Evstigneev, M.P. and Davies, David B. and Veselkov, A.N. (2006) Stochastic models (cooperative and non-cooperative) for NMR analysis of the hetero-association of aromatic molecules in aqueous solution. Chemical Physics 321 (1-2), pp. 25-33. ISSN 0301-0104.
|
Text
Binder1.pdf Download (365kB) | Preview |
Abstract
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 (0.1 M phosphate buffer, pD = 7.1, T = 298 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.
Metadata
| Item Type: | Article |
|---|---|
| Keyword(s) / Subject(s): | hetero-association model, computational algorithm, NMR chemical shifts, cooperativity parameter, aromatic molecules |
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Natural Sciences |
| Depositing User: | Sandra Plummer |
| Date Deposited: | 13 Jun 2006 |
| Last Modified: | 02 Aug 2023 16:47 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/380 |
Statistics
Additional statistics are available via IRStats2.
Archive Staff Only (login required)
