Modeling and insights into the structural basis of chemical acute aquatic toxicity.
Ecotoxicol Environ Saf
; 242: 113940, 2022 Sep 01.
Article
en En
| MEDLINE
| ID: mdl-35999760
ABSTRACT
It has become a top global regulatory priority to prevent and control pollution from the release of synthetic chemicals, which continues to affect the aquatic communities. In the past decades, computational tools were largely used to significantly reduce the budget and time cost of chemical acute aquatic toxicity assessment. But the structural basis of toxic compounds was rarely analyzed. In the present study, we collected 1438, 485 and 961 chemicals with acute toxicity data records for three representative aquatic species, including Tetrahymena pyriformis, Daphnia magna, and Fathead minnow, respectively. A series of artificial intelligence models were developed using OCHEM tools. For each aquatic toxicity endpoint, a consensus model was developed based on the top performed individual models. The consensus models provided good performance on external validation sets with total accuracy values 96.88 %, 90.63 %, and 84.90 % for Tetrahymena pyriformis toxicity (TPT), Daphnia magna toxicity (DMT), and Fathead minnow toxicity (FMT), respectively. The models can be freely accessed via https//ochem.eu/article/146910. Moreover, the analysis of physical-chemical properties suggested that several key molecular properties of aquatic toxic compounds were significantly different with those of non-toxic compounds. Thus, these descriptors may be associated to chemical acute aquatic toxicity, and may be useful for the understand of chemical aquatic toxicity. Besides, in this study, the structural alerts for aquatic toxicity were detected using f-score and frequency ratio analysis of predefined substructures. A total of 112, 58 and 33 structural alerts were identified responsible for TPT, DMT, and FMT, respectively. These structural alerts could provide useful information for the mechanisms of chemical aquatic toxicity and visual alerts for environmental assessment. All the structural alerts were integrated in the web-server SApredictor (www.sapredictor.cn).
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Tetrahymena pyriformis
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Contaminantes Químicos del Agua
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Cyprinidae
Tipo de estudio:
Prognostic_studies
Límite:
Animals
Idioma:
En
Revista:
Ecotoxicol Environ Saf
Año:
2022
Tipo del documento:
Article