肺支原体 (M. pulmonis) 是一种新出现的呼吸道感染，通常与前列腺癌相关，属于支原体类别。由于目前的抗生素治疗经常无法从宿主体内完全消除这些病原体，因此改善支原体感染的管理至关重要。本研究的目的是在结构蛋白质组学和机器学习算法的指导下设计和构建有效的保护性疫苗，以提供针对肺支原体感染的保护。通过对肺分枝杆菌整个蛋白质组的彻底检查，已确定适合设计疫苗的四个特定靶标：膜蛋白 P80、脂蛋白、未表征的蛋白和含有 GGDEF 结构域的蛋白。使用人工和循环神经网络对这些蛋白质进行细胞毒性 T 淋巴细胞 (CTL)、辅助 T 淋巴细胞 (HTL) (IFN)-γ ± 和 B 细胞表位的绘制。该设计涉及基于 mRNA 和肽的疫苗的创建，该疫苗由由 GGS 连接体连接的 8 个 CTL 表位、7 个 HTL（IFN 阳性）表位和由 GPGPG 连接体连接的 8 个 B 细胞表位组成。设计的疫苗表现出抗原行为、非过敏性品质和特殊的理化特性。结构模型表明，正确的折叠对于最佳功能至关重要。通过分子对接实验检查了 MEVC 与 Toll 样受体 (TLR)1、TLR2 和 TLR6 的偶联。随后进行分子模拟研究，其中包括结合自由能估计。结果表明，相互作用动力学稳定，结合力强。计算机克隆和优化分析显示优化序列的 GC 含量为 49.776%，CAI 为 0.982。免疫模拟结果显示出强烈的免疫反应，IgM IgG 和二次免疫反应中活性 B 细胞、血浆 B 细胞、调节性 T 细胞、HTL 和 CTL 水平均升高。到第50天时抗原完全清除。这项研究为开发一种有效且安全的候选疫苗来对抗新发现的人肺支原体感染奠定了基础。版权所有 © 2024。由 Elsevier B.V. 出版。

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.Copyright © 2024. Published by Elsevier B.V.