Abstract
The objective of this work was to develop a QSBR model for the prioritization of organic pollutants based on biodegradation rates from a database containing globally harmonized biodegradation tests using relevant molecular descriptors. To do this, we first categorized the chemicals into three groups (Group 1: simple aromatic chemicals with a single ring, Group 2: aromatic chemicals with multiple rings and Group3: Group 1 plus Group 2) based on molecular descriptors, estimated the first order biodegradation rate of the chemicals using rating values derived from the BIOWIN3 model, and finally developed, validated and defined the applicability domain of models for each group using a multiple linear regression approach. All the developed QSBR models complied with OECD principles for QSAR validation. The biodegradation rate in the models for the two groups (Group 2 and 3 chemicals) are associated with abstract molecular descriptors that provide little relevant practical information towards understanding the relationship between chemical structure and biodegradation rates. However, molecular descriptors associated with the QSBR model for Group 1 chemicals (R2 = 0.89, Q2loo = 0.87) provided information on properties that can readily be scrutinised and interpreted in relation to biodegradation processes. In combination, these results lead to the conclusion that QSBRs can be an alternative tool to estimate the persistence of chemicals, some of which can provide further insights into those factors affecting biodegradation.
Highlights
Microbial degradation is one of the important processes that determine the fate of anthropogenic chemicals in the environment
Each chemical was characterized by 4897 molecular descriptors. 4885 descriptors were computed by DRAGON software, used world-wide for the calculation of molecular descriptors [Version 6.0e2014, (Dragon)]
Another 12 descriptors; physio-chemical descriptors (7 descriptors) (Pitter and Chudoba, 1990; Saterbak et al, 2007; Ballabio et al, 2009; Lee and von Gunten, 2012) and quantum-chemical descriptors (5 descriptors) (Stewart, 2007) were obtained from online sources or computed with quantum mechanical method on optimized structure, respectively [Tables SIe6]
Summary
Microbial degradation is one of the important processes that determine the fate of anthropogenic chemicals in the environment. To date only 4214 of the estimated 145,297 chemicals (pre-registered unique substances under EU REACH legislation; ECHA, 2017, Accessed Date: 23/06/ 2017) (ECHA, 2017) have been reliably screened for their biodegradability (OECD, 2017). Performing such tests for the remaining existing and new chemicals is a laborious, costly and perhaps unachievable task. An ability to reliably predict biodegradation rates would help to accelerate and improve hazard and environmental risk assessment of chemicals, while reducing time, monetary cost and potentially unnecessary animal testing requirements (Pavan and Worth, 2008; Rücker and Kümmerer, 2012; Martin et al, 2017a)
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