Computational Tool for Risk Assessment of Nanomaterials: Novel QSTR-Perturbation Model for Simultaneous Prediction of Ecotoxicity and Cytotoxicity of Uncoated and Coated Nanoparticles under Multiple Experimental Conditions

Abstract

Nanomaterials have revolutionized modern science and technology due to their multiple applications in engineering, physics, chemistry, and biomedicine. Nevertheless, the use and manipulation of nanoparticles (NPs) can bring serious damages to living organisms and their ecosystems. For this reason, ecotoxicity and cytotoxicity assays are of special interest in order to determine the potential harmful effects of NPs. Processes based on ecotoxicity and cytotoxicity tests can significantly consume time and financial resources. In this sense, alternative approaches such as quantitative structure-activity/toxicity relationships (QSAR/QSTR) modeling have provided important insights for the better understanding of the biological behavior of NPs that may be responsible for causing toxicity. Until now, QSAR/QSTR models have predicted ecotoxicity or cytotoxicity separately against only one organism (bioindicator species or cell line) and have not reported information regarding the quantitative influence of characteristics other than composition or size. In this work, we developed a unified QSTR-perturbation model to simultaneously probe ecotoxicity and cytotoxicity of NPs under different experimental conditions, including diverse measures of toxicities, multiple biological targets, compositions, sizes and conditions to measure those sizes, shapes, times during which the biological targets were exposed to NPs, and coating agents. The model was created from 36488 cases (NP-NP pairs) and exhibited accuracies higher than 98% in both training and prediction sets. The model was used to predict toxicities of several NPs that were not included in the original data set. The results of the predictions suggest that the present QSTR-perturbation model can be employed as a highly promising tool for the fast and efficient assessment of ecotoxicity and cytotoxicity of NPs.

Evaluation of nano-specific toxicity of zinc oxide, copper oxide, and silver nanoparticles through toxic ratio

“…These methods provide valuable NMs hazard and toxicity data. Moreover, in addition to the regulation of NMs use, in vivo methods, and reducing, refining, and replacing animal experiment principle (3Rs), in vitro and in silico standards have been proposed for nanotoxicity investigations (Burello 2015; Gajewicz et al 2012;Gong et al 2012;He et al 2013;Ivask et al 2010;Kaweeteerawat et al 2015;Kleandrova et al 2014;McCracken et al 2016;Mortimer et al 2010;Qin et al 2008). For further information about the safety of manufactured nanomaterials, readers are referred to OECD regulations (http://www.oecd.org/science/nanosafety/).…”

Latest advances in molecular topology applications for drug discovery

“…Representative seminal works are the ones by Box and Jenkins [63]. More recently, González-Díaz et al [57] and Speck-Planche et al [64,65] also employed moving average operators to construct QSAR models. In a recent paper [66], they introduce the first QSAR perturbation model for the analysis of different antibacterial groups of nanoparticles (NPs).…”

An ISA-TAB-Nano based data collection framework to support data-driven modelling of nanotoxicology

“…A number of nano-QSAR models have been developed for cytotoxicity [13,85,86,87,88,89,90,91] and some models have also been developed for nanomaterial genotoxicity [9,92,93].…”