Beyond the US-SOMO-AF database: a new website for hydrodynamic, structural, and circular dichroism calculations on user-supplied structures

A Perspective on the Prospective Use of AI in Protein Structure Prediction

AlphaFold2 (AF2) and RoseTTaFold (RF) have revolutionized structural biology, serving as highly reliable and effective methods for predicting protein structures. This article explores their impact and limitations, focusing on their integration into experimental pipelines and their application in diverse protein classes, including membrane proteins, intrinsically disordered proteins (IDPs), and oligomers. In experimental pipelines, AF2 models help X-ray crystallography in resolving the phase problem, while complementarity with mass spectrometry and NMR data enhances structure determination and protein flexibility prediction. Predicting the structure of membrane proteins remains challenging for both AF2 and RF due to difficulties in capturing conformational ensembles and interactions with the membrane. Improvements in incorporating membrane-specific features and predicting the structural effect of mutations are crucial. For intrinsically disordered proteins, AF2's confidence score (pLDDT) serves as a competitive disorder predictor, but integrative approaches including molecular dynamics (MD) simulations or hydrophobic cluster analyses are advocated for accurate dynamics representation. AF2 and RF show promising results for oligomeric models, outperforming traditional docking methods, with AlphaFold-Multimer showing improved performance. However, some caveats remain in particular for membrane proteins. Real-life examples demonstrate AF2's predictive capabilities in unknown protein structures, but models should be evaluated for their agreement with experimental data. Furthermore, AF2 models can be used complementarily with MD simulations. In this Perspective, we propose a "wish list" for improving deep-learning-based protein folding prediction models, including using experimental data as constraints and modifying models with binding partners or post-translational modifications. Additionally, a meta-tool for ranking and suggesting composite models is suggested, driving future advancements in this rapidly evolving field.

Spatial arrangement of functional domains in OxyS stress response sRNA

Small noncoding RNAs are an important class of regulatory RNAs in bacteria, often regulating responses to changes in environmental conditions. OxyS is a 110 nt, stable, trans-encoded small RNA found in Escherichia coli and is induced by an increased concentration of hydrogen peroxide. OxyS has an important regulatory role in cell stress response, affecting the expression of multiple genes. In this work, we investigated the structure of OxyS and the interaction with fhlA mRNA using nuclear magnetic resonance spectroscopy, small-angle X-ray scattering, and unbiased molecular dynamics simulations. We determined the secondary structures of isolated stem-loops and confirmed their structural integrity in OxyS. Unexpectedly, stem-loop SL4 was identified in the region that was predicted to be unstructured. Three-dimensional models of OxyS demonstrate that OxyS adopts an extended structure with four solvent-exposed stem-loops, which are available for interaction with other RNAs and proteins. Furthermore, we provide evidence of base-pairing between OxyS and fhlA mRNA.

Proceedings of the 25th Analytical Ultracentrifugation Workshops and Symposium

The 25th International Analytical Ultracentrifugation (AUC) Workshops and Symposium (AUC2022) took place at the University of Lethbridge in Lethbridge, Canada, in July 2022. In total, 104 attendees (Attendance Profile: 104 attendees, 69 in-person, 35 remote. Brazil 1, Canada 24, China 1, Czech Republic 2, Finland 1, France 3, Germany 22, India 3, Italy 1, Japan 4, Spain 1, Switzerland 3, Taiwan 1, United Kingdom 5, United States 32) participated in the event and presented the latest advances in the field. While the primary focus of the conference was to showcase the applications of AUC in chemical, life sciences, and nanoparticle disciplines, several presentations also integrated complementary methods, such as isothermal titration calorimetry, microscale thermophoresis, light scattering (static and dynamic), small-angle X-ray scattering, X-ray crystallography, and cryo-electron microscopy. Additionally, the delegates gained valuable hands-on experience from 20 workshops covering a broad range of applications, experimental designs and systems, and the latest software innovations in solution biophysics. The AUC2022 special volume highlights the sustained innovation, utility and relevance of AUC and related solution biophysical methods across various disciplines, including biochemistry, structural biology, synthetic polymer chemistry, carbohydrate chemistry, protein and nucleic acid characterization, nano-science, and macromolecular interactions.