The study explores the architecture of the nuclear basket within the nuclear pore complex (NPC), focusing on its role in mRNA surveillance and chromatin organization. Using in-cell cryo-electron tomography and integrative modeling, the nuclear baskets of yeast and mammals were analyzed. The nuclear basket is anchored by a double nuclear ring with coiled-coil proteins like Mlp/Tpr, which form struts that end in distal densities, likely docking sites for mRNA. Significant structural variability was observed between species, highlighting the modular nature of the NPC. The double nuclear ring is essential for the basket's stability, which is compromised in NPCs with a single ring. Additionally, a 20-nm exclusion zone around the basket suggests its role in chromatin organization. This study provides a comprehensive structural blueprint of the nuclear basket, offering insights into its function and evolutionary significance across organisms.

PDB-Dev Database links to the models: Collection Identifier: PDBDEV_G_1000004

Yeast NPC Basket: 9A8N, 9A8M  Mammalian NPC Basket: 9A8L, 9A8K

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The study "COCONUT: An Analysis of Coiled-Coil Regions in Proteins" presents the development of COCONUT, a computational tool designed to predict the stability and orientation of coiled-coil motifs in proteins. Coiled-coils, found in 10% of all proteins, are crucial for molecular recognition and protein folding. Using machine learning, COCONUT analyzes hydrophobic core interactions that determine the specificity and stability of coiled-coils. The tool was validated through various scenarios, accurately predicting dimer orientation, residue pairings, and constructing n-stranded models. This research provides a valuable framework for modeling protein assemblies, with implications for protein engineering and therapeutic development. COCONUT's predictions offer new insights into coiled-coil structures, advancing the understanding of these critical protein motifs.

This study focuses on developing computational models to design inhibitors against the Nipah virus (NiV), a deadly pathogen with no approved drugs or vaccines. Researchers modeled the structures of NiV proteins and identified potential therapeutic targets, including the F, G, and M proteins. We used homology modeling and molecular dynamics simulations to predict peptide and small molecule inhibitors. These inhibitors showed strong binding affinities, with the F protein inhibitor potentially blocking viral fusion with the host cell, and the M protein inhibitor preventing virus budding. Additionally, we analyzed sequence variations among different NiV strains to ensure the efficacy of these inhibitors across variants. Our models and predicted inhibitors are made publicly available for further experimental validation. The approach demonstrates the potential for computational tools to accelerate therapeutic development against emerging viruses like NiV.

This study focuses on the 14-3-3 protein family, particularly the ζ isoform, which plays a crucial role in cellular processes by acting as a scaffold for phosphoproteins. We identified that 14-3-3ζ possesses ATPase activity, an atypical feature for this protein family, which is usually known for its role in phosphoprotein binding. This study mapped ATP binding sites within the 14-3-3ζ protein, revealing that ATP binds at the amphipathic groove, which is also the site for phosphoprotein interaction, and at the dimer interface. Mutational analysis indicated that residues E131 and E180 in the amphipathic groove are critical for ATP hydrolysis. Interestingly, ATP binding at the dimer interface acts as a positive allosteric modulator, enhancing ATPase activity at the amphipathic groove. The study also showed that ATP binding could negatively regulate the binding of certain non-phosphorylated peptides, like ExoS, to 14-3-3ζ, offering insights into the dual regulatory roles of ATP in 14-3-3ζ function.

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