Following the widely spread EPR spin-label applications for biosystem characterization, a novel approach is proposed for EPR-based characterization of biosystem complexity. Hereto a computational method based on a hybrid evolutionary optimization (HEO) is introduced. The enormous volume of information obtained from multiple HEO runs is reduced with a novel so-called GHOST condensation method for automatic detection of the degree of system complexity through the construction of two-dimensional solution distributions. The GHOST method shows the ability of automatic quantitative characterization of groups of solutions, e.g. the determination of average spectral parameters and group contributions. The application of the GHOST condensation algorithm is demonstrated on four synthetic examples of different complexity and applied to two physiologically relevant examples--the determination of domains in biomembranes (lateral heterogeneity) and the study of the low-resolution structure of membrane proteins.

(A) Low-angle X-ray scattering (LAXS) of oriented, fully hydrated model membranes yields bending modulus (KC) and (B) wide-angle X-ray scattering (WAXS) yields lipid chain order parameter (SX-ray).

The phase behavior of binary mixtures of egg sphingomyelin and cholesterol has been inspected by attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy in the amide I' band region of the spectrum. Because cholesterol does not have any major absorption bands in this region, effects seen in the spectra of mixtures of sphingomyelin and cholesterol can be attributed to the change in the lipid phase and to the interaction with cholesterol. It is shown that the temperature dependence of the overall bandwidth of the amide I' band displays a phase-specific behavior. In addition, it is observed that the amide I' band for a sample exhibiting phase coexistence can be described by a linear combination of the spectra of the individual lipid phases. Description of changes in the amide I' band shape and by that the study of possible hydrogen bonding interactions of sphingomyelin with cholesterol was assisted by the use of curve fitting. It turns out that the presence of hydrogen bonding between hydroxyl group of cholesterol and carbonyl group of sphingomyelin is obscured by the complexity of different possible hydrogen bonding and coupling between the N-H (N-D) and the CO group vibrations.