A Nano-Combinatorial Library Strategy for the Discovery of Nanotubes with Reduced Protein-Binding, Cytotoxicity, and Immune Response

Zhou, Hongyu; Mu, Qingxin; Gao, Ningning; Liu, Aifeng; Xing, Yuehan; Gao, Sulian; Zhang, Qiu; Qu, Guangbo; Chen, Yuyan; Liu, Gang; Zhang, Bin; Yan, Bing

doi:10.1021/nl0730155

Cited by 138 publications

(202 citation statements)

References 51 publications

(82 reference statements)

Supporting

Mentioning

195

Contrasting

Unclassified

Order By: Relevance

“…They compared the InfaRed (IR) spectra with several descriptors commonly used in (Q)SAR studies and found that IR spectra carries unique information which cannot be obtained from molecular descriptors. (Zhou, et al, 2008) used the spectra of MWNTs for characterization purposes while (Y. Yang, Guo, Hu, Wang, & Wang, 2004) attempted to link XRD data to photocatalytic performance tested by dye decolourisation rate.…”

Section: Np-specific Descriptorsmentioning

confidence: 99%

(Q)SAR modelling of nanomaterial toxicity: A critical review

et al. 2015

View full text Add to dashboard Cite

There is an increasing recognition that nanomaterials pose a risk to human health, and that the novel engineered nanomaterials (ENMs) in the nanotechnology industry and their increasing industrial usage poses the most immediate problem for hazard assessment, as many of them remain untested. The large number of materials and their variants (different sizes and coatings for instance) that require testing and ethical pressure towards non-animal testing means that expensive animal bioassay is precluded, and the use of (quantitative) structure activity relationships ((Q)SAR) models as an alternative source of hazard information should be explored.(Q)SAR modelling can be applied to fill the critical knowledge gaps by making the best use of existing data, prioritize physicochemical parameters driving toxicity, and provide practical solutions to the risk assessment problems caused by the diversity of ENMs. This paper covers the core components required for successful application of (Q)SAR technologies to ENMs toxicity prediction, and summarizes the published nano-(Q)SAR studies and outlines the challenges ahead for nano-(Q)SAR modelling. It provides a critical review of (1) the present status of the availability of ENMs characterization/toxicity data, (2) the characterization of nanostructures that meets the need of (Q)SAR analysis, (3) the summary of published nano-(Q)SAR studies and their limitations, (4) the in silico tools for (Q)SAR screening of nanotoxicity and (5) the prospective directions for the development of nano-(Q)SAR models.

show abstract

Section: Np-specific Descriptorsmentioning

confidence: 99%

(Q)SAR modelling of nanomaterial toxicity: A critical review

et al. 2015

View full text Add to dashboard Cite

show abstract

“…[ 33 ] For animal experiments, the suspensions of f-MWCNTs were prepared in PBS with 1% Tween 80 and sonicated for 1 h to facilitate dispersion.…”

Section: Methodsmentioning

confidence: 99%

“…[ 33 ] To test the effects of this combinatorial f-MWCNT library, which contains 80 members, on CYP3A4 activity in a high-throughput format, we determined the remaining parent drug concentration after incubating library members with NFP in HLM. As shown in Figure 5 , multiple f-MWCNTs with diverse chemistries modulated the enzymatic activity of CYP3A4 over a broad range (60%-131%).…”

Section: Mwcnt Surface Chemistry Affects the Functional Regulation Ofmentioning

confidence: 99%

Modulation of Carbon Nanotubes' Perturbation to the Metabolic Activity of CYP3A4 in the Liver

Zhang

Wang

Liu

et al. 2015

Adv Funct Materials

Self Cite

View full text Add to dashboard Cite

The liver plays an important role in metabolizing foreign materials, such as drugs. The high accumulation of carbon nanotubes and other hydrophobic nanoparticles in the liver has raised concerns that nanoparticles may interfere with liver metabolic function. We report here that carbon nanotubes enter hepatic cells after intravenous introduction and interact with CYP enzymes, including CYP3A4. Surface chemical modifications alter the carbon nanotubes' interactions with CYP450 enzymes in human liver microsomes. They enhance, inhibit, or have no effect on the enzymatic function of CYP3A4. Using a cheminformatics analysis, certain chemical structures are identified on the surface of the carbon nanotubes that induce an enzyme inhibitory effect or prevent disruption of CYP3A4 enzymes.

show abstract

“…In 2008, Zhou et al created a library containing 80 multi-walled nanotubes (MWNTs) with known biological activities [35]. They tested the toxicity of these decorated nanotubes using six different toxicity endpoints (four protein binding activities, cell viability and nitrogen oxide generation).…”

Section:  Sample Sizementioning

confidence: 99%

“…They also revealed the structure-activity relationship between the type of building block and the biocompatibility. The raw data generated by Zhou et al [35] have been assessed below to find out their suitability for developing nano-(Q)SAR models: Their complete dataset is summarized in Table-S5. They attempted to perform multivariate linear regression (MLR) and linear discriminant analysis (LDA) classification techniques on the collected dataset.…”

Section:  Sample Sizementioning

confidence: 99%

Current situation on the availability of nanostructure–biological activity data

Oksel

Wang

2015

SAR and QSAR in Environmental Research

View full text Add to dashboard Cite

The recent developments in nanotechnology have not only increased the number of nanoproducts on the market, but also raised concerns about the safety of engineered nanomaterials (ENMs) for human health and the environment. As the production and use of ENMs are increasing, we are approaching the point at which it is impossible to individually assess the toxicity of a vast number of ENMs. Therefore, it is desirable to use time-effective computational methods, such as the quantitative structure-activity relationship (QSAR) models, in order to predict the toxicity of ENMs. However, the accuracy of the nano-(Q)SARs is directly tied to the quality of the data from which the model is estimated.Although the amount of available nanotoxicity data is insufficient for generating robust nano-(Q)SAR models in most cases, there are a handful of studies that provide appropriate experimental data for (Q)SAR-like modelling investigations. The aim of this study is to review the available literature data that are particularly suitable for nano-(Q)SAR modelling.We hope that this paper can serve as a starting point for those who would like to know more about the current availability of experimental data on the health effects of ENMs for future modelling purposes.

show abstract

A Nano-Combinatorial Library Strategy for the Discovery of Nanotubes with Reduced Protein-Binding, Cytotoxicity, and Immune Response

Cited by 138 publications

References 51 publications

(Q)SAR modelling of nanomaterial toxicity: A critical review

(Q)SAR modelling of nanomaterial toxicity: A critical review

Modulation of Carbon Nanotubes' Perturbation to the Metabolic Activity of CYP3A4 in the Liver

Current situation on the availability of nanostructure–biological activity data

Contact Info

Product

Resources

About