The control of supramolecular systems requires a thorough understanding of their dynamics on a molecular level. We present fluorescence correlation spectroscopy (FCS) as a powerful spectroscopic tool to study supramolecular dynamics with single molecule sensitivity. The formation of a supramolecular complex between beta-cyclodextrin (beta-CD) as host and pyronines Y (PY) and B (PB) as guests is studied by FCS. Global target analysis of full correlation curves with a newly derived theoretical model yields in a single experiment the fluorescence lifetimes and the diffusion coefficients of free and complexed guests and the rate constants describing the complexation dynamics. These data give insight into the recently published surprising fact that the association equilibrium constant of beta-CD with PY is much lower than that with the much bulkier guest PB. FCS shows that the stability of the complexes is dictated by the dissociation and not by the association process. The association rate constants are very similar for both guests and among the highest reported for this type of systems, although much lower than the diffusion-controlled collision rate constant. A two-step model including the formation of an encounter complex allows one to identify the unimolecular inclusion reaction as the rate-limiting step. Simulations indicate that this step may be controlled by geometrical and orientational requirements. These depend on critical molecular dimensions which are only weakly affected by the different alkyl substituents of PY and PB. Diffusion coefficients of PY and PB, of their complexes, and of rhodamine 110 are given and compared to those of similar molecules.

The systematic description of the complex photophysical behaviour of pyrene in surfactant solutions in combination with a quantitative model for the surfactant concentrations reproduces with high accuracy the steady-state and the time resolved fluorescence intensity of pyrene in surfactant solutions near the cmc, both in the monomer and in the excimer emission bands. We present concise model equations that can be used for the analysis of the pyrene fluorescence intensity in order to estimate fundamental parameters of the pyrene-surfactant system, such as the binding equilibrium constant K of pyrene to a given surfactant micelle, the rate constant of excimer formation in micelles, and the equilibrium constant of pyrene-surfactant quenching. The values of the binding equilibrium constant K(TX100)=3300·10³ M⁻¹ and K(SDS)=190·10³ M⁻¹ for Triton X-100 (TX100) and SDS micelles, respectively, show that the partition of pyrene between bulk water and micelles cannot be ignored, even at relatively high surfactant concentrations above the cmc. We apply the model to the determination of the cmc from the pyrene fluorescence intensity, especially from the intensity ratio at two vibronic bands in the monomer emission or from the ratio of excimer to monomer emission intensity. We relate the finite width of the transition region below and above the cmc with the observed changes in the pyrene fluorescence in this region.

The oligomers formed during the early steps of amyloid aggregation are thought to be responsible for the neurotoxic damage associated with Alzheimer's disease. It is therefore of great interest to characterize this early aggregation process and the aggregates formed, especially for the most significant peptide in amyloid fibrils, Amyloid-β(1-42) (Aβ42). For this purpose, we directly monitored the changes in size and concentration of initially monomeric Aβ42 samples, using Fluorescence Correlation Spectroscopy. We found that Aβ42 undergoes aggregation only when the amount of amyloid monomers exceeds the critical aggregation concentration (cac) of about 90 nM. This spontaneous, cooperative process resembles surfactants self-assembly and yields stable micellelike oligomers whose size (≈50 monomers, R h ≈ 7-11 nm) and elongated shape are independent of incubation time and peptide concentration. These findings reveal essential features of in vitro amyloid aggregation, which may illuminate the complex in vivo process.Alzheimer's disease (AD) is a neurodegenerative disease characterized by the presence of Amyloid-β plaques in the brain. Although the causal relationship between these protein fibrillar aggregates and the neurodegenerative disease has not been established yet, the 'amyloid hypothesis' , that accumulation and aggregation of amyloid-β peptide initiates a cascade of neurodegenerative events, has been widely accepted [1][2][3] . Impairment of Amyloid-β clearance in AD patients seems to be the main cause for accumulation of the peptide 4,5 . It is thought that the neurotoxic species that trigger the amyloid cascade leading to neurodegeneration are early non-fibrillar aggregates, which may also be the precursors of the amyloid fibrils 2,6-8 . The dominant peptides in amyloid fibrils are Amyloid-β(1-42) (Aβ42) and Amyloid-β(1-40) (Aβ40), with Aβ42 being the more fibrillogenic of the two, with a much stronger tendency to aggregate [9][10][11] .There is ample literature on the mechanism underlying amyloid fibril formation 12,13 . Most kinetic studies agree on a complex nucleation-growth mechanism, where the differences in the microscopic rates and in the relevance of secondary nucleation processes determine the degree of aggregation and can account for the differences between Aβ40 and Aβ42 11,14 . For such nucleation-dependent processes, a critical aggregation concentration (cac) is predicted, above which aggregation takes place 10 . For Aβ40 the formation of micelle-like intermediates was reported, with a critical concentration in the micromolar range [15][16][17] , whereas recent studies have found nanomolar cac values for both Aβ40 and Aβ42 [18][19][20] . The latter values fit better with the reported physiological concentrations of Aβ in the picomolar to nanomolar range which may be locally higher due to accumulation or impairment of clearance 4,5,18,21,22 . A possible reason for the discrepancy in the cac values may be the strong adsorption of Amyloids Aβ40 and Aβ42 to interfaces 23 , which can lead to great ...

An empirical model for the concentrations of monomeric and micellized surfactants in solution is presented as a consistent approach for the quantitative analysis of data obtained with different experimental techniques from surfactant solutions. The concentration model provides an objective definition of the critical micelle concentration (cmc) and yields precise and well defined values of derived physical parameters. The use of a general concentration model eliminates subjective graphical procedures, reduces methodological differences, and thus allows one to compare directly the results of different techniques or to perform global fits. The application and validity of the model are demonstrated with electrical conductivity, surface tension, NMR chemical shift, and self-diffusion coefficient data for the surfactants SDS, CTAB, DTAB, and LAS. In all cases, the derived models yield excellent fits of the data. It is also shown that there is no need to assume the existence of different premicellar species in order to explain the chemical shifts and self-diffusion coefficients of SDS as claimed recently by some authors.