Frontiers in cellular and infection microbiology · 2025
Innovative epitopes in Staphylococcal Protein-A an immuno-informatics approach to combat MDR-MRSA infections.
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Zhou Pengjun, Shi Xing, Xia Jinquan, Wang Yifei, Dong Shaowei
Аннотация
BACKGROUND: Methicillin-resistant Staphylococcus aureus (MRSA) poses a significant challenge in clinical environments due to its resistance to standard antibiotics. Staphylococcal Protein A (SpA), a crucial virulence factor of MRSA, undermines host immune responses, making it an attractive target for vaccine development. This study aimed to identify potential epitopes within SpA that could elicit robust immune responses, ultimately contributing to the combat against multidrug-resistant (MDR) MRSA.
METHODS: The SpA protein sequence was retrieved from the UniProt database, with various bioinformatics tools employed for epitope prediction. T-cell epitopes were identified using the Tepitool server, focusing on high-affinity interactions with prevalent human leukocyte antigens (HLAs). B-cell epitopes were predicted using the BepiPred tool. Predicted epitopes underwent docking studies with HLA molecules to evaluate binding properties. In-silico analyses confirmed the antigenicity, promiscuity, and non-glycosylated nature of the selected epitopes.
RESULTS: Several T and B cell epitopes within SpA were identified, showcasing high binding affinities and extensive population coverage. A multi-epitope vaccine construct, linked by synthetic linkers and an adjuvant, was modelled, refined, and validated through various bioinformatics assessments. The vaccine candidate was subsequently docked with Toll-like receptor 4 (TLR-4) to evaluate its potential for immunogenicity.
CONCLUSION: This study lays the groundwork for developing epitope-based vaccines targeting SpA in MRSA, identifying promising candidates for experimental validation and contributing to innovative immunotherapeutic strategies against MRSA infections.
METHODS: The SpA protein sequence was retrieved from the UniProt database, with various bioinformatics tools employed for epitope prediction. T-cell epitopes were identified using the Tepitool server, focusing on high-affinity interactions with prevalent human leukocyte antigens (HLAs). B-cell epitopes were predicted using the BepiPred tool. Predicted epitopes underwent docking studies with HLA molecules to evaluate binding properties. In-silico analyses confirmed the antigenicity, promiscuity, and non-glycosylated nature of the selected epitopes.
RESULTS: Several T and B cell epitopes within SpA were identified, showcasing high binding affinities and extensive population coverage. A multi-epitope vaccine construct, linked by synthetic linkers and an adjuvant, was modelled, refined, and validated through various bioinformatics assessments. The vaccine candidate was subsequently docked with Toll-like receptor 4 (TLR-4) to evaluate its potential for immunogenicity.
CONCLUSION: This study lays the groundwork for developing epitope-based vaccines targeting SpA in MRSA, identifying promising candidates for experimental validation and contributing to innovative immunotherapeutic strategies against MRSA infections.