BackgroundStreptococcus pneumoniae(SPN) is the agent responsible for causing respiratory diseases, including pneumonia, which causes severe health hazards and child deaths globally. Antibiotics are used to treat SPN as a first-line treatment, but nowadays, SPN is showing resistance to several antibiotics. A vaccine can overcome this global problem by preventing this deadly pathogen. The conventional methods of wet-laboratory vaccine design and development are an intense, lengthy, and costly procedure. In contrast, epitope-based in silico vaccine designing can save time, money, and energy. In this study, pneumococcal surface protein A (PspA), one of the major virulence factors of SPN, is used to design a multi-epitope vaccine.MethodsFor designing the vaccine, the sequence of PspA was retrieved, and then, phylogenetic analysis was performed. Several CTL epitopes, HTL epitopes, and LBL epitopes of PspA were all predicted by using several bioinformatics tools. After checking the antigenicity, allergenicity, and toxicity scores, the best epitopes were selected for the vaccine construction, and then, physicochemical and immunological properties were analyzed. Subsequently, vaccine 3D structure prediction, refinement, and validation were performed. Molecular docking, molecular dynamic simulation, and immune simulation were performed to ensure the binding between HLA and TLR4. Finally, codon adaptation and in silico cloning were performed to transfer into a suitable vector.ResultsThe constructed multi-epitope vaccine showed a strong binding affinity with the receptor molecule TLR4. Analysis of molecular dynamic simulation, C-immune simulation, codon adaptation, and in silico cloning validated that our designed vaccine is a suitable candidate against SPN.ConclusionThe in silico analysis has proven the vaccine as an alternative medication to combat againstS. pneumoniae. The designated vaccine can be further tested in the wet lab, and a novel vaccine can be developed.Supplementary InformationThe online version contains supplementary material available at 10.1186/s43141-023-00506-9.