Universal nanohydrophobicity predictions using virtual nanoparticle library

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 n...

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Detalles Bibliográficos
Autores principales: Wang, Wenyi, Yan, Xiliang, Zhao, Linlin, Russo, Daniel P., Wang, Shenqing, Liu, Yin, Sedykh, Alexander, Zhao, Xiaoli, Yan, Bing, Zhu, Hao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2019
Materias:
Preliminary Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6689884/
https://www.ncbi.nlm.nih.gov/pubmed/30659400
http://dx.doi.org/10.1186/s13321-019-0329-8
Descripción
Sumario: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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13321-019-0329-8) contains supplementary material, which is available to authorized users.

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