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

Svedberg, Patrik; Gustavsson, Mikael; Kristiansson, Erik; Spilsbury, Francis

Abstract

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.(c) 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

Más información

Título según WOS: ID WOS:001105264400001 Not found in local WOS DB
Título de la Revista: DATA IN BRIEF
Volumen: 51
Editorial: Elsevier
Fecha de publicación: 2023
DOI:

10.1016/j.dib.2023.109719

Notas: ISI