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Universal nanohydrophobicity predictions using virtual nanoparticle library.
Journal of Cheminformatics ( IF 8.6 ) Pub Date : 2019-01-18 , DOI: 10.1186/s13321-019-0329-8 Wenyi Wang 1 , Xiliang Yan 1, 2 , Linlin Zhao 1 , Daniel P Russo 1 , Shenqing Wang 2 , Yin Liu 3 , Alexander Sedykh 1, 4 , Xiaoli Zhao 5 , Bing Yan 2, 6 , Hao Zhu 1, 7, 8
Journal of Cheminformatics ( IF 8.6 ) Pub Date : 2019-01-18 , DOI: 10.1186/s13321-019-0329-8 Wenyi Wang 1 , Xiliang Yan 1, 2 , Linlin Zhao 1 , Daniel P Russo 1 , Shenqing Wang 2 , Yin Liu 3 , Alexander Sedykh 1, 4 , Xiaoli Zhao 5 , Bing Yan 2, 6 , Hao Zhu 1, 7, 8
Affiliation
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.
中文翻译:
使用虚拟纳米粒子库的通用纳米疏水性预测。
为了促进新的纳米材料,特别是纳米药物的开发,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。这项研究的核心是开发具有计算纳米结构模拟的大型虚拟金纳米颗粒(vGNP)库。基于vGNP库,开发了纳米疏水性模型,然后针对外部合成和测试的GNP进行了验证。这种方法和结果模型是一种有效且通用的工具,可以在合成之前可视化和预测新纳米材料的关键理化性质,指导纳米材料设计。
更新日期:2019-01-18
中文翻译:
使用虚拟纳米粒子库的通用纳米疏水性预测。
为了促进新的纳米材料,特别是纳米药物的开发,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。这项研究的核心是开发具有计算纳米结构模拟的大型虚拟金纳米颗粒(vGNP)库。基于vGNP库,开发了纳米疏水性模型,然后针对外部合成和测试的GNP进行了验证。这种方法和结果模型是一种有效且通用的工具,可以在合成之前可视化和预测新纳米材料的关键理化性质,指导纳米材料设计。