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Table of Contents
ORIGINAL ARTICLE
Year : 2022  |  Volume : 1  |  Issue : 1  |  Page : 54-62

In silico screening and characterization of novel natural peptides as spike protein inhibitors of novel coronavirus (severe acute respiratory syndrome coronavirus 2)


Department of Biotechnology, School of Biotechnology, Gangadhar Meher University, Sambalpur, Odisha, India

Date of Submission09-Jan-2022
Date of Decision05-Mar-2022
Date of Acceptance11-Mar-2022
Date of Web Publication23-Mar-2022

Correspondence Address:
Raghunath Satpathy
School of Biotechnology, Gangadhar Meher University, Amruta Vihar, Sambalpur, Odisha
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jpdtsm.jpdtsm_7_22

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  Abstract 


BACKGROUND: The present work is a computational approach to discover the novel peptides that can interact and inhibit the action of spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
MATERIALS AND METHODS: A total of 193 numbers probable naturally occurring antiviral peptides were retrieved from the antimicrobial database. The three-dimensional structure of all the peptides was predicted by the Chimera tool followed by energy minimization. Similarly, the spike protein of SARS-CoV-2 chain A (PDB ID 6VBY) structure was obtained from the Protein Data Bank (PDB) and used as the receptor.
RESULTS: Protein–protein docking was performed for all the peptides followed by some screening criteria that resulted in three numbers of potential peptides such as CAP11 binds to a receptor-binding domain (RBD), mytilin B to S1/S2 cleavage regions, and mBD-1 as N-terminal-binding domain of spike protein. Further screening and evaluation of solubility and the toxic properties of the peptides it was obtained that the peptide molecules CAP11 and mytilin B are nontoxic. Further, the RBD-binding nature of CAP11 peptide was evaluated comparatively by taking the human ACE2 protein and RBD region of the wild-type SARS-CoV-2, triple mutant, South African mutant (B.1.351), by using molecular docking followed by interface analysis. It was predicted that the CAP11 peptide was able to bind perfectly with the RBD domain of both wild type and triple mutant one but not to the South African mutant.

Keywords: ACE2 protein, antiviral peptides, interface analysis, molecular docking, receptor-binding domain, severe acute respiratory syndrome coronavirus 2, solubility, spike protein, toxicity prediction


How to cite this article:
Satpathy R, Dash N. In silico screening and characterization of novel natural peptides as spike protein inhibitors of novel coronavirus (severe acute respiratory syndrome coronavirus 2). J Prev Diagn Treat Strategies Med 2022;1:54-62

How to cite this URL:
Satpathy R, Dash N. In silico screening and characterization of novel natural peptides as spike protein inhibitors of novel coronavirus (severe acute respiratory syndrome coronavirus 2). J Prev Diagn Treat Strategies Med [serial online] 2022 [cited 2022 May 24];1:54-62. Available from: http://www.jpdtsm.com/text.asp?2022/1/1/54/340556




  Introduction Top


Antiviral peptides are an important group of therapeutically active biological molecules produced by a variety of organisms and act against several pathogenic viruses. They interact with several essential components of the virus and interfere with their infection-causing process.[1],[2],[3] Furthermore, due to the least side effects and drug resistance properties, currently, peptide-based therapeutics can be a major form of treatment in recent times. The recent outbreak of COVID-19 was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). There is a surface glycoprotein called spike protein that is getting embedded in the viral membrane responsible for host cell fusion with ACE2 protein of the host cell, cell entry and followed by replication leads to the further infection process.[4],[5] Hence, the discovery and development of the inhibitor to target the spike protein might be a remarkable effort toward the COVID-19 medication. Hence, the researchers are currently focusing on the development of probable drug molecules, antimicrobial peptides (AMPs), vaccines, and so on to combat the COVID-19 infection.[6],[7] A broad range of bacteria, fungi, parasites, and viruses infect the host body. However, the AMPs present in the body help in preventing infection directly or indirectly involved in the innate immunity of the host. Several AMPs were reported in the database derived from different kingdom levels.[8],[9],[10]

Spike glycoprotein (S) of SARS-CoV-2 consists of 1273 acids and trimeric. This is consisting of two basic subunits S1 and S2. Normally, the spike protein is arranged in the outer N-terminus, the transmembrane domain interspersed in viral membrane, and the C-terminus on the cytosolic side. When the corona strain comes in contact with the host cell just before fusion, there is a further rearrangement of S protein established to let the viral cell enter into the host membrane and it is also covered with multiple polysaccharide molecules which help spikes to hide from the host immune surveillance to get easily entered [Figure 1].[11],[12] 1-13 amino acids of the S1 subunit codes for the signal peptide and next fourteen to six hundred eighty-five amino acid codes for next part of S1 subunit whereas rest six hundred eighty-six to 1273 aa residues codes for S2 subunit. Next to the N-terminal domain (NTD) of the S1 subunit, there is the presence of a receptor-binding domain (RBD) that binds with hAce2. The rest is followed by fusion peptide, heptapeptide repeat sequence 1 h1, and heptapeptide repeat sequence HR2, a transmembrane domain and cytosolic domain comprising the S2 subunit. The two different confirmations that is open and closed state of RBD were well studied from cryo-electron microscopy. For efficient viral infection machinery, the spike protein of SARS-CoV2 is needed to be cleaved at the junction between S1 and S2 subunits by host cell proteases like TMPRSS2 which is a serine protease to activate the membrane fusion domain.[13] Shedding light upon the increasing resistance to antiviral drug molecules, it will be a major challenge to develop more potent antiviral therapeutics. Based on their potential application, effectiveness, and pharmacokinetic properties, antiviral peptides will be a better option. The research was carried out for a long time to treat different viral infections by using the old trial-and-error method. For example, nucleoside and nonnucleoside analogs like brivudine, azidothymidine, and acyclovir work effectively against varicella-zoster virus, HIV, and herpes simplex virus. However, the development of these therapeutics takes lots of time with high toxicity levels and is costlier. Hence, using fewer toxic proteins and antiviral peptides will be a major alternative for the treatment of all viruses. As enfuvirtide also inhibits HIV infection with low toxic level.[14],[15],[16]
Figure 1: Structure of severe acute respiratory syndrome coronavirus 2 spike protein (created with www.biorendor.com)

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For the diseases that are difficult to target, these antiviral peptides play an important role in the prevention of protein–protein interactions along with longer half-life and shorter market time that serve as advantageous features. The drawback of using these is minute drug tolerance as compared to chemically available drugs. Although peptides are highly specific, still storage circumstances create a problem that leads to less oral bioavailability and increasing metabolism. Hence, AVPs as a novel way to target viral proteins that boost up the research at the same time. Many more AVPs were developed to work against spike protein and fusion protein against respiratory viruses such as SARS-CoV-2, MERS-CoV, and SARS-CoV. After encountering the potential of therapeutic peptides, this research work has focused on less exposed proteins to design AVPs targeting CoV-2.[17],[18],[19],[20],[21]


  Materials and Methods Top


System configuration used

  • Processor: Intel® Core™ i3-10100 CPU at 3.60GHz
  • Installed memory (RAM): 8.00 GB
  • System Type: 64-bit Operating System, Windows 10.


Retrieval of antiviral peptide molecule and property prediction

193 antiviral peptides sequence information was obtained from the Antimicrobial Peptide Database (APD) available at https://aps.unmc.edu/(as on date September 13, 2021). The database contains a total of 3283 AMPs including 193 antiviral peptides from six different kingdoms. In the database information like peptide sequences, accession numbers, sources, etc., are available. The physicochemical properties of all 193 antiviral peptide sequences were computed by using the ProtParam tool (https://web.expasy.org/protparam/). ProtParam is a sophisticated web-based tool that takes the amino acid sequence as the input and computes different parameters as the output. Seven different parameters, i.e., number of amino acids in each antiviral peptide, number of negatively and positively charged residues, molecular weight, instability index, aliphatic index, and grand average of hydropathicity of the retrieval AVP, were computed for the considered peptide sequences [Figure 2].
Figure 2: Flow chart describes the important methodology used in the present work

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3D structure prediction peptides by Chimera tool and validation of the predicted structures

For structure prediction, Chimera version 1.15 tool was used (https://www.cgl.ucsf. edu/chimera/). UCSF Chimera is a program used for molecular structure prediction, visualization, energy minimization, sequence alignment, and other related analyses.[22] For building molecular 3D structure in Chimera, the edit structure module was used to provide the amino acid sequence as input, and finally, the 3D structure was obtained by clicking the “build structure” module. Further, the energy minimization of the built 3D structure was performed by using minimize structure module of the Chimera software. The initial energy of the original peptide structure and final energy after the energy minimization step were obtained and analyzed. The energy-minimized structure in the Protein Data Bank format (.pdb) was kept for further analysis.

Structural validation of the predicted 3D structure peptides

The energy-minimized structure of the peptides was subjected to a structural validation process. Several validation parameters were considered for the docking analysis. The percentage of residues that lies in the allowed region of the peptide was computed by the use of the Ramachandran plot. For that, the Procheck module of SAVES v6.0 server was used (https://saves.mbi.ucla.edu/). Similarly, another tool Errat available in the server was used to compute the nonbonded interactions of proteins. Errat's result provides the overall quality factor for every input 3D structure. Those AVPs were observed having the scores (overall quality factor), as well as allowed regions >90, were considered for docking. In these criteria out of 193 total peptides, 163 peptides were selected further for the molecular docking process.

Docking study of severe acute respiratory syndrome coronavirus 2 spike protein and peptide

Molecular docking is a method to predict the interaction pattern of ligand and receptor molecules by using specific scoring and search algorithms.[23],[24] In this work, the docking tool Hex 8.0 software was used for molecular docking simulation study (https://hex1.software.informer.com/8.0/). Hex provides an excellent guider user interface (GUI) to compute and predict the ligand-receptor interaction whenever given in the pdb structural format.[25] For the docking study, the available 3D structure in the Protein Data Bank (PDB) of SARS-CoV-2 spike protein structure 6VYB chain A was used as a receptor molecule. Similarly, the predicted 3D structures of the peptides were used as the ligands and molecular docking was performed. The default parameter of the Hex tool was chosen during the docking calculations [Figure 3].
Figure 3: The 6VYB chain A and important subunits and domains

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Interface analysis of protein–peptide interaction

Each of the docked structures of protein (receptor)-peptide (ligand) complexes in pdb format was subjected to protein–peptide interface analysis for identification of common binding interfaces. For the interface analysis, Spider web server was used (http://sppider.cchmc.org/). The interface analysis was used to determine the specific numbers of amino acid interactions in different domain regions of the spike protein as well as the surface area of the binding interface. All these pieces of information were computed and tabulated for further analysis.

Screening of the peptides by docking score

After docking and interface analysis, all the peptides were classified into three categories such as RBD binder, NTD binder, and S1/S2-binding interface binder. Furthermore, for further screening purposes, the threshold value of the Hex docking score ≤−300 was used.

Screening of AVPs with PeptideRanker

The peptides were further screened for their bioactivity potential by using the PeptideRanker tool. It is an online server to determine the threshold value of peptides (http://distilldeep.ucd.ie/PeptideRanker). A standard threshold value above 0.5 predicted for peptides is considered as bioactive.

Toxicity analysis by ToxinPred tool

After screening the best-selected peptides were further undergone the toxicity analysis by the ToxinPred tool (https://webs. iiitd.edu.in/raghava/toxinpred). The tool analyzes the peptides and classifies in into toxic and nontoxic ones based on certain criteria.

Docking complex analysis of the selected peptides by PRODIGY server

PRODIGY (Protein-Binding Energy Prediction) is a web server used to accurately determine the binding strength from the three-dimensional structure of peptide–protein complex and available at https://wenmr.science.uu.nl/prodigy/. During the calculation, the peptide–protein complex in PDB format was given as input. Default parameter was set to calculate the dissociation constant, binding free energy in Kcal, % of polar and charged amino acids on the noninteracting region as the output.

Case study of the receptor-binding domain inhibition activity of the predicted peptides

After the final screening is over, the RBD-binding peptide was examined further about its effectiveness in its applications. For that, three different RBD regions were chosen from the PDB: wild type (PDB ID 6VBY), triple mutant viral strain (PDB ID 7IWW), and South African (B.1.351) mutant SARS-CoV-2. The binding affinity and interacting amino acids were analyzed along with the comparative analysis of ACE2 protein.


  Results Top


All the 193 peptides along with their sequence information source with APD ID were retrieved from the APD database. For the physicochemical properties, Expert Protein Analysis System was used and several parameters are computed. The details about the retrieved peptides are given in [Supplementary Material 1].



3D structure prediction of the peptide molecules and molecular docking study

Chimera tool was used to predict the 3D structure of AVPs was determined followed by the energy minimization of the structure. For energy minimization purposes, steepest-descent method was used. To validate modeled structure of every AVP, SAVES 6.0 server was used. Here, we considered two parameters, i.e., PROCHECK and ERRAT. ERRAT is used for determining patterns of nonbonded atomic interactions, thereby verification of protein structure. PROCHECK is a tool used to check the chemical properties of proteins and then analyzed the result of protein structures.

This structure was developed by electron microscopy methods having a resolution of 3.2 Angstrom. The structure contains three chains, and for this study, chain A was obtained from the original file by using the PyMol visualization software tool (https://pymol.org/). Hex 8.0 software was used for docking of the peptide–protein complex. This software showed the interaction or binding affinity between AVP and spike protein. The docking complexes in the pdb format were obtained, and score was tabulated for all the peptides and is shown in [Supplementary Material 2].



Screening of the peptides based on docking score and binding pattern with the domains of the spike protein

After docking the protein–peptide interface analysis was performed and binding of amino acids to the domain region and surface area of these interactions were computed. Several screening criteria were used to screen the potential peptides. Based on the binding to the different positions to the domains of the spike proteins, the peptides were classified into four categories. The criteria for categorization, the peptide should have at least 10 amino acid interactions in that particular domain. Category 1 contains NTD-binding peptides, Category II is the RBD-binding peptides, and Category III is the S1/S2-binding peptides. The first screening method adopted was the docking score is <−300. This generated 107 peptides out of a total of 193 considered peptides. NTD binder (4 Nos.), RBD binder (1 No.), and S1/S2 interface binder (90 numbers). Similarly, 12 numbers of peptides showed no significant affinity toward any of these domains. The peptides that show no binding preference to the major domains were ignored for further analysis.

Screening of bioactive peptides with PeptideRanker

PeptideRanker was used to predict the bioactiveness of different categories of the screened peptides taken in a separate group. Three numbers of bioactive peptides were predicted based on the probability value computed from the PeptideRanker tool for each category of molecules.

As per the criteria of the PeptideRanker tool, a probability score of >0.8 is considered as error-free prediction of the bioactive peptides.[26] All three selected peptides have a probability value >0.8, hence considered as bioactive [Table 1]. The best-selected peptides binding to RBD, NTD, and S1/S2 domains are represented in an electrostatic surface area view in [Figure 4], [Figure 5], [Figure 6]. The red round mark represents the peptide-binding position with the spike protein domains [Table 2].
Table 1: Screening of best bioactive peptides specific to receptor-binding domain, N-terminal domain, and S1/S2

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Figure 4: Before (left side) and after (right side) docking view of the AP00677 peptide ID with severe acute respiratory syndrome coronavirus 2 spike protein (6VBY chain A)

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Figure 5: Before (left side) and after (right side) docking view of the AP00333 peptide ID with severe acute respiratory syndrome coronavirus 2 spike protein (6VBY chain A)

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Figure 6: Before (left side) and after (right side) docking view of the AP00272 peptide ID with severe acute respiratory syndrome coronavirus 2 spike protein (6VBY chain A)

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Table 2: Interface analysis result of the selected three peptides

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Binding affinity study of the selected peptide complex by PRODIGY server

PRODIGY web server to determine the proficiency of binding affinity of above three peptide complexes followed by interface residue analysis. The dissociation constant values for all the three peptides were obtained as −8.3 Kcal/mole for CAP11 peptide, −8.0 Kcal/mole for the mBD-1, and − 8.5 Kcal/mole for mytilin B peptide binding. Furthermore, the larger part of the spike protein was observed as neutral, where slightly positive amino acid residues of the peptide molecules interact.

Solubility and toxicity prediction of the selected peptides

Prediction of toxicity and solubility is an important in silico approach to predict the therapeutic property of the peptide. Six different physicochemical properties were estimated for the three selected peptides by using the PepCalc server. In all the cases, the peptides were obtained as good soluble in water and had a net-positive charge [Table 3].
Table 3: Interface analysis result of the selected three peptides

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Further, the three selected peptides were subjected to toxicity analysis by using the ToxinPred analytical tool.

However, the toxicity analysis of the peptide mBD-1 shows the toxic properties, hence the particular peptide may not be suitable for therapeutic purposes [Figure 7].
Figure 7: Snapshot showing ToxinPred output of CAP11, mytilin B, and mBD-1 peptides

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A case study evaluating the receptor-binding domain-binding activity of the CAP11 peptide

To study the interaction of the RBD-binding activity of CAP11 peptide, three different experimental protein structures were obtained from the PDB [Table 4]. The RBD domain region 319–515 was obtained by the PyMol tool. The predicted structure of the CAP11 peptide was used as a ligand.
Table 4: Structural information used for the case study

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Docking study was conducted with the peptide with the ACE2 as well as the peptide with the RBD regions of the selected peptide given in the table by using the Hex 8.0 tool followed by docking complex and interface analysis by PRODIGY web tool. The common amino acid residues interact with the RBD domain as well as ACE2 protein was analyzed comparatively by visualizing the structure by PyMol software tool. In the docking analysis of wild-type RBD-peptide-ACE2 complex was analyzed and revealed that there are some common amino acid residues Asp364, Ser366, Tyr369, Asn370, Ser371, Ala372, Ser373, Phe377, Lys378, Asp405, Arg408, and Val503 are involved in the interaction. The binding pose was visualized and illustrated that this peptide strongly binds to the ACE2 in the interface region and hence can be suitably used to inhibit wild-type SARS-CoV-2 infection [Figure 8]a.
Figure 8: The receptor-binding domain (green color) and ACE2 (pink color)-binding pose of the CAP11 peptide (yellow color): (a) with wild-type receptor-binding domain, (b) with triple mutant receptor-binding domain, and (c) with South African mutant (B.1.351)

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Similarly, in the case of triple mutant RBD-peptide-ACE2 indicates the common interface interacting amino acids are Arg346, Ala352, Trp353, Asp354, Arg355, Lys356, Arg357, Arg466, Ile468, Ser469, Thr470. The visualization of the docking pattern signifies that CAP11 AVP also worked potentially against the triple mutant strain of SARS-CoV-2 [Figure 8]b. In the case of South African (B.1.351) RBD-peptide-ACE2 complex analysis, it was obtained that none of the amino acids was obtained to interact in the RBD-ACE2 interface region [Figure 8]c.


  Discussions Top


Several peptides have been predicted by researchers that are previously studied and observed to be effective in the treatment of several antiviral therapeutics. Barlow et al., in 2014, described the therapeutic importance of cathelicidins, an important family of cationic host defense peptides, and consider the implications for novel antiviral therapeutic approaches.[27] Peng et al. conducted in vitro experiments in chicken cathelicidins to investigate their activity against the different influenza A virus strains.[28] Sousa et al. using experimental models by the in vitro approach described the antiviral nature of the human cathelicidin peptides against the human rhinoviruses.[29] Yu et al. experimented with AMPs human cathelicidin (AMP) LL-37 and engineered LL-37 AMPs that can successfully prevent the infection caused by the West Africa Ebola virus.[30] The S protein of SARS-CoV-2 can be used as an important target to which the therapeutic molecule such as peptide can bind and may inhibit the spike-ACE2 interactions.[11],[31] Several peptides have been studied by researchers to inhibit this interaction. A study by Wang et al. showed that SARS-CoV-2 S1-ACE2 interaction can be inhibited by the application of human intestinal alpha-defensin HD5 peptide.[32] In another in silico study, the antiviral peptide known as LL-37 is also found to be effective for the AVE2-RBD-binding activity.[33] Lei et al. in 2020 designed an ACE2-derived peptide for preventing coronavirus infection inhibiting SARS-CoV-2 entry.[34] Hadni et al., in 2020, also designed a peptide sequence bound to the RBD region of SARS-CoV-2, SARS-CoV, and MERS-CoV formed by the combination of three different peptides.[35] Currie et al. described the application of the cathelicidin peptides as host defense peptides, which exhibit both modulatory and killing properties are found effective against the respiratory syncytial virus.[36] Wang et al. examined the human cathelicidin LL37-binding efficiency with the ACE2 enzyme by an in vitro experiment. As an outcome, the binding of peptides decreases the spike protein adherence leads to the protection of cells against SARS-CoV-2 infection.[37] Yu et al. recently in their work described the virucidal activity of the cathelicidin antimicrobial peptides (human LL-37 and mouse CRAMP) specifically preventing enveloped virus such as Enterovirus 7, in comparison to the nonenveloped virus. These peptides were observed to interfere with the viral replication mechanism to exhibit virucidal activity.[38] From the present investigation, the mytilin B peptide peptides were obtained might be effective against the spike protein of SARS-CoV-2. There are different types of mytilins are available from the source Mytilus galloprovincialis, a marine mollusc, and show the modest level of sequence conservation. For the past two decades, mytilins have been previously reported and extensively studied in Mytilus species.[39],[40],[41] Dang et al. 2015 described the strong antiviral nature of mytilin peptide. The synthetic derivative of the mytilin peptide was analyzed as effective against the white spot syndrome virus.[42] However, no such literature was obtained that mytilin B as the suitable peptide-based therapeutic molecule that can be targeted to spike-ACE interface of the SARS-CoV-2 virus. However, in our study, it was predicted that this particular peptide can be suitably used to inhibit the SARS-CoV-2 virus, by binding to the S1/S2 region of the spike protein.


  Conclusion Top


A newly evolving, highly pathogenic novel coronavirus SARS-CoV-2 continues to affect public health globally and also causes a crisis in the country's economic status. Due to the high mortality rate of arises from viral infections, the development of effective antiviral peptides has emerged in the form of effective therapeutics. The virus contains a surface glycoprotein called spike protein that is essential for host cell fusion and replication process. Several treatment methods have been adopted to combat the SARS-CoV-2. However, the application of antiviral peptides will be a promising agent for the prevention of viral infection as it is associated with specificity and less toxicity. In the present work, a total of 193 antiviral peptides were screened by using various computational methods. Molecular docking followed by protein–protein interface analysis resulted that CAP11 peptide binds to the receptor-binding domain, mBD-1 binds to the NTD, and mytilin B binds to S1/S2 cleavage domain in SARS-CoV-2. Further case study regarding binding of RBD regions of the wild type, triple mutant, South African mutant (B.1.351) by the use of molecular docking study predicted that the peptide CAP11 is capable to bind to the wild type, triple mutant but not to the South African mutant (B.1.351). Similarly, mytilin B was predicted as the novel peptide as no report to date is available for its anti-SARS-CoV-2 effect. As a subsequent follow-up work, molecular dynamics simulation can be performed to obtain more reliable results.

Limitation of study

Spike glycoprotein of SARS-CoV-2 is part of a highly susceptible for mutation, hence targeting the peptide to inhibit the protein might be a challenging task. Even after successful computational prediction, evaluating the real-time effectiveness of the AVPs is difficult as it is dependent on several parameters such as tissue penetration, stability in the plasma, creating unwanted immunogenic responses, and so on. The present work is a computational prediction, hence experimental validation is necessary to address its necessary therapeutic application of the predicted peptides as effective spike protein inhibitor of SARS-CoV-2.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7], [Figure 8]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

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