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- W2949403267 abstract "This paper is devoted to computer-aided design of new extractants of the uranyl cation involving three main steps: (i) a QSPR study, (ii) generation and screening of a virtual combinatorial library, and (iii) synthesis of several predicted compounds and their experimental extraction studies. First, we performed a QSPR modeling of the distribution coefficient (logD) of uranyl extracted by phosphoryl-containing podands from water to 1,2-dichloroethane. Two different approaches were used: one based on classical structural and physicochemical descriptors (implemented in the CODESSA PRO program) and another one based on fragment descriptors (implemented in the TRAIL program). Three statistically significant models obtained with TRAIL involve as descriptors either sequences of atoms and bonds or atoms with their close environment (augmented atoms). The best models of CODESSA PRO include its own molecular descriptors as well as fragment descriptors obtained with TRAIL. At the second step, a virtual combinatori..." @default.
- W2949403267 created "2019-06-27" @default.
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- W2949403267 date "2004-09-28" @default.
- W2949403267 modified "2023-09-25" @default.
- W2949403267 title "“In Silico” Design of New Uranyl Extractants Based on Phosphoryl-Containing Podands: QSPR Studies, Generation and Screening of Virtual Combinatorial Library, and Experimental Tests." @default.
- W2949403267 cites W2218897511 @default.
- W2949403267 doi "https://doi.org/10.1002/chin.200439205" @default.
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