Conformational Ensembles from Experimental Data and Computer Simulations

Conformational Ensembles from Experimental Data

and Computer Simulations

Poster Abstracts

35-POS

Board 35

Teaming up Molecular Dynamics Simulations with Mass-Spectrometry and ssNMR to

Reveal the Dynamic Architecture of the Amyloid Precursor Protein’s Transmembrane

Domain

Alexander Götz

, Hannes Heinel

, Philipp Högel

, Alexander Vogel

, Dieter Langosch

, Daniel

Huster

, Christina Scharnagl

Technical University of Munich, Garching, Germany,

Technical University of Munich,

Freising, Germany.

University of Leipzig, Leipzig, Germany,

Alzheimer’s disease (AD) is characterized by accumulation of toxic β-amyloid (Aβ) in the brain

and neuronal death. Aβ peptides of different lengths are produced by stepwise proteolytic

cleavage within the transmembrane domain (TMD) of the amyloid precursor protein (APP) by γ-

secretase. Aβ toxicity is related to fragment length, which correlates with cleavage at ε48 or ε49.

Mutations located in the C-terminal domain of APP (TM-C) shift production towards the longer,

aggregation-prone Aβ42, associated with early-onset familial AD (FAD). No FAD mutations are

known for the N-terminal domain (TM-N) as well as the central GGVV hinge region. A highly

anisotropic TMD fluctuation pattern defines a hierarchically organized substrate dynamic. To

further investigate the dynamic architecture of the APP TMD, a joint approach of molecular

dynamics simulations, mass-spectrometry and solid-state nuclear magnetic resonance is used,

comparing wild-type (WT) APP with designed G38L, G38P and the I45T FAD mutant. The

TMD’s intrinsic dynamics is studied in POPC and POPE/POPG bilayers, while the environment

of substrate bound in γ-secretase’s aqueous active site is mimicked by a TFE/H

O mixture. No

mutant enhances helix unwinding at the scissile bonds locally. Rather, G38 mutants affect

fluctuations in TM-N, while increased fluctuations upstream the ε-sites in I45T are consistent

with our results for other FADs. Different solvents induce mainly differences of the extent of

TMD fluctuations. Lipid composition does not impact the TMD’s internal dynamics, but

enforces different overall rotational dynamics. Since TM-C dynamics is associated with disease’s

onset, while TM-N dynamics is not, we propose a model where processing of the substrate

utilizes the hierarchy of its TMD flexibility: Binding-induced stiffening of TM-N promotes the

functional importance of motions localized in the cleavage domain.