همایش ملی بیوانفورماتیک ایران

صفحه اصلی / 4th international edition and 13th Iranian Conference on Bioinformatics

Designing self-assembled peptide nanovaccine (SAPN) against Respiratory syncytial virus (RSV): An Immunoinformatic approach

نویسندگان :

Marzieh Mehdieh¹ Farahnaz Zare²

1- Shiraz University of Medical Sciences 2- Shiraz University of Medical Sciences

کلمات کلیدی :

Respiratory Syncytial Virus،Vaccine Design،Immunoinformatic،Self-Assembly Peptide

چکیده :

Introduction:Respiratory Syncytial Virus (RSV) is a highly contagious virus primarily affecting the respiratory tract and posing significant health risks to infants, young children, older adults, and immunocompromised individuals. Nearly all children contract RSV by age two, with some requiring hospitalization for severe respiratory illness. The development of effective RSV vaccines is a major advancement, and as of mid-2023, two vaccines approved for older adults show moderate to high efficacy in preventing symptomatic RSV-related lower respiratory tract disease (LRTD). Clinical trials indicate that these vaccines can substantially reduce severe RSV infections over multiple seasons, potentially easing the burden of the virus among vulnerable groups (Britton, A, 2024). Self-assembled peptide nanoparticles (SAPNs) are promising tools in vaccine design due to their ability to form stable nanostructures that enhance immune responses. These peptides can self-organize into various forms like nanofibers and hydrogels, providing robust antigen presentation and improved stability. SAPNs can also incorporate adjuvants and target specific immune cells, boosting the vaccine's efficacy and safety. This innovative approach offers a versatile platform for developing next-generation vaccines (Abdullah, T and et al, 2020). Method:First, genomic sequences from RSV subtypes A and B were analyzed, and membrane proteins were selected for further study. Gene sequences were examined using IEDB to identify MHCI, MHCII, and B-cell epitopes. The toxigenic, allergenic, and antigenic properties were assessed using Toxinpred, Allertop, and Vaxijen, respectively. Identical epitopes with optimal conditions from both subtypes were chosen for vaccine design, and the final epitopes were derived from the RSV F and G proteins. The vaccine sequence includes HisTag, MHCI epitopes, MHCII epitopes, pentamer and trimer oligomeric domains, B-cell epitopes, and a soluble tag. The vaccine amino acid sequence was assessed using Vaxijen, Toxinpred, Allertop, and Protparam. The secondary and tertiary structures were then defined using Psipred and AlphaFold2 Colab, respectively. Following structure energy minimization, homomer structures were predicted using the GalaxyHomomer server to model RSV-SAPN. Docking of the vaccine with TLRs (TLR1-4 and TLR9) was performed using the Cluspro server. Result:The vaccine construct, containing MHCI, MHCII, B cell epitopes, trimer, and pentamer domains, was developed using proteins F and G from RSV subtypes A and B. The schematic structure of the designed vaccine construct is shown in Figure 1A. The theoretical physicochemical properties are: pI = 9.09, number of amino acids = 392, GRAVY = -0.521, and stability = 45.58. The secondary and 3D structures are shown in Figures 1B and 1C. The homo-oligomer of our protein was predicted using GalaxyHomomer. Based on docking results, the 3-mer structure of the protein had the best score (docking score = 769.093) (Figure 1D). The vaccine construct was docked with TLR receptors using Cluspro, and the lowest energy interactions with TLR1 (-1451.7), TLR2 (-1515.0), TLR3 (-1558.7), TLR4 (-1549.4), and TLR9 (-1971.5) were selected and analyzed using LigPlot-plus and PyMOL software (Figures 2-6). The antigenicity of the vaccine was estimated 0.4524 by VaxiJen, exceeding the 0.4 threshold. Based on Allertop result, the vaccine is likely a non-allergen, and Toxinpred also indicated the protein is a non-toxin.