超高效液相色谱-串联质谱法测定鸡肉中4种蛋白酶抑制剂

建立了鸡肉中4种蛋白酶抑制剂（沙奎那韦、利托那韦、奈非那韦、茚地那韦）的超高效液相色谱-串联质谱（UPLC-MS/MS）检测方法。样品经30%（v/v）乙腈水溶液（含1%（v/v）三氯乙酸）振荡提取、混合型阳离子交换MCX柱净化,采用Luna^® C8色谱柱（150 mm×2 mm,3 μm）,以0.2%（v/v）甲酸水溶液（含5 mmol/L乙酸铵）和乙腈为流动相进行梯度洗脱,采用电喷雾电离（ESI⁺）源和多反应监测（MRM）模式检测。结果表明,在0.1~20.0 μg/L范围内,4种目标化合物呈良好的线性关系,相关系数（r²）大于0.99,方法的定量限（S/N=10）为0.20~0.90 μg/kg;鸡肉组织中4种目标化合物在1.0、2.0和10.0 μg/kg 3个水平下的平均加标回收率为69.0%~106.0%,日内和日间相对标准偏差（RSD）为2.2%~13.8%（n=6）和3.6%~14.6%（n=3）。该法简单、高效、灵敏、准确,可用于鸡肉中沙奎那韦、利托那韦、奈非那韦、茚地那韦残留量的测定。     

An integrated method for metabolite detection and identification using a linear ion trap/Orbitrap mass spectrometer and multiple data processing techniques: application to indinavir metabolite detection

A new strategy using a hybrid linear ion trap/Orbitrap mass spectrometer and multiple post-acquisition data mining techniques was evaluated and applied to the detection and characterization of in vitro metabolites of indinavir. Accurate-mass, full-scan MS and MS/MS data sets were acquired with a generic data-dependent method and processed with extracted-ion chromatography (EIC), mass-defect filter (MDF), product-ion filter (PIF), and neutral-loss filter (NLF) techniques. The high-resolution EIC process was shown to be highly effective in the detection of common metabolites with predicted molecular weights. The MDF process, which searched for metabolites based on the similarity of mass defects of metabolites to those of indinavir and its core substructures, was able to find uncommon metabolites not detected by the EIC processing. The high-resolution PIF and NLF processes selectively detected metabolites that underwent fragmentation pathways similar to those of indinavir or its known metabolites. As a result, a total of 15 metabolites including two new indinavir metabolites were detected and characterized in a rat liver S9 incubation sample. Overall, these data mining techniques, which employed distinct metabolite search mechanisms, were complementary and effective in detecting both common and uncommon metabolites. In summary, the results demonstrated that this analytical strategy enables the high-throughput acquisition of accurate-mass LC/MS data sets, comprehensive search of a variety of metabolites through the post-acquisition processes, and effective structural characterization based on elemental compositions of metabolite molecules and their product ions.