Identifying the Unknowns: Fragmentation Trees and Molecular Fingerprints

从少量物质中快速识别小化合物在代谢组学、天然产物研究、生物标记物发现、环境研究和诊断学等生物学和医学领域具有重要意义。如今，质谱学(MS)是鉴定小分子的关键技术。在过去的几年里，MS数据的数量和复杂性一直在快速增长。这些数据的计算分析被认为是当今代谢组学和小分子研究的主要技术障碍之一。大约十年前，我的团队提出了碎裂树作为测量中的碎裂反应的模型，并开发了天狼星来计算这种碎裂树。大约五年前，我们开发了CSI：FingerID，用于使用串联MS数据在分子结构数据库中进行搜索，整合了碎片树以提高搜索性能。作为前一个资助期的一部分，我们开发了Canopus用于化合物类的全面分配而不需要结构说明，以及Zodiac用于在完整数据集中进行分子式分配。在第二个资助期，我们将进行四个不同的生物学案例研究，以展示我们的计算工具的能力和通用性；我们将继续将LC-MS/MS处理集成到天狼星中；我们将开发Epimetheus用于验证CSI：FingerID搜索结果；我们将对天狼星和CSI：FingerID进行深入评估；我们将完成从前一个资助期分离嵌合体光谱的工作；我们将使Zodiac更快、更好；最后，我们将开发一种基于网络的分子指纹校正方法，进一步提高CSI：FingerID的性能。

Rapid identification of small compounds from small amounts of substance is of interest in many areas of biology and medicine such as metabolomics, natural products research, biomarker discovery, environmental research and diagnostics. Today, mass spectrometry (MS) is a key technology for the identification of small molecules. Over the last years, the amount and complexity of MS data has been growing rapidly. Computational analysis of such data is presumed to be one of the major technological hurdles in metabolomics and small molecule research today.About a decade ago, my group proposed fragmentation trees as a model for the fragmentation reactions in the measurement, and developed SIRIUS to compute such fragmentation trees. About five years ago, we developed CSI:FingerID for searching in molecular structure databases using tandem MS data, integrating fragmentation trees to boost search performance. As part of the previous funding period, we developed CANOPUS of the comprehensive assignment of compound classes without the need for structural elucidation, and ZODIAC for molecular formula assignments in complete datasets. We released version 4 of SIRIUS, which was named "method to watch" by Nature Methods, and demonstrated the power of our methods in biological case studies.In the second funding period, we will perform four diverse biological case studies, to demonstrate the power and versatility of our computational tools; we will continue our integration of LC-MS/MS processing into SIRIUS; we will develop Epimetheus for the validation of CSI:FingerID search results; we will perform in-depth evaluations of SIRIUS and CSI:FingerID; we will complete our work on separating chimeric spectra from the previous funding period; we will make ZODIAC faster and better; and finally, we will develop a method for network-based correction of molecular fingerprints, to further boost CSI:FingerID's performance.