Universal nanohydrophobicity predictions using virtual nanoparticle library

Universal nanohydrophobicity predictions using virtual nanoparticle library

Abstract To facilitate the development of new nanomaterials, especially nanomedicines, a novel computational approach was developed to precisely predict the hydrophobicity of gold nanoparticles (GNPs). The core of this study was to develop a large virtual gold nanoparticle (vGNP) library with comput...

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Bibliographic Details
Main Authors: Wenyi Wang, Xiliang Yan, Linlin Zhao, Daniel P. Russo, Shenqing Wang, Yin Liu, Alexander Sedykh, Xiaoli Zhao, Bing Yan, Hao Zhu
Format: Article
Language:English
Published: BMC 2019-01-01
Series:Journal of Cheminformatics
Subjects:
Nanohydrohobicity
Surface chemistry
Surface simulations
Nanomaterials design
Virtual nanoparticle library
Predictive model
Online Access:http://link.springer.com/article/10.1186/s13321-019-0329-8
Description
Summary:Abstract To facilitate the development of new nanomaterials, especially nanomedicines, a novel computational approach was developed to precisely predict the hydrophobicity of gold nanoparticles (GNPs). The core of this study was to develop a large virtual gold nanoparticle (vGNP) library with computational nanostructure simulations. Based on the vGNP library, a nanohydrophobicity model was developed and then validated against externally synthesized and tested GNPs. This approach and resulted model is an efficient and effective universal tool to visualize and predict critical physicochemical properties of new nanomaterials before synthesis, guiding nanomaterial design.
ISSN:1758-2946

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