Journal of Molecular Biology最新文献

The steady-state abundance of mRNA is governed by the interplay between transcription and degradation, yet the contribution of RNA stability to cancer biology remains incompletely understood. Here, we systematically investigate RNA decay dynamics across 22 cancer types using RNA-seq data from the Cancer Cell Line Encyclopedia. By inferring transcriptome-wide RNA stability profiles, we identify distinct molecular subtypes defined by post-transcriptional regulation. Integrative analyses reveal that RNA-binding proteins (RBPs) and microRNAs (miRNAs), including SNRPA and RBMX, act as key modulators of RNA stability and are essential for cancer cell proliferation and survival. Somatic mutations, particularly those affecting miRNA binding sites, were found to significantly perturb RNA decay, implicating dysregulation of pathways such as nonsense-mediated decay. Furthermore, machine learning models demonstrate that RNA stability profiles predict sensitivity to 24 anticancer drugs, nominating specific RBPs as candidate biomarkers for therapeutic response. Collectively, our findings establish RNA stability as a pivotal layer of gene regulation in cancer, with broad implications for molecular stratification and precision oncology.

Cellular metabolic systems but also the extracellular environment can generate reactive oxygen species that lead to oxidation of methionine (MET) and interfere with protein folding and protein-protein association. The molecular mechanism of how MET oxidation (MEO) influences conformational stability and binding is not well understood. We employ alchemical free energy simulations to systematically study the influence of MET oxidation on protein-protein binding using the tetramerization domain of the tumor suppression protein p53 as a model system. A single MEO in one tetramerisation domain destabilizes the tetramer by ≈1.1-1.6 kcal/mol depending slightly on the MEO diastereomer. The simulations on double and triple oxidations reveal increased destabilisation (≈ 3-7 kcal/mol) and significant cooperative effects depending on the relative position of the oxidized residues. The MET oxidation effects are of similar magnitude for the change in stability of the human prion protein (HHP) that served as a second model system and also agree with available experimental data. The calculations predict a significant dependence of stability changes on the position of the MEO and also indicate non-additive effects of multiple oxidations which may play a role to protect proteins from oxidative damage and stress. Analysis of the Molecular Dynamics trajectories allowed us to interpret the oxidation effects in molecular detail. The simulation methodology could also serve as a general protocol to analyze single and multiple MET oxidations in other systems and its influence on protein binding and stability.

E. coli RecBCD, a hetero-trimeric helicase and nuclease, functions in double stranded (ds) DNA break repair. RecBCD possesses ATPase motor domains within both RecB (3' to 5') and RecD (5' to 3') and a nuclease domain within RecB (RecB^Nuc). RecBCD binds to double stranded DNA ends and initiates DNA unwinding by first melting several DNA base pairs (bp) using only its binding free energy. The RecB^Nuc domain is docked ∼70 Å from the duplex DNA binding site in RecBCD-DNA structures but appears to be dynamic and able to move from its docked position. Here, we compare DNA binding of RecBCD and a variant, RecB^ΔNucCD, in which the 30 kDa nuclease domain has been deleted. RecBCD binding to a blunt DNA end is enthalpically unfavorable and entropically driven. Deletion of RecB^Nuc results in an increase in DNA binding affinity, suggesting an allosteric effect of RecB^Nuc. RecB^ΔNucCD binding to DNA possessing fully 'pre-melted' DNA ends is associated with a large favorable ΔH_obs, but much smaller than observed for RecBCD, suggesting that deletion of RecB^Nuc limits bp melting from a blunt DNA. We also solved cryo-EM structures showing only 4 bp melted upon RecB^ΔNucCD binding to a blunt ended DNA duplex, less than the 11 bp melted upon RecBCD binding. Thus, the RecB nuclease domain regulates the extent of bp melting by RecBCD. These results suggest that RecB^Nuc may manifest its long-range allosteric effect on DNA binding and DNA melting via linker-linker interactions between RecB and RecC.

The nuclear factor κB (NF-κB) pathway governs innate immunity, orchestrating rapid transcriptional responses to infection. While the pathway is often depicted as a linear signaling cascade, NF-κB functions within a complex network of cooperative partnerships with other transcription factors and co-regulators. Here, current data about these NF-κB-centered transcriptional partnerships are described with a focus on the model organism Drosophila melanogaster and a comparative analysis with homologous mammalian factors. We detail how Drosophila NF-κB factors (Relish, Dif, and Dorsal) cooperate with each other and other transcription regulators, such as Charon, PARP-1, Akirin, SWI/SNF, Mediator, Stat92E, AP-1, FOXO, Nubbin, Caudal, DEAF1, and GATA family transcription factors, to precisely shape immune specificity and homeostasis. We explore the evolutionary conservation of these mechanisms in mammals, where homologous factors similarly shape NF-κB activity to control inflammatory and antiviral responses. While the core principle of NF-κB cooperativity is ancient, the network has expanded and diversified in mammals, reflecting increased genomic and regulatory complexity. This comparative perspective underscores that the functions of NF-κB are fundamentally defined by its context-dependent partnership network.

Understanding RNA structures - essential for uncovering their biological functions, interactions, and therapeutic potential - relies on both experimental techniques and computational approaches increasingly driven by artificial intelligence. The latter are transforming RNA structural research but depend on large, reliable datasets, which remain limited, particularly for RNA-protein and RNA-DNA complexes. To address this gap, we present RNAsolo 2.0 (https://rnasolo.cs.put.poznan.pl/), an open-access database integrating cleaned, non-redundant RNA 3D structures with detailed information on their intermolecular interactions. Building on the original RNAsolo, which has attracted over 16,000 page views from ∼5,600 users, this release adds Rfam-based family classification, >2,500 precompiled benchmark sets, and multimodal representations encompassing sequence, secondary and tertiary structure, as well as torsion angle data. RNAsolo 2.0 enables searches for RNAs that interact with specific proteins, ligands, or ions, and provides an interactive view of their binding interfaces. The tool offers a robust, user-friendly platform for RNA structural biology and next-generation AI-driven modeling.

Microbiota-derived metabolites serve as key messengers mediating host-microbe and microbe-microbe interactions, often through specialized primary metabolic pathways. gutSMASH was initially developed to systematically identify the metabolic gene clusters (MGCs) that encode these pathways in anaerobic gut microbial genomes. Here, we present gutSMASH 2.0, a major update that significantly expands its functionality. This version introduces 14 new detection rules covering 12 additional types of MGCs. The comparative genomics framework was enhanced with 26 experimentally validated MGCs and 15,024 gene clusters from the Cultivated Genome Reference 2 (CGR2) collection. Furthermore, gutSMASH 2.0 integrates transcription factor binding site prediction using LogoMotif's methodology, enabling investigation of MGC regulatory elements. Together, these improvements make gutSMASH a more powerful tool for automated discovery and analysis of niche-determining metabolic pathways in the gut microbiome. gutSMASH 2.0 is freely available at https://gutsmash.bioinformatics.nl/.