Abstract

Solid-state NMR is ideal for studying membranes and membrane-associated proteins and peptides that are difficult or impossible to study by other means. Disorder and heterogeneity that are typical of these types of samples, however, makes analysis of the resulting challenging. Examples include (a) heterogeneous distributions of 31P chemical shift tensor parameters that report on phospholipid headgroup disorder; and (b) distributions of internuclear distances measured by rotational-echo double-resonance (REDOR), for example, of heteronuclear pairs within membrane-associated peptides. A method that uses an adaptation of Boltzmann statistics maximum entropy for a model-free approach to analysis of this type of troublesome data provides the means to characterize the distributions of such heterogeneous systems.In the case of REDOR data, the method can reveal multiple distances with relatively few data points, which is of particular benefit in application to biological systems where signal lifetimes are limited by relaxation. This has been recently extended to include spin systems for which the observe nucleus is dipolar coupled to two or three dephasing nuclei. The method reverses the practice where preconceived internuclear distance models are slowly optimised to better “fit” experimental REDOR data, and instead provides the information necessary to construct models based on unbiased data analysis. Examples include application to membrane-associated Alzheimer's β peptide. In the case of chemical shift tensor analysis, we have applied the method to arbitrarily complex phospholipid mixtures for analysis of subtle perturbations, for example, by association of antimicrobial peptides with model membrane systems.

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