Coarse-grained Molecular Dynamics-guided Immunoinformatics to Explain the Binder and Non-binder Classification of Cytotoxic T-cell Epitope for Sars-cov-2 Peptide-based Vaccine Discovery

Abstract

Epitope-based peptide vaccine can elicit T-cell immunity against SARS-CoV-2 to clear the infection. However, finding the best epitope from the whole antigen is challenging. A peptide screening using immunoinformatics usually starts from MHC-binding peptide, immunogenicity, cross-reactivity with the human proteome, to toxicity analysis. This pipeline classified the peptides into three categories, i.e., strong-, weak-, and non-binder, without incorporating the structural aspect. For this reason, the molecular detail that discriminates the binders from non-binder is interesting to be investigated. In this study, five CTL epitopes against HLA-A*02:01 were identified from the coarse-grained molecular dynamics-guided immunoinformatics screening. The strong binder showed distinctive activities from the non-binder in terms of structural and energetic properties. Furthermore, the second residue from the nonameric peptide was most important in the interaction with HLA-A*02:01. By understanding the nature of MHC-peptide interaction, we hoped to improve the chance of finding the best epitope for a peptide vaccine candidate.

Introduction

The increasing variants of SARS-CoV-2 viruses raised concerns about the vaccine’s effectiveness, which currently is based on the whole-inactivated virus, mRNA, adenovirus viral vector, and recombinant protein [1,2]. Furthermore, since the new variant mutations occur on the surface epitope of spike protein, they might escape from the existing spike-based vaccine-induced neutralizing antibodies [3–5]. Therefore, it is important to develop a vaccine based on the conserved epitopes, yet immunogenic, to elicit a broad immune response towards many variants of Covid-19, including Omicron and its derivatives.

A successful trial of a peptide-based Covid-19 vaccine showed broad protection against many problematic SARS-CoV-2 variants [6,7]. It is specifically designed to elicit T-cell immunity against the virus rather than the neutralizing antibody [8]. This kind of vaccine could be used as a booster to strengthen cellular immunity to clear the infection and halt the progression of the infection into a severe disease [9]. Also, it may be helpful for people who did not mount enough strong immune responses after the vaccine shot due to B-cell deficiencies [8].

Methods

Sequences retrieval of complete genes encoding SARS-CoV-2 spike protein

The genetic sequences encoded the Spike (S) viral proteins from Wuhan clinical data corresponding to the accession number EPI_ISL_529967 deposited in the GISAID repository (https://www.gisaid.org/). Subsequently, the FASTA formatted sequences of this protein were defined as a query sequence in T-cell epitope predictions. As for the other variant of SARS-CoV-2, such as Delta and Omicron, we use the CoVariants web server (https://www.covariant.org/) that provides an overview of SARS-CoV-2 variants and mutations that are of interest. We have placed the workflow diagram of this study in Fig 1.

Results

SARS-CoV-2 spike T-cells epitope peptide candidates from immunoinformatics screening

The prediction of CTL epitope peptides against SARS-CoV-2 was performed using immunoinformatics screening with several selection steps to obtain the most potential epitope peptide. This epitope prediction was conducted using NetMHCpan1, based on its affinity to HLA-A*02:01 as the most widespread supertype [46,47]. Further, it was sorted by the immunogenicity and affinity score parameters. This process resulted in a list of 47 nonameric peptides of SARS-CoV-2 spike protein that bind to HLA-A*02:01 and are categorized as strong-, weak-, and non-binder (Table 1). The top two peptides are FIAGLIAIV (FIA) and YLQPRTFLL (YLQ), which had the highest immunogenicity and affinity score, labeled as the strong-binder. The EQDKNTQEV (EQD) and VYDPLQPEL (VYD) with the lowest affinity score were taken as the weak-binder. Whereas the TNGTKRFDN (TNG) was chosen as the non-binder due to its zero EL score. It is worth noting that based on the multiple-sequence alignment, these peptides were conserved among the wild type of SARS-CoV-2 and other variants of concern. Thus, suggesting broad coverage protection when these peptides are developed as a vaccine. 

Discussion

One of the vaccine types that is interesting to study is peptide-based vaccines because of their broad spectrum against multiple variants and their capability to induce cellular and humoral immunity with the least risk of allergy and autoimmune to develop [18,52]. It also presented unique properties regarding selectivity and specificity toward specific targets, making it safe and stable [6,53]. This recent year, some researchers have been focusing on this platform, as shown by the number of peptide-based vaccines entering clinical trial phases. There are 178 vaccines in trial phase I and 115 in phase II until 2020, covering various diseases [6]. Referring to World Health Organization (WHO) reports on the Covid-19 vaccine tracker and landscape, 13 peptide-based vaccines proceed to the preclinical phase. Also, five other candidates (CoVepiT, EpiVacCorona, IMP CoVac-1, PepGNP-SARSCoV2, and UB-612) continued in the clinical phase until April 2022 [7]. For instance; CoVac-1 is a multi-peptide-based vaccine candidate designed to produce widespread and long-term SARS-CoV-2 T-cell immunity similar to that acquired by natural infection, unaffected by the variants of concern (VOCs). Furthermore, it has a decent safety profile and generates robust T-cell responses following a single immunization, according to trial phase I [8]. Hence, in this study, we project the peptide-based vaccine as our platform for the postliminary work.

Acknowledgments

The authors would like to thank the Research Center for Molecular Biotechnology and Bioinformatics–Universitas Padjadjaran for providing a computing research facility.

Citation: Yusuf M, Destiarani W, Widayat W, Yosua Y, Gumilar G, Tanudireja AS, et al. (2023) Coarse-grained molecular dynamics-guided immunoinformatics to explain the binder and non-binder classification of Cytotoxic T-cell epitope for SARS-CoV-2 peptide-based vaccine discovery. PLoS ONE 18(10): e0292156. https://doi.org/10.1371/journal.pone.0292156

Editor: Sheikh Arslan Sehgal, The Islamia University of Bahawalpur Pakistan, PAKISTAN

Received: July 26, 2023; Accepted: September 13, 2023; Published: October 5, 2023

Copyright: © 2023 Yusuf et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The datasets analyzed during the current study are available in the GISAID repository with accession number EPI_ISL_529967 (https://gisaid.org/), UniProtKB repository 2021_04 release (225,619,586 sequences) (https://www.uniprot.org/release-notes/2021-11-17-release), and Protein Data Bank repository (PDB ID: 1I7U) (https://www.rcsb.org/structure/1i7u).

Funding: M.Y. received funding from Indonesia Endowment Fund for Education (LPDP) and Indonesian Science Fund (DIPI) through RISPRO International Collaboration [grant number: RISPRO/KI/B1/KOM/5/1986/3/2020]. APC is funded by Universitas Padjadjaran. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0292156#abstract0