Search bioRxiv⌕ Search

bioRxiv · 10.1101/2024.12.30.630732

Characterization and modulation of human insulin degrading enzyme conformational dynamics to control enzyme activity

Abstract

Insulin degrading enzyme (IDE) is a dimeric M16A zinc metalloprotease that degrades amyloidogenic peptides diverse in shape and sequence, including insulin and amyloid-{beta}, to prevent toxic amyloid fibril formation. IDE has a hollow catalytic chamber formed by two [~]55 kDa N- and C-domains (IDE-N and IDE-C, respectively), in which peptides bind, unfold, and are repositioned for proteolysis. IDE is known to transition between a closed state, poised for catalysis, and an open state, able to release cleavage products and bind a new substrate. Here, we present six cryo-EM structures of the IDE dimer at 3.0-5.1 [A] resolution, obtained in the presence of a sub-saturating concentration of insulin. Combining cryo-EM heterogeneity analysis with all-atom molecular dynamics (MD) simulations, we identified the structural basis and key residues for IDE conformational dynamics that were not previously revealed by IDE static structures. Notably R668 serves as a molecular latch mediating the open-close transition and facilitates key protein motions through charge-swapping interactions at the IDE-N/C interface. Our small-angle X-ray scattering analysis and enzymatic assays of an R668A mutant indicate a profound alteration of conformational dynamics and catalytic activity. By integrating coarse-grained MD simulations, our analysis reveals that IDE unfolds its substrates through the coordinated motion between IDE-N and IDE-C, as well as {beta}-sheet formation between IDE and insulin. Additionally, our time-resolved cryo-EM analysis uncovers IDE allostery within the IDE dimer. Collectively, our findings demonstrate the strength of combining experimental and computational approaches to probe protein dynamics and pave the way for developing substrate-specific modulators of IDE activity.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Mancl, J. M., Liang, w. G., bayhi, N. L., Wei, H., Carragher, B., Potter, C. S., Tang, W.-J.. 2024-12-30. Characterization and modulation of human insulin degrading enzyme conformational dynamics to control enzyme activity. https://doi.org/10.1101/2024.12.30.630732

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Scaling of structural variability of ecDNA polymer condensates with copy number boosts and stabilises oncogene regulatory contacts

Extrachromosomal DNAs (ecDNAs) form highly heterogeneous condensates in cancer cells that drive oncogene overexpression, yet how structural variability coexists with stable gene regulation remains unclear. Here, we develop a minimal polymer physics model of MYC-harbouring COLO320-DM ecDNAs, where BRD4-like complexes bind and bridge cognate sites along ecDNA rings. Above a critical binder concentration, ecDNAs phase separate into condensates exhibiting diverse conformations because of their thermodynamic folding degeneracy. Despite this variability, condensates retain conserved interaction scaffolds that give rise to reproducible contact patterns, including in-trans associated domains (I-TADs), genomic regions enriched in intermolecular regulatory contacts between distinct ecDNAs. We find that condensate 3D architecture follows universal scaling relations with ecDNA copy number, n, remaining robust to model parameter changes. Regulatory contacts within I TADs increase linearly with n, yet they are one order of magnitude stronger than in size matched control regions outside I TADs, whereas their relative fluctuations are markedly suppressed as n increases. This scaling produces enhanced, low-noise regulatory environments for oncogenes embedded within I-TADs, such as PVT1-MYC fusions, whereas the canonical MYC copy, located outside, is less amplified as experimentally observed. Our findings reveal universal polymer physics principles underlying ecDNA condensate organization, offering a mechanistic basis for selective oncogene amplification and potential advantages in cancer progression.

biophysics↗

High-resolution mapping of RNA structural maturation during Cas9 assembly with ABEL-FRET

The structural flexibility of RNA is essential for forming ribonucleoprotein (RNP) complexes, which regulate diverse biological processes. This intrinsic property permits RNA to act as a dynamic scaffold along the assembly pathway as it folds into a specific structure for initial recognition by protein and undergoes conformational rearrangements for functional maturation as a complex. Yet, RNA flexibility and RNP multicomponent assembly create significant obstacles for traditional structural methods. To overcome these challenges, we applied recently developed ABEL-FRET spectroscopy to measure tether-free single-molecule Forster resonance energy transfer (smFRET) over extended observation times. Furthermore, ABEL-FRET enables the unique ability for simultaneous measurements of ultrahigh resolution smFRET and hydrodynamic size of individual complexes, which offers distinct advantages for studying dynamic RNA molecules that undergo assembly via sequential binding events. Using ABEL-FRET, we explored how the guide RNA (gRNA) of CRISPR genome editing system folds and modulates its structural flexibility to carry out the roles required for each assembly state from its unbound apo form to the functional Cas9 RNP state for target DNA cleavage. Multi-perspective view of gRNA structure gained by probing its two primary functional domains enabled to capture dramatic changes in gRNA flexibility that are highly dependent on its specific structural domains as well as assembly states. Collectively, our work with ABEL-FRET highlights the intrinsic link between the structural flexibility of RNA and its functionality in RNP assembly.

biophysics↗

De novo design of functional RNAs through higher-order interactions

Designing RNA sequences that reliably adopt functional three-dimensional structures remains a central challenge in RNA engineering because folding depends on cooperative interactions beyond canonical base pairing. Here we present DS3dRNA, an interaction-based framework for de novo RNA sequence design that combines a three-body statistical potential with physics-guided sequence sampling and supports design against multiple conformations. Across the evaluated benchmarks, DS3dRNA outperformed representative RNA inverse-design methods in native-sequence recovery and agreement between predicted and target structures. Energy-sequence-quality analyses further showed that lower design energies generally accompanied higher sequence recovery and macro-averaged F1 scores (MacroF1). Experimentally tested Mango II designs retained high-affinity fluorogenic activity, and five twister ribozyme designs yielded mean endpoint cleavage fractions of 37.7-50.6%, compared with 23.5% for the wild type. These results establish explicit higher-order interaction scoring as a complementary approach to emerging data-driven RNA design methods and provide a framework for designing functional RNAs from experimental or predicted structural ensembles.

biophysics↗