Literature DB >> 24362319

Using experimental data of Escherichia coli to develop a QSAR model for predicting the photo-induced cytotoxicity of metal oxide nanoparticles.

Kavitha Pathakoti1, Ming-Ju Huang2, John D Watts3, Xiaojia He1, Huey-Min Hwang4.   

Abstract

A quantitative structure-activity relationship (QSAR) study of seventeen metal oxide nanoparticles (MNPs), in regard to their photo-induced toxicity to bacteria Escherichia coli, was developed by using quantum chemical methods. A simple and statistically significant QSAR model (F=33.83, R(2)=0.87) was successfully developed for the dark group based on two descriptors, absolute electronegativity of the metal and the metal oxide. Similarly, a best correlation (F=20.51, R(2)=0.804) was obtained to predict the photo-induced toxicity of MNPs by using two descriptors, molar heat capacity and average of the alpha and beta LUMO (lowest unoccupied molecular orbital) energies of the metal oxide. Revelation of these influential molecular descriptors may be useful in elucidating the mechanisms of nanotoxicity and for predicting the environmental risk associated with release of the MNPs. In addition, the developed model may have a role in the future design and manufacture of safe nanomaterials.
Copyright © 2013 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Bacteria; Electronegativity; LUMO energy; Metal oxide nanoparticles; Phototoxicity

Mesh:

Substances:

Year:  2013        PMID: 24362319     DOI: 10.1016/j.jphotobiol.2013.11.023

Source DB:  PubMed          Journal:  J Photochem Photobiol B        ISSN: 1011-1344            Impact factor:   6.252


  15 in total

1.  Predicting Nano-Bio Interactions by Integrating Nanoparticle Libraries and Quantitative Nanostructure Activity Relationship Modeling.

Authors:  Wenyi Wang; Alexander Sedykh; Hainan Sun; Linlin Zhao; Daniel P Russo; Hongyu Zhou; Bing Yan; Hao Zhu
Journal:  ACS Nano       Date:  2017-11-22       Impact factor: 15.881

Review 2.  Big Data and Artificial Intelligence Modeling for Drug Discovery.

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Journal:  Annu Rev Pharmacol Toxicol       Date:  2019-09-13       Impact factor: 13.820

3.  Evaluating the cytotoxicity of a large pool of metal oxide nanoparticles to Escherichia coli: Mechanistic understanding through In Vitro and In Silico studies.

Authors:  Supratik Kar; Kavitha Pathakoti; Paul B Tchounwou; Danuta Leszczynska; Jerzy Leszczynski
Journal:  Chemosphere       Date:  2020-09-25       Impact factor: 7.086

4.  Development of a nano-QSPR model to predict band gaps of spherical metal oxide nanoparticles.

Authors:  Jiaxing Wang; Ya Wang; Yang Huang; Willie J G M Peijnenburg; Jingwen Chen; Xuehua Li
Journal:  RSC Adv       Date:  2019-03-14       Impact factor: 4.036

Review 5.  Current Knowledge on the Use of Computational Toxicology in Hazard Assessment of Metallic Engineered Nanomaterials.

Authors:  Guangchao Chen; Willie Peijnenburg; Yinlong Xiao; Martina G Vijver
Journal:  Int J Mol Sci       Date:  2017-07-12       Impact factor: 5.923

Review 6.  Metal Oxide Nanomaterial QNAR Models: Available Structural Descriptors and Understanding of Toxicity Mechanisms.

Authors:  Jiali Ying; Ting Zhang; Meng Tang
Journal:  Nanomaterials (Basel)       Date:  2015-10-12       Impact factor: 5.076

7.  Towards the Development of Global Nano-Quantitative Structure-Property Relationship Models: Zeta Potentials of Metal Oxide Nanoparticles.

Authors:  Andrey A Toropov; Natalia Sizochenko; Alla P Toropova; Jerzy Leszczynski
Journal:  Nanomaterials (Basel)       Date:  2018-04-15       Impact factor: 5.076

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

Authors:  Richard L Marchese Robinson; Mark T D Cronin; Andrea-Nicole Richarz; Robert Rallo
Journal:  Beilstein J Nanotechnol       Date:  2015-10-05       Impact factor: 3.649

Review 9.  In silico toxicology: computational methods for the prediction of chemical toxicity.

Authors:  Arwa B Raies; Vladimir B Bajic
Journal:  Wiley Interdiscip Rev Comput Mol Sci       Date:  2016-01-06

Review 10.  A Review of Recent Advances towards the Development of (Quantitative) Structure-Activity Relationships for Metallic Nanomaterials.

Authors:  Guangchao Chen; Martina G Vijver; Yinlong Xiao; Willie J G M Peijnenburg
Journal:  Materials (Basel)       Date:  2017-08-31       Impact factor: 3.623

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