Traditional Quantitative Structure-Activity Relationships (QSAR) models based on molecular descriptors as translators of chemical information show some drawbacks in predicting toxicity of nanomaterials due to their unique properties and to their nonhomogeneous structure.This chapter provides instructions on how to use CORAL, freely available software for building nano-QSAR models. CORAL makes use of descriptors based on "quasi-SMILES" representing physicochemical features and/or experimental conditions as an alternative to traditional SMILES encoding chemical structure to build up predictive nano-QSAR models for cytotoxicity.
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http://dx.doi.org/10.1007/978-1-4939-6960-9_22 | DOI Listing |
Environ Toxicol Chem
January 2025
School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, PR China.
In silico methods are increasingly important in predicting the ecotoxicity of engineered nanomaterials (ENMs), encompassing both individual and mixture toxicity predictions. It is widely recognized that ENMs trigger oxidative stress effects by generating intracellular reactive oxygen species (ROS), serving as a key mechanism in their cytotoxicity studies. However, existing in silico methods still face significant challenges in predicting the oxidative stress effects induced by ENMs.
View Article and Find Full Text PDFACS Appl Mater Interfaces
December 2024
Institute of Environmental Research at Greater Bay Area, Key Laboratory for Water Quality and Conservation of the Pearl River Delta, Ministry of Education, Guangzhou University, Guangzhou 510006, China.
Screening nanomaterials (NMs) with desired properties from the extensive chemical space presents significant challenges. The potential toxicity of NMs further limits their applications in biological systems. Traditional methods struggle with these complexities, but generative models offer a possible solution to producing new molecules without prior knowledge.
View Article and Find Full Text PDFBeilstein J Nanotechnol
July 2024
ProtoQSAR S.L., CEEI Valencia, Avda. Benjamin Franklin 12, 46980 Paterna, Spain.
Quantitative structure-activity relationship (QSAR) models are routinely used to predict the properties and biological activity of chemicals to direct synthetic advances, perform massive screenings, and even to register new substances according to international regulations. Currently, nanoscale QSAR (nano-QSAR) models, adapting this methodology to predict the intrinsic features of nanomaterials (NMs) and quantitatively assess their risks, are blooming. One of the challenges is the characterization of the NMs.
View Article and Find Full Text PDFEnviron Pollut
March 2024
College of Safety Science and Engineering, Nanjing Tech University, Nanjing, 211816, Jiangsu, PR China.
In recent years, nanomaterials have found extensive applications across diverse domains owing to their distinctive physical and chemical characteristics. It is of great importance in theoretical and practical terms to carry out the relationship between structural characteristics of nanomaterials and different cytotoxicity and to achieve practical assessment and prediction of cytotoxicity. This study investigated the intrinsic quantitative constitutive relationships between the cytotoxicity of nano-metal oxides on human normal lung epithelial cells and human lung adenocarcinoma cells.
View Article and Find Full Text PDFBeilstein J Nanotechnol
September 2023
Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700032, India.
Nanoparticles with their unique features have attracted researchers over the past decades. Heavy metals, upon release and emission, may interact with different environmental components, which may lead to co-exposure to living organisms. Nanoscale titanium dioxide (nano-TiO) can adsorb heavy metals.
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