A quantitative structure-biodegradation relationship (QSBR) approach to predict biodegradation rates of aromatic chemicals

Kishor Acharya*, David Werner, Jan Dolfing, Maciej Barycki, Paola Meynet, Wojciech Mrozik, Oladapo Komolafe, Tomasz Puzyn, Russell J. Davenport

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
1 Downloads (Pure)

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.

Original languageEnglish
Pages (from-to)181-190
Number of pages10
JournalWater Research
Volume157
DOIs
Publication statusPublished - 15 Jun 2019
Externally publishedYes

Fingerprint Dive into the research topics of 'A quantitative structure-biodegradation relationship (QSBR) approach to predict biodegradation rates of aromatic chemicals'. Together they form a unique fingerprint.

Cite this