Analytical Sciences

Abstract − Analytical Sciences, 35(2), 201 (2019).

Chromatographic Retention Assisted Deconvolution of Liquid Chromatography–Mass Spectrometry Chromatogram of Natural Products
Qi CHANG,*1 Yun SHAO,*2 Yang YANG,*3 Han YU,*4 and Renqi WANG*1,*2,*3
*1 Gansu Institute for Drug Control, Lanzhou 730070, China
*2 Key Laboratory of Tibetan Medicine Research, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China
*3 College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou 730000, China
*4 School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
A chromatographic retention assisted denoising and peak picking algorithm (CRAD) is developed for preprocessing liquid chromatography–mass spectrometry (LC-MS) datasets of natural products. The retention behaviors of ions with the same m/z value are investigated under a series of elution conditions. The detected ions are identified as real compounds if their chromatographic retention behaviors fit well with the Snyder–Soczewinski model. Further, the ions with similar retention behaviors and isotope ratios are clustered. This method enables rapid identification of precursor ions when chemical standards or databases are unavailable. It also helps eliminate unexpected baseline disturbances and improve the resolution of LC-MS chromatograms. Unlike conventional deconvolution strategies, this method distinguishes the chemical properties of precursor ions through their dynamic retention behaviors. The algorithm is demonstrated with LC-MS datasets of control samples. In the application of such algorithms on a more complicated natural extract from Lycium ruthenicum Murr., 206 precursor ions were facilely determined.