Suppr超能文献

使用虚拟纳米粒子库进行通用的纳米疏水性预测。

Universal nanohydrophobicity predictions using virtual nanoparticle library.

作者信息

Wang Wenyi, Yan Xiliang, Zhao Linlin, Russo Daniel P, Wang Shenqing, Liu Yin, Sedykh Alexander, Zhao Xiaoli, Yan Bing, Zhu Hao

机构信息

The Rutgers Center for Computational and Integrative Biology, Camden, NJ, 08102, USA.

School of Chemistry and Chemical Engineering, Shandong University, Jinan, 250100, China.

出版信息

J Cheminform. 2019 Jan 18;11(1):6. doi: 10.1186/s13321-019-0329-8.

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.

摘要

为促进新型纳米材料尤其是纳米药物的开发,人们开发了一种新颖的计算方法来精确预测金纳米颗粒(GNP)的疏水性。本研究的核心是通过计算纳米结构模拟来构建一个大型虚拟金纳米颗粒(vGNP)库。基于该vGNP库,开发了一种纳米疏水性模型,然后针对外部合成和测试的GNP进行了验证。这种方法及所得模型是一种高效且有效的通用工具,可在合成前可视化和预测新型纳米材料的关键物理化学性质,从而指导纳米材料的设计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d5/6689884/f7aba6b8f55f/13321_2019_329_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验