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Start Over Author "Shuya Yoshida" Journal journal of chemical information and modeling
2 results on '"Shuya Yoshida"'

1. Automated Extraction of Information on Chemical–P-glycoprotein Interactions from the Literature

Author

Shuya Yoshida, Fumiyoshi Yamashita, Mitsuru Hashida, Atsushi Ose, Yuichi Sugiyama, and Kazuya Maeda

Subjects
ATP Binding Cassette Transporter, Subfamily B, Databases, Pharmaceutical, Computer science, General Chemical Engineering, Chemical nomenclature, Context (language use), Library and Information Sciences, Ligands, Substrate Specificity, Small Molecule Libraries, Drug Discovery, Cytochrome P-450 CYP3A, Data Mining, Humans, Natural Language Processing, Information retrieval, Recall, Drug discovery, Membrane Transport Proteins, General Chemistry, Databases, Bibliographic, Computer Science Applications, P-Glycoprotein Interactions, Cytochrome P-450 CYP3A Inhibitors, Clinical safety, Identification (biology), Databases, Chemical, Sentence
Abstract

Knowledge of the interactions between drugs and transporters is important for drug discovery and development as well as for the evaluation of their clinical safety. We recently developed a text-mining system for the automatic extraction of information on chemical-CYP3A4 interactions from the literature. This system is based on natural language processing and can extract chemical names and their interaction patterns according to sentence context. The present study aimed to extend this system to the extraction of information regarding chemical-transporter interactions. For this purpose, the key verb list designed for cytochrome P450 enzymes was replaced with that for known drug transporters. The performance of the system was then tested by examining the accuracy of information on chemical-P-glycoprotein (P-gp) interactions extracted from randomly selected PubMed abstracts. The system achieved 89.8% recall and 84.2% precision for the identification of chemical names and 71.7% recall and 78.6% precision for the extraction of chemical-P-gp interactions.

Published
2013
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2. Automated information extraction and structure-activity relationship analysis of cytochrome P450 substrates

Author

Fumiyoshi Yamashita, Chunlai Feng, Shuya Yoshida, Takayuki Itoh, and Mitsuru Hashida

Subjects
CYP2D6, Databases, Factual, Computer science, General Chemical Engineering, Speech recognition, Chemical nomenclature, Context (language use), Computational biology, Library and Information Sciences, computer.software_genre, Data modeling, Automation, Structure-Activity Relationship, Cytochrome P-450 Enzyme System, Cytochrome P-450 Enzyme Inhibitors, Data Mining, Humans, Enzyme Inhibitors, biology, Decision Trees, CYP1A2, Cytochrome P450, Reproducibility of Results, General Chemistry, Computer Science Applications, Isoenzymes, Information extraction, Enzyme Induction, biology.protein, computer, PubChem
Abstract

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.

Published
2011

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