Designing a multi-Epitope Vaccine against Parkinson’s Disease: An Immunoinformatics and AI approach

Background and aims: Parkinson’s disease (PD) is caused by significant loss of nigral cells andthe proliferation of α-synuclein in distinct regions of the cortex, spinal cord, and brain stem. It isestimated that between ۵ to ۲۰ cases of PD occur per ۱۰۰,۰۰۰ people in years. While some casesof PD can be linked to genetic inheritance patterns, some cases could be related to environmentalelements or a combination of genetical and environmental aspects. There is controversy surroundingthe potential role of infections in causing PD. A neurovirulent strain of influenza type A virushas been displayed to particularly target the substantia nigra. However, some infections, such aschickenpox, mumps, measles, and Helicobacter pylori, are inversely related to PD. Additionally,proteins such as glucocerebrosidase (GBA), leucine-rich repeat kinase ۲ (LRRK-۲), and α-synucleincould play a vital function in susceptibility to PD. In this article, we designed a multi-epitopevaccine against human proteins, bacteria, and viruses that are predisposing factors for PD. Weused computational reverse vaccinology to deviate immune response and Th۱/Th۲ balance via theintroduction of a novel immunogenetic chimera protein.Method: Epitopes from proteins, bacteria, and viruses were identified. Predicting MHC-۱, MHC-۲, and CTL epitopes using bioinformatics online tools. Then these epitopes were linked togetherwith a TAT peptide, adjuvant, and IL-۱۰ inducer sequence to form a chimeric vaccine. The vaccinesequence was created using MODELLER, and the ۳D structure was refined using a Ramachandranplot. The vaccine and TLR-۴ were docked, and a molecular dynamics (MD) simulationof the vaccine-TLR۴ complex was performed using GROMACS. The C-ImmSim server was usedto stimulate the immune response to the chimeric vaccine. We predicted the solubility, antigenicity,and allergenicity of the structure.Results: The developed model was confirmed to be stable with an enhanced ERRAT outcomeabove ۸۰%. The Ramachandran plot exhibited that over ۹۵% of the residues resided in a favorableand permissible location. Molecular dynamics simulations (MDS) demonstrated that the dockedvaccine-TLR۴ had a stable formation. Moreover, the result related to solubility, antigenicity, andallergenicity were acceptable. GRAAVY evaluation showed the vaccine was mildly hydrophilic.We designed a vaccine against viruses that have a protective role against Parkinson›s as by suchpathogenic epitopes the immune system will be stimulated in a similar manner. Ultimately, simulationsof the immune response showed a good reaction from both the innate and adaptive immunesystems. The memory response and cytokine profiles were favorable. SnapGene cloningand gel simulations showed successful cloning of the vaccine protein in pET-۲۱ b(+) / MEV.Conclusion: We developed an immunogenic vaccine against PD using Immunoinformatics andcorroborated its favorable properties. This vaccine has significant value because it serves multiplepurposes, providing immunity against all mentioned risk factors and PD itself. The resultsobtained through computer simulation can aid researchers in developing a vaccine for PD in real-world preclinical and clinical experiments.

کلیدواژه ها:

Parkinson’s disease ، chimeric vaccine ، Immunoinformatics ، bioinformatics