In-silico design of a multi-epitope for developing sero-diagnosis detection of SARS-CoV-2 using spike glycoprotein and nucleocapsid antigens

Abstract

COVID-19 is a pandemic disease caused by novel corona virus, SARS-CoV-2, initially originated from China. In response to this serious life-threatening disease, designing and developing more accurate and sensitive tests are crucial. The aim of this study is designing a multi-epitope of spike and nucleocapsid antigens of COVID-19 virus by bioinformatics methods. The sequences of nucleotides obtained from the NCBI Nucleotide Database. Transmembrane structures of proteins were predicted by TMHMM Server and the prediction of signal peptide of proteins was performed by Signal P Server. B-cell epitopes' prediction was performed by the online prediction server of IEDB server. Beta turn structure of linear epitopes was also performed using the IEDB server. Conformational epitope prediction was performed using the CBTOPE and eventually, eight antigenic epitopes with high physicochemical properties were selected, and then, all eight epitopes were blasted using the NCBI website. The analyses revealed that α-helices, extended strands, β-turns, and random coils were 28.59%, 23.25%, 3.38%, and 44.78% for S protein, 21.24%, 16.71%, 6.92%, and 55.13% for N Protein, respectively. The S and N protein three-dimensional structure was predicted using the prediction I-TASSER server. In the current study, bioinformatics tools were used to design a multi-epitope peptide based on the type of antigen and its physiochemical properties and SVM method (Machine Learning) to design multi-epitopes that have a high avidity against SARS-CoV-2 antibodies to detect infections by COVID-19.

Keywords: Multi-epitopes; Nucleocapsid phosphoprotein; SARS-CoV2; Serological tests; Spike glycoprotein.

Fig. 1

The secondary structure of retrieved amino acid sequences by SOPMA server. A Spike glycoprotein (S protein); B nucleocapsid phosphoprotein (N protein)

Fig. 2

Three-dimensional structure prediction of SARS-CoV-2 antigens and selection of antigenic epitopes; A spike glycoprotein; B nucleocapsid protein using I-TASSER server

Fig. 3

Validation of the quality of nucleocapsid protein and spike glycoprotein: A validation of 3D models by Ramachandran plot; B validation of 3D models by ProSA-web

Fig. 4

A Predicting and designing multi-epitope; B three-dimensional structure of a multi-epitope designed by I-TASSER sever and the position of the amino acid sequence of nucleocapsid protein and spike glycoprotein epitopes on the 3D structure of the multi-epitope using the Chimera Version 1.8

Fig. 5

3D structure of final multi-epitope predicted using I-TASSER server. A Model 1: C-score =  − 2.76; B model 2: C-score =  − 1.95; C model 3: C-score =  − 3.21; d model 4: C-score =  − 3.29; e model 5: C-score =  − 4.78

Fig. 6

Validation of final construct of multi-epitope by A Ramachandran plot; B and C ProSA-web plot and local model quality for 3D structure of final construct, plotting energies of the final construct, respectively; D Verify3D method to evaluate a 3D model of final multi-epitope

Fig. 7

The multi-epitope protein sequence was reverse translated into nucleotide sequence using the J-CAT

Fig. 8

Workflow summary of SARS-CoV-2 multi-epitope design steps for designing a proposed serological diagnostic test for COVID-19 diagnosis