Investigation of the influence of protein corona composition on gold nanoparticle bioactivity using machine learning approaches. Issue 7 (2nd July 2016)
- Record Type:
- Journal Article
- Title:
- Investigation of the influence of protein corona composition on gold nanoparticle bioactivity using machine learning approaches. Issue 7 (2nd July 2016)
- Main Title:
- Investigation of the influence of protein corona composition on gold nanoparticle bioactivity using machine learning approaches
- Authors:
- Papa, E.
Doucet, J. P.
Sangion, A.
Doucet-Panaye, A. - Abstract:
- Abstract: The understanding of the mechanisms and interactions that occur when nanomaterials enter biological systems is important to improve their future use. The adsorption of proteins from biological fluids in a physiological environment to form a corona on the surface of nanoparticles represents a key step that influences nanoparticle behaviour. In this study, the quantitative description of the composition of the protein corona was used to study the effect on cell association induced by 84 surface-modified gold nanoparticles of different sizes. Quantitative relationships between the protein corona and the activity of the gold nanoparticles were modelled by using several machine learning-based linear and non-linear approaches. Models based on a selection of only six serum proteins had robust and predictive results. The Projection Pursuit Regression method had the best performances ( r 2 = 0.91; Q 2 loo = 0.81; r 2 ext = 0.79). The present study confirmed the utility of protein corona composition to predict the bioactivity of gold nanoparticles and identified the main proteins that act as promoters or inhibitors of cell association. In addition, the comparison of several techniques showed which strategies offer the best results in prediction and could be used to support new toxicological studies on gold-based nanomaterials.
- Is Part Of:
- SAR and QSAR in environmental research. Volume 27:Issue 7(2016)
- Journal:
- SAR and QSAR in environmental research
- Issue:
- Volume 27:Issue 7(2016)
- Issue Display:
- Volume 27, Issue 7 (2016)
- Year:
- 2016
- Volume:
- 27
- Issue:
- 7
- Issue Sort Value:
- 2016-0027-0007-0000
- Page Start:
- 521
- Page End:
- 538
- Publication Date:
- 2016-07-02
- Subjects:
- Nanoparticles -- in silico models -- machine learning -- computational nanotoxicology -- protein corona
Structure-activity relationships (Biochemistry) -- Periodicals
QSAR (Biochemistry) -- Periodicals
572.4 - Journal URLs:
- http://www.tandfonline.com/toc/gsar20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/1062936X.2016.1197310 ↗
- Languages:
- English
- ISSNs:
- 1062-936X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8075.965500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14470.xml