Apolipoprotein E4 has extensive conformational heterogeneity in lipid-free and lipid-bound forms.
Melissa D Stuchell-BreretonMaxwell I ZimmermanJustin J MillerUpasana L MallimadugulaJ Jeremías InciccoDebjit RoyLouis G SmithJasmine CubukBerevan BabanGregory T DeKosterCarl FriedenGregory R BowmanAndrea SorannoPublished in: Proceedings of the National Academy of Sciences of the United States of America (2023)
The ε4-allele variant of apolipoprotein E (ApoE4) is the strongest genetic risk factor for Alzheimer's disease, although it only differs from its neutral counterpart ApoE3 by a single amino acid substitution. While ApoE4 influences the formation of plaques and neurofibrillary tangles, the structural determinants of pathogenicity remain undetermined due to limited structural information. Previous studies have led to conflicting models of the C-terminal region positioning with respect to the N-terminal domain across isoforms largely because the data are potentially confounded by the presence of heterogeneous oligomers. Here, we apply a combination of single-molecule spectroscopy and molecular dynamics simulations to construct an atomically detailed model of monomeric ApoE4 and probe the effect of lipid association. Importantly, our approach overcomes previous limitations by allowing us to work at picomolar concentrations where only the monomer is present. Our data reveal that ApoE4 is far more disordered and extended than previously thought and retains significant conformational heterogeneity after binding lipids. Comparing the proximity of the N- and C-terminal domains across the three major isoforms (ApoE4, ApoE3, and ApoE2) suggests that all maintain heterogeneous conformations in their monomeric form, with ApoE2 adopting a slightly more compact ensemble. Overall, these data provide a foundation for understanding how ApoE4 differs from nonpathogenic and protective variants of the protein.
Keyphrases
- cognitive decline
- high fat diet
- single molecule
- molecular dynamics simulations
- mild cognitive impairment
- adipose tissue
- fatty acid
- single cell
- molecular dynamics
- pseudomonas aeruginosa
- metabolic syndrome
- escherichia coli
- transcription factor
- quantum dots
- healthcare
- atomic force microscopy
- small molecule
- living cells
- mass spectrometry
- protein protein
- deep learning
- binding protein
- artificial intelligence
- data analysis
- neural network
- convolutional neural network
- candida albicans
- high speed