Automated information extraction and structure-activity relationship analysis of cytochrome P450 substrates.
Information on CYP-chemical interactions was comprehensively explored by a text-mining technique, to confirm our previous structure-activity relationship model for CYP substrates (Yamashita et al. J. Chem. Inf. Model. 2008, 48, 364-369). The text-mining technique is based on natural language processing and can extract chemical names and their interaction patterns according to sentence context. After chemicals were automatically extracted and classified into CYP substrates, inhibitors, and inducers, 709 substrates were retrieved from the PubChem database and categorized as 216, 145, 136, 217, 156, and 379 substrates for CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4, respectively. Although the previous classification model was developed using data from only 161 compounds, the model classified the substrates found by text-mining analysis with reasonable accuracy. This confirmed the validity of both the multi-objective classification model for CYP substrates and the text-mining procedure.
Graduate School of Pharmaceutical Sciences, Kyoto University, Sakyo-ku, Kyoto, Japan. yama@pharm.kyoto-u.ac.jp
Fumiyoshi
F
Yamashita
Chunlai
C
Feng
Shuya
S
Yoshida
Takayuki
T
Itoh
Mitsuru
M
Hashida
D001331:Automation; D065607:Cytochrome P-450 Enzyme Inhibitors; D003577:Cytochrome P-450 Enzyme System / Q000096:biosynthesis / Q000378:metabolism*; D057225:Data Mining / Q000379:methods*; D016208:Databases, Factual; D003663:Decision Trees; D004790:Enzyme Induction / Q000187:drug effects; D004791:Enzyme Inhibitors / Q000494:pharmacology; D006801:Humans; D007527:Isoenzymes / Q000037:antagonists & inhibitors / Q000096:biosynthesis / Q000378:metabolism; D015203:Reproducibility of Results; D013329:Structure-Activity Relationship
D065607:Cytochrome P-450 Enzyme Inhibitors; D004791:Enzyme Inhibitors; D007527:Isoenzymes; D003577:Cytochrome P-450 Enzyme System