Dataset on aquatic ecotoxicity predictions of 2697 chemicals, using three quantitative structure-activity relationship platforms
Journal article, 2023

Empirical and in silico data on the aquatic ecotoxicology of 2697 organic chemicals were collected in order to compile a dataset for assessing the predictive power of current Quantitative Structure Activity Relationship (QSAR) models and software platforms. This document presents the dataset and the data pipeline for its creation. Empirical data were collected from the US EPA ECOTOX Knowledgebase (ECOTOX) and the EFSA (European Food Safety Authority) report “Completion of data entry of pesticide ecotoxicology Tier 1 study endpoints in a XML schema – database”. Only data for OECD recommended algae, daphnia and fish species were retained. QSAR toxicity predictions were calculated for each chemical and each of six endpoints using ECOSAR, VEGA and the Toxicity Estimation Software Tool (T.E.S.T.) platforms. Finally, the dataset was amended with SMILES, InChIKey, pKa and logP collected from webchem and PubChem.

Quantitative structure-activity relationship

Chemical toxicity

ECOSAR

Toxicity estimation software tool

VEGA

Author

Patrik Svedberg

University of Gothenburg

Pedro A. Inostroza

RWTH Aachen University

University of Gothenburg

Mikael Gustavsson

University of Gothenburg

Erik Kristiansson

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Francis Spilsbury

University of Gothenburg

Thomas Backhaus

RWTH Aachen University

University of Gothenburg

Data in Brief

23523409 (eISSN)

Vol. 51 109719

Subject Categories

Biochemistry and Molecular Biology

Ecology

Pharmacology and Toxicology

Environmental Sciences

DOI

10.1016/j.dib.2023.109719

PubMed

37965605

More information

Latest update

11/10/2023