Integrated structural proteomics and machine learning-guided mapping of a highly protective precision vaccine against mycoplasma pulmonis
Author | Abbas, Khan |
Author | Ammar Zahid, Muhammad |
Author | Farrukh, Farheen |
Author | Salah Abdelsalam, Shahenda |
Author | Mohammad, Anwar |
Author | Al-Zoubi, Raed M. |
Author | Shkoor, Mohanad |
Author | Ait Hssain, Ali |
Author | Wei, Dong-Qing |
Author | Agouni, Abdelali |
Available date | 2024-08-27T06:16:16Z |
Publication Date | 2024-11-15 |
Publication Name | International Immunopharmacology |
Identifier | http://dx.doi.org/10.1016/j.intimp.2024.112833 |
Citation | Khan, A., Zahid, M. A., Farrukh, F., Abdelsalam, S. S., Mohammad, A., Al-Zoubi, R. M., ... & Agouni, A. (2024). Integrated structural proteomics and machine learning-guided mapping of a highly protective precision vaccine against mycoplasma pulmonis. International Immunopharmacology, 141, 112833. |
ISSN | 15675769 |
Abstract | Mycoplasma pulmonis (M. pulmonis) is an emerging respiratory infection commonly linked to prostate cancer, and it is classified under the group of mycoplasmas. Improved management of mycoplasma infections is essential due to the frequent ineffectiveness of current antibiotic treatments in completely eliminating these pathogens from the host. The objective of this study is to design and construct effective and protective vaccines guided by structural proteomics and machine learning algorithms to provide protection against the M. pulmonis infection. Through a thorough examination of the entire proteome of M. pulmonis, four specific targets Membrane protein P80, Lipoprotein, Uncharacterized protein and GGDEF domain-containing protein have been identified as appropriate for designing a vaccine. The proteins underwent mapping of cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL) (IFN)-γ ±, and B-cell epitopes using artificial and recurrent neural networks. The design involved the creation of mRNA and peptide-based vaccine, which consisted of 8 CTL epitopes associated by GGS linkers, 7 HTL (IFN-positive) epitopes, and 8 B-cell epitopes joined by GPGPG linkers. The vaccine designed exhibit antigenic behavior, non-allergenic qualities, and exceptional physicochemical attributes. Structural modeling revealed that correct folding is crucial for optimal functioning. The coupling of the MEVC and Toll-like Receptors (TLR)1, TLR2, and TLR6 was examined through molecular docking experiments. This was followed by molecular simulation investigations, which included binding free energy estimations. The results indicated that the dynamics of the interaction were stable, and the binding was strong. In silico cloning and optimization analysis revealed an optimized sequence with a GC content of 49.776 % and a CAI of 0.982. The immunological simulation results showed strong immune responses, with elevated levels of active and plasma B-cells, regulatory T-cells, HTL, and CTL in both IgM+IgG and secondary immune responses. The antigen was completely cleared by the 50th day. This study lays the foundation for creating a potent and secure vaccine candidate to combat the newly identified M. pulmonis infection in people. |
Sponsor | This work was supported by Qatar National Research Fund [grant No. ARG01-0601-230451] and Qatar University grant No. QUPD-CPH-23/24-592. The statements made herein are solely the responsibility of the authors. M.A.Z. and S.S.A. are supported by Ph.D. graduate assistantships from the Office of Graduate Studies (Qatar University). |
Language | en |
Publisher | Elsevier |
Subject | Mycoplasma Structural proteomics Vaccine Molecular simulation Immune simulation |
Type | Article |
Volume Number | 141 |
ESSN | 1878-1705 |
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