Optimization and Validation of High-Resolution Mass Spectrometry Data Analysis Parameters
Optimization and Validation of High-Resolution Mass Spectrometry Data Analysis Parameters
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DOI：
10.1093/jat/bkw112
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发表时间：
2017-01-01
影响因子：
2.5
通讯作者：
Lynch, Kara L.
中科院分区：
文献类型：
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作者：
Colby, Jennifer M.;Thoren, Katie L.;Lynch, Kara L.
高分辨率质谱（HRMS）已被公认为在各种生物基质中进行综合药物筛选的有价值的工具。HRMS仪器收集非目标的、准确的质量数据，允许在单个分析运行中识别已知和未知化合物。实施HRMS药物筛选的最具挑战性的方面之一是建立用于识别化合物的适当数据分析参数。与其他类型的质谱数据不同，尚未建立HRMS数据分析和可接受性标准的指南。尽管许多实验室已经发表了关于HRMS用于药物筛选的实用性的文章，但很少有实验室包括关于他们如何确定允许误差和设置阳性标准的细节。在此之前，我们开发并验证了一个全面的169化合物药物筛选的高分辨率四极杆飞行时间质谱仪。在这里，我们报告的详细程序，我们用来确定适当的阳性标准，我们的筛选程序。我们的方法是经验性的;我们收集数据，并使用常用软件进行分析。我们发现，使用阈值为70的组合评分方法，其中70%的权重给予文库匹配，10%的权重给予质量误差、保留时间误差和同位素模式差异中的每一个，提供了99.2%的最佳药物鉴定效率。我们的研究结果表明，在准确识别化合物的库匹配的重要性，并强调了强大的产品离子光谱，包含信息的谱系，质量和相对丰度的片段的效用。我们描述的方法很容易适应，包括替代参数，可能是在与各种HRMS平台相关的软件。通过仔细选择误差限和阳性标准，HRMS仪器能够产生高质量、高置信度的结果，从而减少对确证性检测的需求。
High-resolution mass spectrometry (HRMS) has gained recognition as a valuable tool for comprehensive drug screening in a variety of biological matrices. HRMS instruments collect untargeted, accurate mass data, which permit identification of known and unknown compounds in a single analytical run. One of the most challenging aspects of implementing an HRMS drug screen is establishing appropriate data analysis parameters for identifying compounds. Unlike other types of mass spectrometry data, guidelines for HRMS data analysis and acceptability criteria have not been established. Although many laboratories have published on the utility of HRMS for drug screening, few have included details on how they determined allowable errors and set positivity criteria. Previously, we developed and validated a comprehensive 169-compound drug screen on a high-resolution quadrupole time of flight mass spectrometer. Here we report the detailed procedure that we used to determine appropriate positivity criteria for our screening procedure. Our approach was empirical; we collected data and analyzed it with commonly available software. We found that a combined scoring approach using a threshold of 70, with 70% weight given to library match and 10% weight given to each of mass error, retention time error and isotope pattern difference provided optimum drug identification efficiency of 99.2%. Our results demonstrate the importance of library matching in accurately identifying compounds, and underscore the utility of robust product ion spectra that contain information on the lineage, mass and relative abundance of fragments. The method we describe is easily adaptable to include alternative parameters that may be available in software associated with a variety of HRMS platforms. With careful selection of error limits and positivity criteria, HRMS instruments are capable of producing high-quality, high-confidence results that may reduce the need for confirmatory testing.