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Article

Deactivation of SARS-CoV-2 via Shielding of Spike Glycoprotein Using Carbon Quantum Dots: Bioinformatic Perspective

1
Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, ON M5S 3H6, Canada
2
Toxicology Research Center, Medical Basic Sciences Research Institute, Ahvaz Jundishapur University of Medical Sciences, Ahvaz 6135733184, Iran
3
Department of Biology, Faculty of Science, Shahid Chamran University of Ahvaz, Ahvaz 6135733184, Iran
4
Department of Chemistry, Faculty of Science, Shahid Chamran University of Ahvaz, Ahvaz 6135733184, Iran
*
Author to whom correspondence should be addressed.
Submission received: 17 June 2021 / Revised: 5 July 2021 / Accepted: 8 July 2021 / Published: 13 July 2021

Abstract

:
The interaction of the spike (S) glycoprotein of SARS-CoV-2 with angiotensin-converting enzyme 2 (ACE2) correlates with increased virus transmissibility and disease severity in humans. Two strategies may be considered for preventive or treatment purposes: the blockage of the ACE2 receptors or the shielding of receptor-binding domains (RBD) in the Sprotein of COVID-19, as well as the S2 cleavage site that is used by the furin enzyme of the host cells in the late phase of virus activation. Herein, the interaction of carbon quantum dots (CQDs) with the Sprotein of SARS-CoV-2 was investigated using molecular docking and molecular dynamics. CQD molecules were optimized by the HF/3-21G level of theory; the probable interactions between the CQDs with Sprotein were studied by blind docking mode, considering the Sprotein as the receptor and CQDs as ligands. Ethanol, folic acid, Favipiravir, two kinds of functionalized triangular hexagonal graphene, and four kinds of functionalized CQDs were studied on a comparative basis. The results show that OH and amine-functionalized CQDs tend to interact with three branches of Sprotein, especially RBD. The fact that they can block the S2 cleavage site leads to their potential use as a therapeutic agent.

1. Introduction

Coronavirus disease (COVID-19) was first identified in Wuhan, China, in December 2019. It was a global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease represents variable manifestations, varying from simple to life-threatening, leading to more than 170 million cases with 3.5 million deaths by May 2021.Angiotensin-converting enzyme 2 (ACE2) is the primary cellular receptor for both the severe acute respiratory syndrome-coronavirus (SARS-CoV-1) [1,2] and the new coronavirus (SARS-CoV-2) [3,4]. The virus binds to this receptor via its surface glycoprotein, called spike or S protein, with infectivity consequence. This fact has led to several investigations of the structure and function of the spike (S) glycoprotein for SARS-CoV-2 [1,5,6]. Electron microscopy studies have shown that the S glycoprotein of SARS-CoV-2 interacts with cell membrane receptors. The S protein is composed of two functional subunits that are responsible for binding and entering the host cell: the S1 and S2 subunits, respectively (Figure 1) [5,6]. For many CoVs, S is cleaved at the boundary between the S1 and S2 subunits. Furin mediates S1-S2 cleavage, and as a result, SARs-CoV-2 enters the cells and grows, causing the well characterized symptoms of the disease. Shuai Xia et al. [7] underlined the molecular mechanism of COVID-19 infection, in which they demonstrated that the binding of RBD in the S1 subunit of the S protein on the virus binds to the ACE2 receptor on the target cell. This is followed by the formation of a six-helix bundle (6-HB) fusion core between the heptad repeat 1 (HR1) and heptad repeat 2 (HR2) domains in the S2 subunit of the protein.
The formation of this fusion core brings the viral and cellular membranes into close proximity for fusion and resulting infection. A graphical representation of the 1D structure of the coronavirus spike protein is also shown in Figure 1. Here, the fusion peptide (FP), as well as heptad repeats 1 and 2 (HR1 and HR2), are structural units in coronavirus S2 that are a factor in membrane fusion.
Considerable research efforts have been conducted on a worldwide basis, with the goal of finding a suitable antiviral for the treatment of this disease [8]. In this regard, nanomaterials, which are extensively employed as anti-bacterial agents [9], constitute promising and efficient platforms to modulate the viral infection cycle. Nanomaterials been used recently in the development of fluorometric and electrochemical biosensors for rapid and accurate detection of COVID-19 via functionalization with different species, such as RNAs [10,11]. The sensing mechanisms in these studies offer the possibility of predicting interactions with viruses in terms of antiviral behavior or for protecting the living cells. The high surface-to-volume ratio and the multivalent character of particles, such as nanomaterials and quantum dots, allow for the attachment of ligands, which can in turn attach to the cell receptor and block viral entry into the cell. In this connection, researchers have discussed the antiviral activities of carbon quantum dots (CQDs) and their potential use as future antiviral materials [2,3,4,5,6,7,8,9,10,11,12,13,14]. For example, Łoczechinet al. [13] have investigated the effect of different functionalized CQDs on coronavirus growth and on the prevention of entrance to cells. In this case, 3 out of 7 tested CQDs were demonstrated to cause significant interreference with human coronavirus HCoV-229E-Luc infection in a concentration-dependent manner. A CQDnanoporous membrane was used for the preparation of sunlight-sterilized reusable face masks [12]. Boron-doped CQDs were also used for the experimental study of respiratory aerosol transport to the lungs in the treatment of bronchitis [15].
Prediction of the interaction modes of a ligand with a biomolecule as a receptor can be achieved via molecular docking software. The software searches high-dimensional space effectively and uses a scoring function that correctly ranks candidate modes of binding. An example is the examination of the interaction of coumarin and catechin with SARS-CoV2 and ACE2 of the human cell membrane [16]. In a recent molecular docking study, it was pointed out that folic acid, a water-soluble B vitamin, can prevent COVID-19 cellular entrance through the inhibition of Furin activity, resulting in the prevention of S1-S2 cleavage [17]. The results of this research imply that folate interacts with cell receptors and Furin. It was also shown that carbon quantum dots synthesized using folic acid as a carbon source produce the presence of the acid on their surface [18]. They also possess high quantum yields and could be used in cell imaging. In light of these studies, there is significant potential for the employment of carbon dots in the war against COVID-19 [19]. Furthermore, it is postulated that molecular docking is a suitable technique for the prediction of the interaction of CQDs with the S protein of SAR-COV2,which warrants further evaluation of their possible use as an antiviral agent. SARS-CoV-2 plays an important role in the virus’ life cycle, which makes it a potential target for inhibition by drugs. In the present work, the interaction of different functionalized CQDs with COVID-19 S-glycoprotein is simulated using the molecular docking method. In addition, two triangular hexagonal graphenes (THGs), folic acid, Favipiravir, and ethanol molecules were tested for comparison purposes.

2. Methods

2.1. Coordinate Structure Retrieval and Preparation

The coordinate structure of the SARS-CoV-2 S protein with PDB ID 6VYB was retrieved from the protein data bank (https://www.rcsb.org/; accessed on 25 December 2020) The structure was obtained by the X-ray diffraction technique and refined at a resolution of 2.16 Å. This structure was equilibrated and energy-minimized in GROMACS 2020.2 software to lower than 300 kJ mol1 in pH 7, 37 °C, and 1 atmosphere. Both ab-initio and density functional theory (DFT) calculations were also used to obtain the optimized geometries of the considered CQDs (which have 30 carbon atoms in their backbones) and the other selected molecules, excluding S protein. The calculations were performed at the HF/3-21G level of theory, followed by the B3LYP/6-31G** method implemented in Gaussian 09 software [20]. The obtained structures are given in Figure 2. Functional groups of the considered CQDs model drugs included hydroxyl (OH-CQD, THG1, THG2, ethanolic), carboxylic (COOH-CQD), epoxy (OH-NH2-CQD), and amide (CONH2-CQD) functionals. We investigated the interactions of small molecules, such as ethanol and Favipiravir (C5H4FN3O2) (which has a fluorine atom in its structure),for comparison.

2.2. Molecular Docking Simulations

To survey the potential anchoring sites on SARS-CoV-2 S protein for drug binding and to verify their ability to bind and mask RBD and/or S1-S2 cleavage sites, blind docking experiments were performed using the Hex 8.0.0 program (http://www.loria.fr/~ritchied/hex/; accessed on 15 December 2020) installed in a Linux operating system. Shape (and only Shape), Shape+Electrostatic, and Shape+Electrostatic+Dars with macro sampling were three different methods used in three different experiments on optimized protein structures, with the protein acting as a receptor and the drugs acting as ligands. These experiments were used to consider the non-bonding interactions of hydrogen bonds and electrostatic forces, as well as the structural complementarity of compounds to enzymes’ active sites. The best pose and the binding energies of a total of 100 poses were recorded for further statistical analysis. The parameters used for docking in HEX 8.0.0 software are presented in Table 1.

2.3. Molecular Dynamic (MD) Simulation

MD simulations were performed using GROMACS 2020.2 (www.gromacs.org; accessed on 15 December 2020) with the AMBER99 force field. All simulated structures were centered typically in a triclinic box (with dimensions of 8.15 × 9.06 × 9.58 nm) with a minimum distance of 1 nm between each atom of the protein and the box. The boxes were then filled with an SPCE water model shell of 1 nm thickness. The ionic strength was adjusted to make sure all simulations were electrically neutral. Energy minimization was executed by the steepest descent method and the conjugated gradient method for the subsequent steps in order to minimize the system energy to lower than 200 kJ·mol−1. Non-bonded forces were modeled using the particle-mesh Ewald (PME) method with a cutoff distance of 10 Å. A stepwise procedure was used to equilibrate the system. This procedure consisted of a first cycle of 100 ps positional restraints MD with a force constant of 1000 kJ·mol1 nm2 applied to the atoms of the protein with solvent atoms free to move, followed by 100 ps MD simulations in the isothermal–isobaric (NPT) ensemble to equilibrate pressure and temperature. The initial velocities were taken randomly from a Maxwellian distribution at 300 K. The temperature was held constant (300 K) using the V-rescale algorithm. Pressure was determined using the Parrinello–Ramhan barostat. Long-range electrostatic interactions were calculated using the particle mesh Ewald summation methods. Lennard–Jones interactions were calculated using a cutoff of 1 Å. The time step was 2 fs, and simulations were typically 50 ns long. Coordinates were saved every 50 ps.

3. Results and Discussion

The spike protein of COVID-19 contains three amino acid sequences (three branches), each having 1104 amino acids. A single region of the S protein, termed the receptor-binding domain (RBD) [5,21], includes amino acids from 319 to 541 (Figure 1).
RBD binds the ACE2 receptor, and then the nearby enzyme cleaves the spike protein (cleavage domain: sequence 788–806) and releases the spike fusion peptide, facilitating the entry of the virus into the cell. Every drug that could block RBD can effectively prevent the interaction of the receptor with the virus. The results of molecular docking for the considered molecules are shown in Figure 3. Additionally, the average binding energies, as well as the active site occupation percentages, are gathered in Table 2.
The molecular docking studies show that two different CQDs (OH-CQD and NH2-OH-CQD with 80% and 85% coverages, respectively) out of four effectively block RBD (Figure 3A–D and Table 2), although all of them are effective (Figures S1–S4). Analysis of variance indicates that there is a significant difference between all molecules, and in terms of the obtained interaction energies, OH-CQD performs better than the others. Table 2 demonstrates that the percentage of OH-CQDs and NH2-OH-CQD molecules that interact with the RBD of COVID-19 Sprotein is higher than amide-CQD (64%) and COOH-CQD (67%). THG1 and TGH2 have no interaction with either RBD or the cleavage domain (Figures S5 and S6 and Table 2). Favipiravir as a prescribed drug for COVID-19 treatment [22] was also considered in this docking study to compare the energy of its interaction with Sprotein with that of CQDs. As indicated in Table 2, Favipiravir is available at RBD (44%) with an interaction energy of −487kJ mol1, whereas EtOH as a disinfectant is mostly available at RBD with the least interaction energy of −148.5 kJ mol−1 (Figures S7–S9). Therefore, OH-CQD and NH2-OH-CQD, with binding energies of −699.3 and −592.2 kJ·mol1 and active site occupations of 80% and 85%, respectively, constitute the best candidates in our series.
Folic acid blocks the S1–S2 cleavage region and may prevent SARS-CoV-2 from entering the cell. The number of folic acid molecules that interact with the RBD is very low in comparison with the CQDs. This result is consistent with the recent research that confirms the binding of folic acid with Furin [5], which may be used to manage the respiratory disease caused by COVID-19. Folic acid loaded CQDs have previously been synthesized for cell imaging [4].The surface folate speeds up the entry of CQDs into the cell, and the bright fluorescence of the CQDs improves the image quality [23].This research has shown that folate can bind to the cell receptor. Having considered these findings, folate functionalized CQDs may be useful in the treatment and deactivation of SARS-CoV-2. Additionally, CQDs can deliver antiviral medicine to the RBD and cleavage domain (CD), resulting in the prevention of viral infection.
It should be noted that the interaction energies were correlated with the size and molecular weight of the considered ligand, i.e., increasing the size or molecular weight of the ligand caused an increase in the binding energy.
The S protein-drug interaction was driven mainly by hydrogen bonds. To investigate these interactions, the hydrogen bonds formed between the S protein and NH2-OH-CQD, as a representative of the tested CQDs (having shown the highest interaction), were extracted from the Hex 8.0.0 calculations. Figure 4 shows the large view of the interaction pose of CQDs with S protein. According to this figure, hydrogen bonding is formed between hydroxy and epoxy groups of NH2-OH-CQD and amino acid residue in the S protein as the receptor. The amino acids involved in these interactions wereGLN115, SER349, TYR351, ASN450, ARG466, THR470, GLU471, and SER494. The hydrogen atoms of the NH2 group on TYR351, ARG466, and THR470 residues formed two hydrogen bonds with epoxy oxygen on NH2-OH-CQDs, while COO- (carboxyl group) of SER349 and SER494 boundto the H atom of OH on the CQDs.
Molecular dynamics simulations were started from the most stable coordinates (the structure with the most negative binding energy), obtained from molecular docking. These simulations were only performed on OH-CQDs, NH2-OH-CQD, and THG2 systems, all of which have considerable binding energies. In all cases, at the end of simulations the CQD ligands were moved out of Sprotein. This might be due to the flatness of the molecules used as ligands or to the interaction of the CQD species with the solvent molecules.The results werepromising for THG2 because docking data (Table 2) suggested no interaction between THGs and RBD. Additionally, the use of these CQDs in the solid phase (for example, as a mask) may solve this problem; CQDs could strongly bind to the active sites of S protein in the absence of water molecules. The final step of 50 ns simulation for the NH2-OH-CQD molecule is shown in Figure 5.
RMSD analysis indicated that the protein started stabilizing after nearly 10 ns and maintained its stability until 50 ns (see Figure 5). An average RMSD value of 2 nm was obtained for the whole complex from 10 ns to 20 ns. Overall, the results show that NH2-CQD did not influence the protein’s structural stability and NH2-CQD itself retained its structural integrity.

4. Conclusions

This work represents the first theoretical study on the interactions between CQDs and the Sprotein of coronavirus, to the best of our knowledge. CQDs (as green particles with low cell toxicity) could be a suitable alternative for antiviral activity, especially with respect to the new coronavirus, SARS-CoV-2. The interaction energies of all the considered molecules with the S protein of SARS-CoV-2 are high and deserve experimental evaluation (the interaction energies are related to the size and weight of the molecule). The results also indicate that the functional groups on the carbon dots play an essential role with regard to the extent of the interaction and consequently its effectiveness. MD studies show that the interaction of the Sprotein with carbon dots is unfavorable in aqueous solutions. The comparison of the docking results of EtOH with those of CQDs suggests the potential use of hydroxy and NH2 functionalized CQDs as a disinfectant at high concentrations (ethanol has killing ability of 70% v/v as a disinfectant). Experimental evaluation is required to prove this assumption, which is based on the number of molecules available at RBD and the possibility of their interaction with the virus in the solid phase (CQDs deposited on the surface). Binding proven antiviral drugs (such as Favipiravir) to carbon quantum dots may reduce both the dose of the pharmaceuticals and the side effects. Therefore, theoretical evaluations of different antiviral drugs and functionalized CQDs are under consideration in our laboratory. In terms of practicality, such particles can be synthesized with facilities with available and low-cost carbon sources.

Supplementary Materials

The following are available online at https://0-www-mdpi-com.brum.beds.ac.uk/article/10.3390/covid1010011/s1, Figure S1: Distribution of NH2-OH-CQD in SARS-CoV-2 S-protein obtained by molecular docking. interaction with three branches of COVID-19 S protein (Up)and distributed CQDs (down), Figure S2: Distribution of OH-CQD in SARS-CoV-2 S-protein obtained by molecular docking. interaction with three branches of COVID-19 S protein (Up)and distributed CQDs (down), Figure S3: Distribution of COOH-CQD in SARS-CoV-2 S-protein obtained by molecular docking. interaction with three branches of COVID-19 S protein (Up)and distributed CQDs (down), Figure S4: Distribution of Amide-CQD in SARS-CoV-2 S-protein obtained by molecular docking. interaction with three branches of COVID-19 S protein (Up)and distributed CQDs (down), Figure S5: Distribution of Carbon nano-flake THG1 in SARS-CoV-2 S-protein obtained by molecular docking. interaction with three branches of COVID-19 S protein (Up)and distributed CQDs (down). Figure S6: Distribution of Carbon nano-flake THG2 in SARS-CoV-2 S-protein obtained by molecular docking. interaction with three branches of COVID-19 S protein (Up)and distributed CQDs (down). Figure S7: Interaction of SARS-CoV-2 S-protein with Folic Acid using molecular docking. interaction with three branches of COVID-19 S protein (Up)and distributed CQDs (down). Figure S8: Distribution of EtOH in SARS-CoV-2 S-protein obtained by molecular docking. interaction with three branches of COVID-19 S protein (Up)and distributed CQDs (down), Figure S9: Distribution of Favipiravir in SARS-CoV-2 S-protein obtained by molecular docking. interaction with three branches of COVID-19 S protein (Up)and distributed CQDs (down).

Author Contributions

Conceptualization, Z.R.; methodology, Z.R., M.R.D., and S.N.; software, M.R.D. and S.N.; validation, Z.R., M.R.D., and S.N.; formal analysis, M.R.D. and S.N.; investigation, Z.R., M.R.D., and S.N.; resources, S.N.; data curation, Z.R., M.R.D., and S.N.; writing—original draft preparation, Z.R.; writing—review and editing, Z.R., M.R.D., S.N., and M.T.; visualization, Z.R., S.N., and M.T.; supervision, M.T.; project administration, Z.R.; funding acquisition, S.N. All authors have read and agreed to the published version of the manuscript.

Funding

Grant number G1399, Shahid Chamran University of Ahvaz.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data sharing is not applicable to this article.

Acknowledgments

The authors gratefully acknowledged the financial support of the Shahid Chamran University of Ahvaz under grant number G1399.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Schematic of SARS-CoV-2 and its spike glycoprotein (S protein).
Figure 1. Schematic of SARS-CoV-2 and its spike glycoprotein (S protein).
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Figure 2. Optimized structures of the proposed interacting agents.
Figure 2. Optimized structures of the proposed interacting agents.
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Figure 3. Distribution of 100 (A) OH-CQD, (B) COOH-CQD, (C) Amide-CQD, (D) and NH2-OH-CQD molecules within SARS-CoV-2 Sprotein using molecular docking.
Figure 3. Distribution of 100 (A) OH-CQD, (B) COOH-CQD, (C) Amide-CQD, (D) and NH2-OH-CQD molecules within SARS-CoV-2 Sprotein using molecular docking.
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Figure 4. Illustration of the hydrogen bonds formed between the S protein of SARS-CoV-2 and the NH2-OH-CQDs.
Figure 4. Illustration of the hydrogen bonds formed between the S protein of SARS-CoV-2 and the NH2-OH-CQDs.
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Figure 5. Plot of RMSD (in nm) fitted as a function of time (in ns) for the backbone of protein and the NH2-CQD molecule (left), and image after 50 ns MD simulation for NH2-OH-CQD and S protein interaction of SARS-CoV-2.
Figure 5. Plot of RMSD (in nm) fitted as a function of time (in ns) for the backbone of protein and the NH2-CQD molecule (left), and image after 50 ns MD simulation for NH2-OH-CQD and S protein interaction of SARS-CoV-2.
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Table 1. Parameters used for docking in the HEX 8.0.0 program.
Table 1. Parameters used for docking in the HEX 8.0.0 program.
ParameterValueDescription
Grid Dimension0.6With 100 solutions
Receptor range60With step size 7.5
Ligand (CQDS) range60With step size 7.5
Twist range90With step size 5.5
Distance range40With box size 10
Scan step0.8
Final Scan25
Table 2. The interaction energies and the percentage of binding sites occupied by the considered carbon species in two crucial regions of SARS-CoV-2 Sprotein.
Table 2. The interaction energies and the percentage of binding sites occupied by the considered carbon species in two crucial regions of SARS-CoV-2 Sprotein.
Carbon SpecieskJ·mole −1319–541 a788–806 b
OH-CQDs−699.38014
Amide-CQDs−689.7640
COOH-CQDs−652.1673
NH2-OH-CQDs−592.28514
THG1−369.800
THG2−422.900
Favipirvir−487.2440
Folic Acid−425.31046
EtOH−148.5845
a: receptor binding domain (RBD); b: cleavage domain (CD).
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Ramezani, Z.; Dayer, M.R.; Noorizadeh, S.; Thompson, M. Deactivation of SARS-CoV-2 via Shielding of Spike Glycoprotein Using Carbon Quantum Dots: Bioinformatic Perspective. COVID 2021, 1, 120-129. https://0-doi-org.brum.beds.ac.uk/10.3390/covid1010011

AMA Style

Ramezani Z, Dayer MR, Noorizadeh S, Thompson M. Deactivation of SARS-CoV-2 via Shielding of Spike Glycoprotein Using Carbon Quantum Dots: Bioinformatic Perspective. COVID. 2021; 1(1):120-129. https://0-doi-org.brum.beds.ac.uk/10.3390/covid1010011

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Ramezani, Zahra, Mohammad Reza Dayer, Siamak Noorizadeh, and Michael Thompson. 2021. "Deactivation of SARS-CoV-2 via Shielding of Spike Glycoprotein Using Carbon Quantum Dots: Bioinformatic Perspective" COVID 1, no. 1: 120-129. https://0-doi-org.brum.beds.ac.uk/10.3390/covid1010011

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