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.
|Journal||Wiley Interdisciplinary Reviews: Computational Molecular Science|
|Publication status||Accepted/In press - 2021|