Auerbach David, Aspenleiter Julia, Volmer Dietrich A
Institute of Bioanalytical Chemistry, Saarland University, Saarbrücken, Germany.
J Am Soc Mass Spectrom. 2014 Sep;25(9):1610-21. doi: 10.1007/s13361-014-0934-8. Epub 2014 Jun 14.
Differential ion mobility spectrometry (DMS) coupled to mass spectrometry is increasingly used in both quantitative analyses of biological samples and as a means of removing background interferences for enhanced selectivity and improved quality of mass spectra. However, DMS separation efficiency using dry inert gases often lacks the required selectivity to achieve baseline separation. Polar gas-phase modifiers such as alcohols are therefore frequently employed to improve selectivity via clustering/declustering processes. The choice of an optimal modifier currently relies on trial and error experiments, making method development a tedious activity. It was the goal of this study to establish a means of CV prediction for compounds using a homologous series of alcohols as gas-phase modifiers. This prediction was based on linear regression of compensation voltages of two calibration runs for the alcohols with the lowest and the highest molecular weights and readily available descriptors such as proton affinity and gas phase acidity of the modifier molecules. All experiments were performed on a commercial quadrupole linear ion trap mass spectrometer equipped with a DMS device between electrospray ionization source and entrance quadrupole lens. We evaluated our approach using a homologous series of 4-alkylbenzoic acids and a selection of 23 small molecules of high chemical diversity. Predicted CV values typically deviated from the experimentally determined values by less than 0.5 V. Several test compounds changed their ion mobility behavior for the investigated gas phase modifiers (e.g., from type B to type A) and thus could thus not be evaluated.
差分离子迁移谱(DMS)与质谱联用,越来越多地用于生物样品的定量分析,并作为一种去除背景干扰的手段,以提高选择性和质谱质量。然而,使用干燥惰性气体的DMS分离效率往往缺乏实现基线分离所需的选择性。因此,经常使用极性气相改性剂(如醇类),通过聚类/解聚过程提高选择性。目前,最佳改性剂的选择依赖于反复试验,这使得方法开发变得繁琐。本研究的目的是建立一种使用一系列同系醇作为气相改性剂来预测化合物补偿电压(CV)的方法。该预测基于对分子量最低和最高的两种醇的校准运行补偿电压与改性剂分子的质子亲和性和气相酸度等易于获得的描述符进行线性回归。所有实验均在一台商业四极杆线性离子阱质谱仪上进行,该质谱仪在电喷雾电离源和入口四极杆透镜之间配备了DMS装置。我们使用一系列同系的4-烷基苯甲酸和23种具有高化学多样性的小分子对我们的方法进行了评估。预测的CV值通常与实验测定值的偏差小于0.5V。几种测试化合物在所研究的气相改性剂作用下改变了它们的离子迁移行为(例如,从B型变为A型),因此无法进行评估。