Active site geometry stabilization of a presenilin homolog by the lipid bilayer promotes intramembrane proteolysis

Cleavage of membrane proteins in the lipid bilayer by intramembrane proteases is crucial for health and disease. Although different lipid environments can potently modulate their activity, how this is linked to their structural dynamics is unclear. Here, we show that the carboxy-peptidase-like activity of the archaeal intramembrane protease PSH, a homolog of the Alzheimer’s disease-associated presenilin/γ-secretase is impaired in micelles and promoted in a lipid bilayer. Comparative molecular dynamics simulations revealed that important elements for substrate binding such as transmembrane domain 6a of PSH are more labile in micelles and stabilized in the lipid bilayer. Moreover, consistent with an enhanced interaction of PSH with a transition-state analog inhibitor, the bilayer promoted the formation of the enzyme’s catalytic active site geometry. Our data indicate that the lipid environment of an intramembrane protease plays a critical role in structural stabilization and active site arrangement of the enzyme-substrate complex thereby promoting intramembrane proteolysis.


Sample-size estimation
 You should state whether an appropriate sample size was computed when the study was being designed  You should state the statistical method of sample size computation and any required assumptions  If no explicit power analysis was used, you should describe how you decided what sample (replicate) size (number) to use Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission:

Replicates
 You should report how often each experiment was performed  You should include a definition of biological versus technical replication  The data obtained should be provided and sufficient information should be provided to indicate the number of independent biological and/or technical replicates  If you encountered any outliers, you should describe how these were handled  Criteria for exclusion/inclusion of data should be clearly stated  High-throughput sequence data should be uploaded before submission, with a private link for reviewers provided (these are available from both GEO and ArrayExpress) Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: No power analysis was performed at study design. The biochemical experiments showed only very little interexperimental variations, therefore a common number of 3-6 experiments was performed.
A definition of biological replicates can be found in the figure legend of Figure 1C. In all figures, the biological replicates describe experiments with independent protease preparations. For the immunoblots and/or mass spectrometry spectra in Figures 1, 2, 3, 4, 7 and 8, respectively, one representative figure from several independent biological replicates was shown. The number of experiments performed are indicated in the respective figure legends.
For each system in the computational analysis, three different simulations were performed as stated in the Materials and Methods section as well as in the corresponding figure legends.

Statistical reporting
 Statistical analysis methods should be described and justified  Raw data should be presented in figures whenever informative to do so (typically when N per group is less than 10)  For each experiment, you should identify the statistical tests used, exact values of N, definitions of center, methods of multiple test correction, and dispersion and precision measures (e.g., mean, median, SD, SEM, confidence intervals; and, for the major substantive results, a measure of effect size (e.g., Pearson's r, Cohen's d)  Report exact p-values wherever possible alongside the summary statistics and 95% confidence intervals. These should be reported for all key questions and not only when the p-value is less than 0.05.
Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: (For large datasets, or papers with a very large number of statistical tests, you may upload a single table file with tests, Ns, etc., with reference to sections in the manuscript.)

Group allocation
 Indicate how samples were allocated into experimental groups (in the case of clinical studies, please specify allocation to treatment method); if randomization was used, please also state if restricted randomization was applied  Indicate if masking was used during group allocation, data collection and/or data analysis Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: Additional data files ("source data")  We encourage you to upload relevant additional data files, such as numerical data that are represented as a graph in a figure, or as a summary table  Where provided, these should be in the most useful format, and they can be uploaded as "Source data" files linked to a main figure or table  Include model definition files including the full list of parameters used  Include code used for data analysis (e.g., R, MatLab)  Avoid stating that data files are "available upon request" Please indicate the figures or tables for which source data files have been provided: For the biochemical experiments, no statistical analysis was performed because of the large effect size.
Group allocation is not applicable for this study For all figures the source data are provided in the respective source data files. The coordinate and trajectory files of all simulations can be accessed at Zenodo: https://doi.org/10.5281/zenodo.6487373