Computational prediction and molecular mechanism of γ-secretase modulators

Emerging structures and dynamic mechanisms of γ-secretase for Alzheimer's disease

γ-Secretase, called "the proteasome of the membrane," is a membrane-embedded protease complex that cleaves 150+ peptide substrates with central roles in biology and medicine, including amyloid precursor protein and the Notch family of cell-surface receptors. Mutations in γ-secretase and amyloid precursor protein lead to early-onset familial Alzheimer's disease. γ-Secretase has thus served as a critical drug target for treating familial Alzheimer's disease and the more common late-onset Alzheimer's disease as well. However, critical gaps remain in understanding the mechanisms of processive proteolysis of substrates, the effects of familial Alzheimer's disease mutations, and allosteric modulation of substrate cleavage by γ-secretase. In this review, we focus on recent studies of structural dynamic mechanisms of γ-secretase. Different mechanisms, including the "Fit-Stay-Trim," "Sliding-Unwinding," and "Tilting-Unwinding," have been proposed for substrate proteolysis of amyloid precursor protein by γ-secretase based on all-atom molecular dynamics simulations. While an incorrect registry of the Notch1 substrate was identified in the cryo-electron microscopy structure of Notch1-bound γ-secretase, molecular dynamics simulations on a resolved model of Notch1-bound γ-secretase that was reconstructed using the amyloid precursor protein-bound γ-secretase as a template successfully captured γ-secretase activation for proper cleavages of both wildtype and mutant Notch, being consistent with biochemical experimental findings. The approach could be potentially applied to decipher the processing mechanisms of various substrates by γ-secretase. In addition, controversy over the effects of familial Alzheimer's disease mutations, particularly the issue of whether they stabilize or destabilize γ-secretase-substrate complexes, is discussed. Finally, an outlook is provided for future studies of γ-secretase, including pathways of substrate binding and product release, effects of modulators on familial Alzheimer's disease mutations of the γ-secretase-substrate complexes. Comprehensive understanding of the functional mechanisms of γ-secretase will greatly facilitate the rational design of effective drug molecules for treating familial Alzheimer's disease and perhaps Alzheimer's disease in general.

Evaluation of Virtual Screening Strategies for the Identification of γ-Secretase Inhibitors and Modulators

γ-Secretase is an intramembrane aspartyl protease that is important in regulating normal cell physiology via cleavage of over 100 transmembrane proteins, including Amyloid Precursor Protein (APP) and Notch family receptors. However, aberrant proteolysis of substrates has implications in the progression of disease pathologies, including Alzheimer's disease (AD), cancers, and skin disorders. While several γ-secretase inhibitors have been identified, there has been toxicity observed in clinical trials associated with non-selective enzyme inhibition. To address this, γ-secretase modulators have been identified and pursued as more selective agents. Recent structural evidence has provided an insight into how γ-secretase inhibitors and modulators are recognized by γ-secretase, providing a platform for rational drug design targeting this protease. In this study, docking- and pharmacophore-based screening approaches were evaluated for their ability to identify, from libraries of known inhibitors and modulators with decoys with similar physicochemical properties, γ-secretase inhibitors and modulators. Using these libraries, we defined strategies for identifying both γ-secretase inhibitors and modulators incorporating an initial pharmacophore-based screen followed by a docking-based screen, with each strategy employing distinct γ-secretase structures. Furthermore, known γ-secretase inhibitors and modulators were able to be identified from an external set of bioactive molecules following application of the derived screening strategies. The approaches described herein will inform the discovery of novel small molecules targeting γ-secretase.

Association of CSF Aβ38 Levels With Risk of Alzheimer Disease-Related Decline

OBJECTIVE

Experimental studies suggest that the balance between short and long Aβ species might modulate the toxic effects of Aβ in Alzheimer's disease (AD) but clinical evidence is lacking. We studied whether Aβ38 levels in cerebrospinal fluid (CSF) relate to risk of AD dementia and cognitive decline.

METHODS

CSF Aβ38 levels were measured in 656 individuals across two clinical cohorts - the Swedish BioFINDER study and the Alzheimer's Disease Neuroimaging Initiative (ADNI). Cox regression models were used to evaluate the association between baseline Aβ38 levels and risk of AD dementia in AD-biomarker positive individuals (AD+; determined by CSF P-tau/Aβ42 ratio) with subjective cognitive decline (SCD) or mild cognitive impairment (MCI). Linear mixed effects models were used to evaluate the association between baseline Aβ38 levels and cognitive decline as measured by the Mini-Mental State Examination (MMSE) in AD+ participants with SCD, MCI or AD dementia.

RESULTS

In the BioFINDER cohort, high Aβ38 levels were associated with slower decline in MMSE (β = 0.30 points / sd., P = 0.001) and with lower risk of conversion to AD dementia (HR = 0.83 per sd., P = 0.03). In the ADNI cohort, higher Aβ38 levels were associated with less decline in MMSE (β = 0.27, P = 0.01), but not risk of conversion to AD dementia (P = 0.66). Aβ38 levels in both cohorts were significantly associated with both cognitive and clinical outcomes when further adjusted for CSF P-tau or CSF Aβ42 levels.

INTERPRETATION

Higher CSF Aβ38 levels are associated with lower risk of AD-related changes in two independent clinical cohorts. These findings suggest that γ-secretase modulators could be effective as disease-altering therapy.

Characterizing the Chemical Space of γ-Secretase Inhibitors and Modulators

γ-Secretase (GS) is one of the most attractive molecular targets for the treatment of Alzheimer's disease (AD). Its key role in the final step of amyloid-β peptides generation and its relationship in the cascade of events for disease development have caught the attention of many pharmaceutical groups. Over the past years, different inhibitors and modulators have been evaluated as promising therapeutics against AD. However, despite the great chemical diversity of the reported compounds, a global classification and visual representation of the chemical space for GS inhibitors and modulators remain unavailable. In the present work, we carried out a two-dimensional (2D) chemical space analysis from different classes and subclasses of GS inhibitors and modulators based on their structural similarity. Along with the novel structural information available for GS complexes, our analysis opens the possibility to identify compounds with high molecular similarity, critical to finding new chemical structures through the optimization of existing compounds and relating them with a potential binding site.