RNA Binding: Getting Specific about Specificity

Advancing ecotoxicity assessment: Leveraging pre-trained model for bee toxicity and compound degradability prediction

The prediction of ecological toxicity plays an increasingly important role in modern society. However, the existing models often suffer from poor performance and limited predictive capabilities. In this study, we propose a novel approach for ecological toxicity assessment based on pre-trained models. By leveraging pre-training techniques and graph neural network models, we establish a highperformance predictive model. Furthermore, we incorporate a variational autoencoder to optimize the model, enabling simultaneous discrimination of toxicity to bees and molecular degradability. Additionally, despite the low similarity between the endogenous hormones in bees and the compounds in our dataset, our model confidently predicts that these hormones are non-toxic to bees, which further strengthens the credibility and accuracy of our model. We also discovered the negative correlation between the degradation and bee toxicity of compounds. In summary, this study presents an ecological toxicity assessment model with outstanding performance. The proposed model accurately predicts the toxicity of chemicals to bees and their degradability capabilities, offering valuable technical support to relevant fields.

Electrostatic modulation of multiple binding events between loquacious-PD and double-stranded RNA

Electrostatics can alter the RNA-binding properties of proteins that display structure selectivity without sequence specificity. Loquacious-PD relies on this broad scope response to mediate the interaction of endonucleases with double stranded RNAs. Multimodal spectroscopic probes with in situ perturbations reveal an efficient and stable binding mechanism that disfavors high protein density complexes and is sensitive to local electrostatics.

Two distinct binding modes provide the RNA-binding protein RbFox with extraordinary sequence specificity

Specificity of RNA-binding proteins for target sequences varies considerably. Yet, it is not understood how certain few proteins achieve markedly higher sequence specificity than most others. Here we show that the RNA Recognition Motif of RbFox accomplishes extraordinary sequence specificity by employing functionally and structurally distinct binding modes. Affinity measurements of RbFox for all binding site variants reveal the existence of two distinct binding modes. The first exclusively accommodates cognate and closely related RNAs with high affinity. The second mode accommodates all other RNAs with reduced affinity by imposing large thermodynamic penalties on non-cognate sequences. NMR studies indicate marked structural differences between the two binding modes, including large conformational rearrangements distant from the RNA-binding site. Distinct binding modes by a single RNA-binding module explain extraordinary sequence selectivity and reveal an unknown layer of functional diversity, cross talk and regulation in RNA-protein interactions.

Transient Protein-RNA Interactions Guide Nascent Ribosomal RNA Folding

Ribosome assembly is an efficient but complex and heterogeneous process during which ribosomal proteins assemble on the nascent rRNA during transcription. Understanding how the interplay between nascent RNA folding and protein binding determines the fate of transcripts remains a major challenge. Here, using single-molecule fluorescence microscopy, we follow assembly of the entire 3' domain of the bacterial small ribosomal subunit in real time. We find that co-transcriptional rRNA folding is complicated by the formation of long-range RNA interactions and that r-proteins self-chaperone the rRNA folding process prior to stable incorporation into a ribonucleoprotein (RNP) complex. Assembly is initiated by transient rather than stable protein binding, and the protein-RNA binding dynamics gradually decrease during assembly. This work questions the paradigm of strictly sequential and cooperative ribosome assembly and suggests that transient binding of RNA binding proteins to cellular RNAs could provide a general mechanism to shape nascent RNA folding during RNP assembly.

Many Activities, One Structure: Functional Plasticity of Ribozyme Folds

Catalytic RNAs, or ribozymes, are involved in a number of essential biological processes, such as replication of RNA genomes and mobile genetic elements, RNA splicing, translation, and RNA degradation. The function of ribozymes requires the formation of active sites decorated with RNA functional groups within defined three-dimensional (3D) structures. The genotype (sequence) of RNAs ultimately determines what 3D structures they adopt (as a function of their environmental conditions). These 3D structures, in turn, give rise to biochemical activity, which can further elaborate them by catalytic rearrangements or association with other molecules. The fitness landscape of a non-periodic linear polymer, such as RNA, relates its primary structure to a phenotype. Two major challenges in the analysis of ribozymes is to map all possible genotypes to their corresponding catalytic activity (that is, to determine their fitness landscape experimentally), and to understand whether their genotypes and three-dimensional structures can support multiple different catalytic functions. Recently, the combined results of experiments that employ in vitro evolution methods, high-throughput sequencing and crystallographic structure determination have hinted at answers to these two questions: while the fitness landscape of ribozymes is rugged, meaning that their catalytic activity cannot be optimized by a smooth trajectory in sequence space, once an RNA achieves a stable three-dimensional fold, it can be endowed with distinctly different biochemical activities through small changes in genotype. This functional plasticity of highly structured RNAs may be particularly advantageous for the adaptation of organisms to drastic changes in selective pressure, or for the development of new biotechnological tools.