FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, North Carolina, USA.
Drug Discovery Science and Technology, AbbVie Inc., North Chicago, Illinois, USA.
J Mass Spectrom. 2022 Jun;57(6):e4869. doi: 10.1002/jms.4869.
Mass spectrometry (MS) is an effective analytical tool for high-throughput screening (HTS) in the drug discovery field. Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) MS is a high-throughput platform that has achieved analysis times of sub-seconds-per-sample. Due to the high-throughput analysis speed, methods are needed to increase the analyte signal while decreasing the variability in IR-MALDESI-MS analyses to improve data quality and reduce false-positive hits. The Z-factor is used as a statistic of assay quality that can be improved by reducing the variation of target ion abundances or increasing signal. Herein we report optimal solvent compositions for increasing measured analyte abundances with direct analysis by IR-MALDESI-MS. We also evaluate normalization strategies, such as adding a normalization standard that is similar or dissimilar in structure to the model target drug, to reduce the variability of measured analyte abundances with direct analyses by IR-MALDESI-MS in both positive and negative ionization modes.
质谱(MS)是药物发现领域高通量筛选(HTS)的有效分析工具。红外基质辅助激光解吸电喷雾电离(IR-MALDESI)MS 是一种高通量平台,已经实现了亚秒级/样本的分析时间。由于高通量分析速度,需要有方法来增加分析物信号,同时降低 IR-MALDESI-MS 分析中的变异性,以提高数据质量并减少假阳性命中。Z 因子可用作分析质量的统计量,可以通过减少目标离子丰度的变化或增加信号来提高。在此,我们报告了通过 IR-MALDESI-MS 直接分析来增加测量分析物丰度的最佳溶剂组成。我们还评估了归一化策略,例如添加与模型靶药物在结构上相似或不同的归一化标准,以降低正负离子模式下通过 IR-MALDESI-MS 直接分析测量分析物丰度的变异性。