AQUA Tox: A web tool for predicting aquatic toxicity in rotifer species using intrinsic explainable models

The widespread use of chemicals in various industries, including agriculture, cosmetics, pharmaceuticals, and textiles, poses significant environmental risks, particularly in aquatic ecosystems. This study focuses on the toxicity of organic compounds on two rotifer species, Brachionus calyciflorus and Brachionus plicatilis, widely used as bioindicators in ecotoxicology. A database of toxicity data (LC<sub>50</sub>) was compiled and QSAR/QSTR models were developed to predict chemical toxicity in both freshwater (FW) and saltwater (SW) environments. Using molecular descriptors, the study identified critical factors influencing toxicity, such as hydrophobicity and the presence of chlorine atoms. The models demonstrated strong predictive performance, with R² values exceeding 70 % for both FW and SW conditions. Key descriptors influencing toxicity included hydrophobicity and chlorine content. The models demonstrated strong predictive performance, with R² values exceeding 70 %. A user-friendly web application was developed, enabling the scientific community to assess the aquatic toxicity of chemicals. This tool aids in the design of safer, more sustainable substances, facilitating regulatory compliance and minimizing environmental impacts. The findings highlight the importance of combining computational methods with technological applications for environmental protection.

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Publication Details

Journal
Journal of Hazardous Materials
Published
2025-03-26
DOI
https://doi.org/10.1016/j.jhazmat.2025.138050
Citations
3
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
4.51

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article

AQUA Tox: A web tool for predicting aquatic toxicity in rotifer species using intrinsic explainable models

Humberto González‐Díaz, Gerardo M. Casañola‐Martín, Karel Diéguez‐Santana, Roldan Torres-Gutiérrez et al.
3 citations
Journal of Hazardous Materials
Computational Drug Discovery Methods
4.51
article

AQUA Tox: A web tool for predicting aquatic toxicity in rotifer species using intrinsic explainable models

Humberto González‐Díaz, Gerardo M. Casañola‐Martín, Karel Diéguez‐Santana, Roldan Torres-Gutiérrez, Bakhtiyor Rasulev
article en
3 citations

Abstract

The widespread use of chemicals in various industries, including agriculture, cosmetics, pharmaceuticals, and textiles, poses significant environmental risks, particularly in aquatic ecosystems. This study focuses on the toxicity of organic compounds on two rotifer species, Brachionus calyciflorus and Brachionus plicatilis, widely used as bioindicators in ecotoxicology. A database of toxicity data (LC<sub>50</sub>) was compiled and QSAR/QSTR models were developed to predict chemical toxicity in both freshwater (FW) and saltwater (SW) environments. Using molecular descriptors, the study identified critical factors influencing toxicity, such as hydrophobicity and the presence of chlorine atoms. The models demonstrated strong predictive performance, with R² values exceeding 70 % for both FW and SW conditions. Key descriptors influencing toxicity included hydrophobicity and chlorine content. The models demonstrated strong predictive performance, with R² values exceeding 70 %. A user-friendly web application was developed, enabling the scientific community to assess the aquatic toxicity of chemicals. This tool aids in the design of safer, more sustainable substances, facilitating regulatory compliance and minimizing environmental impacts. The findings highlight the importance of combining computational methods with technological applications for environmental protection.

Journal of Hazardous MaterialsVol. 492
University of the Basque Country (ES), Universidad Regional Amazónica IKIAM (EC), North Dakota State University (US)
North Dakota State University, Ministerio de Ciencia, Innovación y Universidades, Eusko Jaurlaritza
Life below water
Openalex Percentile: Top 6%
Computational Drug Discovery Methods
4.51
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