Burnim, A. | Search bioRxiv

bioRxiv2025

Ancestral proteins trace the emergence of substrate specificity and oligomerization within bacterial DEDDy dinucleases

Nucleases play a crucial role in bacterial physiology, influencing processes such as DNA repair, genome maintenance, and host-pathogen interactions. We recently identified a class of nucleases, diDNases, which are encoded on mobile genetic elements and homologous to the house-keeping nanoRNase C (NrnC). Despite their shared structural fold, diDNases and NrnC orthologs exhibit differences. DiDNases form dimers and preferably cleave DNA dinucleotides, whereas NrnC homologs assemble into octamers that do not discriminate between RNA or DNA dinucleotides. Here, we investigate the evolutionary divergence of these enzymes using ancestral sequence reconstruction. Our results show that both diDNases and NrnC orthologs originated from a dimeric ancestor with intermediate substrate preferences. Structural analyses of ancestral and extant dinucleases provide a molecular rational for how gradual changes in conformation gave rise to substrate preferences, oligomeric state, and catalytic efficiency of these related, yet distinct enzyme clades. These findings provide insights into how small structural modifications enable large-scale changes in molecular assembly and functional specialization harnessing a conserved protein fold. In addition, the preference of the early ancestors for DNA dinucleotides and preservation of this activity in all extant enzymes strongly argues for a biological function of DNA dinucleotides.

evolutionary biology↗

bioRxiv2024

Conformational Landscapes of a Class I Ribonucleotide Reductase Complex during Turnover Reveal Intrinsic Dynamics and Asymmetry

Understanding the structural dynamics associated with enzymatic catalysis has been a long-standing goal of biochemistry. With the advent of modern cryo-electron microscopy (cryo-EM), it has become conceivable to redefine a proteins structure as the continuum of all conformations and their distributions. However, capturing and interpreting this information remains challenging. Here, we use classification and deep-learning-based analyses to characterize the conformational heterogeneity of a class I ribonucleotide reductase (RNR) during turnover. By converting the resulting information into physically interpretable 2D conformational landscapes, we demonstrate that RNR continuously samples a wide range of motions while maintaining surprising asymmetry to regulate the two halves of its turnover cycle. Remarkably, we directly observe the appearance of highly transient conformations needed for catalysis, as well as the interaction of RNR with its endogenous reductant thioredoxin also contributing to the asymmetry and dynamics of the enzyme complex. Overall, this work highlights the role of conformational dynamics in regulating key steps in enzyme mechanisms.

biophysics↗