QSPR Modelling of Potentiometric HCO3−/Cl− Selectivity for Polymeric Membrane Sensors

Nadezhda V. Vladimirova, Julia Ashina, D. Kirsanov
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Abstract

Since the development process of new sensors is long and tedious, it would be very helpful to develop a model that could predict sensor properties based on active compound structure without the actual synthesis and characterization of the corresponding sensors. In this work, the model for the prediction of logK (HCO3−/Cl−) was constructed based on 40 ligand structures suggested in the literature for carbonate sensing. Substructural molecular fragments (SMF) were used to describe the structure of compounds, where fragments were considered as sequences of bonds and atoms. The projection on latent structures (PLS) method was used to calculate the regression model.
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聚合物膜传感器电位HCO3−/Cl−选择性的QSPR建模
由于新型传感器的开发过程漫长而繁琐,因此,在不实际合成和表征相应传感器的情况下,开发一种基于活性化合物结构的传感器性能预测模型是非常有帮助的。在这项工作中,基于文献中提出的40种用于碳酸盐传感的配体结构,构建了logK (HCO3−/Cl−)的预测模型。亚结构分子片段(SMF)被用来描述化合物的结构,其中片段被认为是键和原子的序列。采用隐结构投影法(PLS)计算回归模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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