Fuzzy-precise positioning: A pre-search algorithm based on feature peaks of mass spectra for acceleration of chemical compound recognition

摘要

A mass spectral library pre-search algorithm, fuzzy-precise positioning (FPP), is described for rapid and accurate identification of chemical compound. This algorithm works on the basis of the molecular ion feature peaks and fragment ion feature peaks of mass spectra. The algorithm mainly includes three stages: feature peaks selection, fuzzy positioning and precise positioning. For query spectra and reference spectra, four molecular ion feature peaks and six fragment ion feature peaks are selected and their corresponding mass-to-charge ratio (m/z) values are recorded, respectively. After that, fuzzy positioning is conducted to skip some unrelated spectra in the reference library by comparing maximum and minimum m/z values of feature peaks of query spectra with those of reference spectra. Finally, in the precise positioning stage, ten m/z values of feature peaks of the query spectra are matched with those of remaining reference spectra one by one. If the matching number is larger than five, this reference spectrum can be remained as a candidate spectrum. After traversing all the reference spectra remained after fuzzy positioning, final pre-search results can be obtained. To evaluate the performace of the the proposed algorithm, a series of experiments are designed by using main library and replicate library of NIST11 as reference library and query library, respectively. Moreover, real application data are used to verify the performance of FPP method. Compared to two-step spectral library pre-search (TSLP) algorithm and ten-peakmethod, the results show that FPP method can obtain higher accuracy, smaller pre-search space, shorter time consumption and less remaining spectra. (C) 2019 Elsevier B.V. All rights reserved.