In neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD) and prion diseases, deposits of aggregated disease-specific proteins are found. Oligomeric aggregates are presumed to be the key neurotoxic agent. Here we describe the novel oligomer modulator anle138b [3-(1,3-benzodioxol-5-yl)-5-(3-bromophenyl)-1H-pyrazole], an aggregation inhibitor we developed based on a systematic high-throughput screening campaign combined with medicinal chemistry optimization. In vitro, anle138b blocked the formation of pathological aggregates of prion protein (PrPSc) and of α-synuclein (α-syn), which is deposited in PD and other synucleinopathies such as dementia with Lewy bodies (DLB) and multiple system atrophy (MSA). Notably, anle138b strongly inhibited all prion strains tested including BSE-derived and human prions. Anle138b showed structure-dependent binding to pathological aggregates and strongly inhibited formation of pathological oligomers in vitro and in vivo both for prion protein and α-synuclein. Both in mouse models of prion disease and in three different PD mouse models, anle138b strongly inhibited oligomer accumulation, neuronal degeneration, and disease progression in vivo. Anle138b had no detectable toxicity at therapeutic doses and an excellent oral bioavailability and blood–brain-barrier penetration. Our findings indicate that oligomer modulators provide a new approach for disease-modifying therapy in these diseases, for which only symptomatic treatment is available so far. Moreover, our findings suggest that pathological oligomers in neurodegenerative diseases share structural features, although the main protein component is disease-specific, indicating that compounds such as anle138b that modulate oligomer formation by targeting structure-dependent epitopes can have a broad spectrum of activity in the treatment of different protein aggregation diseases.Electronic supplementary materialThe online version of this article (doi:10.1007/s00401-013-1114-9) contains supplementary material, which is available to authorized users.
Several neurodegenerative diseases, including
Conformational changes and aggregation of specific proteins are hallmarks of a number of diseases, like Alzheimer's disease, Parkinson's disease, and prion diseases. In the case of prion diseases, the prion protein (PrP), a neuronal glycoprotein, undergoes a conformational change from the normal, mainly alpha-helical conformation to a disease-associated, mainly beta-sheeted scrapie isoform (PrP Sc ), which forms amyloid aggregates. This conversion, which is crucial for disease progression, depends on direct PrP C /PrP Sc interaction. We developed a high-throughput assay based on scanning for intensely fluorescent targets (SIFT) for the identification of drugs which interfere with this interaction at the molecular level. Screening of a library of 10,000 drug-like compounds yielded 256 primary hits, 80 of which were confirmed by dose response curves with halfmaximal inhibitory effects ranging from 0.3 to 60 M. Among these, six compounds displayed an inhibitory effect on PrP Sc propagation in scrapie-infected N2a cells. Four of these candidate drugs share an N-benzylidene-benzohydrazide core structure. Thus, the combination of high-throughput in vitro assay with the established cell culture system provides a rapid and efficient method to identify new antiprion drugs, which corroborates that interaction of PrP C and PrP Sc is a crucial molecular step in the propagation of prions. Moreover, SIFTbased screening may facilitate the search for drugs against other diseases linked to protein aggregation.
A high-dimensional time series obtained by simulating a complex and stochastic dynamical system (like a peptide in solution) may code an underlying multiple-state Markov process. We present a computational approach to most plausibly identify and reconstruct this process from the simulated trajectory. Using a mixture of normal distributions we first construct a maximum likelihood estimate of the point density associated with this time series and thus obtain a density-oriented partition of the data space. This discretization allows us to estimate the transfer operator as a matrix of moderate dimension at sufficient statistics. A nonlinear dynamics involving that matrix and, alternatively, a deterministic coarse-graining procedure are employed to construct respective hierarchies of Markov models, from which the model most plausibly mapping the generating stochastic process is selected by consideration of certain observables. Within both procedures the data are classified in terms of prototypical points, the conformations, marking the various Markov states. As a typical example, the approach is applied to analyze the conformational dynamics of a tripeptide in solution. The corresponding high-dimensional time series has been obtained from an extended molecular dynamics simulation.
The point mutations M205S and M205R have been demonstrated to severely disturb the folding and maturation process of the cellular prion protein (PrP(C)). These disturbances have been interpreted as consequences of mutation-induced structural changes in PrP, which are suggested to involve helix 1 and its attachment to helix 3, because the mutated residue M205 of helix 3 is located at the interface of these two helices. Furthermore, current models of the prion protein scrapie (PrP(Sc)), which is the pathogenic isoform of PrP(C) in prion diseases, imply that helix 1 disappears during refolding of PrP(C) into PrP(Sc). Based on molecular-dynamics simulations of wild-type and mutant PrP(C) in aqueous solution, we show here that the native PrP(C) structure becomes strongly distorted within a few nanoseconds, once the point mutations M205S and M205R have been applied. In the case of M205R, this distortion is characterized by a motion of helix 1 away from the hydrophobic core into the aqueous environment and a subsequent structural decay. Together with experimental evidence on model peptides, this decay suggests that the hydrophobic attachment of helix 1 to helix 3 at M205 is required for its correct folding into its stable native structure.
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