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Table of Contents
Year : 2023  |  Volume : 9  |  Issue : 1  |  Page : 61-70

Identification of SARS-CoV-2 spike protein inhibitors from Urtica dioica to develop herbal-based therapeutics against COVID-19

1 Cell and Molecular Biology Laboratory, Department of Zoology, Soban Singh Jeena University Campus, Almora; Department of Zoology, Kumaun University, Nainital Uttarakhand, India
2 Department of Biotechnology, National Institute of Technology, Raipur (Chhattisgarh), India
3 Cell and Molecular Biology Laboratory, Department of Zoology, Soban Singh Jeena University Campus, Almora, Uttarakhand, India

Date of Submission27-Jul-2021
Date of Acceptance09-Oct-2021
Date of Web Publication17-Oct-2022

Correspondence Address:
Dr. Awanish Kumar
Department of Biotechnology, National Institute of Technology, Raipur, Chhattisgarh
Dr. Mukesh Samant
Cell and Molecular Biology Laboratory, Department of Zoology, Soban Singh Jeena University Campus, Almora, Uttarakhand
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/2311-8571.358784

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Objective: The high transmission rate and mutations of SARS-CoV-2 have made it a global pandemic, and the shortage of any effective clinical treatment has created such a commotion. There are some synthetic antiviral drugs, such as remdesivir and lopinavir that are being repurposed to treat SARS-CoV-2, but all of these demonstrate extreme side effects in humans. Hence, promoting herbal-based drug development has become crucial as they are cost-effective and have lesser or no side effects. Urtica dioica is abundant in the Himalayan region and the compounds present in it have shown significant antiviral and anti-SARS activity. Therefore, molecular docking studies were performed to identify SARS-CoV-2 spike protein inhibitors from U. dioica to combat the COVID-19 disease. Materials and Methods: Compounds from U. dioica were screened using the bioinformatic approach, and subsequently, these compounds were docked with the S1 subunit of the COVID-19 spike protein (PDB ID: 6YOR). Molecular docking was carried out using the PyRx software (0.8 version) and further examined by employing the Discovery Studio Visualizer. Results: About all the selected compounds showed significant binding energy (e.g., beta-sitosterol: −10.3 kcal/mol) in contrast to the control chloroquine phosphate. This binding was observed with the spike protein residues that were common in the old strain and the more contagious newly modified B.1.1.7 strain of SARS-CoV-2. Conclusions: Thus, our study can be used in effective drug development against SARS-CoV-2 and its mutant strains also.

Keywords: Herbal therapeutics, molecular docking, SARS-CoV-2, spike protein, Urtica dioica

How to cite this article:
Upreti S, Prusty JS, Kumar A, Samant M. Identification of SARS-CoV-2 spike protein inhibitors from Urtica dioica to develop herbal-based therapeutics against COVID-19. World J Tradit Chin Med 2023;9:61-70

How to cite this URL:
Upreti S, Prusty JS, Kumar A, Samant M. Identification of SARS-CoV-2 spike protein inhibitors from Urtica dioica to develop herbal-based therapeutics against COVID-19. World J Tradit Chin Med [serial online] 2023 [cited 2023 Jun 2];9:61-70. Available from: https://www.wjtcm.net/text.asp?2023/9/1/61/358784

  Introduction Top

The outburst of COVID-19 was reported first in the Wuhan city of China;[1] later, its outbreak was observed worldwide, making it a global pandemic causing 6,297,512 deaths and 526,072,852 cases as of May 20, 2022. Coronavirus is a positive ssRNA virus, comprising four genera, viz., alpha, beta, gamma, and delta.[2] Studies suggest that the alpha and the beta forms of the virus infect mammals; however, the gamma and the delta forms of the virus infect birds.[3] The alpha coronaviruses 229E and NL63 infect humans, while the human-infecting beta coronaviruses are HKU1, MERS-CoV, OC43, SARS-CoV, and SARS-CoV-2.[4] SARS-CoV-2 primarily affects the respiratory and gastrointestinal systems, and it has a spike (S) protein that is responsible for giving it a crown-like appearance, hence the name coronavirus. S protein that acts as a ligand for the receptor angiotensin-converting enzyme 2 (ACE-2) of the host cell (contributing to the tissue tropism and infectivity of the coronavirus) consists of ~1200 amino acids and is a member of the class-I type of viral fusion protein.[5],[6] It is a homotrimer with two subunits S1 (globular subunit) and S2 (that form the stalk). The S1 subunit consists of a highly conserved receptor-binding domain (RBD) that binds with the host cell ACE-2 receptors, leading to the host-specific recognition.[7] Moreover, the S2 subunit consists of a cleavage site that is cleaved by TMPRSS2 (a host cell protease), leading to the internalization of the virus.

The havoc caused by the novel coronavirus along with the new virulent strains formed by the frequent mutations in the spike protein remains a matter of chaos. Among the novel variants, the newly discovered SARS-CoV-2 B.1.1.7 strain (first reported in the United Kingdom) is assumed to be a highly virulent strain.[8] Most of the vaccines that have been developed to overcome the novel coronavirus target the spike (S) protein. However, the B.1.1.7 strain has been examined, and it was found that it possesses significant mutations in its spike protein; hence, the development of some effective herbal-based drugs is still an urgent need. Some compounds that have shown effective results against SARS and MERS in the past were examined and repurposed against SARS-CoV-2;[9],[10],[11] however, none of these drugs have still passed Phase III of the clinical trial. Currently available antivirals are toxic and demonstrate extreme side effects in humans, such as diarrhea, anemia, dizziness, angioedema, dry mouth, menstrual cycle irregularities, atrioventricular block, renal failure, and hepatotoxicity.[12],[13],[14] Hence, herbal-based compounds may be crucial for the development of cost-effective therapeutic agents. Various plants from the Himalayan range have already been explored to treat an array of diseases. Urtica dioica, which is profusely present in the Himalayan region, has been reported for its antiviral and anticancerous activities.[15],[16],[17],[18] Recently, we have also demonstrated the anti-SARS-CoV-2 activity of various compounds from Urtica by docking these compounds to the ACE-2 receptor.[19] In this study, compounds from Urtica have been further explored as putative anti-SARS-CoV-2 agents by targeting the S1 subunit of the S protein. We have selected some effective antiviral and anticancerous compounds from U. dioica, viz., beta-sitosterol, alpha-tocopherol, tetramethyl-1, 2, 3, 5, 6, 7, 8, 8a-octahydronaphthalen-1-ol, quercetin, and violaxanthin.[16],[17] Moreover, U. dioica compounds (quercetin, luteolin, beta-sitosterol, and kaempferol) have also been reported for their effective results against the SARS-CoV (members of the order Nidovirales).[17] We have performed molecular docking of different compounds from Urtica with the spike protein's S1 subunit, and very significant docking scores were obtained in comparison to the positive control chloroquine phosphate. Moreover, it was also found that the interacting amino acid residues of the S1 subunit are common in both SARS-CoV-2 and its mutated B.1.1.7 strain. Thus, these compounds could be effective against both original and the modified B.1.1.7 strains of COVID-19. Therefore, the U. dioica compounds involved in our study could be a potential lead in the expansion of efficient therapeutics against SARS-CoV-2.

  Materials and Methods Top

Building the phytochemical library

We have selected 40 compounds from U. dioica, with potential biological activity[15],[16],[17],[18] using different search engines, viz., PubMed, DLAD4U, and Carrot2, to explore various research papers [Table 1].
Table 1: Protein and drug candidates undergoing docking experiment with their best docking score and involved active amino acid residues of 6YOR

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Dataset search for protein selection and preparation

X-ray crystallographic structures of the SARS-CoV-2 spike protein S1 (PDB ID: 6YOR) in complex with CR3022 Fab (resolution: 3.30 Å) were taken from the database PDB (URL: https://www.rcsb.org). The basic criteria for choosing PDB were minimum resolution and conformation of the docked ligands, being the same as in the crystallized protein structure after performing redocking. Another criterion is that the selected protein's three-dimensional (3D) structure should not have any protein breaks. However, we considered Ramachandran plot statistics as the most important filter for the selection of protein that none of the amino acid residues were present in disallowed regions. The SARS-CoV-2 spike protein S1 3D structure was prepared by UCSF Chimera 10.1, which is a tool used for preparing structures before docking. Protein binding sites of chains were selected, and others are removed using the Chimera tool. Co-crystallized water molecules, nonpolar hydrogens, small molecules, non-essential residues and lone pairs were removed from the chosen proteins to make them ready for docking. Hydrogens and Gasteiger charges were then added and merged.

Ligands preparation

All the selected ligands were acquired from the compound database PubChem (URL: https://pubchem.ncbi.nlm.nih.gov). The compound preparation steps of U. dioica were performed as follows: (i) conversions of 2D structure to 3D, (ii) structure correction, (iii) generating the structure variations, and (iv) structure optimization and validation. The screened ligands were downloaded in 2D SDF format and then converted to 3D SDF format using the Chem3D version 18.0 tool for ligand chemical structure design. The screened ligands were downloaded in the 2D structure of SDF format and further subjected to energy minimization using a virtual screen tool. By minimizing energy, the geometric optimization was executed to obtain a lower energy conformation for each ligand, i.e., until the value of root mean square gradient reached a value <0.001 kcal/mol through the virtual screening tool Open Babel of PyRx 0.8 (San Diego, California, USA). In the PyRx virtual screening tool, such energy-minimized structures were considered for docking. Before testing U. dioica compounds' potentiality against 6YOR, a broad-spectrum antiviral compound chloroquine phosphate (PubChem CID-64927) was used.

Phylogeny and homology modeling

The sequence of amino acids from various human-infecting coronavirus spike proteins was aligned using multiple sequence alignment tool, Clustal W (UCD, Dublin, Ireland). The spike protein sequences of the novel coronavirus (QII57161.1) along with its mutated strain and other human-infecting coronaviruses, viz., MERS-CoV (QEJ82226.1), SARS-CoV (APO40579.1), human coronavirus OC43 (AAR01015.1), NL63 (AVL25591.1), 229E (AWH62679.1), and HKU1 (AYN64561.1) were retrieved in the FASTA format using the protein database NCBI (www.ncbi.nlm.nih.gov/protein/). Further, this alignment of these sequences was carried out to examine the variations in the S protein, and using this alignment, a phylogenetic tree was subsequently developed.

Virtual screening of receptor–ligand docking

Molecular screening of the compounds was performed using the virtual tool PyRx and AutoDock wizard as the engine for the process of docking.[20] This virtual tool was employed for screening of ligands that includes both AutoDock Vina and AutoDock with the Lamarckian Genetic Algorithm (LGA) as a scoring function.[21],[22] Using the PyRx virtual screening tool, all the docking studies were achieved by employing the blind docking method (using the grid box that was large enough to cover the structure of the whole protein and encounter any possible interaction between receptor–ligand). During the docking period, the ligands were considered to rotate freely and the protein was considered to be as rigid. The configuration file for grid parameters was obtained using the Auto Grid engine of the PyRx virtual tool. This application also was used to predict the amino acid residue in the active sites of protein (target) that interact with their respective selected compounds (ligands). All docking studies were performed in which active site dimensions were set in the grid box by encompassing all possible ligand–receptor complex, and the dimensions were set as X = 221.6993, Y = 248.1436, and Z = 244.3667 to dock all the ligands, where 8 maximum exhaustiveness were calculated for each ligand. The results <1.0 Å in positional root mean square deviation were considered best and clustered together to get favorable binding. The binding energy with the most negative values was considered as the ligand having a maximum affinity for binding. Molecules having top-scoring in the largest cluster were analyzed and considered most stable. Ligand conformers were automatically docked to the receptor protein and the most stable conformer was used for postdocking. Using Discover Studio Visualizer 3.0 (Dassault Systemes BIOVIA, San Diego, California, USA), the final visualization of docked conformers was performed. To understand the effect of active antiviral and selected phytochemical lead molecules on SARS-CoV-2 spike S1 protein, molecular docking of the total of 40 selected phytochemicals of U. dioica and one standard antiviral compound (chloroquine phosphate) were tested with the PyRx virtual screen tool as control.

  Results Top

Phylogenetic analysis

The evaluation of phylogenetic relationship among various human-infecting coronaviruses (SARS-CoV-2, SARS-CoV-2–mutated strain: B.1.1.7 strain, MERS-CoV, SARS-CoV, human coronavirus OC43, NL63, 229E, and HKU1) was executed [Figure 1]. It was found that the mutated B.1.1.7 strain is about 99.293% similar to the SARS-CoV-2; further, SARS-CoV-2 was about 28.776% similar to MERS-CoV, 71.406% similar to SARS-CoV, 27.572% similar to OC43, 10.901% similar to NL63, 22.921% similar to 229E, and 26.742% similar to HKU1. Such a high level of similarity between SARS-CoV-2 and its mutated B.1.1.7 strain suggests that the compound involved in our study can be effective against both B.1.1.7 strain and SARS-CoV-2. B.1.1.7 has been examined for the mutations in its spike protein, and it was observed that there were six positions with significant amino acid variations, and only two of these mutations are present in the RBD region, which consists of about 254 amino acids (330–583). The modified B.1.1.7 strain has the following changes in the sequence of the amino acids: N501Y, A570D, P681H, T716I, S982A, and D1118H, and three deletions at 69 (H), 70 (V), and 144 (Y).[8] The compounds involved in our study target the amino acid residues that are similar to both the SARS-CoV-2 and the B.1.1.7 strain, hence making them more successful in the efficient drug development against both the original and mutated strain of COVID-19.
Figure 1: Multiple sequence alignment and phylogenetic relationship of different human infecting coronaviruses along with the mutated strain of SARS-CoV-2 (B.1.1.7). (a) Using the Network Protein Sequence Analysis online tool, the protein sequences were aligned by the ClustalW 2.1 algorithm, and aligned sequences were graphically viewed by the Easy Sequencing in PostScript (ESPript) program. Various mutations in the SARS-CoV-2 B.1.1.7 strain have been highlighted and deletion has been encircled. (b) Phylogenetic analysis was conducted on ClustalW 2.1 aligned sequences using the neighbor-joining method and bootstrap analysis (1000 repeats) by the Poisson model method of MEGA v5.2

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  Docking of Ligand Molecules with SARS-CoV-2 Spike S1 Protein Top

In the current investigation, we have used molecular docking that guided differential evolution via combining the differential evolution–optimization technique with a cavity prediction algorithm.[23] Docking predicted the interaction model between the biomolecule and small molecule for an established binding site in terms of binding energy. Binding energy suggests the affinity of a specific ligand and the strength by which a ligand interacts with and binds to the pocket of the target protein. We have selected SARS-CoV-2 spike S1 protein which is highly important for viral entry to the host immune system.[24] After successful docking of these compounds into their therapeutic targets, the results have shown various modes of drug–protein interaction are obtained with specific binding energy (docking score) [Table 1].

Interaction between virulent spike S1 protein and phytochemicals of Urtica dioica

The results obtained from this experiment indicated both stronger and weaker interactions of the potential drug candidates against the target protein. The binding mode with the least binding affinity is considered the best binding mode because it is the most stable for the ligand. The least binding energy which indicates a better fit for all the drugs against SARS-CoV-2 spike S1 protein is summarized in [Table 1]. It also reveals molecular data represented in terms of binding affinity (ΔG in kcal/mol) for a selected therapeutic target protein with all selected drugs. Results presented in [Table 1] indicated that all these compounds were binding to viral spike S1 protein. Different ligands show the highest binding affinity against the target protein and these data are represented in rank order (higher docking scores to lower). After visualizing the protein–ligand complex in Discovery Studio Visualizer 3.0, it was found that SARS spike glycoproteins are involved in the interaction with their respective ligands. It was found that all ligands are binding to the target protein with good binding energies, but the binding affinity of beta-sitosterol is more favorable than other lead compounds. The docking of beta-sitosterol with the SARS-CoV-2 spike S1 protein revealed that beta-sitosterol (ligand) shows high binding energies with chain A of protein with the affinity of −10.3 kcal/mol. To interact with the protein, beta-sitosterol acquires the central pocket surrounded by chain A which leads to hydrophobic interaction between beta-sitosterol and amino acid residues of the protein. The interaction at the amino acid level was checked by docking. Similarly, the docking analysis [Figure 2] indicated significant interaction in the binding pocket of 6YOR protein with chloroquine phosphate (standard drug) with an affinity of −4.8 kcal/mol. The major interaction between chloroquine phosphate and the target protein is characterized by carbon-hydrogen bond and alkyl types of interaction. Only two of the hydrogen bonding interaction was observed with the active amino acids such as Phe 515 and Asp 428 of the target protein. In reality, we have not set any specific amino acid as rigid precision though the availability of some information on active side amino acid residues. In our present work, we have determined the docking or binding free energy [Figure 3] which reflects the five top-ranked binding interactions to COVID-19 spike S1 protein. Beta-sitosterol has shown the most efficient docking with the lowest binding energy of −10.3 kcal/mol, by the formation of one alkyl type of interaction with Val 367 (4.48 Å) and one pi-alkyl type of interaction with Phe 374 (4.61 Å) [Figure 3]a. The lowest binding energy shown by the alpha-tocopherol dock was −9.2 kcal/mol, making it the second most efficient ligand with spike protein of SARS-CoV-2 [Figure 3]b. It forms different ligand–protein interaction which includes two pi-donor types of interaction with an active residue of Trp 436 (3.37 Å and 3.94 Å), one pi-sigma bond with Trp 436 (3. 67 Å), five alkyl and two pi-alkyl types of interaction with the amino acids of Val 367 (4.99 Å, 4.61 Å, and 4.46 Å), Leu 368 (5.13 Å), and Leu 335 (4.54 Å), as well as Phe 338 (4.96 Å) and Phe 342 (4.72 Å), respectively. Tetramethyl-1, 2, 3, 5, 6, 7, 8, 8a-octahydronaphthalen-1-ol was found to be another inhibitor [Figure 3]c, making it the third most efficient ligand with the binding energy of −8.8 kcal/mol. It forms one conventional H-bond with the Ileu 472 residue (2.98 Å), and three alkyls and one pi-alkyl interaction were also formed with Arg 457 (4.45 Å), Lys 458 (4.01 Å), Pro 491 (4.99 Å), and Tyr 453 (5.11 Å), respectively. As shown in [Figure 3]d, molecular docking of the ligand quercetin with the binding energy of −8.5 kcal/mol, was found to be an effective inhibitor of the spike S1 protein of SARS-CoV-2. This interaction formed a significant amount of conventional hydrogen bonds with the residues Arg 454 (2.96 Å and 2.94 Å), Arg 457 (2.94 Å), Ser 459 (2.46 Å and 2.72 Å), Ser 469 (2.93 Å), Asp 467 (2.70 Å), Glu 471 (3.21 Å), and Ile 472 (2.97 Å). In addition, one carbon-hydrogen bond was formed with the active residue Tyr 473 (3.41 Å). Violaxanthin indicated in [Figure 3]e was also found as another topmost efficient ligand that generates the lowest binding energy of −8.2 kcal/mol with the target virulent protein. Single conventional hydrogen bond interaction is observed between the amino acid Arg 355 (2.20 Å) and the H-donor of violaxanthin. Along with that, one pi-sigma and one pi-alkyl type of interaction were also visible in the hydrophobic pocket of the target protein with the amino acid Phe 464 (3.70 Å and 5.13 Å). In silico studies revealed that the selected ligand molecules showed good binding energy (−10.3 kcal/mol to −4.8 kcal/mol) toward the target protein. All the top docked compounds pose well-established bonds with one or more amino acids' residue in the SARS-CoV-2 spike protein S1 binding pocket. The top-ranked molecule with the lowest binding affinities and high docking score (in terms of negative value) was used as a standard selection generally in most of the docking programs. Beta-sitosterol has the most negative ΔG value followed by alpha-tocopherol and then tetramethyl-1, 2, 3, 5, 6, 7, 8, 8a-octahydronaphthalen-1-ol, respectively. This can be directly associated with the number of noncovalent interactions. Within the active site of SARS-CoV-2 spike S1 protein, these ligands undergo with the surrounding residues.
Figure 2: Chloroquine phosphate docked in SARS-CoV-2 spike S1 protein with (a) amino acid residues involved in interaction and (b) two-dimensional interaction of chloroquine phosphate with amino acid residues with hydrogen bond (green color dash line)

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Figure 3: The SARS-CoV-2 spike S1 protein and binding interaction of drug ligands showing top-ranked high binding affinity with comparison to chloroquine phosphate (−4.8 kcal/mol). (a) Beta-sitosterol (−10.3 kcal/mol) docked in SARS-CoV-2 spike S1 protein, (b) alpha-tocopherol (−9.2 kcal/mol) docked in SARS-CoV-2 spike S1 protein, (c) tetramethyl-1,2,3,5,6,7,8,8a-octahydronaphthalen-1-ol (−8.8 kcal/mol) docked in SARS-CoV-2 spike S1 protein, (d) quercetin (−8.5 kcal/mol) docked in SARS-CoV-2 spike S1 protein, and (e) Violaxanthin (−8.2 kcal/mol) docked in SARS-CoV-2 spike S1 protein

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  Discussion Top

The commotion created by the novel coronavirus has caused numerous severities and has stalled all activities around the world. Currently, there are no drugs available for combating this novel form of the coronavirus; however, some drugs such as remdesivir, lopinavir/rotinavir[25],[26] (synthetic drugs, used to treat viral infections), chloroquine, and hydroxychloroquine (antimalarial drugs) are being currently used to treat this particular virus,[26] but these drugs are associated with various side effects; hence, employing natural compounds to treat the novel coronavirus will facilitate the development of some effective antiviral herbal-based drugs. U. dioica, a plant with antiviral, anticancerous, antioxidant, anti-inflammatory, analgesic, immune-modulatory, hepatoprotective, and antidiabetic properties, is a very abundant plant in the Himalayan region;[15],[16],[17] moreover, it has also been found to be effective against the member of the order Nidovirales (includes the family Coronaviridae). Our study includes some active compounds from Urtica that were used to target the S protein by molecular docking approach.

As an imperative part of drug discovery programs, in silico screening capacity of U. dioica phytoconstituents against the pathogen causing COVID-19 was explored. Authors have attempted a ligand or target-based computational screening of plant U. dioica for binding site analysis, ligand affinity, and molecular docking against the S1 subunit of the SARS-CoV-2 spike protein, which is responsible for disease establishment and pathogenesis. The exterior of SARS-CoV-2 is enclosed by the glycosylated spike protein, which has the S1 and S2 subunits. The obtained result signifies the fact that out of 40 selected ligand compounds from U. dioica, almost all compounds have shown the highest binding affinity in comparison to −4.8 kcal/mol (chloroquine phosphate). The final docked confirmations obtained for different compounds were evaluated based on the binding compatibility, nature of bonds, and interacting amino acid residues. As expected, these lead molecules are showing minimum energy for binding with the 6YOR target followed by chloroquine phosphate. This result further advocated the exploration of these natural molecules as a lead anti-COVID-19 agent because since ancient times, natural products especially from plant origin have been widely used to treat diseases and it is very imperative to search and know the effectiveness of plants like U. dioica on the new strain of SARS-CoV-2.

The novel coronavirus enters the host cell once the S1 subunit (RBD region) binds to the host cell ACE-2 receptor, blocking the RAS system in the host,[7] and later TMPRSS2 (a host cell protease) cleaves the S2 subunit at some particular regions, leading to the activation and internalization of the virus [Figure 4]a. Among all the bioactive compounds that were undertaken from Urtica, beta-sitosterol (Compound 1) displayed the highest docking score (−10.3 kcal/mol), followed by alpha-tocopherol (−9.2 kcal/mol), tetramethyl-1, 2, 3, 5, 6, 7, 8, 8a-octahydronaphthalen-1-ol (−8.8 kcal/mol), and quercetin (−8.5 kcal/mol). These bioactive compounds can act by two tentative pathways to surmount COVID-19. First, these compounds can bind with the RBD region of the spike protein, thus preventing its binding with the ACE-2 receptor of the host, impeding the host cell recognition. Second, these compounds can bind at the cleavage site present in the S2 subunit, thus preventing the host cell protease from activating the virus, consequently blocking the viral entry in the host cell, resulting in the normal functioning of the Renin Angiotensin System (RAS) system in the host [Figure 4]b.
Figure 4: SARS-CoV-2 infection: (a) The receptor binding domain region of the S1 subunit binds with the angiotensin-converting enzyme 2 receptor of the host cell and blocks the RAS system, further TMPRSS2 cleaves the S2 subunit at some definite regions, resulting in the activation and internalization of the virus inside the host cell. In the host cell, the virus multiplies and infects as many cells as it can, leading to the collapse of the host. (b) To surmount the coronavirus disease, these bioactive compounds can act by two tentative pathways. First, these compounds can bind with the receptor binding domain region of the spike protein and prevent it from binding with the angiotensin-converting enzyme 2 receptor of the host, thus impeding the host cell recognition. Second, these compounds can bind at the cleavage site present in the S2 subunit, thus preventing the host cell protease from activating the virus, consequently blocking the viral entry in the host cell

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  Conclusions Top

In conclusion, this study demonstrated that all the selected compounds can act as lead molecules. Among these compounds, beta-sitosterol was found to exhibit the highest binding affinity, i.e., −10.3 kcal/mol, followed by alpha-tocopherol (−9.2 kcal/mol), tetramethyl-1, 2, 3, 5, 6, 7, 8, 8a-octahydronaphthalen-1-ol (−8.8 kcal/mol), quercetin (−8.5 kcal/mol), and violaxanthin (−8.2 kcal/mol). Moreover, the newly modified B.1.1.7 strain of the novel coronavirus did not show any mutations in the putative binding sites; hence, we can predict that the compounds used in our study can also target the B.1.1.7 strain. Therefore, our study can be further assessed for in vitro studies and clinical trials against the coronavirus disease; henceforth, these compounds would play a crucial role in the development of target-specific therapeutics against the novel coronavirus.


The authors are thankful to the Department of Zoology, Kumaun University SSJ Campus, Almora, Uttarakhand, India, and the Department of Biotechnology, National Institute of Technology, Raipur, Chhattisgarh, India, for providing the facility for this work. This work is supported by the DST-FIST grant SR/FST/LS-I/2018/131 to the Department of Zoology.

Financial support and sponsorship

This work was supported by the DST-FIST grant SR/FST/LS-I/2018/131 to the Department of Zoology.

Conflicts of interest

There are no conflicts of interest.

  References Top

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  [Figure 1], [Figure 2], [Figure 3], [Figure 4]

  [Table 1]


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