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ACS Chem Neurosci. 2019 Mar 20;10(3):1826-1840. doi: 10.1021/acschemneuro.8b00725. Epub 2019 Jan 30.

Structural Modeling of γ-Secretase Aβ n Complex Formation and Substrate Processing.

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1
Physics Department T38 , Technical University of Munich , James-Frank-Str. 1 , 85748 Garching , Germany.

Abstract

The intramembrane aspartyl protease γ-secretase (GSEC) cleaves single-span transmembrane helices including the C-terminal fragment of the amyloid precursor protein (APP). This substrate is initially cleaved at the ϵ-site followed by successive processing (trimming) events mostly in steps of three amino acids. GSEC is responsible for the formation of N-terminal APP amyloid-β (Aβ) peptides of different length (e.g., Aβ42) that can form aggregates involved in Alzheimer's disease pathogenesis. The molecular mechanism of GSEC-APP substrate recognition is key for understanding how different peptide products are formed and could help in designing APP-selective modulators. Based on the known structure of apo GSEC and the APP-C99 fragment we have generated putative structural models of the initial binding in three different possible modes using extensive molecular dynamics (MD) simulations. The binding mode with the substrate helix located in a cleft between the transmembrane helices 2 and 3 of the presenilin subunit was identified as a most likely binding mode. Based on this arrangement, the processing steps were investigated using restraint MD simulations to pull the scissile bond (for each processing step) into a transition like (cleavable) state. This allowed us to analyze in detail the motions and energetic contributions of participating residues. The structural model agrees qualitatively well with the influence of many mutations in GSEC and C99. It also explains the effects of inhibitors, cross-linking, as well as spectroscopic data on GSEC substrate binding and can serve as working model for the future planning of structural and biochemical studies.

KEYWORDS:

amyloid precursor formation; membrane protein dynamics; molecular docking; molecular dynamics simulation; γ-Secretase substrate interaction; γ-secretase substrate processing

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