Saved in:
| Main Author: | |
|---|---|
| Format: | Recurso digital |
| Language: | |
| Published: |
Zenodo
2024
|
| Online Access: | https://doi.org/10.5281/zenodo.10854649 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866902014342987776 |
|---|---|
| author | D.Pravallika, Dr.J.Gopala Krishna |
| author_facet | D.Pravallika, Dr.J.Gopala Krishna |
| contents | <div> <p><em><span>A variety number of nanoparticles will increase rapidly in coming years and there is a need<span> </span>for new methods to test the toxicity of the materials. Now a days experimental evaluation of<span> </span>the<span> </span>safety<span> </span>of<span> </span>chemicals<span> </span>is<span> </span>expensive<span> </span>and<span> </span>time<span> </span>consuming.<span> </span>Computational<span> </span>nano<span> </span>QSAR<span> </span>models<span> </span>have been found to be efficient alternatives for predicting the toxicity of metal oxide nano<span> </span>particles.</span></em></p> <p><em><span>The present study proposes a computational QSAR models for predicting the toxicity of<span> </span>MEONPs. Two types of mechanisms are collectively applied in a nano QSAR model,which<span> </span>provides control over the toxicity of metal oxide nanoparticles. The two parameters, enthalpy<span> </span><span>of formation of gaseous cation (∆H</span>me+<span>) and polarization force(Z/r) were elucidated to make a<span> </span></span>significant<span> </span>contribution for<span> </span>the toxic<span> </span>effect of the<span> </span>metal oxide<span> </span>nanoparticles.</span></em></p> </div> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_10854649 |
| institution | Zenodo |
| language | |
| publishDate | 2024 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | NANO-QSAR MODELING FOR PREDICTING THE TOXICITY OF METAL-BASED METAL OXIDE NANOPARTICALS: AN IN-DEPTH EXPLORATION D.Pravallika, Dr.J.Gopala Krishna <div> <p><em><span>A variety number of nanoparticles will increase rapidly in coming years and there is a need<span> </span>for new methods to test the toxicity of the materials. Now a days experimental evaluation of<span> </span>the<span> </span>safety<span> </span>of<span> </span>chemicals<span> </span>is<span> </span>expensive<span> </span>and<span> </span>time<span> </span>consuming.<span> </span>Computational<span> </span>nano<span> </span>QSAR<span> </span>models<span> </span>have been found to be efficient alternatives for predicting the toxicity of metal oxide nano<span> </span>particles.</span></em></p> <p><em><span>The present study proposes a computational QSAR models for predicting the toxicity of<span> </span>MEONPs. Two types of mechanisms are collectively applied in a nano QSAR model,which<span> </span>provides control over the toxicity of metal oxide nanoparticles. The two parameters, enthalpy<span> </span><span>of formation of gaseous cation (∆H</span>me+<span>) and polarization force(Z/r) were elucidated to make a<span> </span></span>significant<span> </span>contribution for<span> </span>the toxic<span> </span>effect of the<span> </span>metal oxide<span> </span>nanoparticles.</span></em></p> </div> |
| title | NANO-QSAR MODELING FOR PREDICTING THE TOXICITY OF METAL-BASED METAL OXIDE NANOPARTICALS: AN IN-DEPTH EXPLORATION |
| url | https://doi.org/10.5281/zenodo.10854649 |