Mechanisms of γ-Secretase Activation and Substrate Processing.

ACS Cent Sci

Center for Computational Biology and Department of Molecular Biosciences, and Department of Medicinal Chemistry, School of Pharmacy, University of Kansas, Lawrence, Kansas 66047, United States.

Published: June 2020

Amyloid β-peptide, the principal component of characteristic cerebral plaques of Alzheimer's disease (AD), is produced through intramembrane proteolysis of the amyloid precursor protein (APP) by γ-secretase. Despite the importance in the pathogenesis of AD, the mechanisms of intramembrane proteolysis and substrate processing by γ-secretase remain poorly understood. Here, complementary all-atom simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method and biochemical experiments were combined to investigate substrate processing of wildtype and mutant APP by γ-secretase. The GaMD simulations captured spontaneous activation of γ-secretase, with hydrogen bonded catalytic aspartates and water poised for proteolysis of APP at the ε cleavage site. Furthermore, GaMD simulations revealed that familial AD mutations I45F and T48P enhanced the initial ε cleavage between residues Leu49-Val50, while M51F mutation shifted the ε cleavage site to the amide bond between Thr48-Leu49. Detailed analysis of the GaMD simulations allowed us to identify distinct low-energy conformational states of γ-secretase, different secondary structures of the wildtype and mutant APP substrate, and important active-site subpockets for catalytic function of the enzyme. The simulation findings were highly consistent with experimental analyses of APP proteolytic products using mass spectrometry and Western blotting. Taken together, the GaMD simulations and biochemical experiments have enabled us to elucidate the mechanisms of γ-secretase activation and substrate processing, which should facilitate rational computer-aided drug design targeting this functionally important enzyme.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7318072PMC
http://dx.doi.org/10.1021/acscentsci.0c00296DOI Listing

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