bims-lances 2024-06-23 papers

Issue of 2024‒06‒23
two papers selected by
James M. Krieger, National Centre for Biotechnology

Int J Mol Sci. 2024 May 23. pii: 5665. [Epub ahead of print]25(11):

Mitigating the Blurring Effect of CryoEM Averaging on a Flexible and Highly Symmetric Protein Complex through Sub-Particle Reconstruction.

Diana S Suder, Shane Gonen.

Many macromolecules are inherently flexible as a feature of their structure and function. During single-particle CryoEM processing, flexible protein regions can be detrimental to high-resolution reconstruction as signals from thousands of particles are averaged together. This "blurring" effect can be difficult to overcome and is possibly more pronounced when averaging highly symmetric complexes. Approaches to mitigating flexibility during CryoEM processing are becoming increasingly critical as the technique advances and is applied to more dynamic proteins and complexes. Here, we detail the use of sub-particle averaging and signal subtraction techniques to precisely target and resolve flexible DARPin protein attachments on a designed tetrahedrally symmetric protein scaffold called DARP14. Particles are first aligned as full complexes, and then the symmetry is reduced by alignment and focused refinement of the constituent subunits. The final reconstructions we obtained were vastly improved over the fully symmetric reconstructions, with observable secondary structure and side-chain placement. Additionally, we were also able to reconstruct the core region of the scaffold to 2.7 Å. The data processing protocol outlined here is applicable to other dynamic and symmetric protein complexes, and our improved maps could allow for new structure-guided variant designs of DARP14.

Keywords: CryoEM; cage; flexibility; protein design; scaffold; single-particle; sub-particle

DOI: https://doi.org/10.3390/ijms25115665

Elife. 2024 Jun 21. pii: RP90606. [Epub ahead of print]12

Automated multiconformer model building for X-ray crystallography and cryo-EM.

Stephanie A Wankowicz, Ashraya Ravikumar, Shivani Sharma, Blake Riley, Akshay Raju, Daniel W Hogan, Jessica Flowers, Henry van den Bedem, Daniel A Keedy, James S Fraser.

In their folded state, biomolecules exchange between multiple conformational states that are crucial for their function. Traditional structural biology methods, such as X-ray crystallography and cryogenic electron microscopy (cryo-EM), produce density maps that are ensemble averages, reflecting molecules in various conformations. Yet, most models derived from these maps explicitly represent only a single conformation, overlooking the complexity of biomolecular structures. To accurately reflect the diversity of biomolecular forms, there is a pressing need to shift toward modeling structural ensembles that mirror the experimental data. However, the challenge of distinguishing signal from noise complicates manual efforts to create these models. In response, we introduce the latest enhancements to qFit, an automated computational strategy designed to incorporate protein conformational heterogeneity into models built into density maps. These algorithmic improvements in qFit are substantiated by superior Rfree and geometry metrics across a wide range of proteins. Importantly, unlike more complex multicopy ensemble models, the multiconformer models produced by qFit can be manually modified in most major model building software (e.g., Coot) and fit can be further improved by refinement using standard pipelines (e.g., Phenix, Refmac, Buster). By reducing the barrier of creating multiconformer models, qFit can foster the development of new hypotheses about the relationship between macromolecular conformational dynamics and function.

Keywords: X-ray crystallography; conformational heterogeneity; cryo-EM; molecular biophysics; none; protein dynamics; structural biology

DOI: https://doi.org/10.7554/eLife.90606