Advanced NMR, computational, and hybrid methods for metabolomics

项目总结 代谢组学的高级核磁共振、计算和混合方法 代谢组学的出现有望彻底改变人们对生物系统的理解。 从代谢物的角度来看，对疾病的诊断和治疗具有重要意义。 尽管最近在复杂代谢组学混合物的图谱和定量方面取得了进展，例如 尿液、血清和癌组织，核磁共振和质谱学，重要的方法学挑战 留下来。拟议的研究计划旨在通过以下方式解决一些紧迫的挑战 开发将核磁共振与化学信息学和质谱学相结合的新方法 通过显影对未知代谢物及其化学和结构基元的新表征 以及维护先进的网络服务器和代谢组学数据库(COLMAR)， 高效、用户友好地分析高度复杂的代谢组谱数据，通过开发 用于复杂代谢组学混合物的光谱去卷积和定量的自动化工具 蛋白质核磁共振应用的协同效应，以及通过开发新的混合方法来桥接 代谢组学与其他Omics领域。拟议的研究将促进传播 代谢组学作为生物医学科学界的一种强大、多功能和可管理的工具 协同效应对蛋白质科学也有好处。这些活动有望带来更好的 从代谢物的角度理解广泛的生物学问题，以利于 人类健康。

PROJECT SUMMARY Advanced NMR, computational, and hybrid methods for metabolomics The emergence of metabolomics promises to revolutionize the understanding of biological systems from a metabolite perspective with important implications for the diagnosis and treatment of disease. Despite recent progress in the profiling and quantitation of complex metabolomics mixtures, such as urine, serum, and cancer tissue, by NMR and mass spectrometry, important methodological challenges remain. The proposed research program aims at addressing some of these urgent challenges by developing new approaches to integrate NMR with cheminformatics and mass spectrometry for the de novo characterization of unknown metabolites and their chemical and structural motifs, by developing and maintaining advanced webservers and metabolomics databases (COLMAR) for the reliable, efficient, and user-friendly analysis of highly complex metabolomics spectroscopic data, by developing automated tools for the spectral deconvolution and quantitation of complex metabolomics mixtures with synergies for protein NMR applications, and by developing new hybrid approaches to bridge metabolomics with other Omics fields. The proposed research will promote the dissemination of metabolomics as a powerful, versatile, and manageable tool to the biomedical scientific community with synergistic benefits also for protein science. These activities are expected to lead to a better understanding of a broad range of biological questions from a metabolite perspective for the benefit of human health.