion. J Infect Dis 211: 947-955.
    [99] Jackson LA, Anderson EJ, Rouphael NG, et al. (2020) An mRNA vaccine against SARS-CoV-2—preliminary report. N Engl J Med . doi: 10.1056/NEJMoa2022483
    [100] Alberer M, Gnad-Vogt U, Hong HS, et al. (2017) Safety and immunogenicity of a mRNA rabies vaccine in healthy adults: an open-label, non-randomised, prospective, first-in-human phase 1 clinical trial. Lancet 390: 1511-1520.
    [101] Bahl K, Senn JJ, Yuzhakov O, et al. (2017) Preclinical and clinical demonstration of immunogenicity by mRNA vaccines against H10N8 and H7N9 influenza viruses. Mol Ther 25: 1316-1327.
    [102] Feldman RA, Fuhr R, Smolenov I, et al. (2019) mRNA vaccines against H10N8 and H7N9 influenza viruses of pandemic potential are immunogenic and well tolerated in healthy adults in phase 1 randomized clinical trials. Vaccine 37: 3326-3334.
    [103] Ding Y, Jiang Z, Saha K, et al. (2014) Gold nanoparticles for nucleic acid delivery. Mol Ther 22: 1075-1083.
    [104] Liu J, Miao L, Sui J, et al. (2020) Nanoparticle cancer vaccines: Design considerations and recent advances. Asian J Pharm Sci . doi: 10.1016/j.ajps.2019.10.006
    [105] Yeom JH, Ryou SM, Won M, et al. (2013) Inhibition of xenograft tumor growth by gold nanoparticle-DNA oligonucleotide conjugates-assisted delivery of BAX mRNA. PLoS One 8: e75369.
    [106] Azmi F, Ahmad Fuaad AAH, Skwarczynski M, et al. (2014) Recent progress in adjuvant discovery for peptide-based subunit vaccines. Hum Vaccin Immunother 10: 778-796.
    [107] Coffman RL, Sher A, Seder RA (2010) Vaccine adjuvants: Putting innate immunity to work. Immunity 33: 492-503.
    [108] Reed SG, Orr MT, Fox CB (2013) Key roles of adjuvants in modern vaccines. Nat Med 19: 1597-1608.
    [109] Oleszycka E, Lavelle EC (2014) Immunomodulatory properties of the vaccine adjuvant alum. Curr Opin Immunol 28: 1-5.
    [110] Alving CR (2009) Vaccine adjuvants. Vaccines for Biodefense and Emerging and Neglected Diseases London: Elsevier, 115-129.
    [111] Hussein WM, Liu TY, Skwarczynski M, et al. (2014) Toll-like receptor agonists: a patent review (2011–2013). Expert Opin Ther Pat 24: 453-470.
    [112] Montomoli E, Piccirella S, Khadang B, et al. (2011) Current adjuvants and new perspectives in vaccine formulation. Expert Rev Vaccines 10: 1053-1061.
    [113] Mamo T, Poland GA (2012) Nanovaccinology: The next generation of vaccines meets 21st century materials science and engineering. Vaccine 30: 6609-6611.
    [114] Banchereau J, Briere F, Caux C, et al. (2000) Immunobiology of dendritic cells. Annu Rev Immunol 18: 767-811.
    [115] Oyewumi MO, Kumar A, Cui ZR (2010) Nano-microparticles as immune adjuvants: correlating particle sizes and the resultant immune responses. Expert Rev Vaccines 9: 1095-1107.
    [116] Marasini N, Skwarczynski M, Toth I (2014) Oral delivery of nanoparticle-based vaccines. Expert Rev Vaccines 13: 1361-1376.
    [117] Kawai T, Akira S (2011) Toll-like receptors and their crosstalk with other innate receptors in infection and immunity. Immunity 34: 637-650.
    [118] Vasilichin VA, Tsymbal SA, Fakhardo AF, et al. (2020) Effects of metal oxide nanoparticles on Toll-like receptor mRNAs in human monocytes. Nanomaterials (Basel) 10: 127.
    [119] Roy R, Kumar D, Sharma A, et al. (2014) ZnO nanoparticles induced adjuvant effect via toll-like receptors and Src signaling in Balb/c mice. Toxicol Lett 230: 421-433.
    [120] De Temmerman M-L, Rejman J, Demeester J, et al. (2011) Particulate vaccines: on the quest for optimal delivery and immune response. Drug Discov Today 16: 569-582.
    [121] Hafner AM, Corthésy B, Merkle HP (2013) Particulate formulations for the delivery of poly(I: C) as vaccine adjuvant. Adv Drug Deliv Rev 65: 1386-1399.

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