Hossain, Md Kamal, Davidson, Majid ORCID: 0000-0002-3241-6444, Feehan, Jack ORCID: 0000-0002-9627-1299, Deraos, George, Nurgali, Kulmira ORCID: 0000-0002-2597-6929, Matsoukas, John ORCID: 0000-0001-5554-2964 and Apostolopoulos, Vasso ORCID: 0000-0001-6788-2771 (2023) Development of methamphetamine conjugated vaccine through hapten design: in vitro and in vivo characterization. Vaccines, 11 (2). ISSN 2076-393X

Abstract

Background: Methamphetamine (METH) substance-use disorder is an ever-growing global health issue with no effective treatment. Anti-METH vaccines are under investigation as an alternative to existing psychological interventions. This platform has made significant progress over past decades mainly in preclinical stages, and efforts to develop an anti-METH vaccine with a high antibody response are of utmost importance. Methodology: A novel conjugated anti-METH vaccine was developed using METH HCl as the starting material for the design of hapten, a peptide linker consisting of five lysines and five glycines, and finally immunogenic carrier mannan, which is novel to this platform. All the chemical reaction steps were confirmed by several analytical techniques, and the immunogenicity of the developed vaccine was investigated in a mouse model. Results: Thin-layer chromatography and gas chromatography confirmed the reaction between METH and peptide linker. UV, NMR and color tests were used to confirm the presence of the aldehyde groups in oxidized mannan (OM). The final conjugated vaccine was confirmed by UV and LC-MS. The stability of mannan, the METH hapten, and the final vaccine was evaluated by UV and LC-MS and demonstrated satisfactory stability over 3 months in various storage conditions. Animal studies supported the immunogenicity of the novel vaccine. Conclusions: We successfully developed and characterized a novel METH vaccine in vitro and in vivo. The present study findings are encouraging and will form the basis of further exploration to assess its effectiveness to prevent METH addiction in preclinical models.

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