Integrative structural biology of protein-RNA interactions in four dimensions.

Beyond prediction: Why experimental structural biology remains essential in plants.

Structural biology is undergoing a transformative era driven by advances in artificial intelligence (AI)-based protein structure prediction and cryo-electron microscopy. Predictive approaches have dramatically expanded structural coverage across proteomes and are increasingly integrated into experimental workflows. However, protein function frequently depends on dynamic molecular processes including ligand-dependent conformational remodeling, transient interactions, cooperative assembly, and transport-state transitions that remain difficult to define from static computational models alone. These challenges are particularly evident in plants, where signaling pathways often involve environmentally responsive receptor complexes, lineage-expanded regulatory proteins, and transient assemblies. Here, we discuss how experimental structural biology continues to advance plant biology by revealing mechanisms underlying hormone perception, immune receptor activation, transporter function, and enzymatic regulation. From early landmark discoveries such as the crystallization of urease to recent cryo-electron microscopy studies of dynamic signaling complexes, plant systems have repeatedly uncovered molecular architectures, chemically modified intermediates, and regulatory principles that require direct structural and biochemical characterization. Plant proteins also remain markedly underrepresented in structural databases, leaving many plant-specific pathways structurally unresolved. Together, these observations highlight the continuing importance of experimental structural biology for defining biologically relevant molecular states and enabling structure-guided strategies for crop improvement and agricultural biotechnology.

Experimental and Computational Approaches to Identify RNA–Protein Interactions

RNA-binding proteins (RBPs) are essential regulators of RNA metabolism and gene expression, influencing processes such as splicing, stability, localization, and translation. Despite their critical roles in health and disease, including cancer, identifying RNA–protein interactions remains challenging due to technical limitations and biases of existing methods. Here we review and compare experimental techniques—including in vitro affinity purification, in vivo crosslinking, and proximity labeling—and computational prediction tools for RBP identification. We assess their strengths, limitations, and applicability across biological contexts, emphasizing the benefits of integrating experimental and computational strategies. Our analysis provides practical guidelines for selecting appropriate methodologies tailored to different cell types and research goals. These insights aim to facilitate more accurate mapping of RNA–protein interactomes, thereby advancing understanding of RBP functions and supporting the development of novel therapeutic interventions targeting RNA–protein complexes.

Characterization of RNA Structure Dynamics with Trans-Factors Using Single-Molecule Optical Tweezers.

Probing the complexity of cellular RNA folding: Ensembles, intermediates, and isoforms.

RNA molecules populate complex structural landscapes that are continuously reshaped throughout the RNA lifecycle by equilibrium and non-equilibrium processes. Resolving these structural landscapes represents a central challenge in RNA biochemistry. We review recent advances in RNA chemical probing, sequencing, and computational deconvolution technologies that are revolutionizing our ability to measure the complexities of RNA folding in cells and the deep involvement of these complexities in RNA functional mechanisms. We highlight new methods for deconvolving structural ensembles, distinguishing isoform-specific architectures using long-read sequencing, capturing co-transcriptional folding intermediates in vivo, and measuring higher-order RNA structures while also underscoring remaining challenges. We conclude by outlining future directions in probe development, sequencing, and integrative modeling, and discuss how resolving RNA structural ensembles with increasingly high resolution will likely reveal new therapeutic opportunities to selectively target functional RNA heterogeneity.

Going high-throughput: Dynamic conformations and interactions in vivo

Proteins are intrinsically dynamic molecules that continuously explore conformational ensembles to execute biological functions. Conventional structural biology methods rely on in vitro reconstitution of purified components and therefore capture predominantly static snapshots, often overlooking the regulatory roles of the cellular microenvironment, such as molecular crowding, weak interaction networks, and post-translational modifications. This limitation has driven an urgent need to transition from in vitro reconstruction to in vivo characterization within living cells. Nuclear magnetic resonance (NMR) spectroscopy provides atomic-resolution insights into structure and motions spanning multiple timescales, yet its application is constrained by molecular weight limits, isotopic labeling requirements, and inherently low throughput. Cross-linking mass spectrometry (XL-MS) complements NMR by delivering sparse but long-range spatial restraints without an upper molecular weight limit. The integration of NMR and XL-MS establishes a powerful synergistic framework that bridges atomic-resolution local structures and large-scale interaction topologies, thereby enabling comprehensive characterization of protein dynamic conformations and interaction networks in native environments. Here, we review how this integrative strategy advances the understanding of intrinsically disordered proteins, multi-domain proteins, and dynamic protein-protein interaction networks in native cellular environments. We further discuss emerging technological frontiers, including hyperpolarized NMR, photo-cross-linking, organelle-resolved analysis, and artificial intelligence-guided integrative modeling, which together promise to transform our ability to resolve the true functional states of proteins inside cells.

RNA Structure and Its Function.