结合结构蛋白组学和机器学习的高效保护性精准疫苗对抗肺炎支原体的研究

肺炎支原体（M. pulmonis）是一种新兴的呼吸道感染，常与前列腺癌相关，属于支原体类。鉴于现有抗生素治疗在完全清除这些病原体方面常常无效，改善对支原体感染的管理显得尤为重要。本研究旨在利用结构蛋白组学和机器学习算法设计并构建高效且具有保护作用的疫苗，以预防M. pulmonis感染。通过对M. pulmonis全蛋白组的详细分析，确定了膜蛋白P80、脂蛋白、未表征蛋白和含GGDEF结构域蛋白这四个特定靶点，用于疫苗设计。使用人工神经网络和循环神经网络对细胞毒性T淋巴细胞（CTL）、辅助T淋巴细胞（HTL）(IFN)±和B细胞表位进行映射。设计包括构建mRNA和肽基疫苗，含8个CTL表位（GGS连接）、7个HTL(IFN阳性)表位和8个B细胞表位（GPGPG连接）。所设计疫苗显示出良好的抗原性、非过敏性和优异的理化性质。结构建模表明正确折叠对于最佳功能至关重要。通过分子对接，分析了多肽疫苗与Toll样受体（TLR）1、TLR2和TLR6的结合情况，随后进行分子模拟和结合自由能估算，结果显示相互作用稳定且结合强劲。体外克隆和优化分析得到GC含量为49.776%，优化指数（CAI）为0.982的序列。免疫模拟显示免疫反应强烈，IgM+IgG和二次免疫反应中活跃和血浆B细胞、调节性T细胞、HTL和CTL水平升高。抗原在第50天被完全清除。本研究为开发一种能有效应对新发现的肺炎支原体感染的安全疫苗奠定了基础。

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.