Department of Pharmaceutical Sciences, College of Pharmacy, QU Health, Qatar University, P.O. Box 2713, Doha, Qatar.
Department of Pharmaceutical Sciences, College of Pharmacy, QU Health, Qatar University, P.O. Box 2713, Doha, Qatar.
Int Immunopharmacol. 2024 Nov 15;141:112833. doi: 10.1016/j.intimp.2024.112833. Epub 2024 Aug 16.
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.
肺炎支原体(M. pulmonis)是一种新兴的呼吸道感染,通常与前列腺癌有关,属于支原体群。由于目前的抗生素治疗在完全清除宿主中的这些病原体方面经常无效,因此必须改善支原体感染的管理。本研究的目的是通过结构蛋白质组学和机器学习算法设计和构建有效的保护性疫苗,以提供针对 M. pulmonis 感染的保护。通过对 M. pulmonis 整个蛋白质组的全面研究,已经确定了四种特定的靶标:膜蛋白 P80、脂蛋白、未鉴定蛋白和含有 GGDEF 结构域的蛋白,这些蛋白适合用于设计疫苗。使用人工和递归神经网络对细胞毒性 T 淋巴细胞(CTL)、辅助 T 淋巴细胞(HTL)(IFN)-γ±和 B 细胞表位进行了映射。设计涉及创建由 GGS 接头连接的 8 个 CTL 表位、7 个 HTL(IFN-阳性)表位和由 GPGPG 接头连接的 8 个 B 细胞表位的 mRNA 和肽基疫苗。设计的疫苗表现出抗原性、非变应原性和优异的物理化学特性。结构建模表明正确折叠对于最佳功能至关重要。通过分子对接实验研究了 MEVC 与 Toll 样受体(TLR)1、TLR2 和 TLR6 的偶联。随后进行了分子模拟研究,包括结合自由能估计。结果表明相互作用的动力学稳定,结合牢固。在计算机中克隆和优化分析揭示了一个优化序列,其 GC 含量为 49.776%,CAI 为 0.982。免疫模拟结果表明,在 IgM+IgG 和二次免疫反应中,活性和血浆 B 细胞、调节性 T 细胞、HTL 和 CTL 的水平均升高,产生了强烈的免疫反应。抗原在第 50 天被完全清除。这项研究为开发针对新发现的 M. pulmonis 感染的有效和安全的疫苗候选物奠定了基础。