کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5377044 | 1504338 | 2006 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Stochastic models (cooperative and non-cooperative) for NMR analysis of the hetero-association of aromatic molecules in aqueous solution
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی تئوریک و عملی
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چکیده انگلیسی
Stochastic cooperative (STOCH-C) and non-cooperative (STOCH-NC) models have been developed for NMR analysis of the hetero-association of aromatic compounds in solution, in order to take into account all physically meaningful association reactions of molecules in which there are no limitations on the lengths of the aggregates and complexes. These algorithmical approaches are compared with previously published basic (BASE) and generalized (GEN) analytical statistical thermodynamical models of hetero-association of biologically active aromatic molecules using the same sets of published NMR data measured under the same solution conditions (0.1Â M phosphate buffer, pDÂ =Â 7.1, TÂ =Â 298Â K). It is shown that, within experimental errors, the BASE analytical model may be used to describe molecular systems characterized by relatively small contributions of hetero-association reactions, whereas the GEN model may be applied to hetero-association reactions of any aromatic compound with different self-association properties. The STOCH-C computational algorithm enabled the effect on hetero-association of the interactions of molecules with different cooperativity parameters of self-association to be estimated for the first time and it is proposed that the algorithm for the stochastic models has great potential for detailed investigation and understanding of the interactions of aromatic molecules in solution.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chemical Physics - Volume 321, Issues 1â2, 25 January 2006, Pages 25-33
Journal: Chemical Physics - Volume 321, Issues 1â2, 25 January 2006, Pages 25-33
نویسندگان
Maxim P. Evstigneev, David B. Davies, Alexei N. Veselkov,