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Prediction of Rate Constant for Supramolecular Systems with Multiconfigurations
Tao Guo1, Haiyan Li1, Li Wu1,2
1Center for Drug Delivery Systems, Shanghai Institute of Materia Medica, Chinese Academy of Sciences , Shanghai 201203, China.
Abstract:
The control of supramolecular systems requires a thorough understanding of their dynamics, especially on a molecular level. It is extremely difficult to determine the thermokinetic parameters of supramolecular systems, such as drug-cyclodextrin complexes with fast association/dissociation processes by experimental techniques. In this paper, molecular modeling combined with novel mathematical relationships integrating the thermodynamic/thermokinetic parameters of a series of isomeric multiconfigurations to predict the overall parameters in a range of pH values have been employed to study supramolecular dynamics at the molecular level. A suitable form of Eyring's equation was derived and a two-stage model was introduced. The new approach enabled accurate prediction of the apparent dissociation/association (k(off)/k(on)) and unbinding/binding (k-r/kr) rate constants of the ubiquitous multiconfiguration complexes of the supramolecular system. The pyronine Y (PY) was used as a model system for the validation of the presented method. Interestingly, the predicted k(off) value ((40 ± 1) × 10(5) s(-1), 298 K) of PY is largely in agreement with that previously determined by fluorescence correlation spectroscopy ((5 ± 3) × 10(5) s(-1), 298 K). Moreover, the k(off)/k(on) and k-r/kr for flurbiprofen-β-cylcodextrin and ibuprofen-β-cyclodextrin systems were also predicted and suggested that the association processes are diffusion-controlled. The methodology is considered to be especially useful in the design and selection of excipients for a supramolecular system with preferred association and dissociation rate constants and understanding their mechanisms. It is believed that this new approach could be applicable to a wide range of ligand-receptor supramolecular systems and will surely help in understanding their complex mechanism.
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