key: cord-259340-1ir19s25 authors: Das, Rohit Pritam; Jagadeb, Manaswini; Rath, Surya Narayan title: Identification of peptide candidate against COVID-19 through reverse vaccinology: An immunoinformatics approach date: 2020-07-01 journal: bioRxiv DOI: 10.1101/2020.07.01.150805 sha: doc_id: 259340 cord_uid: 1ir19s25 Novel corona virus disease 2019 (COVID-19) is emerging as a pandemic situation and declared as a global health emergency by WHO. Due to lack of specific medicine and vaccine, viral infection has gained a frightening rate and created a devastating state across the globe. Here the authors have attempted to design epitope based potential peptide as a vaccine candidate using immunoinformatics approach. As of evidence from literatures, SARS-CoV-2 Spike protein is a key protein to initiate the viral infection within a host cell thus used here as a reasonable vaccine target. We have predicted a 9-mer peptide as representative of both B-cell and T-cell epitopic region along with suitable properties such as antigenic and non-allergenic. To its support, strong molecular interaction of the predicted peptide was also observed with MHC molecules and Toll Like receptors. The present study may helpful to step forward in the development of vaccine candidates against COVID-19. The disease COVID-19 outbreak caused due to emergence of novel severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) [1] . According to WHO, the novel corona virus has affected more than 5.5 million people with a fatality of 3, 46,969 across the globe as of May 25, 2020 . Respiratory droplets, direct contact and fecal-to-oral transmission are conventional routs for SARS-CoV-2 [2] . The symptoms of SARS-CoV-2 infection include fever, dry cough, shortness of breath, runny nose and sore throat [3, 4] . The rate of transmission and death is gaining severity due to ignorance of specific drug and vaccine against it. SARS-CoV-2 is a positive-sense single-stranded RNA virus and its genome is around 29.7 kB long with twelve putative open reading frames (ORFs) that encode different structural and non-structural proteins. The first SARS-CoV-2 (Wuhan-Hu-1) genome was successfully sequenced and submitted to GenBank on January 5, 2020 (Accession no. MN908947.3) [3] . One-third of the genome is responsible for coding the structural proteins in SARS-CoV-2, namely, spike (S), envelope (E), membrane (M), and nucleocapsid (N) of SARS-CoV-2 are potential antigen for neutralizing antibody preparation and may be prospective therapeutics [5] . After entering into host body, the virion attaches to the host cell membrane and the viral Spike protein S1interacts with a functional host cell receptor known as angiotensin-converting enzyme 2 (ACE2). Thereafter, Spike protein S2 mediates the fusion of the virion and cellular membranes by acting as a class I viral fusion protein [6] . During this phase, the protein attains at least three conformational states: pre-fusion native state, pre-hairpin intermediate state, and post-fusion hairpin state [7] . As SARS-CoV-2 S glycoprotein is surface-attached and has potentiality to initiates the infection thus could be a promising vaccine target. In this connection, epitope based peptide design have remarkable privilege than conventional vaccine development. Peptide based vaccine are most popular since they are specific, generate long lasting immunity, able to avoid undesirable immune responses and are reasonably cheaper [8] . In addition, epitope based vaccine design has been aided by robust computational techniques [9] . Therefore, authors have focused on discovery of epitope from SARS-CoV-2 S glycoprotein. The T-cell epitopes are typically peptide fragments, whereas the B-cell epitopes can be proteins, lipids, nucleic acids or carbohydrates [10, 11, 12] . Based on literature, the peptide is considered sufficient for activation of the appropriate cellular and humoral responses as it is the fragment of antigenic protein [13, 14] . Here we have identified peptide as vaccine candidate as the peptide vaccines are comparatively easy for production, chemically stable, and absence of infectious potential [15] . The present study would throw lights on vaccine development against COVID-19. Protein sequence of S glycoprotein was retrieved from UniProt (ID: P0DTC2) database [16] . The Gene name is "S" which belongs to Severe acute respiratory syndrome corona virus 2 (2019-nCoV) (SARS-CoV-2). The B-cell epitopic regions present in SARS-CoV-2 S protein were identified using BcePred prediction server (https://webs.iiitd.edu.in/cgibin/bcepred/) [17] . It helped to predict linear epitopes from S protein sequence using physico-chemical properties. MHC binding prediction includes the prediction of binding sites for both CD4+ and CD8+. The IEDB analysis resource (http://tools.iedb.org/main/) predicts specific T-cell epitopes to bind with MHC class I molecules along with IC50 (half maximal inhibitory concentration) values. Similarly, it employs different methods to predict MHC Class II epitopes, including a consensus approach which combines NN-align, SMM-align and combinatorial library methods [18] . The crystal structure of HLA-B*35:01 (PDB ID: 4LNR) presenting MHC class I molecule in complex form with the peptide (RPQVPLRPMTY) was retrieved from PDB database [19] . Similarly, as representative of MHC-II, the crystal structure of HLA-DR1 (PDB ID: 1T5X) in complex form with a synthetic peptide (AAYSDQATPLLLSPR) was retrieved from PDB. PepFold server [20, 21] was used to build the tertiary structural model of predicted peptides. Molecular docking was performed between the predicted peptides and MHC representative structures using PatchDock web server [22, 23, 24] . Determination of antigenic and allergenic properties are two important factor related to peptide based vaccine designing. The antigenicity of predicted peptides was calculated using VaxiJen tool [25] with the cut off value 0.4. AllerTOP v. 2.0 [26] and AllergenFP v.1.0 tool [27] was used to predict allergenic property of predicted peptides. In order to find the molecular properties of predicted peptides, Innovagen's peptide calculator was used. It makes calculations and estimations on physiochemical properties like peptide molecular weight, peptide extinction coefficient, peptide net charge at neutral pH and peptide iso-electric point. Crystal structures of human Toll-Like receptors such as TLR2 (PDB ID: 6NIG) and TLR4 (PDB ID: 4G8A) was extracted from PDB and subjected for structural preparation. Interaction of both TLR2 and TLR4 structures with the predicted peptides were performed using PatchDock web server [22, 23, 24] . The complete sequence of SARS-CoV-2 S protein (UniProt ID: P0DTC2) is of 1,273 amino acids length. Average antigenic propensity was calculated as 1.0416 from 63 antigenic determinants within its primary sequence. The antigenic plot (Figure 1 ) between amino acid residues with respect to propensity strongly established S protein antigenicity. Prediction of B-cell epitope is a crucial step in epitope base vaccine design [28] . The potential role of Toll-Like receptor mediated host-parasites interaction is well established. Particularly, TLR2 and TLR4 are well known mediums for interaction between filarial parasites and host innate immune system [11, 14, 15] . Therefore, in this study we have studied the interaction between predicted peptides (Pep-9 and Pep-15) and Toll-Like receptors (TLR2 and TLR4). The result suggested Pep-9 more strongly interacted with TLR2 than TLR4 (Table 3, Figure 6 ). Further, strongest binding affinity (ACE score) was observed between TLR2-Pep15 docked complex (Table 3, Figure 6 ). Moreover, Pep-9 is found more significantly binding with both TLR2 and TLR4 (Table 3, Figure 6 ). This study is focused on the prediction of effective epitopes from Spike protein of SARS-CoV-2. Among all possible epitopes, Pep-9 and Pep-15 were claimed as more effective candidates. Again, it was observed that the Pep-9 as more suitable than Pep-15 in order to be a possible vaccine candidates. Further, in vitro and in vivo validation is required to confirm the prediction. Overall, this study would be informative towards new vaccine development for prevention of widespread COVID-19. 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Immunome research An introduction to B-cell epitope mapping and in silico epitope prediction We are thankful to Dr. Pawan Kumar Agrawal, Vice chancellor, Odisha University of Agriculture and Technology, Bhubaneswar for his moral support and valuable suggestion. The authors declare no competing interest.