Copper stabilizes antiparallel ß-sheet fibrils of the amyloid ß40 (Aß40)-Iowa variant.

Cerebral amyloid angiopathy (CAA) is a vascular disorder that primarily involves deposition of the 40-residue-long ß-amyloid peptide (Aß40) in and along small blood vessels of the brain. CAA is often associated with Alzheimer's disease (AD), which is characterized by amyloid plaques in the brain parenchyma enriched in the Aß42 peptide. Several recent studies have suggested a structural origin that underlies the differences between the vascular amyloid deposits in CAA and the parenchymal plaques in AD. We previously have found that amyloid fibrils in vascular amyloid contain antiparallel ß-sheet, whereas previous studies by other researchers have reported parallel ß-sheet in fibrils from parenchymal amyloid. Using X-ray fluorescence microscopy, here we found that copper strongly co-localizes with vascular amyloid in human sporadic CAA and familial Iowa-type CAA brains compared with control brain blood vessels lacking amyloid deposits. We show that binding of Cu(II) ions to antiparallel fibrils can block the conversion of these fibrils to the more stable parallel, in-register conformation and enhances their ability to serve as templates for seeded growth. These results provide an explanation for how thermodynamically less stable antiparallel fibrils may form amyloid in or on cerebral vessels by using Cu(II) as a structural cofactor.

Rapid Rescoring and Refinement of Ligand-Receptor Complexes Using Replica Exchange Molecular Dynamics with a Monte Carlo Pose Reservoir.

Virtual screening (VS) involves generation of poses for a library of ligands and ranking using simplified energy functions and limited flexibility. Top-scored poses are used to rank and prioritize ligands. Here, we adapt the reservoir replica exchange molecular dynamics (res-REMD) method to rerank poses generated through VS. REMD simulations are carried out but with occasional Monte Carlo jumps to alternate VS-generated poses using a Metropolis criterion. The simulations converge within 10 ns for all systems, generating populations of alternate poses in the context of fully flexible ligand and protein side chains. The protocol is applied to four model protein-ligand complexes, where DOCK resulted in two successes and two scoring failures. In all four systems, the most populated cluster from the final ensemble exhibits high similarity to the crystallographic pose with ligand RMSD values under 2.0 Å. Both DOCK failures were rescued. For one DOCK success, the protocol identified the correct pose but also sampled an alternate pose at equal probability. Opportunities for future improvements and extensions are discussed.