Volume : 11, Issue : 03, March – 2024
Title:
NANO-QSAR MODELING FOR PREDICTING THE TOXICITY OF METAL-BASED METAL OXIDE NANOPARTICALS: AN IN-DEPTH EXPLORATION
Authors :
D.Pravallika, Dr.J.Gopala Krishna
Abstract :
A variety number of nanoparticles will increase rapidly in coming years and there is a need for new methods to test the toxicity of the materials. Now a days experimental evaluation of the safety of chemicals is expensive and time consuming. Computational nano QSAR models have been found to be efficient alternatives for predicting the toxicity of metal oxide nano particles.
The present study proposes a computational QSAR models for predicting the toxicity of MEONPs. Two types of mechanisms are collectively applied in a nano QSAR model,which provides control over the toxicity of metal oxide nanoparticles. The two parameters, enthalpy of formation of gaseous cation (∆Hme+) and polarization force(Z/r) were elucidated to make a significant contribution for the toxic effect of the metal oxide nanoparticles.
Cite This Article:
Please cite this article in press J.Gopala Krishna et al., Nano-QSAR Modeling For Predicting The Toxicity Of Metal-Based Metal Oxide Nanoparticles: An In-Depth Exploration,, Indo Am. J. P. Sci, 2024; 11 (03).
Number of Downloads : 10
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