ISiCLE：分子碰撞截面计算管道，用于建立用于化合物鉴定的大型计算机参考库
ISiCLE: A molecular collision cross section calculation pipeline for establishing large in silico reference libraries for compound identification
摘要：
对复杂样品中的代谢物和其他化学物质进行全面和可靠的鉴定，将彻底改变我们对这些化学多样性分子在生物系统中所起作用的理解。尽管最近取得了进展，代谢组学研究仍然导致检测到不成比例的特征数量，而不能确信地分配给化学结构。这种不足是由代谢组学中最重要的一个限制所驱动的：依赖于通过分析真实的参考化学品构建的参考库。为此，我们开发了计算机化学库引擎（ISiCLE），这是一种用于生成化学性质库的高性能计算友好型化学信息学工作流程。在这里描述的实例中，我们预测可能的三维分子构象使用化学标识符作为输入，从碰撞截面（CCS）派生。该方法采用最先进的第一原理模拟，其特点是使用分子动力学、量子化学和离子迁移率计算来生成结构和库，所有这些都没有训练数据。重要的是，ISiCLE的优化包括对流行的MOBCAL代码进行重构，用于基于概率的迁移率计算，将其计算效率提高了两个数量级以上。计算的CCS值与1，983个实验测量的CCS值进行了验证，并与先前报告的CCS计算方法进行了比较。建立了一个在线数据库，分享计算的和实验的CCS值（metabolomics.pnnl.gov），最初包括一个有100多万条目的CCS图书馆。最后，三个成功的应用程序的分子表征使用计算CCS的描述。这项工作代表了一种很有前途的方法，以解决小分子鉴定的局限性。
英文摘要：
Comprehensive and confident identifications of metabolites and other chemicals in complex samples will revolutionize our understanding of the role these chemically diverse molecules play in biological systems. Despite recent advances, metabolomics studies still result in the detection of a disproportionate number of features than cannot be confidently assigned to a chemical structure. This inadequacy is driven by the single most significant limitation in metabolomics: the reliance on reference libraries constructed by analysis of authentic reference chemicals. To this end, we have developed the in silico chemical library engine (ISiCLE), a high-performance computing-friendly cheminformatics workflow for generating libraries of chemical properties. In the instantiation described here, we predict probable three-dimensional molecular conformers using chemical identifiers as input, from which collision cross sections (CCS) are derived. The approach employs state-of-the-art first-principles simulation, distinguished by use of molecular dynamics, quantum chemistry, and ion mobility calculations to generate structures and libraries, all without training data. Importantly, optimization of ISiCLE included a refactoring of the popular MOBCAL code for trajectory-based mobility calculations, improving its computational efficiency by over two orders of magnitude. Calculated CCS values were validated against 1,983 experimentally-measured CCS values and compared to previously reported CCS calculation approaches. An online database is introduced for sharing both calculated and experimental CCS values (metabolomics.pnnl.gov), initially including a CCS library with over 1 million entries. Finally, three successful applications of molecule characterization using calculated CCS are described. This work represents a promising method to address the limitations of small molecule identification.
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