Clapperton, J. A. | Search bioRxiv

bioRxiv2025

Chronobot: Deep learning guided time-resolved cryo-EM captures molecular choreography of RecA in homology search

The function of proteins and other biological macromolecules is regulated by conformational dynamics1. Many functional changes take place on millisecond timescales which cannot be experimentally captured by manual sample preparation for cryo-EM2. Here we introduce Chronobot, a robust, data-driven platform enabling reproducible, time-resolved cryo-EM sample preparation to visualize these transient intermediates. We quantify ice thickness, an important precondition and thus a reliable predictor of 3D reconstruction quality, using two complementary methods: a bespoke deep learning model analysing high-speed camera videos of the grid just before vitrification, and detailed ice thickness quantifications of outputs from common TEM screening workflows like the EPU software. Combining these methods enables rapid optimisation, resulting in an 11-fold improvement in cryo-EM sample quality compared to our previously reported workflow3. To demonstrate the Chronobot in capturing transient reaction intermediates visualised through cryo-EM and single particle analysis we focused on RecA homology search. The RecA family of recombinases perform the essential task of rapidly scanning for homologous dsDNA sequences to initiate homologous recombination. The dynamics of these RecA-dsDNA interactions occur on millisecond timescales, limiting structural insights4. We capture time-resolved homology search intermediates at 250 milliseconds. These structures reveal the involvement of the secondary DNA binding site in initial capture of dsDNA before homology sampling occurs. We also observe three-strand homology sampling intermediates, where the homologous strand is not fully displaced, and homology is not stably bound. Our results suggest a model of how RecA-family recombinases function in early homologous recombination, by coordinating the incoming DNA between RecAs various DNA binding sites depending on the stage of homology search and the presence of suUicient homology. We anticipate the Chronobot method to be broadly applicable to processes which cannot be captured by manual sample preparation methods. In addition, by leveraging AI inference, our rapid user feedback mechanisms allow for per-sample optimisation of grid conditions, increasing the likelihood of success and reducing the sample requirements of each time-resolved experiment.

biochemistry↗

bioRxiv2025

Structural Basis of CSN-mediated SCF Deneddylation

Cullin-RING ligases (CRLs) are the largest family of E3 ligases, with their ubiquitination activity dynamically regulated by neddylation and deneddylation by the COP9 signalosome (CSN). CSN-mediated deneddylation not only deactivates CRLs but also enables substrate receptor exchange, fine-tuning CRL specificity. CSN has emerged as a promising drug target, yet the structural basis underlying its catalytic mechanism remains insufficiently understood. To address this, we used cryo-electron microscopy (cryo-EM) analysis of CSN-CRL1 (SCF) complexes to uncover distinct functional states, capturing key intermediates of the deneddylation cycle. The earliest state represents an initial docking step in which CSN remains autoinhibited. In contrast, the catalytic intermediate reveals the fully engaged state, with the CSN5 Ins-1 loop, RBX1 RING, and neddylated Cullin WHB domains repositioned for isopeptide bond cleavage. We further resolve four dissociation intermediates that define the stepwise release of CSN from its deneddylated product, highlighting a central role for RBX1RING in stabilising key interactions throughout this process. Additionally, our structures reveal the previously uncharacterised position of CSNAP, which integrates into the CSN scaffold at a groove formed by CSN3 and CSN8. Together, our study provides a comprehensive mechanistic model of CSN function, linking CRL recognition, catalytic activation, and stepwise disengagement. These insights lay the groundwork for the rational design of CSN inhibitors, offering new opportunities to modulate CRL activity for therapeutic applications. Key TakeawaysO_LIHigh-resolution cryo-EM structures capture key intermediates of the CSN-mediated SCF deneddylation cycle C_LIO_LIStructural identification of CSNAP places it within a previously uncharacterized groove at the interface of CSN3 and CSN8. C_LIO_LIPre-catalytic and catalytic states define the conformational transitions of CSN5Ins-1, RBX1RING, and N8WHB that enable isopeptide bond cleavage. C_LIO_LIFour dissociation intermediates reveal a sequential pathway for CSN disengagement, with RBX1RING playing a central role in stabilising key interactions. C_LI

biochemistry↗