Multiple Sequence Alignment:
Receptor binding domain of COVID-19 is 192 amino acids long (within position 330-522 amino acids) lying in S1 region of spike glycoprotein. When comparing the receptor binding motif with the BatCoV RaTG13 there was variation between the two virus strains (Fig II). The important changes were observed at position 439 (Lys→Asn), 440 (His→Asn), 441 (Ile→Leu), 443 (Thr→Lys), 445(Glu→Val), 449 (Phe→Tyr), 459 (Ala→Ser), 478 (Lys→Thr), 483 (Gln→Val), 484 (Thr→Glu), 486 (Leu→Phe), 490 (Tyr→Phe), 492 (Ile→Leu), 493 (Tyr→Gln), 494 (Arg→Ser), 498 (Tyr→Gln), 501 (Asp→Asn), 505 (His→Tyr). The changes at positions 441, 486, 492, 493, 498, and 505 may not have any obvious effect on binding due to similar properties of amino acids.
B-Cell epitopes within Receptor Binding Domain: Continuous B-cell epitopes were predicted using B-cell epitope prediction methods on IEDB server. The Kolaskar & Tongaonkar method predicted 11 antigenic epitopes in the receptor binding domain (Table I) which can prompt B-cell responses. Surface accessibility analysis revealed 4 epitopes with surface accessibility (Table II). Flexibility of epitopes is a measure of antigenicity [53]. The flexible epitopes in RBD were at positions 352-362, 380-392, 400-410, 421-433, 434-451, 454-473, 472-487, 495-506. Beta turns are the more flexible regions of the protein. According to Chou & Fasman predictions the beta turn epitopes were at positions 437-443, 455-468, 422-428, 495-500. Linear epitopes determined by Bepipred method are shown in Table 3. On the basis of consensus of all the methods, the peptides that can induce B-cell response were placed at positions 423-428, 455-461, 494-500. The 423-428, 455-461, 494-500, were the peptides that may prompt B-cell responses as predicted by ElliPro method. The mapping of epitopes on three dimensional structure of protein is shown in Fig III.Cytotoxic T-cell Epitope Prediction:
The default setting in the NetCTL server was used to predict T cell epitopes. On the basis of highest combinatorial scores, five epitopes were opted for subsequent analysis (Table IV). On the basis of NetCTL scores the peptides with the highest score was CVADYSVLY. Further analysis of all the five peptides for their binding with MHC-I showed that peptide CVADYSVLY illustrated binding with maximum MHC-I alleles (HLA-A*26:01, HLA-A*01:01, HLA-A*30:02, HLA-B*35:01, HLA-A*11:01, HLA-B*15:01, HLA-A*68:01, HLA-A*03:01, HLA-B*53:01, HLA-C*07:01). The next peptide showing the binding with maximum number of alleles was FTNVYADSF.
Helper T-cell Epitope Prediction:
A total of 9 peptides were predicted which exhibited strong affinity for MHC-II alleles (Table V). Among these the peptide YRLFRKSNL and VYAWNRKRI reflected affinity for maximum number of alleles. YRLFRKSNL held strong affinity with large number of MHC-II allele including: DRB1_0103, DRB1_0701, DRB1_0801, DRB1_0802, DRB1_1602, DRB4_0103, DRB1_1001, DRB1_1101, DRB1_1501, DRB4_0103, DRB5_0101.
B- and T-cell Epitopes Feature Profiling:
To identify the best epitope for vaccine construction, different features of T-cell epitopes were determined (Table VI). The identified epitopes didn’t show any homology with human proteins, didn’t exhibited mutations and predicted to be non-toxic. The peptides which were digested by fewer enzymes have been considered good potential vaccine candidates (Table VI). Antigenicity of the peptides depicted that CTL specific peptides can be antigenic except ERDISTEIY. In case of helper T-cell epitopes, FELLHAPAT, TGCVIAWNS, and VLYNSASFS were highly antigenic while other peptides were less antigenic. In case of B-cell epitopes, all the 3 peptides were antigenic. Interaction Analysis of CTL Epitopes with MHC-I Specific Alleles:
Two peptides (CVADYSVLY, FTNVYADSF) with the maximum number of bindings with HLA alleles were selected for interaction analysis. PEPFOLD created 5 models for each peptide and the model with the best score was selected for further analysis. HLA-A*0101 was selected as representative allele for interaction analysis. The docking of HLA-A with the top ranking peptide resulted in generation of 50 complexes for each peptide. The peptide 3 (CVADYSVLY) binds with HLA with binding energy of -11.3 KJ/mol. Detailed interaction analysis revealed that peptide is having H-bonding interactions with Asp-115, Arg-156, Tyr-99 and Asn-77 (Fig IV-a). Peptide 4 (FTNVYADSF) binds with the HLA-A with an energy value of -12.6 KJ/mol. The peptide is exhibiting H-bonding interactions with Glu-63, Arg-156, Gln-155, Asn-77, Thr-143, and Lys-146 (Fig IV-b).
Interaction Analysis of HTL Epitopes with MHC-II Specific Alleles:
Two of the peptides (YRLFRKSNL, VYAWNRKRI) that showed affinity with maximum number of MHC-II alleles were selected for interaction analysis. Docking of peptides with HLA-DRB5 depicted both the peptides to be binding with strong affinity. The Peptide 6 and peptide 5 with maximum number of alleles were used to study affinity of these peptides with DRB5_0101. Peptide 5 (YRLFRKSNL) bound with the energy of -10.2KJ/mol while peptide 6 (VYAWNRKRI) bound with the energy of -11.3 KJ/mol. The residues Asp-70, Asn-62, Arg-71, Glu-55 of HLA-DRB5 were having H-bonding interactions with peptide 5 (Fig IV-c). Interaction analysis revealed that Ser-53, Asp-11, Asp-30, and Asp-70 of HLA-DRB5 were exhibiting H-bonding interactions with peptide 6 (Fig IV-d).
Interaction analysis of BatCoV RaTG13 with bACE2:
The interactions of BatCoV RaTG13 with bACE2 was done using HADDOCK. 155 different complexes of BatCoV RaTG13:bACE2 were generated that clustered into 12 groups. Table S1 is showing the Z scores of all the seven clusters, size of each cluster, RMSD from the overall lowest-energy structure, and energy values of electrostatic, Van der Waals, and de-solvation. The cluster with the best HADDOCK score (-178.9±3.6) was further used for analysis. Detailed interaction analysis showed that 26 residues of bACE2 and 9 residues of BatCoV RaTG13 were present at the interface. These residues were involved in 12 H-bonded, 2 Salt bridges and 157 non-bonded contacts. The detailed interactions are shown in table VII and Fig V.0 V. The important residues of batCoV RaTG13 that were involved in interactions with bACE2 are Lys-417, Leu-455, Phe-456, Asn-487, Tyr-489, Asp-501, His-505. The important conserved residues of BatCoV RaTG13 that involved in interactions and overlapping with epitopes are Leu-455, Phe-456. These residues are lied in one B-cell epitope (455-LFRKSN-461) and T-cell epitope (453-YRLFRKSNL-461). The important interacting residues of BatCoV RaTG13 with bACE2 and a comparison with COVID-19:hACE2 is shown in Fig VI.