Methodology

Automated extraction of chemical structure information from digital raster images

Jungkap Park^1,2 , Gus R Rosania^1,3 , Kerby A Shedden^1,4 , Mandee Nguyen³ , Naesung Lyu⁵ and Kazuhiro Saitou^1,2

¹  Michigan Alliance for Cheminformatic Exploration

²  Department of Mechanical Engineering, the University of Michigan, 2350 Hayward Street, Ann Arbor, MI 48109, USA

³  Department of Pharmaceutical Sciences, the University of Michigan College of Pharmacy, 428 Church Street, Ann Arbor, MI 48109, USA

⁴  Department of Statistics, the University of Michigan, 1085 South University, Ann Arbor, MI 48109, USA

⁵  Ford Motor Company, 3104B, Advanced Engineering Center, 2400 Village Rd., Dearborn, MI 48121, USA

author email corresponding author email

Chemistry Central Journal 2009, 3:4doi:10.1186/1752-153X-3-4

Published:	5 February 2009

Abstract

Background

To search for chemical structures in research articles, diagrams or text representing molecules need to be translated to a standard chemical file format compatible with cheminformatic search engines. Nevertheless, chemical information contained in research articles is often referenced as analog diagrams of chemical structures embedded in digital raster images. To automate analog-to-digital conversion of chemical structure diagrams in scientific research articles, several software systems have been developed. But their algorithmic performance and utility in cheminformatic research have not been investigated.

Results

This paper aims to provide critical reviews for these systems and also report our recent development of ChemReader – a fully automated tool for extracting chemical structure diagrams in research articles and converting them into standard, searchable chemical file formats. Basic algorithms for recognizing lines and letters representing bonds and atoms in chemical structure diagrams can be independently run in sequence from a graphical user interface-and the algorithm parameters can be readily changed-to facilitate additional development specifically tailored to a chemical database annotation scheme. Compared with existing software programs such as OSRA, Kekule, and CLiDE, our results indicate that ChemReader outperforms other software systems on several sets of sample images from diverse sources in terms of the rate of correct outputs and the accuracy on extracting molecular substructure patterns.

Conclusion

The availability of ChemReader as a cheminformatic tool for extracting chemical structure information from digital raster images allows research and development groups to enrich their chemical structure databases by annotating the entries with published research articles. Based on its stable performance and high accuracy, ChemReader may be sufficiently accurate for annotating the chemical database with links to scientific research articles.