An immunoinformatics approach to epitope-based vaccine design against PspA in Streptococcus pneumoniae

Lincon Mazumder; Muhammad Shahab; Saidul Islam; Mahmuda Begum; Jonas Ivan Nobre Oliveira; Shamima Begum; Shahina Akter

doi:10.1186/s43141-023-00506-9

An immunoinformatics approach to epitope-based vaccine design against PspA in Streptococcus pneumoniae

J Genet Eng Biotechnol. 2023 May 11;21(1):57. doi: 10.1186/s43141-023-00506-9.

Authors

Lincon Mazumder¹, Muhammad Shahab², Saidul Islam¹, Mahmuda Begum³, Jonas Ivan Nobre Oliveira⁴, Shamima Begum¹, Shahina Akter⁵

Affiliations

¹ Department of Microbiology, Jagannath University, Dhaka, 1100, Bangladesh.
² State Key Laboratories of Chemical Resources Engineering, Beijing University of Chemical Technology, Beijing, 100029, China.
³ Bangladesh Council of Scientific & Industrial Research (BCSIR), Dhaka, 1205, Bangladesh.
⁴ Departamento de Biof ́ısica E Farmacologia, Universidade Federal Do Rio Grande doNorte, Natal, RN, 59072-970, Brazil.
⁵ Bangladesh Council of Scientific & Industrial Research (BCSIR), Dhaka, 1205, Bangladesh. shupty2010@gmail.com.

Abstract

Background: Streptococcus 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.

Methods: For 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.

Results: The 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.

Conclusion: The in silico analysis has proven the vaccine as an alternative medication to combat against S. pneumoniae. The designated vaccine can be further tested in the wet lab, and a novel vaccine can be developed.

Keywords: CTL; HTL; LBL; SPN; TLR4; pneumococcal surface protein A (PspA).