bims-lances 2025-03-16 papers

Nat Commun. 2025 Mar 12. 16(1): 2458

Conformational landscapes of a class I ribonucleotide reductase complex during turnover reveal intrinsic dynamics and asymmetry.

Da Xu, William C Thomas, Audrey A Burnim, Nozomi Ando.

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 protein's 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.

DOI: https://doi.org/10.1038/s41467-025-57735-4

Structure. 2025 Mar 05. pii: S0969-2126(25)00057-7. [Epub ahead of print]

Automated model-free analysis of cryo-EM volume ensembles with SIREn.

Laurel F Kinman, Maria V Carreira, Barrett M Powell, Joseph H Davis.

Cryogenic electron microscopy (cryo-EM) has the potential to capture snapshots of proteins in motion and generate hypotheses linking conformational states to biological function. This potential has been increasingly realized by the advent of machine learning models that allow 100s-1,000s of 3D density maps to be generated from a single dataset. How to identify distinct structural states within these volume ensembles and quantify their relative occupancies remain open questions. Here, we present an approach to inferring variable regions directly from a volume ensemble based on the statistical co-occupancy of voxels, as well as a 3D convolutional neural network that predicts binarization thresholds for volumes in an unbiased and automated manner. We show that these tools recapitulate known heterogeneity in a variety of simulated and real cryo-EM datasets and highlight how integrating these tools with existing data processing pipelines enables improved particle curation.

Keywords: cryo-EM; cryo-ET; cryoDRGN; deep learning; structural biology

DOI: https://doi.org/10.1016/j.str.2025.02.004

J Struct Biol. 2025 Mar 05. pii: S1047-8477(25)00019-X. [Epub ahead of print]217(2): 108184

Improving CryoEM maps of symmetry-mismatched macromolecular assemblies: A case study on the flagellar motor.

Prashant K Singh, T M Iverson.

Advances in cryo-electron microscopy instrumentation and sample preparation have significantly improved the ability to collect quality data for biomolecular structures. However, achieving resolutions consistent with data quality remains challenging in structures with symmetry mismatches. As a case study, the bacterial flagellar motor is a large complex essential for bacterial chemotaxis and virulence. This motor contains a smaller membrane-supramembrane ring (MS-ring) and a larger cytoplasmic ring (C-ring). These two features have a 33:34 symmetry mismatch when expressed in E. coli. Because close symmetry mismatches are the most difficult to deconvolute, this makes the flagellar motor an excellent model system to evaluate refinement strategies for symmetry mismatch. We compared the performance of masked refinement, local refinement, and particle subtracted refinement on the same data. We found that particle subtraction prior to refinement was critical for approaching the smaller MS-ring. Additional processing resulted in final resolutions of 3.1 Å for the MS-ring and 3.0 Å for the C-ring, which improves the resolution of the MS-ring by 0.3 Å and the resolution of the C-ring by 1.0 Å as compared to past work. Although particle subtraction is fairly well-established, it is rarely applied to problems of symmetry mismatch, making this case study a valuable demonstration of its utility in this context.

Keywords: C-ring; Cryo electron microscopy; CryoEM; Flagellar motor; Focused refinement; Local refinement; MS-ring; Macromolecular complexes; Methods; Particle subtraction; Stoichiometric heterogeneity; Symmetry mismatch

DOI: https://doi.org/10.1016/j.jsb.2025.108184

Proc Natl Acad Sci U S A. 2025 Mar 18. 122(11): e2415674122

Integrative spatiotemporal modeling of biomolecular processes: Application to the assembly of the nuclear pore complex.

Andrew P Latham, Wanlu Zhang, Jeremy O B Tempkin, Shotaro Otsuka, Jan Ellenberg, Andrej Sali.

Dynamic processes involving biomolecules are essential for the function of the cell. Here, we introduce an integrative method for computing models of these processes based on multiple heterogeneous sources of information, including time-resolved experimental data and physical models of dynamic processes. First, for each time point, a set of coarse models of compositional and structural heterogeneity is computed (heterogeneity models). Second, for each heterogeneity model, a set of static integrative structure models is computed (a snapshot model). Finally, these snapshot models are selected and connected into a series of trajectories that optimize the likelihood of both the snapshot models and transitions between them (a trajectory model). The method is demonstrated by application to the assembly process of the human nuclear pore complex in the context of the reforming nuclear envelope during mitotic cell division, based on live-cell correlated electron tomography, bulk fluorescence correlation spectroscopy-calibrated quantitative live imaging, and a structural model of the fully assembled nuclear pore complex. Modeling of the assembly process improves the model precision over static integrative structure modeling alone. The method is applicable to a wide range of time-dependent systems in cell biology and is available to the broader scientific community through an implementation in the open source Integrative Modeling Platform (IMP) software.

Keywords: integrative modeling; molecular dynamics; nuclear pore complex

DOI: https://doi.org/10.1073/pnas.2415674122

Brief Bioinform. 2025 Mar 04. pii: bbaf091. [Epub ahead of print]26(2):

DockEM: an enhanced method for atomic-scale protein-ligand docking refinement leveraging low-to-medium resolution cryo-EM density maps.

Jing Zou, Wenyi Zhang, Jun Hu, Xiaogen Zhou, Biao Zhang.

Protein-ligand docking plays a pivotal role in virtual drug screening, and recent advancements in cryo-electron microscopy (cryo-EM) technology have significantly accelerated the progress of structure-based drug discovery. However, the majority of cryo-EM density maps are of medium to low resolution (3-10 Å), which presents challenges in effectively integrating cryo-EM data into molecular docking workflows. In this study, we present an updated protein-ligand docking method, DockEM, which leverages local cryo-EM density maps and physical energy refinement to precisely dock ligands into specific protein binding sites. Tested on a dataset of 121 protein-ligand compound, our results demonstrate that DockEM outperforms other advanced docking methods. The strength of DockEM lies in its ability to incorporate cryo-EM density map information, effectively leveraging the structural information of ligands embedded within these maps. This advancement enhances the use of cryo-EM density maps in virtual drug screening, offering a more reliable framework for drug discovery.

Keywords: REMC simulation; cryo-EM; docking; protein–ligand; refinement

DOI: https://doi.org/10.1093/bib/bbaf091