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Updated: Aug 5, 2026

Production of E. coli-expressed Self-Assembling Protein Nanoparticles for Vaccines Requiring Trimeric Epitope Presentation
Published on: August 21, 2019
A novel multi-epitope mRNA vaccine against Escherichia coli using an in silico reverse vaccinology approach
Shakeela Parveen1,2, Javeria Abbasi3, Muhammad Hussain4
1Guangxi Key Laboratory of Beibu Gulf Marine Biodiversity Conservation, Beibu Gulf University, Guangxi, 535011, PR China. drshakeela@gscwu.edu.pk.
Abstract:
The adaptable nature of Escherichia coli, shifting from benign to virulent forms, poses a major healthcare challenge due to rising multidrug resistance and hypervirulence. In this study, using an in silico reverse vaccinology approach, we designed a multiepitope mRNA vaccine candidate targeting the Shiga toxin 1 (Stx1) of Shiga toxin-producing E. coli (STEC). Two cytotoxic T-Lymphocyte (CTL), three Helper T-Lymphocyte (HTL), and two Linear B-Lymphocyte (LBL) epitopes were identified and selected through stringent computational filtering based on high antigenicity, non-allergenicity, and non-toxicity. These epitopes were joined using optimized linkers (EAAK, AAY, GPGPG, KK) and the adjuvant PefE to form a stable 184-residue multi-epitope construct. Physicochemical profiling predicted a molecular weight of 19969.45 Da, an antigenicity score of 0.9278 (VaxiJen v.2.0), a basic isoelectric point (pI) of 10.31, and structural stability. Structural analysis revealed 21.74% alpha-helical content. Molecular docking exhibited strong binding with human Toll-like receptor 2 TLR2 and TLR4, with weighted energy scores of - 1096.2 and - 1110.5 kcal/mol, respectively, mediated by extensive hydrogen-bonding and salt-bridge networks. In silico immune simulation projected a strong clonal expansion of B-cells, active T-helper and cytotoxic T-cells, and higher cytokine production (IFN-γ, IL-10). Codon Adaptation Index (CAI) of 0.87 and a stable mRNA secondary structure were predicted with a minimum free energy (MFE) of - 204.10 kcal/mol. While these computational findings provide immunogenic potential, they represent a predictive hypothesis. Subsequent in vitro synthesis and in vivo testing in animal models are essential to validate its safety, immunogenicity, and protective efficacy.

