Abstract
Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) experiments require a suitable match of the matrix and target compounds to achieve a selective and sensitive analysis. However, it is still difficult to predict which metabolites are ionizable with a given matrix and which factors lead to an efficient ionization. In the present study, we extracted structural properties of metabolites that contribute to their ionization in MALDI-MS analyses exploiting our experimental data set. The MALDI-MS experiment was performed for 200 standard metabolites using 9-aminoacridine (9-AA) as the matrix. We then developed a prediction model for the ionization profiles (both the ionizability and ionization efficiency) of metabolites using a quantitative structure-property relationship (QSPR) approach. The classification model for the ionizability achieved a 91 % accuracy, and the regression model for the ionization efficiency reached a rank correlation coefficient of 0.77. An analysis of the descriptors contributing to such model construction suggested that the proton affinity is a major determinant of the ionization, whereas some substructures hinder efficient ionization. This study will lead to the development of more rational and predictable MALDI-MS analyses.
| Original language | English |
|---|---|
| Pages (from-to) | 1-5 |
| Number of pages | 5 |
| Journal | Journal of the American Society for Mass Spectrometry |
| Volume | 25 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 1 2014 |
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All Science Journal Classification (ASJC) codes
- Structural Biology
- Spectroscopy
Cite this
MALDI efficiency of metabolites quantitatively associated with their structural properties : A quantitative structure-property relationship (QSPR) approach. / Yukihira, Daichi; Miura, Daisuke; Fujimura, Yoshinori; Umemura, Yoshikatsu; Yamaguchi, Shinichi; Funatsu, Shinji; Yamazaki, Makoto; Ohta, Tetsuya; Inoue, Hiroaki; Shindo, Mitsuru; Wariishi, Hiroyuki.
In: Journal of the American Society for Mass Spectrometry, Vol. 25, No. 1, 01.01.2014, p. 1-5.Research output: Contribution to journal › Article
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TY - JOUR
T1 - MALDI efficiency of metabolites quantitatively associated with their structural properties
T2 - A quantitative structure-property relationship (QSPR) approach
AU - Yukihira, Daichi
AU - Miura, Daisuke
AU - Fujimura, Yoshinori
AU - Umemura, Yoshikatsu
AU - Yamaguchi, Shinichi
AU - Funatsu, Shinji
AU - Yamazaki, Makoto
AU - Ohta, Tetsuya
AU - Inoue, Hiroaki
AU - Shindo, Mitsuru
AU - Wariishi, Hiroyuki
PY - 2014/1/1
Y1 - 2014/1/1
N2 - Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) experiments require a suitable match of the matrix and target compounds to achieve a selective and sensitive analysis. However, it is still difficult to predict which metabolites are ionizable with a given matrix and which factors lead to an efficient ionization. In the present study, we extracted structural properties of metabolites that contribute to their ionization in MALDI-MS analyses exploiting our experimental data set. The MALDI-MS experiment was performed for 200 standard metabolites using 9-aminoacridine (9-AA) as the matrix. We then developed a prediction model for the ionization profiles (both the ionizability and ionization efficiency) of metabolites using a quantitative structure-property relationship (QSPR) approach. The classification model for the ionizability achieved a 91 % accuracy, and the regression model for the ionization efficiency reached a rank correlation coefficient of 0.77. An analysis of the descriptors contributing to such model construction suggested that the proton affinity is a major determinant of the ionization, whereas some substructures hinder efficient ionization. This study will lead to the development of more rational and predictable MALDI-MS analyses.
AB - Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) experiments require a suitable match of the matrix and target compounds to achieve a selective and sensitive analysis. However, it is still difficult to predict which metabolites are ionizable with a given matrix and which factors lead to an efficient ionization. In the present study, we extracted structural properties of metabolites that contribute to their ionization in MALDI-MS analyses exploiting our experimental data set. The MALDI-MS experiment was performed for 200 standard metabolites using 9-aminoacridine (9-AA) as the matrix. We then developed a prediction model for the ionization profiles (both the ionizability and ionization efficiency) of metabolites using a quantitative structure-property relationship (QSPR) approach. The classification model for the ionizability achieved a 91 % accuracy, and the regression model for the ionization efficiency reached a rank correlation coefficient of 0.77. An analysis of the descriptors contributing to such model construction suggested that the proton affinity is a major determinant of the ionization, whereas some substructures hinder efficient ionization. This study will lead to the development of more rational and predictable MALDI-MS analyses.
UR - http://www.scopus.com/inward/record.url?scp=84892661318&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84892661318&partnerID=8YFLogxK
U2 - 10.1007/s13361-013-0772-0
DO - 10.1007/s13361-013-0772-0
M3 - Article
C2 - 24249043
AN - SCOPUS:84892661318
VL - 25
SP - 1
EP - 5
JO - Journal of the American Society for Mass Spectrometry
JF - Journal of the American Society for Mass Spectrometry
SN - 1044-0305
IS - 1
ER -