key: cord-0889488-lmstdmyb
authors: Jain, Neha; Shankar, Uma; Majee, Prativa; Kumar, Amit
title: Scrutinizing the SARS-CoV-2 protein information for the designing an effective vaccine encompassing both the T-cell and B-cell epitopes
date: 2020-04-01
journal: bioRxiv
DOI: 10.1101/2020.03.26.009209
sha: 4f196a2c87a747cb03adee9b609d7d5c367e749a
doc_id: 889488
cord_uid: lmstdmyb

Novel SARS coronavirus (SARS-CoV-2) has caused a pandemic condition world-wide and has been declared as public health emergency of International concern by WHO in a very short span of time. The community transmission of this highly infectious virus has severely affected various parts of China, Italy, Spain and USA among others. The prophylactic solution against SARS-CoV-2 infection is challenging due to the high mutation rate of its RNA genome. Herein, we exploited a next generation vaccinology approach to construct a multi-epitope vaccine candidate against SARS-CoV-2 with high antigenicity, safety and efficacy to combat this deadly infectious agent. The whole proteome was scrutinized for the screening of highly conserved, antigenic, non-allergen and non-toxic epitopes having high population coverage that can elicit both humoral and cellular mediated immune response against COVID-19 infection. These epitopes along with four different adjuvants were utilized to construct a multi-epitope vaccine candidate that can generate strong immunological memory response having high efficacy in humans. Various physiochemical analyses revealed the formation of a stable vaccine product having a high propensity to form a protective solution against the detrimental SARS-CoV-2 strain with high efficacy. The vaccine candidate interacted with immunological receptor TLR3 with high affinity depicting the generation of innate immunity. Further, the codon optimization and in silico expression show the plausibility of the high expression and easy purification of the vaccine product. Thus, this present study provides an initial platform of the rapid generation of an efficacious protective vaccine for combating COVID-19.

should robustly activate both the humoral and the cell-mediated immunity to establish strong protection against the pathogen [10] . The antibody generation by B-cell activation as well as acute viral clearance by T-cells along with virus-specific memory generation by CD8+ Tcells are equally important to develop immunity against the coronavirus [11] . In case of respiratory virus like coronaviruses, the mucosal immunity plays an essential role and therefore route of administration of the vaccine is also important in the context of vaccine development. Vaccines designed against previously reported SARS-CoV and MERS-CoV majorly focuses on the Spike protein of virus which consists of S1 and S2 subunits bearing the receptor binding domain (RBD) of the virus and cell fusion machinery respectively.

Mutations in the spike protein have also been reported to be responsible for the change in host cell tropism [12] . The S protein is considered most antigenic and thereby can evoke immune responses and generate neutralizing antibodies that can block the virus attachment to the host cells [13] . Other viral proteins which were explored for vaccine development include N protein, E protein and the NSP16 proteins [14] [15] [16] [17] [18] . Almost all the platforms for vaccine development for SARS-CoV and MERS-CoV have been investigated including the lifeattenuated ones, recombinant viruses, sub-unit protein vaccines, DNA vaccines, Viral vectorbased vaccines, nanoparticle-based vaccines, etc. which may form the base for the vaccine designing against the newly emerged SARS-CoV-2 [10, 19] . Here we have designed a multiepitope-based vaccine for the SARS-CoV-2 using next generation vaccinology approach where the recently available genome and proteome of the SARS-CoV-2 were maneuvered and a potential vaccine candidate was conceived. Similar strategy was employed previously for SARS-CoV and MERS-CoV [20] [21] [22] [23] [24] [25] as well as certain findings are reported for the newly emerged SARS-CoV-2 [26] [27] [28] . While immunoinformatics techniques was utilized by groups to predict the B-cell and cytotoxic T-cell epitopes in the SARS-CoV-2 surface glycoprotein, N protein [27] [28] [29] , others have utilized the information to design epitope-based vaccine based on the SARS-CoV-2 spike glycoprotein [26] . Along with the structural proteins, utilizing the non-structural and accessory proteins for the vaccine development can aid in better development of an efficacious vaccine for long term by neutralizing the mutation rate of this RNA virus. In this study, we explored the whole proteome of SARS-CoV-2 to scrutinize the highly conserved antigenic epitopes for the construction of a multi-epitope vaccine candidate that can effectively elicit both humoral and cellular mediated immune response against COVID-19. The constructed vaccine product has high population coverage and along with adaptive immunity, can as well lead to initiation of innate immune response further enhancing the generation of memory immunity.

With the continuous transmission of the virus across borders and increasing health burden on the global scale, SARS-CoV-2 demands an urgent immunization therapy. As depicted by Shan Lu, the Community Acquired Coronavirus Infection (CACI) caused by this virus can shatter the socio-economic condition worldwide and the development of vaccine against the SARS-CoV-2 should be encouraged to manage the present situation as well as it can serve as a prototype for other coronaviruses [30, 31] . Thereby, our analysis provides a platform for the development of a protective vaccine candidate that can be tested in-vitro and in-vivo and may lead to faster development of an efficient vaccine against the SARS-CoV-2 infection.

The complete proteome of latest reported novel Wuhan strain of SARS Coronavirus (SARS-CoV-2) was downloaded from the Nucleotide database available at National Center for Biotechnology Information (NCBI). The database was also thoroughly searched for the genomes of other available human infecting strains of Coronavirus till date and was downloaded for further analysis.

For the antigenic analysis of the proteome of the COVID-19 strain, VaxiJen v2.0 server available at http://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html [32] .

For antigenicity prediction of the Proteins of SARS-CoV-2 with higher accuracy, Virus model available at the VaxiJen server with a threshold of 0.4 was utilized.

Proteins with a VaxiJen score ≥ 0.4 were taken for epitope prediction analysis.

MHC class I and II alleles were selected on the basis of their occurrence worldwide.

We focused specially on the countries which are severely affected by the deadly [33] . For MHC II, DRB1_0101,   DRB1_0301, DRB1_0401, DRB1_0405, DRB1_0701, DRB1_0802, DRB1_0901,   DRB1_1101, DRB1_1201, DRB1_1302, DRB1_1501, HLA-DPA10103-DPB10101,   HLA-DPA10201-DPB10201,  HLA-DPA10301-DPB10301,  HLA-DQA10101-DQB10201, HLA-DQA10301-DQB10301, HLA-DQA10401-DQB10401, HLA-DQA10501-DQB10501,  HLA-DQA10102-DQB10202,  HLA-DQA10402-DQB10402 covering 99.71 % world population were used for the epitope screening.

Various online servers were explored for the accurate prediction of Helper T Lymphocytes (HTL) epitopes. Firstly, the antigenic proteins were analyzed by using [37] . Only the epitopes with VaxiJen score ≥ 0.4 and predicted to be non-toxic and non-allergens, were taken for further screening. The best HLA-non-allergenic epitope pair with the highest VaxiJen score was taken for constructing the multi-epitope vaccine. [39] and for the allergenicity, the AllerTop v.

2.0 was used (https://www.ddg-pharmfac.net/AllerTOP/method.html) [40] .

Thereafter, the non-allergenic strong binders with a positive immunogenicity score were checked for their toxic nature by utilizing the ToxinPred server (https://webs.iiitd.edu.in/raghava/toxinpred/motif_scan.php).

The presence of selected best epitopes in all the reported human infecting SARScoronavirus strain were checked by using Epitope Conservancy Analysis tool of IEDB (http://tools.iedb.org/conservancy/) [41] . Only the epitopes having 100% conservation were used for multi-epitope vaccine construction.

The MHC class I ad class II molecules were downloaded from RCSB PDB database (https://www.rcsb.org/). Those that were not available were in PDB database were retrieved from pHLA database (https://www.phla3d.com.br/) [42] . The structures of the SARS-CoV-2 proteins were constructed using I-TASSER (https://zhanglab.ccmb.med.umich.edu/I-TASSER/) [43] and HTL and CTL epitopes were mapped and their structures were retrieved using PyMol tool. For the molecular interaction analysis of the predicted best HLA-epitope pairs for both MHC class I and class II alleles, ClusPro protein-protein docking tool (https://cluspro.org/login.php) [44] was utilized.

ABCpred tool based on artificial neural network was explored for B-cell epitope prediction (https://webs.iiitd.edu.in/raghava/abcpred/index.html) [45] . For higher accuracy, the threshold for the prediction was kept 0.90. The predicted epitopes were checked for their antigenicity using VaxiJen server, allergenicity by using AlgPred and toxicity by ToxinPred server.

For constructing a multi-epitope vaccine construct, the selected best HTL, CTL and B-cell epitopes were joined by using GPGPG, AAG and KK linkers respectively. For the better immunogenic response, four adjuvants namely, β-defensin, universal memory T cell helper peptide (TpD), PADRE sequence and a M cell ligand were added by using EAAAK linker into the vaccine construct.

The antigenicity of the vaccine construct, VaxiJen server was exploited. For the allergenicity analysis of the vaccine construct, three different tools namely AlgPred, AllerTop and AllergenFP v.1.0 (http://ddg-pharmfac.net/AllergenFP/index.html) [46] were utilized.

To check the population coverage of the vaccine construct, Population coverage tool available at IEDB (http://tools.iedb.org/population/) [47] server was utilized. The HLA class I and class II alleles in the final construct were entered in the tool and the population coverage of the alleles were calculated for the top 26 countries that are severely affected by the SARS-COV-2 virus. The analysis was performed for HLA I and HLA II separately as well as in combination.

Expasy's ProtParam (https://web.expasy.org/protparam/) [48] was explored for the physiochemical properties evaluation of the vaccine construct. ProtParam evaluates the peptide sequence and provides the molecular weight, theoretical pI, extinction coefficient, estimated half-life, instability index, and grand average of hydropathicity (GRAVY). Solubility of the construct was calculated using SolPro tool available at SCRATCH protein predictor server (http://scratch.proteomics.ics.uci.edu/) [49] .

Secondary structure of the multi-epitope vaccine construct was predicted using SOPMA(https://npsaprabi.ibcp.fr/cgibin/npsa_automat.pl?page=/NPSA/npsa_sopma.html) [50] and PSI-PRED (http://bioinf.cs.ucl.ac.uk/psipred/) server [51] . For the tertiary structure prediction of the vaccine construct Robetta server (http://robetta.bakerlab.org/) based on ab initio and homology modelling was utilized [52] . The predicted structure was refined by using 3D Refine (http://sysbio.rnet.missouri.edu/3Drefine/) [53] and further by GalaxyRefine (http://galaxy.seoklab.org/cgi-bin/submit.cgi?type=REFINE) [54] .

The structures were evaluated by constructing Ramachandran plot using RAMPAGE (http://mordred.bioc.cam.ac.uk/~rapper/rampage.php) and the quality was assessed using ERRAT server (https://servicesn.mbi.ucla.edu/ERRAT/).

The refined modelled structure of the multi-epitope vaccine construct was further evaluated for its stability in the real environment by simulating it in a water sphere using NAMD-standard molecular dynamics tool (https://www.ks.uiuc.edu/Research/namd/) by using parallel processors. The required structure files (.psf) were generated by psfgen using Visual Molecular Dynamics (VMD) tool v.1.9.3 by utlizing CHARMM force fields for proteins. Initially, a 10,000 steps energy minimization was performed followed by subsequent heating the system from 0 K to 310 K. Thereafter, a 20 ns standard molecular dynamics was performed and trajectory DCD file generated was used to evaluate RMSD. The change in kinetic, potential and total energy was evaluated for these 20 ns simulation using VMD.

To check the interaction of the multi-epitope vaccine construct with two immunoreceptors, TLR-3 and TLR-8, ClusPro docking server was used and the resultant best complexes were then simulated for 20 ns in a water sphere using NAMD.

Escherichia coli K12 satrain, the construct was first converted to cDNA using Reverse translate tool available at Expasy server. The resultant DNA was further optimized for enhanced protein expression by using JCAT server [55] . Finally, the cDNA construct was inserted into the pET28a (+) vector using HindIII and BamHI restriction sites.

The complete proteome of the Wuhan seafood market pneumonia virus isolate Wuhan-Hu-1 (nucleotide accession number -NC_045512.2) was retrieved from the NCBI database.

SARS-CoV-2 proteome consists of a polyprotein ORF1ab and several structural proteins.

ORF1ab encodes for various non-structural proteins including Host translation inhibitor nsp1, RNA dependent RNA polymerase (RnRp), Helicase, Guanine-N7 methyltransferase etc. that plays a critical role in the virus multiplication and survival inside the host. Structural proteins include Spike glycoprotein, Envelope protein, membrane protein and nucleocapsid protein.

The Fasta sequences of all these proteins were retrieved from NCBI and used for epitope screening ( Table 1 ). All the sequences were analyzed for their antigenic nature by using

VaxiJen server which is based upon auto cross covariance (ACC) transformation. VaxiJen classifies the proteins into antigens and non-antigens solely based on the physiochemical properties and is sequence alignment independent. The ACC score threshold for the virus model is kept 0.4 that increases the prediction accuracy. All the SARS-CoV-2 proteins except NSP16 (2'-O-ribose methyltransferase) resulted in the ACC score higher than 0.4 depicting the antigenic nature of the viral proteome (Table 1 ). All the antigenic proteins were further screened for the presence of HTL, CTL and B-cell epitopes by using various tools and databases ( Figure 1 ).

T-Lymphocytes play a central role in activating the cell mediated innate and adaptive immune response against the foreign particles. As well they are the sole players in generating immunological memory that provides long lasting immune response. Thus, the vaccinology approach revolves around the screening of proteome for the high affinity Helper T Table S2 ). Overlapping sequences were merged into one or both MHC class I and class II binding epitopes Apart from cellular mediated immunity, the humoral immune response mediates pathogen clearance in the antibody dependent manner. Hence the proteome of SARC-CoV-2 was further scanned for linear B-cell epitopes by using ABCPred server. For higher selectivity and sensitivity, the threshold of ABCPred was kept 0.9. The predicted epitopes were checked for their antigenicity, allergenicity and toxicity and the best epitopes were taken for further consideration. On the basis of above criteria, we received one B-cell epitope each for Nucleocapsid, Guanine-N7 methyltransferase (ExoN), ORF3a, ORF7a, and Surface glycoprotein (Supplementary Table S3 ). The locations of the selected epitopes in the respective protein structures are represented by Figure 2 . Overall, the antigenic 13 HTL and 12 CTL epitopes having highest affinity for the respective HLA alleles and 5 B-cell epitopes that are non-allergenic, non-toxic and can generate a potential immune response were selected for incorporation into the multi-epitope vaccine construct.

The presence of conserved epitopes in a vaccine can lead to an effective immunization against all the strains of the pathogen. Thus, the selected HTL, CTL and BCL epitopes were analyzed for their conservancy among the various human infecting strains of coronavirus.

Interestingly, all the selected epitopes were 100 % conserved throughout the coronavirus family and this can lead to a robust vaccine development. Figure 3C ).

An ideal vaccine should harbor conserved epitopes, have multi-valency and can elicit both cellular and humoral mediated immune response in the host. A subunit vaccine contains minimal elements that are antigenic and required for the stimulation of prolonged protective or therapeutic immune response. In the recent times, various reports have shown the construction of multi subunit vaccine by utilizing highly antigenic HTL, CTL and BCL epitopes. Herein, we constructed a multi-epitope vaccine candidate by combining 13 HTL, 12

CTL and 4 BCL epitopes that were highly conserved, antigenic, non-toxic and non-allergens ( Figure 4 ).

In the recent times, various small peptides are been explored that acts as an adjuvant and can potentiate the multi-epitope vaccine mediated immune response by activating humoral immunity. Taking this into consideration, apart from the conserved epitopes, four adjuvants were also added so as to boost the protective immune response against SARS-CoV- (Table 2) . Antigenicity is a preliminary requisite of a successful vaccine candidate. A vaccine construct must possess both immunogenicity and antigenicity to elicit the humoral and cell-mediated immune response.

Upon analyzing the vaccine construct sequence in VaxiJen server, the constructed vaccine was found to be antigenic in nature with an overall prediction score of 0.6199. The score signifies the antigenic potential of the vaccine construct that may have the potential to evoke the immune response inside the host. On allergenicity analysis, all the three tools AlgPred, AllergenFP and AllerTop supported the non-allergenic nature of the vaccine construct while toxicity analysis revealed the non-toxic behavior of the construct ( Table 2 ). In summary, the constructed epitope was observed to be stable, soluble, antigenic, non-allergenic and nontoxic.

Secondary and tertiary structure helps in the functional annotation of the multi-epitope vaccines. It also helps in analyzing the interaction of this vaccine construct with the immunological receptors like TLRs. Secondary structure of the protein was analyzed by using SOPMA and PSIPRED server that revealed the presence of ~40 % alpha helix, ~20 % β-sheet, ~30 % coils and ~6 % β turns in the vaccine construct ( Figure 5 and Supplementary Figure S3 ). Tertiary structure of the vaccine was predicted by threading based homology modelling using Robetta server ( Figure 6A ). Ramachandran plot analysis of the modelled structure revealed the presence of 95.5 % residues in the most favoured regions and 4.5 % in the additionally allowed regions ( Figure 6B ). Quality factor was analyzed by using ERRAT2 server and was obtained to be 90.47 depicting a good modelled structure ( Figure 6C ). To further refine the modelled structure, 3D refine and GalaxyRefine were utilized that leads to 97.4 % residues in the most favoured region and 2.6 % residues in the additionally allowed region. The quality factor of the refined structure was observed to be 94.29% depicting the improvement of the modelled structure ( Figure 6D -F).

Refined structure of the model construct was further check for its stability in real environment by simulating it for 20 ns in a water sphere. 10,000 steps energy minimization was performed to minimize the potential energy of the system. Unnecessary or false geometry of the protein structures are repaid by performing energy minimization resulting in a more stable stoichiometry. Before energy minimization, the potential energy was observed to be -447451.2005 Kcal/mol. After 10,000 steps the protein was minimized with a potential energy of -676040.4692 kcal/mol ( Figure 7A) . The system was subsequently heated from 0 K to 310 K and then 10 ns molecular dynamic simulation was performed. The temperature remained constant throughout the simulation process ( Figure 7B ). The DCD trajectory file was analysed for analysing the movement of the atoms during the simulation course and RMSD was calculated. Upon analysing the RMSD of SARS-CoV-2 vaccine construct, it was observed that, the system gained equilibrium at ~4 ns and then remained constant till 10 ns depicting the stability of the vaccine construct ( Figure 7C ). Furthermore, upon analysing the change in kinetic, potential and total energy of the system, it was observed that after a quick initial change in all the three, they remained constant throughout the simulation further strengthening the stability of the vaccine construct ( Figure 7D-F) . Furthermore, the bond energy, VdW energy, dihedral and improper dihedral energy analysis revealed no change throughout the 10 ns dynamics simulation. Root mean square fluctuation (RMSF) analysis revealed the rigidness of the atoms in vaccine construct with a slight mobility observed at ~ 120 and 501 residues (Supplementary Figure S4) . Thus, simulation analysis revealed the stability of the vaccine construct in the real environment. The refined vaccine construct structure was therefore used for interaction analysis with immunological receptor TLR3.

Proteinprotein docking of immune receptor TLR3 and the constructed vaccine was carried out using ClusPro server. In total 30 TLR3-vaccine construct complexes were generated. The fifth model with the lowest energy weighted score of -1427.4 was considered as best TLR3vaccine complex (Figure 8 A-B and Supplementary Table S4 ). The vaccine construct interacted with the ligand binding grove of TLR-3 generating a strong TLR3-vaccine construct complex. The stability of the complex was further analyzed by performing 10ns standard molecular dynamics simulation studies using NAMD suite. The 10,000 steps energy minimization of the complex lead to the generation of a minimized energy complex with energy of -756791.5601 Kcal/mol ( Figure 8C ). After subsequent heating the system from 0 K to 310 K, the temperature was kept constant throughout ( Figure 8D ). Energy plots depicted no major changes throughout the simulation ( Figure 8E -G and Supplementary Figure S5 ).

RMSF analysis of the complex showed a mobility region at ~740 th residue and ~1100 residue of the TLR3-vaccine complex ( Figure 8H ). On trajectory analysis, the RMSD plot was constructed that revealed the major deviations during the initial 1.5 ns, thereafter the system remained constant till 10 ns.

For the insertion of the vaccine construct into a plasmid vector, the 602 amino acid long protein sequence was reverse translated to cDNA of 1806 nucleotide length. The expression system of the expression host varies with each other and the cDNA needs to be adapted as per the host codon usage. For the optimal expression of the vaccine product in Escherichia coli K12 host, the resultant cDNA was codon optimized according using JCAT server. Also, during optimization, rho-independent transcription terminator and prokaryotic ribosomal binding sites were avoided in middle of the cDNA sequence so as to generate an optimal and complete protein expression. Further, for inserting the construct in the cloning vector, the cleavage sites of BamHI and HindIII were also avoided. The CAI value (codon adaptation index) of the cDNA before adaptation was observed to be 0.5379 and a GC content of 59.52 % ( Figure 9A ). After adaptation, the CAI score of the improved sequence was increased to 0.946 with 52.54 % GC content ( Figure 9B and Supplementary data S1). The enhanced CAI score depicts the presence of most abundant codons in Escherichia coli K12. The adapted cDNA sequence was used for In silico cloning purpose.

Escherichia coli K12 strain was selected as a host for cloning purpose as the expression and purification of multi-epitope vaccines are easier in this bacterium. pET28a(+) expression vector was cleaved using BamHI and HindIII restriction enzyme and the cDNA was inserted near the ribosome binding site using Snapgene. 6X histidine tag was added at the 3' end for the isolation and purification of the vaccine construct ( Figure 9C ).

severely affecting humans worldwide. The SARS-CoV-2 is highly contagious virus with a high mortality rate especially in immunocompromised and elderly persons. Vaccines are the utmost need of the time to succumb the rising infections due to COVID-19 and represent the best way to combat infectious diseases in the community. Conventional vaccine development methods are time-consuming, laborious and expensive and in this regard, the in-silico immuno-informatics approach have proved to a boon [59] . Moreover, the availability of large number of efficient tools to predict the immuno-determinants, and large database of information facilitate and accelerate this whole process of vaccine designing [60] . Multiepitope vaccines are designed by using the most antigenic conserved part of the pathogen's proteins that makes them more effective and can help in combating the high mutation rate in RNA viruses. These epitope-based vaccines have added advantages of being safe, stable, highly specific, cost-curtailing, easy to produce in bulk, and provides option to manipulate the epitopes for designing of a better vaccine candidate [61] . This method of vaccine development has proved to be promising enough for different microbial diseases including both bacterial and viral [25, [62] [63] [64] [65] [66] [67] .

Herein, we applied reverse vaccinology approach for designing of a multi-epitope Secondary structure prediction revealed the predominance of alpha helix while the tertiary structure obtained from threading provides the spatial arrangement of amino-acid in space. The obtained modelled structure was further refined that increased its overall quality.

To Table S1-S4 and Supplementary Data S1

Data conceptualization and methodology was performed by AK. In silcio prediction were performed by NJ, US and PM. Analysis was performed by NJ. NJ and PM collectively wrote the manuscript. A.K. did the review and editing. 

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The authors acknowledge Computer server facility provided by Dr.