key: cord-1000460-2o6kw7c7 authors: Al Saba, Abdullah; Adiba, Maisha; Saha, Piyal; Hosen, Md. Ismail; Chakraborty, Sajib; Nabi, A.H.M. Nurun title: An in-depth in silico and immunoinformatics approach for designing a potential multi-epitope construct for the effective development of vaccine to combat against SARS-CoV-2 encompassing variants of concern and interest date: 2021-07-30 journal: Comput Biol Med DOI: 10.1016/j.compbiomed.2021.104703 sha: c0a58b3acb851ece3c7d2a5cced7508b74caf3ae doc_id: 1000460 cord_uid: 2o6kw7c7 Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the latest of the several viral pathogens that have acted as a threat to human health around the world. Thus, to prevent COVID-19 and control the outbreak, the development of vaccines against SARS-CoV-2 is one of the most important strategies at present. The study aimed to design a multi-epitope vaccine (MEV) against SARS-CoV-2. For the development of a more effective vaccine, 1549 nucleotide sequences were taken into consideration, including the variants of concern (B.1.1.7, B.1.351, P.1and, B.1.617.2) and variants of interest (B.1.427, B.1.429, B.1.526, B.1.617.1and P.2). A total of 11 SARS-CoV-2 proteins (S, N, E, M, ORF1ab polyprotein, ORF3a, ORF6, ORF7a, ORF7b, ORF8, ORF10) were targeted for T-cell epitope prediction and S protein was targeted for B-cell epitope prediction. MEV was constructed using linkers and adjuvant beta-defensin. The vaccine construct was verified, based on its antigenicity, physicochemical properties, and its binding potential, with corresponding toll-like receptors (TLR2, TLR4), ACE2 receptor, B cell receptor. The selected vaccine construct showed considerable binding with all the receptors and a significant immune response, including elevated antibody titer and B cell population along with augmented activity of T(H) cells, Tc cells and NK cells. Thus, immunoinformatics and in silico-based approaches were used for constructing MEV which is capable of eliciting both innate and adaptive immunity. In conclusion, the vaccine construct developed in this study has all the potential for the development of a next-generation vaccine which may in turn effectively combat the new variants of SARS-CoV-2 identified so far. However, in vitro and animal studies are warranted to justify our findings for its utility as probable therapeutics. Although many variants contain the E484Q and L452R separately, recently both of these 119 mutations were found together in India. They were designated as a "double mutant" which is of 120 B.1.617 lineage [27] . 121 While there are many approaches for vaccine development like killed vaccine, live-attenuated 122 vaccine, DNA/RNA vaccines, etc., epitope-based chimeric or subunit vaccines have advantages 123 over them. This is because an ideal multi-epitope vaccine (MEV) can enhance immune response 124 and eventually scale down the risk of re-infection by magnifying the host immunogenicity [28] . 125 Moreover, they are safer as they do not require an entire pathogen. Also, highly promiscuous Our approach is to design epitope-based chimeric vaccines by screening all existing proteins in 134 SARS-CoV-2 so that the most immunogenic peptides can be used. In this study, the analysis was The antigenicity of each of the proteins sequences was determined using VaxiJen server 2.0 183 (http://www.ddg-pharmfac.net/vaxijen/). which is a web-based server for the alignment-184 independent prediction of antigenicity [34] . This server predicts each submitted sequence as an 185 antigen or non-antigen along with a probability score. The mean antigenicity score was then were found to be fully overlapping in both tools were selected to be potential epitopes. Based on these results, the qualities of the refined models were validated and the most suitable 320 model was selected for further steps. were selected as the potential B cell epitopes as these were predicted to be non-allergen, non-422 toxic and antigenic (Table 1) . HFRAAYEIDPKLDNYAAYGVVFLHVTYAAYLVIGAVILRHHHHHH" ( Figure 5A ). RaptorX property, it was observed that 41% of the vaccine residues were in an exposed region, 490 22% in moderately exposed region and 36% in a buried region ( Figure 5C ). It was also predicted 491 that only 12 residues (5%) were in a disordered region ( Figure 5D ). Using 3Dpro, the preliminary 3D structure of the MEV was predicted. Here, due to the lack of 494 any proper PDB template this de novo method was used. Thus, to improve the quality, the 495 predicted structure was refined using GalaxyRefine server. This server refined the structure and 496 five refined models were obtained. These models were further evaluated based on their ERRAT 497 score, Ramachandran plot, and ProSA Z-score. On the basis of these results, the best-resulting 498 model was selected for further analyses ( Figure 6A) . Here, the final selected structure was found 499 to have a ProSA Z-score of -2.97. This value confirms its near-native quality as it is placed close 500 to the experimentally resolved structures of similar sizes ( Figure 6B ). From the Ramachandran 501 plot analysis, it was observed that 96.2% residues of the finally selected refined model were in 502 the favorable and allowed region ( Figure 6C ), whereas, before refinement, the favorable region Out of 219 total residues, DiscoTope-2.0 predicted 20 residues as conformational B cell epitope. Whereas, ElliPro and SEPPA v3.0 predicted 97 and 106 residues to possess discontinuous 510 epitope quality. Among them, " 17 R", " 61 YKLP 64 ", " 81 GPGNSYECD 89 ", " 160 PG 161 ", residues 511 were common in all the three predictions ( Figure 6D ). The ElliPro score of these residues ranged 512 between 0.584-0.995. Interaction of vaccines with potential receptors 514 To evaluate the interaction between the MEV construct and TLR2, TLR4, ACE2 receptors, and (Figure 7 and Table 3 ). were used for a more specific outcome as each bioinformatics-based web server has its own 637 algorithm and sensitivity. Thus, rather than random prediction, sequences that overlapped fully 638 in both tools were considered for analysis to obtain a more accurate and reliable result [77]. " 667 NSYECDIPIGAGIC 680 ", " 1111 WFVTQRNFY 1119 ") passed all the featured criteria of being 641 surface accessible, hydrophilic, flexible, and beta-turn containing, along with being non-allergen 642 and non-toxic. These qualities are significant as beta-turns and hydrophilic residues are generally 643 surface-exposed and play a significant role in immune response initiation [78] . For vaccine construction, a multi-epitope based vaccine was preferred compared to a single The vaccine constructs were evaluated based on their physicochemical parameters, as these 669 parameters have a major impact on the success of immunization [85] . For instance, the molecular in the covariance map ( Figure 8F) . A higher number of stiffer regions was present in the vaccine-TLR4 complex, as illustrated by the grey dots in the elastic network ( Figure 8G) . The results from iMODs demonstrated stable binding of the vaccine-TLR4 complex. The MEV construct was optimized by codon adaptation approach that helps to increase protein indicating the disordered and ordered regions of the MEV protein. 1068 Figure 6 . A) The tertiary structure of the MEV construct finally selected in the study, B) Tables and Supplementary Tables. 1102 Tables: Table 1 . Selected potential B cell, MHC class I and class II epitopes. 1104 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 Inactivated COVID-19 vaccine BBV152/COVAXIN 826 effectively neutralizes recently emerged B 1.1.7 variant of SARS-CoV-2 Sputnik V COVID-19 vaccine candidate appears safe and effective Qualitatively distinct modes of Sputnik V 830 vaccine-neutralization escape by SARS-CoV-2 Spike variants Pros and Cons of Covid-19 vaccines and vaccination Designing a multi-epitope peptide based vaccine 834 against SARS-CoV-2 SARS-CoV-2 Variant Classifications and Definitions A dynamic nomenclature proposal for SARS-837 CoV-2 lineages to assist genomic epidemiology Tracking Changes in SARS-CoV-2 Spike: 839 Evidence that D614G Increases Infectivity of the COVID-19 Virus Neutralizing Activity of BNT162b2-Elicited Serum. N. Engl. J. 841 central nervous system A novel design of a multi-antigenic, multistage 973 and multi-epitope vaccine against Helicobacter pylori: An in silico approach Exploring Leishmania secretory proteins to design B 976 and T cell multi-epitope subunit vaccine using immunoinformatics approach Immunoinformatics-guided design of a multi-980 epitope vaccine based on the structural proteins of severe acute respiratory syndrome coronavirus 981 2 Designing a next generation multi-epitope based peptide 983 vaccine candidate against SARS-CoV-2 using computational approaches An insight into the epitope-based peptide 986 vaccine design strategy and studies against COVID-19 A candidate multi-epitope vaccine against SARS-CoV-2 Physico-chemical characterization and topological analysis 991 of pathogenesis-related proteins from Arabidopsis thaliana and Oryza sativa using in-silico 992 approaches TLR2 and TLR4 mediated host immune responses in 994 major infectious diseases: a review Toll-like receptors: the swiss army knife of immunity and vaccine 997 development The Role of TLR2 in Infection and 999 Emerging Roles of DC Crosstalk 1001 in Cancer Immunity Current progress of immunoinformatics approach 1003 harnessed for cellular-and antibody-dependent vaccine design Th1 and Th2 CD4+< Cells Provide Help for B Cell Clonal Expansion and Antibody Synthesis in a Similar Manner Biologic functions of the IFN-c receptors Th1 and Th2 responses: what are they? Engineering genes for predictable protein 1013 expression Codon Optimization in the Production of Recombinant Biotherapeutics: 1015 Potential Risks and Considerations In silico analysis, molecular docking, 1017 molecular dynamic, cloning, expression and purification of chimeric protein in colorectal cancer 1018 treatment Broad and strong memory CD4+ and CD8+ T cells 1020 induced by SARS-CoV-2 in UK convalescent individuals following COVID-19 Designing of Nucleocapsid Protein Based Novel 1023 Multi-epitope Vaccine Against SARS-COV-2 Using Immunoinformatics Approach Design of an epitope-based peptide vaccine against the 1026 SARS-CoV-2: A vaccine-informatics approach Immunogenomics guided design of immunomodulatory 1028 multi-epitope subunit vaccine against the SARS-CoV-2 new variants, and its validation through 1029 in silico cloning and immune simulation Designing an efficient multi-epitope vaccine 1031 displaying interactions with diverse HLA molecules for an efficient humoral and cellular 1032 immune response to prevent COVID-19 infection Vaccinomic approach for novel multi 1034 epitopes vaccine against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) Inset plot shows danger signal together with leukocyte growth 1096 factor IL-2 In silico cloning of MEV gene in a restriction cloning vector pET28a (+) in E.coli 1098 host. Here, the red areas indicate the MEV, and the black areas represent the expression vector