Diffusible subfibrillar aggregates of amyloid proteins are potent neurotoxins and primary suspects in amyloid diseases including Alzheimer's disease. Despite widespread interest, the molecular structures of the amyloid intermediates and the conformational conversions in amyloid misfolding are poorly understood. Here we present a molecular-level examination of sequence-specific secondary structures and supramolecular structures of a neurotoxic amyloid intermediate of the 40-residue β-amyloid (Aβ) peptide involved in Alzheimer's disease. Using solid-state NMR and electron microscopy, we show that, before fibrillization, natively unstructured monomeric Aβ is subject to large conformational changes into a spherical amyloid intermediate of 15–35 nm diameter, which has predominantly parallel β-sheet structures. Structural comparison with Aβ fibrils demonstrates that formation of this β-sheet intermediate I(β) largely defines conformational transitions in amyloid misfolding. Neurotoxicity assays on PC12 cells show that I(β) shows higher toxicity than the fibril, indicating that the β-sheet formation may trigger neurotoxicity.

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We present an approach that speeds up protein solid-state NMR (SSNMR) by 5–20 fold by using paramagnetic doping to condense data-collection time (to ~0.2 s/scan), overcoming a long-standing limitation on slow recycling due to intrinsic 1H T1 longitudinal spin relaxation. By employing low-power schemes under magic-angle spinning at 40 kHz, we show that two-dimensional 13C/13C and 13C/15N SSNMR spectra can be attained for several to tens of nano-moles of β-amyloid fibrils and ubiquitin in just 1–2 days.

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Systematic under-prediction of clearance is frequently associated with in vitro kinetic data when extrapolated using physiological scaling factors, appropriate binding parameters and the well-stirred model. The present study describes a method of removing this systematic bias through application of empirical correction factors derived from regression analyses applied to the in vitro and in vivo data for a defined set of reference compounds. Linear regression lines were established with in vivo intrinsic clearance (CLint), derived from in vivo clearance data and scaled in vitro intrinsic clearance from isolated hepatocyte incubations. The scaled CLint was empirically corrected to a predicted in vivo CLint using the slope and intercept from a uniform weighted linear regression applied to the in vitro to in vivo extrapolation. Cross validation of human data demonstrated that 66% of the reference compounds had a predicted in vivo CLint within two-fold of the observed value. The average absolute fold error (AAFE) for the in vivo CLint predictions was 1.90. For rat, 54% of the compounds had a predicted value within two-fold of the observed and the AAFE was 1.98. Three AstraZeneca projects are used to exemplify how a two-sided prediction interval, applied to the rat regression corrected reference data, can form the basis for assessing the likelihood that, for a given chemical series, the in vitro kinetic data is predictive of in vivo clearance and is therefore appropriate to guide optimisation of compound metabolic stability.

Whether nonconventional hydrogen bonds, such as the C-H···O interaction, are a consequence or a determinant of conformation is a long-running and unresolved issue. Here we outline a solid-state and quantum mechanical study designed to investigate whether a C-H···O interaction can override the significant trans-planar conformational preferences of α-fluoroamide substituents. A profound change in dihedral angle from trans-planar((OCCF)) to cis-planar((OCCF)) observed on introducing an acceptor group for a C-H···O hydrogen bond is consistent with this interaction functioning as a determinant of conformation in certain systems. This testifies to the potential influence of the C-H···O hydrogen bond and is consistent with the assignment of this interaction as a contributor to overall conformation in both model and natural systems.

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