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WIREs Comput Mol Sci
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Understanding familial Alzheimer's disease: The fit‐stay‐trim mechanism of γ‐secretase

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Abstract Understanding Alzheimer's disease is a central challenge of the 21st century, as the disease affects tens of millions of people and kills a million people each year, with current drugs having modest effect. This article reviews how computational science integrating new cryo‐electron microscopy structures and biochemical and clinical data has led to a causative model of familial Alzheimer's disease (fAD). The model's basis is open and compact conformational states of the membrane protease γ‐secretase, controlled by transmembrane helix “fingers” that hold the substrate either tightly or loosely. The two states are in thermal equilibrium and lead to different amounts of long and short Aβ peptides, explaining the much‐debated Aβ42/Aβ40 ratio. Pathogenic mutations shift the equilibrium toward the open state by reducing the stability and hydrophobic packing of the enzyme‐substrate complex, which increases toxic Aβ42 and other longer peptide forms compared with Aβ40. In contrast, drugs that selectively target longer, pathogenic Aβ peptides should preferentially stabilize the compact state to reverse this tendency. The model may explain how inherited mutations cause fAD and provides a molecular roadmap for the development of γ‐secretase modulators, one of the most promising causative treatment strategies in current Alzheimer research. In summary, we showcase the power of modern multiscale computational science in integrating biochemical, protein‐structural, and clinical data to elucidate complex disease mechanisms. This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics Data Science > Chemoinformatics
APP cleavage process. (a) APP domains and sequence cleavage by α‐, β‐, and γ‐secretase. (b) Pathways of APP‐C99 cleavage by γ‐secretase. (c) ε‐cleavage by γ‐secretase. (d) Aβ fragments formed via the two pathways. fAD mutations reduce processivity whereas γ‐secretase modulators (GSMs) increase processivity of the Aβ fragments
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The FIST mechanism in relation to the amyloid hypothesis. The semi‐open protein conformation favors the substrate APP‐C99 processing. The binding of γ‐secretase modulators (M) stabilize the protein‐substrate complex, and thus, increase the retention time of the substrate and cause more trimming to form smaller Aβ peptides. The pathogenic fAD mutations reduce the hydrophobic packing and stability of the protein thereby favoring the open conformation of the protein and thus, impairing substrate retention and cleavage to form longer Aβ peptides
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The FIST (fit‐stay‐trim) model. (a) Room‐temperature MD simulations based on the cryo‐EM coordinates revealed two major conformations, compact and open,82,83 defined by the distance between the two catalytic aspartates (D). (b) Apo‐protein simulations88 found three main conformations, closed, semi‐open and open. (c) QSAR indicates the importance of binding energy, dehydration, hydrogen‐bond optimization, and topology (length vs. size).111 (d) GSMs contribute their binding affinity to stabilize the γ‐secretase‐APPC99 complex, giving extended and more precise cleavage.111,115 (e) In contrast, fAD mutations favor the looser state and reduce the stability of the enzyme‐substrate complex, leading to more diverse and longer peptides60
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Structure and function of γ‐secretase and fAD mutations. (a) γ‐secretase structure (PDB code 6IYC47) in a membrane model. (b) Cleavage of APP by β‐secretase followed by γ‐secretase to form Aβ peptides. (c) Topology of presenilin showing TM1‐9, the two catalytic aspartate residues (d), the hydrophilic loop, and maturation cleavage. (d) Diverse phenotypes of fAD mutations. (e) Correlation between Aβ42/Aβ40 ratio and average age of symptom onset (adapted from figure 5 in Sun et al.48: no significance). (f) Reanalysis data adapted from Figure 1 in Tang et al.49 removal of one outlier results gives significant correlation
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Computer and Information Science > Chemoinformatics
Structure and Mechanism > Computational Biochemistry and Biophysics

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