bims-lances 2024-03-17 papers

Issue of 2024‒03‒17
three papers selected by
James M. Krieger, National Centre for Biotechnology

Nature. 2024 Mar 13.

Time-resolved cryo-EM of G-protein activation by a GPCR.

Makaía M Papasergi-Scott, Guillermo Pérez-Hernández, Hossein Batebi, Yang Gao, Gözde Eskici, Alpay B Seven, Ouliana Panova, Daniel Hilger, Marina Casiraghi, Feng He, Luis Maul, Peter Gmeiner, Brian K Kobilka, Peter W Hildebrand, Georgios Skiniotis.

G-protein-coupled receptors (GPCRs) activate heterotrimeric G proteins by stimulating guanine nucleotide exchange in the Gα subunit1. To visualize this mechanism, we developed a time-resolved cryo-EM approach that examines the progression of ensembles of pre-steady-state intermediates of a GPCR-G-protein complex. By monitoring the transitions of the stimulatory Gs protein in complex with the β2-adrenergic receptor at short sequential time points after GTP addition, we identified the conformational trajectory underlying G-protein activation and functional dissociation from the receptor. Twenty structures generated from sequential overlapping particle subsets along this trajectory, compared to control structures, provide a high-resolution description of the order of main events driving G-protein activation in response to GTP binding. Structural changes propagate from the nucleotide-binding pocket and extend through the GTPase domain, enacting alterations to Gα switch regions and the α5 helix that weaken the G-protein-receptor interface. Molecular dynamics simulations with late structures in the cryo-EM trajectory support that enhanced ordering of GTP on closure of the α-helical domain against the nucleotide-bound Ras-homology domain correlates with α5 helix destabilization and eventual dissociation of the G protein from the GPCR. These findings also highlight the potential of time-resolved cryo-EM as a tool for mechanistic dissection of GPCR signalling events.

DOI: https://doi.org/10.1038/s41586-024-07153-1

J Am Chem Soc. 2024 Mar 13.

Analytical Framework to Understand the Origins of Methyl Side-Chain Dynamics in Protein Assemblies.

Kai Zumpfe, Mélanie Berbon, Birgit Habenstein, Antoine Loquet, Albert A Smith.

Side-chain motions play an important role in understanding protein structure, dynamics, protein-protein, and protein-ligand interactions. However, our understanding of protein side-chain dynamics is currently limited by the lack of analytical tools. Here, we present a novel analytical framework employing experimental nuclear magnetic resonance (NMR) relaxation measurements at atomic resolution combined with molecular dynamics (MD) simulation to characterize with a high level of detail the methyl side-chain dynamics in insoluble protein assemblies, using amyloid fibrils formed by the prion HET-s. We use MD simulation to interpret experimental results, where rotameric hops, including methyl group rotation and χ1/χ2 rotations, cannot be completely described with a single correlation time but rather sample a broad distribution of correlation times, resulting from continuously changing local structure in the fibril. Backbone motion similarly samples a broad range of correlation times, from ∼100 ps to μs, although resulting from mostly different dynamic processes; nonetheless, we find that the backbone is not fully decoupled from the side-chain motion, where changes in side-chain dynamics influence backbone motion and vice versa. While the complexity of side-chain motion in protein assemblies makes it very challenging to obtain perfect agreement between experiment and simulation, our analytical framework improves the interpretation of experimental dynamics measurements for complex protein assemblies.

DOI: https://doi.org/10.1021/jacs.3c12620

J Phys Chem Lett. 2024 Mar 14. 3206-3213

Enhanced Sampling for Conformational Changes and Molecular Mechanisms of Human NTHL1.

Ryan E Odstrcil, Prashanta Dutta, Jin Liu.

The functionalities of proteins rely on protein conformational changes during many processes. Identification of the protein conformations and capturing transitions among different conformations are important but extremely challenging in both experiments and simulations. In this work, we develop a machine learning based approach to identify a reaction coordinate that accelerates the exploration of protein conformational changes in molecular simulations. We implement our approach to study the conformational changes of human NTHL1 during DNA repair. Our results identified three distinct conformations: open (stable), closed (unstable), and bundle (stable). The existence of the bundle conformation can rationalize recent experimental observations. Comparison with an NTHL1 mutant demonstrates that a closely packed cluster of positively charged residues in the linker could be a factor to search when screening for genetic abnormalities. Results will lead to a better modulation of the DNA repair pathway to protect against carcinogenesis.

DOI: https://doi.org/10.1021/acs.jpclett.4c00161