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\begin{document}$$HSO^{ - }_{4}$$\end{document} 6 14 15 1 1 6 14 1 Fig. 1 a b c d e f g  1 1 16 17 18 5 1 19 31 20 21 24 19 22 23 32 21 25 31 m/z \documentclass[12pt]{minimal}
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$$\end{document} 25 26 In order to facilitate the identification of sulfation sites in pharmaceuticals, we developed a mass spectrometry-based protocol that differentiates between the biologically relevant sulfation sites. After completing the studies on several classes of sulfated products, a set of rules was developed to predict the sulfation sites. With these prediction rules, structural feature of sulfation sites can be determined by detecting MS/MS fragmentation pathways of their corresponding sulfated products. With the structural information of sulfation sites, the two key different biological effects of sulfation, “detoxification” and “bioactivation”, can be differentiated, based on literature precedence that links the type of sulfation to its biological fate. Based on that information, relevant properties of sulfated products can be estimated. Experimental Reagents N N N N N N N N N Sulfation of benzylic, allylic alcohols and tertiary hydroxylamines 33 3 2 Sulfation of secondary hydroxylamines 3 Sample pretreatment −4 2 2 2 Mass spectrometry Results and discussion 2 11 15 1 m/z m/z m/z m/z m/z m/z m/z m/z m/z 3 Fig. 2 a b 3 c d e  Fig. 3 a b 3 c d e f g  Table 1 Characteristic fragmentation of selected sulfated products Group No. Chemical name Abundance of characteristic ions in MS/MS (%) m/z - m/z m/z m/z a 1 4-nitrocatechol sulfate a – – –  2 L-ascorbic acid 2-sulfate a – – –  3 Indoxyl sulfate a 52 – –  4 4-nitrophenyl sulfate a – – –  5 β-estradiol 3-sulfate a – – –  6 5-Br-4-Cl-3-indolyl sulfate a 59 – –  7 4-methylumbelliferyl sulfate a – – – b 8 2-aminoethyl hydrogen sulfate  – 100 18 a  9 Poly (vinyl sulfate) – – – a  10 D-glucose 6-sulfate – – – a  11 Chondroitin disaccharide Δdi-6S  – – – a  12 N-acetylglucosamine 6-sulfate – – – a c 13 2-naphthalenemethanol, α-methyl- sulfate – 6.7 a 100  14 Benzyl sulfate – 16 a –  15 (R)-1-phenyl-2-propen-1-sulfate – 26 a 12  16 4-Cl-2-methylbenzyl sulfate – – a 95  17 3-ethoxybenzyl sulfate – 100 a 6.4  18 2-ethoxybenzyl sulfate – 100 a 8.5  19 4-ethoxybenzyl sulfate – 100 a 8.7  20 crotyl sulfate – 55 a 50  21 furfuryl sulfate – – a 39 d 22 N-methyl-hydroxylamine-O-sulfonic acid – 100 a 9.2  23 N-isopropyl- hydroxylamine-O-sulfonic acid – 68 a 5.1  24 N-cyclohexyl-hydroxylamine-O-Sulfonic acid – 27 a 11  25 N,N-diethyl-hydroxylamine-O-sulfonic acid – 92 a 19  26 N-benzoyl-N-phenyl-hydroxylamine-O-sulfonic acid – – a – e 27 N-cyclohexylsulfamic acid – a – –  28 4-methylphenyl-Sulfamic acid – a – –  29 3-hydroxypropyl-sulfamic acid – a – –  30 D-glucosamine 2-sulfate – a – –  31 butyl-sulfamic acid – a – –  32 (R)(+)-α-phenethylsulfamic acid – a – – *A threshold of 5.0% is used for the relative abundance of characteristic ions. The long dash (–) means that the characteristic ion can not be detected or the relative abundance is below 5.0% a Group a: sulfated aromatic alcohols or enols 2 m/z 3 3 1 33 Scheme 1 3  3 m/z 3 m/z 33 2 Scheme 2 m/z  3 3 m/z m/z Group c: sulfated benzylic or allylic alcohols m/z 3 3 33 Scheme 3 m/z  m/z m/z m/z 3 3 m/z 3 m/z 4 m/z 2 Scheme 4 m/z  Group d: sulfated hydroxylamines m/z 3 m/z 3 3 34 5 Scheme 5 m/z  m/z 6 m/z Scheme 6 m/z  Group e: sulfated amines m/z 3 3 34 m/z 7 m/z Scheme 7 m/z  Prediction rules 1 m/z m/z m/z 2 m/z m/z m/z 3 3 m/z − m/z m/z m/z 3 m/z 6 1 Potential application of the prediction rules in characterizing unknown sulfated metabolites 5 6 8 14 m/z 4 3 m/z 6 m/z Fig. 4 The method for characterizing unknown sulfated metabolites  Conclusion A method was developed to determine the structural features of sulfation sites, by detecting the characteristic fragmentation pathway of the corresponding sulfated products in (-) ESI-MS/MS. By summarizing MS/MS data from five different types of sulfated products originating from different sulfation sites, their characteristic fragmentation pathways and characteristic ions were determined. Based on this information, a set of prediction rules was developed to transfer information about the fragmentation pathway of sulfated products to the structural features of the sulfation site. As a result, the proposed prediction rules can be applied in drug metabolite profiling to characterize sulfation sites, to further estimate the biological effect of sulfation, and to evaluate relevant properties of sulfated metabolites.