Title：
A chemically derivatized in silico mass spectral library for fine-structure annotation of phosphoinositides
Authors：
98:11416-11427
Corresponding
Author：
Zhengjiu An, Ye Liu, Jian Ni, Jun Ding*
Pubyear：
2026
Title of
Journal：
Analytical Chemistry
Paper
Code：
Volume：
98
Number：
Page：
11416-11427
Others：
Classification：
Source：
Abstract：
Phosphoinositides (PIPx) are structurally complex lipids with essential roles in cellular signaling and disease. Their biological functions critically depend on subtle molecular characteristics, including headgroup identity, acyl-chain composition, and regioisomerism. However, comprehensive structural annotation of PIPx species by mass spectrometry remains challenging due to their intrinsically low abundance, extensive isomerism, and limited availability of reference spectra. Herein, we report a chemically derivatized in silico mass spectral library that enables the fine-structure annotation of PIPx. A chemical derivatization strategy using (4-(diazomethyl)phenyl)-N,N-dimethylmethanamine (DMPDA) markedly improves the liquid chromatographic behavior and ionization efficiency of PIPx species, resulting in up to a 10-fold increase in detection sensitivity. More importantly, the resulting DMPDA-PIPx derivatives exhibit reprogrammed fragmentation behavior in tandem mass spectrometry, generating diagnostic ions that differentiate phosphate positional isomers as well as acyl-chain composition and sn-positional variants. General fragmentation rules were established and applied to 1,736,028 simulated DMPDA-PIPx structures, yielding an in-depth in silico mass spectral library that spans millions of PIPx structures. Integration of chemical derivatization with in silico library-based spectral matching enables automated annotation of PIPx isomers that are indistinguishable using conventional MS/MS approaches. Application of this workflow to aging mouse tissues reveals pronounced organ-specific heterogeneity in PIPx profiles and distinct tissue-specific remodeling of PIPx isomers during aging.
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