Prediction of biodegradability from chemical structure: Modeling of ready biodegradation test data

• Published in: Environmental toxicology and chemistry 1999-08, Vol.18 (8), p.1763-1768
• Main Authors: Loonen, Hélène, Lindgren, Fredrik, Hansen, Bjørn, Karcher, Walter, Niemelä, Jay, Hiromatsu, Koichi, Takatsuki, Mineo, Peijnenburg, Willie, Rorije, Emiel, Struijś, Jaap
• Format: Article
• Language: English
• Subjects: Applied sciences; Biodegradation; Biodegradation of pollutants; Biological and medical sciences; Biotechnology; Environment and pollution; European Union; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; Global environmental pollution; Industrial applications and implications. Economical aspects; Multivariate analysis; Pollution; Prediction; Structural fragments
• ISSN: 0730-7268; 1552-8618
• DOI: 10.1002/etc.5620180822

Biodegradation data were collected and evaluated for 894 substances with widely varying chemical structures. All data were determined according to the Japanese Ministry of International Trade and Industry (MITI) I test protocol. The MITI I test is a screening test for ready biodegradability and has been described by Organization for Economic Cooperation and Development (OECD) test guideline 301 C and European Union (EU) test guideline C4F. The chemicals were characterized by a set of 127 predefined structural fragments. This data set was used to develop a model for the prediction of the biodegradability of chemicals under standardized OECD and EU ready biodegradation test conditions. Partial least squares (PLS) discriminant analysis was used for the model development. The model was evaluated by means of internal cross‐validation and repeated external validation. The importance of various structural fragments and fragment interactions was investigated. The most important fragments include the presence of a long alkyl chain; hydroxy, ester, and acid groups (enhancing biodegradation); and the presence of one or more aromatic rings and halogen substituents (retarding biodegradation). More than 85% of the model predictions were correct for using the complete data set. The not readily biodegradable predictions were slightly better than the readily biodegradable predictions (86 vs 84%). The average percentage of correct predictions from four external validation studies was 83%. Model optimization by including fragment interactions improved the model predicting capabilities to 89%. It can be concluded that the PLS model provides predictions of high reliability for a diverse range of chemical structures. The predictions conform to the concept of readily biodegradable (or not readily biodegradable) as defined by OECD and EU test guidelines.