Automated Extraction of Information on Chemical鈥揚-glycoprotein Interactions from the Literature

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• 作者：Shuya Yoshida ; Fumiyoshi Yamashita ; Atsushi Ose ; Kazuya Maeda ; Yuichi Sugiyama ; Mitsuru Hashida
• 刊名：Journal of Chemical Information and Modeling
• 出版年：2013
• 出版时间：October 28, 2013
• 年：2013
• 卷：53
• 期：10
• 页码：2506-2510
• 全文大小：189K
• 年卷期：v.53,no.10(October 28, 2013)
• ISSN：1549-960X

文摘

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鈥揅YP3A4 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鈥搕ransporter 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鈥揚-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鈥揚-gp interactions.