Immunoinformatics design of a multi-epitope vaccine for Chlamydia pneumoniae targeting the Indonesian population

Context: Chlamydia pneumoniae is a bacterium that causes respiratory disease, including pneumonia. In this context, vaccines offer a promising opportunity to prevent bacterial infections by mitigating the spread of resistant strains, as antibiotic resistance increasingly prevails. Despite the potential to serve as a sustainable and cost-effective public health strategy, no licensed product has been developed for widespread clinical use. Aims: To design a C. pneumoniae vaccine using immunoinformatics tools targeting outer membrane proteins and based on Indonesian HLA alleles. Methods: A total of 430 proteins were retrieved from UniProt, and epitope prediction was conducted based on prevalent Indonesian HLA alleles. Selected B- and T-cell epitopes were assembled into the vaccine construct, followed by 3D modeling. Subsequently, molecular docking and dynamic simulations were performed to evaluate the interaction between the vaccine candidate and Toll-like receptor 4 (TLR4). In silico cloning was performed using JCat and SnapGene to create a plasmid construct. Results: Seven potential outer membrane proteins were identified. Final epitopes showed strong antigenicity, non-allergenicity, and non-toxicity. The population coverage prediction reported 99.76% and 64.13% compatibility with Indonesia and the world, respectively, suggesting potential efficacy. The refined vaccine model showed an RMSD of 0.234 Å (threshold: 2 Å) and a strong binding affinity for TLR4 (ΔG: –19.7 kcal/mol). Molecular dynamics confirmed stable binding to TLR4. The optimization achieved a codon adaptation index of 1.0 and a GC content of 48.17%. Meanwhile, in silico cloning was completed in the pET-28a(+) vector. Conclusions: These results showed that the designed vaccine elicited immune responses against C. pneumoniae, specifically in the Indonesian population.