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Updated: Mar 17, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
CORAL: Monte Carlo Method as a Tool for the Prediction of the Bioconcentration Factor of Industrial Pollutants
A P Toropova1, A A Toropov2, S E Martyanov3
1Istituto di Ricerche Farmacologiche Mario Negri, 20156, Via La Masa 19, Milano, Italy.
Abstract:
The CORAL software (http://www.insilico.eu/coral/) has been evaluated for application in QSAR modeling of the bioconcentration factor in fish (logBCF). The data used include 237 organic substances (industrial pollutants). Six random splits of the data into sub-training (30-50 %), calibration (20-30 %), test (13-30 %), and validation sets (7-25 %) have been carried out. The following numbers display the average statistical characteristics of the models for the external validation set: correlation coefficient r(2) =0.880±0.017 and standard error of estimation s=0.559±0.131. The best models were obtained with a combined representation of the molecular structure by SMILES together with hydrogen suppressed graph.
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