Exploring possible mechanisms of action for the nanotoxicity and protein binding of decorated nanotubes: interpretation of physicochemical properties from optimal QSAR models

Esposito, Emilio Xavier; Hopfinger, A. J.; Shao, Chi-Yu; Su, Bo‐Han; Chen, Sing-Zuo; Tseng, Yufeng J.

doi:10.1016/j.taap.2015.07.008

Cited by 12 publications

(4 citation statements)

References 63 publications

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“…The predictive power of the proposed models is improved in terms of sensitivity and specificity, especially in the case of the toxicity endpoint, compared to the models developed by Fourches et al 13 and Singh et al 19 Shao et al 12 and Esposito et al 18 reported high accuracy statistics, nevertheless, their findings are not directly comparable with the results reported here, as they considered a decreased dataset focused only on the most toxic 29 MWCNTs.…”

Section: Discussioncontrasting

confidence: 78%

A safe-by-design tool for functionalised nanomaterials through the Enalos Nanoinformatics Cloud platform

et al. 2019

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Section: Discussioncontrasting

confidence: 78%

A safe-by-design tool for functionalised nanomaterials through the Enalos Nanoinformatics Cloud platform

et al. 2019

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“…Sixty-five papers were therefore included in this analysis. Among them, nanoparticle toxicity assessment was performed using prokaryotic cells in 19 papers, ,− ,− eukaryotic cells in 40 papers, ,,− or both in 6 papers. − Please note that the exclusion of some studies from this bibliographic survey doesn’t question their merit or usefulness, it just means they do not match the specific criteria we had previously established.…”

mentioning

confidence: 99%

Importance of Choosing Relevant Biological End Points To Predict Nanoparticle Toxicity with Computational Approaches for Human Health Risk Assessment

Forest

Hochepied

Pourchez

2019

Chem. Res. Toxicol.

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Because it is impossible to assess in vitro or in vivo the toxicity of all nanoparticles available on the market on a case-by-case basis, computational approaches have been proposed as useful alternatives to predict in silico the hazard potential of engineered nanoparticles. Despite promising results, a major issue associated with these mathematical models lies in the a priori choice of the physicochemical descriptors and the biological end points. We performed a thorough bibliographic survey on the biological end points used for nanotoxicology purposes and compared them between experimental and computational approaches. They were found to be disparate: while conventional in vitro nanotoxicology assays usually investigate a large array of biological effects using eukaryotic cells (cytotoxicity, pro-inflammatory response, oxidative stress, genotoxicity), computational studies mostly focus on cell viability and also include studies on prokaryotic cells. We may thus wonder the relevance of building complex mathematical models able to predict accurately a biological end point if this latter is not the most relevant to support human health risk assessment. The choice of biological end points clearly deserves to be more carefully discussed. This could bridge the gap between experimental and computational nanotoxicology studies and allow in silico predictive models to reach their full potential.

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“…Earlier studies on chemical and physical properties of CNTs demonstrated that the electronic properties of CNTs are mainly dependent on their geometries; therefore, investigating properties for functionalized CNTs with different geometries could be an interesting task of research for the tubular systems [20,21]. Avoiding the complicated experiments, computational studies could very well generate the optimized structures and their corresponding electronic properties for the exact models of NTs at the molecular and atomic scales [22][23][24]. Within this work, quantum chemical computations have been performed to explore stabilities and properties for the uracil (U)-functionalized (n, 0) CNTs with different curvatures (n = 3-16) (Figs.…”

Section: Introductionmentioning

confidence: 99%

Functionalization of (n, 0) CNTs (n = 3–16) by uracil: DFT studies

et al. 2018

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Density functional theory (DFT) calculations were performed to investigate stabilities and properties for uracil (U)-functionalized carbon nanotubes (CNTs). To this aim, the optimized molecular properties were evaluated for (n, 0) models of CNTs (n = 3-16) in the original and U-functionalized forms. The results indicated that the dipole moments and energy gaps were independent of tubular diameters whereas the binding energies showed that the U-functionalization could be better achieved for n = 8-11 curvatures of (n, 0) CNTs. Further studies based on the evaluated atomic-scale properties, including quadrupole coupling constants (CQ), indicated that the electronic properties of atoms could detect the effects of diameters variations of (n, 0) CNTs, in which the effects were very much significant for the atoms around the U-functionalization regions. Finally, the achieved results of singular U, original CNTs, and CNT-U hybrids were compared to each other to demonstrate the stabilities and properties for the U-functionalized (n, 0) CNTs.

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Exploring possible mechanisms of action for the nanotoxicity and protein binding of decorated nanotubes: interpretation of physicochemical properties from optimal QSAR models

Cited by 12 publications

References 63 publications

A safe-by-design tool for functionalised nanomaterials through the Enalos Nanoinformatics Cloud platform

A safe-by-design tool for functionalised nanomaterials through the Enalos Nanoinformatics Cloud platform

Importance of Choosing Relevant Biological End Points To Predict Nanoparticle Toxicity with Computational Approaches for Human Health Risk Assessment

Functionalization of (n, 0) CNTs (n = 3–16) by uracil: DFT studies

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