key: cord-0907145-rxpi677s
authors: Khan, Kanwal; Khan, Salman Ali; Jalal, Khurshid; Ul-Haq, Zaheer; Uddin, Reaz
title: Immunoinformatic approach for the construction of multi-epitopes vaccine against omicron COVID-19 variant
date: 2022-05-10
journal: Virology
DOI: 10.1016/j.virol.2022.05.001
sha: 371bd37735ac9aa2afd28d291c939904cae7a205
doc_id: 907145
cord_uid: rxpi677s

The newly discovered SARS-CoV-2 Omicron variant B.1.1.529 is a Variant of Concern (VOC) announced by the World Health Organization (WHO). It's becoming increasingly difficult to keep these variants from spreading over the planet. The fifth wave has begun in several countries because of Omicron variant, and it is posing a threat to human civilization. As a result, we need effective vaccination that can tackle Omicron SARS-CoV-2 variants that are bound to emerge. Therefore, the current study is an initiative to design a peptide-based chimeric vaccine that may potentially battle SARS-CoV-2 Omicron variant. As a result, the most relevant epitopes present in the mutagenic areas of Omicron spike protein were identified using a set of computational tools and immunoinformatic techniques to uncover common MHC-1, MHC-II, and B cell epitopes that may have the ability to influence the host immune mechanism. A final of three epitopes from CD8(+) T-cell, CD4(+) T-cell epitopes, and B-cell were shortlisted from spike protein, and that are highly antigenic, IFN-γ inducer, as well as overlapping for the construction of twelve vaccine models. As a result, the antigenic epitopes were coupled with a flexible and stable peptide linker, and the adjuvant was added at the N-terminal end to create a unique vaccine candidate. The structure of a 3D vaccine candidate was refined, and its quality was assessed by using web servers. However, the applied immunoinformatic study along with the molecular docking and simulation of 12 modeled vaccines constructs against six distinct HLAs, and TLRs (TLR2, and TLR4) complexes revealed that the V1 construct was non-allergenic, non-toxic, highly immunogenic, antigenic, and most stable. The vaccine candidate's stability was confirmed by molecular dynamics investigations. Finally, we studied the expression of the suggested vaccination using codon optimization and in-silico cloning. The current study proposed V1 Multi-Epitope Vaccine (MEV) as a significant vaccine candidate that may help the scientific community to treat SARS-CoV-2 infections.

In December 2019, a novel Beta coronavirus SARS-CoV-2 was identified as the etiological agent 55 of COVID-19, which has been affecting more than 0.318 billion global populations and resulted 56 in 5.5 million fatalities (https://www.worldometers.info/coronavirus/) (Poon & Peiris, 2020 ). On 57 MHC-II epitopes, a cut-off value of 0.2 peptide rank and an IC50 of 100nM for top binders were 161 determined against the worldwide human population's 95 percent HLA variability, i.e., 162 DRB1*0401, DRB1*0701, DRB301:01, DRB1*1301, DRB1*0101, DRB1*0301, DRB1*0801, 163 DRB1*1101, HLA-DRB401:01, DRB1*1501 (Solanki & Tiwari, 2018) . Multiple epitopes with 164 9-14 residues were chosen for downstream investigation. 165

The identified MHCI -II epitopes were clustered to validate their respected MHC restricted alleles 167 using the MHCcluster (Thomsen, Lundegaard, Buus, Lund, & Nielsen, 2013). The clustering 168 performed for these epitopes is resulted in the plotting of heat map for the expression relation 169 epitopes with corresponding alleles. It also generated phylogenetic tree that helped in the 170 assessment of functional relation identification between HLAs and shortlisted epitopes (Ullah, 171 Sarkar, & Islam, 2020). 172

A perfect peptide vaccine may induce long-lasting humoral immunity, identical to the natural 174 immunological response produced by pathogenic infections. The B-cell epitopes stimulate 175 humoral immunity, which can kill infection by creating antibodies against exposed antigens to the 176 human body. The ABCPred (Saha & Raghava, 2006) (Chou, 1978) for beta turn 181 prediction, Kaprplus and Schulz for flexibility scale (Karplus & Schulz, 1985) , and Parker 182 hydrophilicity scale for the identification of hydrophobic content (Parker, Guo, & Hodges, 1986) , 183 respectively. 184

The development of epitope-based vaccines requires an epitope that can trigger immune cells (B 186 and T cells) to react ( 

The AlgPred server for allergenicity analysis with a cut-off of -0.4 and an accuracy of 85 percent 205 was utilized to examine their allergenicity effects to overcome the allergic reaction characteristic 206 of vaccine constructs. Scores less than a threshold are considered as non-allergenic vaccine 207 were processed by using GROMOS96 54A7 force field (Lin & van Gunsteren, 2013) . The vaccine 239 was put at 1.0 Å apart from the box edge in a cubic box that was constructed. Further, solvent 240 molecules of SPC water model were added by using periodic boundary conditions. The addition 241 of counter ions neutralized the solvated system. With a maximum force of < 1000 kJ mol -1 Å −1 , 242 the neutralized system was minimized using the steepest descent technique. The system was 243 gradually heated at constant temperature and pressure in NVT and NPT ensemble for 100 ps using 244 electrostatic long-range interactions, LINCS algorithm, and PME method was applied, 246 respectively. Finally, a 50 ns MD production was performed with coordinates and energies stored 247 every 10 ps in the output trajectory file, according to established procedure (Jalal et al., 2021) . 

The antigenicity of Omicron spike proteins analyzed through VaxiJen server was identified as 280 0.4125 with a cut-off value of 0.4. The analysis indicates the spike protein as antigenic that can 281 stimulate host-immune response. 282

The NetCTL server was used to forecast 1261 T-cell epitopes using a threshold value of 0.75 284 (Supplementary file 1), however, only 131 epitopes were found to exhibit optimum T-cell binding. 285

The MHC-I binding on these 131 epitopes was evaluated using IEBD tool. It identified 286 approximately 2657 MHC-I epitopes (Supplementary file 2). However, based on MHC-I and T-287 cell interaction, 163 epitopes were identified that evoked strong binding affinity using a cut-off 288 criterion of IC50 <100 and percentile rank ≤ 0.2. All the shortlisted epitopes were predicted to be 289 efficient T-cell binders and were evaluated further. 290

The immunogenicity of epitopes determines their ability to induce T-cell responses. The 292 immunogenicity prediction was performed for the shortlisted epitopes. The higher the 293 immunogenicity score, the better epitopes will be at stimulating cellular immunity and T-cells. 294

From the 163 MHC-I shortlisted epitopes, 96 immunogenic epitopes with a positive score cut-off 295 were identified as having significant immunogenic values using the IEBD service. These 296 immunogenic selected epitopes were employed in the development of vaccines.

The toxicity, antigenicity, and conservancy analyses were also performed on the 96 immunogenic 298 epitopes that were shortlisted. The results of the ToxinPred and IEBD conservation tools showed 299 that all 96 sequences were non-toxic and 100% conserved. However, antigenicity analysis using 300 the VaxiJen server resulted in a total of 24 epitopes (Table 1) as antigenic (i.e., score between 0.5 301 and 1.0) and subjected to further evaluation whereas discarding the non-antigen one. 302

Furthermore, 916 MHC-II epitopes were identified employing the IEBD server in addition to 304 MHC-I epitope prediction (Supplementary file 3). We evaluated epitopes based on their percentile 305 rank with <0.2 values and a binding affinity with IC50 <100nM. A total of 15 MHC-II epitopes 306 were predicted by the server following the applied threshold and 100 percent conserved predicted 307 by the IEBD conservancy analysis for MHC-II epitope (Table 2) . 308

The MHCclusters tool was used to evaluate the identified MHC-I/II epitopes in relation to MHC 310 restricted allele and their suitable peptide validated the epitopes found in T-cells. In terms of 311 annotation, the interaction between MHC-I/II and HLAs is displayed as a heat map and 312 phylogenetic dynamic tree with red color representing stronger interaction and yellow color 313 representing weak interaction (Fig. 3) . 314

Ideally, both humoral and cellular immunity are required to successfully eradicate the virus from 316 the body. As a result, B-cell epitopes against Omicron spike protein were discovered using 317 ABCPred, BCPred, and FBCPred. These methods identified 155, 22, and 42 B-cell epitopes using 318 a threshold value of 0.51, and a specificity of 75 percent, (Supplementary File 4- Table S1 ). Chou-319

Fasman beta-turn prediction, Kolaskar Tongaonkar antigenicity, BepiPred linear epitope 320 prediction, Parker hydrophilicity prediction, Karplus-Schulz flexibility prediction, and Emini 321 surface accessibility prediction were also used to further examine and select the resulting B-cell 322 epitopes as highlighted in Fig. 4 . 323

J o u r n a l P r e -p r o o f

The selected B-cell epitopes were used as a template and manually evaluated against MHC-I and 325

MHC-II epitopes to screen out overlapping epitopes. The comparison analysis was resulted in the 326 shortlisting of three epitopes that overlap MHC-I, MHC-II, and B-cell epitopes (Table 3) i.e., 327 TESIVRFPNITNLCPFDEVFNATRFASVYAWNRKRISNCVADYSVLYNLAPFFTFKCYG, 328 PQSAPHGVVFLHVTYVPAQEKNFTTAPAICHDGKAHFPREGVFVSNGTHWF, and 329 TQQLIRAAEIRASANLAATKMSECVLGQSKRVDFCGKG, respectively. 330

Prediction 332

Four adjuvants, PADRE sequences, GGGS, HEYGAEALERAG, and EAAAK linkers were used 333 to insert these four epitopes in a sequential way. The PADRE sequence helped to overcome the 334 universal polymorphism impact of HLA-DR molecules in varied cultures, whereas this 335 combination of adjuvants and linkers leads to activating a large immune response in the body 336 against viruses. The selected epitopes were connected manually through bash shell script to each 337 other using a specialized Glycine-Serine linker i.e., GGGS sequence, H-linker 338 (HEYGAEALERAG) and PADRE Sequence (AKFVAAWTLKAAA). A four molecular adjuvant 339 was added towards the N-terminal direction of the epitopes. These adjuvants were attached to the 340 epitopes by one EAAAK stiff linker. Eventually, twelve vaccine models were constructed using 341 three shortlisted epitopes. Table 4 showed the details of the vaccine constructs. 342

The antigenicity, solubility, and allergenicity of the twelve vaccine models were evaluated further. 343

Eight vaccine models (i.e., V2, V3, V4, V7, V8, V10, V11, and V12) were identified as highly 344 allergic in nature using the AlgPred program with scores ranging from 0.2 to 0.3 and were 345 eliminated. However, the antigenicity predicted by the ANTIGENpro server, and the solubility 346 predicted through SOLpro tool of the remaining four vaccine constructs for their successful 347 expression in E. coli vector. It resulted in the high antigenicity and solubility for remaining four 348 vaccine constructs (V1, V5, V6, and V9) with scores ranging from 0.4 to 0.8 and were thus 349 subjected to further investigation. The ProtParam was used to predict physicochemical features for 350 four shortlisted vaccine designs. The estimated molecular weight of the vaccine's models was 351 ~41KDa, with a pI score of ~5, an instability index score of 28-39, and a high aliphatic score of 352 83-86. On the other hand, the grand average of hydropathicity was estimated to be in the range of 353 adjuvant HBHA. Table 5 lists the allergenicity, solubility, and antigenicity of all twelve vaccines 355 and physico-chemical properties of four vaccine models. 356

The 3D structure of V1 vaccine construct was modeled using the SWISSMODEL tool. The 358 template for V1 was PDB ID: 6NB3, a Spike glycoprotein from MERS-CoV complex with human 359 neutralizing LCA60 antibody Fab fragment with 18% sequence identity, 0.25 GMQE score, and 360

QMEANDisCo Global:0.42 ± 0.06 (Fig. 5) To evaluate the immunological response, the GRAMMX tool was employed to perform a docking 379 analysis to predict the interactions between V1 and the TLR 2 (2Z7X) and TLR 4 complex (PDB 380 3FXI). The adjuvant HBHA protein, which serves as TLR2 and 4 agonist and produces a variety 381 of immune responses was used to build the V1 construct. The PatchDock docking revealed binding 382 energies of -12.12 and -1.29 kcal/mol, showing that V1 and the TLR-2/4 complex have a 383 significant interaction (Table 6) . However, it can be clearly observed that V1 has showed more 384 potency towards TLR2 complex. The Protein-Protein Interactions (PPIs) of the V1 model revealed 385 that it mediates five hydrogen bonds with TLR2, mainly involve Glu177-Leu137, Tyr109-Thr149, 386

Glu178-Arg150, Glu180-Arg150, and Leu57-Ser252 and three salt bridges between Lys208-387 Arg155, Glu180-Arg150, Glu178-Arg150. Whereas two hydrogen bonds with TLR4 were 388 observed with Thr499-Pro254, Ser570-Tyr215 as shown in Fig. 6b . 389

The MD simulation studies were conducted to determine the dynamics and structural stability of Fig.S3a-f) . 422

In addition, the C-Immune tool was used to predict human immune system response after vaccine 423 injection at various time intervals. It confirmed that the immune response was consistent with the 424

Natural killer cells production, interleukins/interferons production, and antibody production (Fig.  426   7) . Following the induction of vaccine injection, an increase in IgG1+IgG2, IgM, and IgG+IgM 427 was seen, leading to a decrease in antigen concentration ( Fig. 8a and 8b) . Upon vaccine construct 428 injections, there was an increase in the production of NK cells, Th (helper), and Tc (cytotoxic) 429 ( Fig. 8c, 8d, and 8e ). In addition, IFN-g production was increased after vaccination (Fig. 8f) . 430

To optimize the codons and reverse translate the V1 for optimal production in E. coli (strain K12), 432 the JCAT tool was employed. The average GC content and CAI value for V1 were estimated to be 433 41.9 percent and 0.61, respectively, resulting in successful vaccine construct expression. Finally, 434 the SnapGene program was used to insert the optimized codon sequence (V1) into the pET30a (+) 435 vector to create the recombinant plasmid (Fig. 9) . The current work identified immunogenic MHC-I, MHC-II, and B-cell epitopes that may be used 471 to build a multi-epitope vaccine utilizing various filters such as: (i) The epitopes must be non-472 toxic, antigenic, non-allergenic, and highly conserved (Table 1 and 2), (ii) have ability to bind to 473 MHC-I/II alleles, and should be overlapping to CTL, HTL, and B-cell epitopes (Table 3) bridges among Glu177-Leu137, Tyr109-Thr149, Glu178-Arg150, Glu180-Arg150, and Leu57-502

Ser252, Lys208-Arg155, Glu180-Arg150, Glu178-Arg150 residues. Whereas two hydrogen bonds 503 with TLR4 were observed with Thr499-Pro254, Ser570-Tyr215 (Fig. 6) . Several studies 504 highlighted the importance of interaction of vaccines with TLR4 such as, Totura et al. 505 demonstrated the susceptibility of mice to SARS-CoV infection is relatively high in TLR4 506 deficient mice compared to wild type (Totura et al., 2015) . Similarly Hu et al. observed that 507 upregulation in expression of TLR4 when exposed to SARS-CoV infection, suggesting the 508 importance of TLR in immune response stimulation (Hu et al., 2012) . 509

Importantly, the vaccine model was seen to be stable at 15 ns after a 50-ns molecular dynamics 510 simulation (Fig. 7) . The V1 model's codon optimization was reverse translated to its cDNA to 511 enable effective expression in the E. coli pET-28a(+) expression vector. The expected GC and CAI 512 values of V1 were 41.9 and 0.61%, respectively, indicating vaccine expression success (Fig. 9) . 513

Comparably, Foroutan et al. performed in silico codon optimization before expressing it in mice 514 (Foroutan et al., 2020) . Immune simulations of vaccine models revealed that the developed vaccine 515 against the Omicron variant evoked a substantial immune response (Fig. 8) 

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J o u r n a l P r e -p r o o f J o u r n a l P r e -p r o o f J o u r n a l P r e -p r o o f