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

Biodegradation rates Molecular descriptors QSBR Quantitative structure activity relationships

Journal

Water research
ISSN: 1879-2448
Titre abrégé: Water Res
Pays: England
ID NLM: 0105072

Informations de publication

Date de publication:
15 Jun 2019
Historique:
received: 19 11 2018
revised: 21 03 2019
accepted: 27 03 2019
pubmed: 7 4 2019
medline: 2 11 2019
entrez: 7 4 2019
Statut: ppublish

Résumé

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 (R

Identifiants

pubmed: 30953853
pii: S0043-1354(19)30287-8
doi: 10.1016/j.watres.2019.03.086
pii:
doi:

Substances chimiques

Environmental Pollutants 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

181-190

Informations de copyright

Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.

Auteurs

Kishor Acharya (K)

School of Engineering, Cassie Building, Newcastle University, Newcastle Upon Tyne, NE1 7RU, United Kingdom. Electronic address: kishor.acharya@ncl.ac.uk.

David Werner (D)

School of Engineering, Cassie Building, Newcastle University, Newcastle Upon Tyne, NE1 7RU, United Kingdom.

Jan Dolfing (J)

School of Engineering, Cassie Building, Newcastle University, Newcastle Upon Tyne, NE1 7RU, United Kingdom.

Maciej Barycki (M)

Laboratory of Environmental Chemometrics, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland.

Paola Meynet (P)

School of Engineering, Cassie Building, Newcastle University, Newcastle Upon Tyne, NE1 7RU, United Kingdom.

Wojciech Mrozik (W)

School of Engineering, Cassie Building, Newcastle University, Newcastle Upon Tyne, NE1 7RU, United Kingdom.

Oladapo Komolafe (O)

School of Engineering, Cassie Building, Newcastle University, Newcastle Upon Tyne, NE1 7RU, United Kingdom.

Tomasz Puzyn (T)

Laboratory of Environmental Chemometrics, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland.

Russell J Davenport (RJ)

School of Engineering, Cassie Building, Newcastle University, Newcastle Upon Tyne, NE1 7RU, United Kingdom.

Articles similaires

Alzheimer Disease Humans Regression Analysis Quantitative Structure-Activity Relationship Drug Design

Prenatal metal exposures and kidney function in adolescence in Project Viva.

Natalie F Price, Pi-I D Lin, Andres Cardenas et al.
1.00
Humans Adolescent Female Pregnancy Prenatal Exposure Delayed Effects
Glycoside Hydrolase Inhibitors Quantitative Structure-Activity Relationship Molecular Docking Simulation alpha-Glucosidases Molecular Dynamics Simulation
Methionine Bacterial Proteins Manganese Brevibacillus Copper

Classifications MeSH