Predicting Cytotoxicity and Enzymatic Activity of Diverse Chemicals Using Goldfish Scale Tissue and Topminnow Hepatoma Cell Line‐based Data

Kahraman, E Nagihan; Saçan, Melek Türker

doi:10.1002/minf.201800127

Cited by 4 publications

(1 citation statement)

References 38 publications

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“…Computational methods have been developed over many years and play a critical role in estimating the aquatic toxicity of both new and existing compounds [ 33 , 34 , 35 , 36 , 37 , 38 , 39 ]. Quantitative structure–activity relationships (QSARs) are an effective method for predicting the aquatic toxicity of chemicals [ 40 , 41 , 42 , 43 , 44 , 45 ].…”

Section: Introductionmentioning

confidence: 99%

Cheminformatics and Machine Learning Approaches to Assess Aquatic Toxicity Profiles of Fullerene Derivatives

Fjodorova,

Novič,

Venko

et al. 2023

IJMS

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Fullerene derivatives (FDs) are widely used in nanomaterials production, the pharmaceutical industry and biomedicine. In the present study, we focused on the potential toxic effects of FDs on the aquatic environment. First, we analyzed the binding affinity of 169 FDs to 10 human proteins (1D6U, 1E3K, 1GOS, 1GS4, 1H82, 1OG5, 1UOM, 2F9Q, 2J0D, 3ERT) obtained from the Protein Data Bank (PDB) and showing high similarity to proteins from aquatic species. Then, the binding activity of 169 FDs to the enzyme acetylcholinesterase (AChE)—as a known target of toxins in fathead minnows and Daphnia magna, causing the inhibition of AChE—was analyzed. Finally, the structural aquatic toxicity alerts obtained from ToxAlert were used to confirm the possible mechanism of action. Machine learning and cheminformatics tools were used to analyze the data. Counter-propagation artificial neural network (CPANN) models were used to determine key binding properties of FDs to proteins associated with aquatic toxicity. Predicting the binding affinity of unknown FDs using quantitative structure–activity relationship (QSAR) models eliminates the need for complex and time-consuming calculations. The results of the study show which structural features of FDs have the greatest impact on aquatic organisms and help prioritize FDs and make manufacturing decisions.

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