Transient RNA–protein interactions in RNA folding

RNA molecules with novel functions have revived interest in the accurate prediction of RNA three-dimensional (3D) structure and folding dynamics. However, existing methods are inefficient in automated 3D structure prediction. Here, we report a robust computational approach for rapid folding of RNA molecules. We develop a simplified RNA model for discrete molecular dynamics (DMD) simulations, incorporating base-pairing and base-stacking interactions. We demonstrate correct folding of 150 structurally diverse RNA sequences. The majority of DMD-predicted 3D structures have <4 A deviations from experimental structures. The secondary structures corresponding to the predicted 3D structures consist of 94% native base-pair interactions. Folding thermodynamics and kinetics of tRNA(Phe), pseudoknots, and mRNA fragments in DMD simulations are in agreement with previous experimental findings. Folding of RNA molecules features transient, non-native conformations, suggesting non-hierarchical RNA folding. Our method allows rapid conformational sampling of RNA folding, with computational time increasing linearly with RNA length. We envision this approach as a promising tool for RNA structural and functional analyses.

Signal flow direction is one of the most important features of the protein-protein interactions in signaling networks. However, almost all the outcomes of current high-throughout techniques for protein-protein interactions mapping are usually supposed to be non-directional. Based on the pairwise interaction domains, here we defined a novel parameter protein interaction directional score and then used it to predict the direction of signal flow between proteins in proteome-wide signaling networks. Using 5-fold cross-validation, our approach obtained a satisfied performance with the accuracy 89.79%, coverage 48.08%, and error ratio 16.91%. As an application, we established an integrated human directional protein interaction network, including 2,237 proteins and 5,530 interactions, and inferred a large amount of novel signaling pathways. Directional protein interaction network was strongly supported by the known signaling pathways literature (with the 87.5% accuracy) and further analyses on the biological annotation, subcellular localization, and network topology property. Thus, this study provided an effective method to define the upstream/downstream relations of interacting protein pairs and a powerful tool to unravel the unknown signaling pathways.

Studying the interaction between proteins is key in understanding their function(s). A very powerful method that is frequently used to study interactions of proteins with other macromolecules in a complex sample is called co-immunoprecipitation. The described co-immunoprecipitation protocol allows to demonstrate and further investigate the interaction between the antiviral myxovirus resistance protein 1 (Mx1) and one of its viral targets, the influenza A virus nucleoprotein (NP). The protocol starts with transfected mammalian cells, but it is also possible to use influenza A virus infected cells as starting material. After cell lysis, the viral NP protein is pulled-down with a specific antibody and the resulting immune-complexes are precipitated with protein G beads. The successful pull-down of NP and the co-immunoprecipitation of the antiviral Mx1 protein are subsequently revealed by western blotting. A prerequisite for successful co-immunoprecipitation of Mx1 with NP is the presence of N-ethylmaleimide (NEM) in the cell lysis buffer. NEM alkylates free thiol groups. Presumably this reaction stabilizes the weak and/or transient NP-Mx1 interaction by preserving a specific conformation of Mx1, its viral target or an unknown third component. An important limitation of co-immunoprecipitation experiments is the inadvertent pull-down of contaminating proteins, caused by nonspecific binding of proteins to the protein G beads or antibodies. Therefore, it is very important to include control settings to exclude false positive results. The described co-immunoprecipitation protocol can be used to study the interaction of Mx proteins from different vertebrate species with viral proteins, any pair of proteins, or of a protein with other macromolecules. The beneficial role of NEM to stabilize weak and/or transient interactions needs to be tested for each interaction pair individually.

Extracellular protein-protein interactions are essential for both intercellular communication and cohesion within multicellular organisms. Approximately a fifth of human genes encode membrane-tethered or secreted proteins, but they are largely absent from recent large-scale protein interaction datasets, making current interaction networks biased and incomplete. This discrepancy is due to the unsuitability of popular high-throughput methods to detect extracellular interactions because of the biochemical intractability of membrane proteins and their interactions. For example, cell surface proteins contain insoluble hydrophobic transmembrane regions, and their extracellular interactions are often highly transient, having half-lives of less than a second. To detect transient extracellular interactions on a large scale, we developed AVEXIS (avidity-based extracellular interaction screen), a high-throughput assay that overcomes these technical issues and can detect very transient interactions (half-lives <or= 0.1 sec) with a low false-positive rate. We used it to systematically screen for receptor-ligand pairs within the zebrafish immunoglobulin superfamily and identified novel ligands for both well-known and orphan receptors. Genes encoding receptor-ligand pairs were often clustered phylogenetically and expressed in the same or adjacent tissues, immediately implying their involvement in similar biological processes. Using AVEXIS, we have determined the first systematic low-affinity extracellular protein interaction network, supported by independent biological data. This technique will now allow large-scale extracellular protein interaction mapping in a broad range of experimental contexts.

In bacteria RNA gene regulatory elements refold dependent on environmental clues between two or more long-lived conformational states each associated with a distinct regulatory state. The refolding kinetics are strongly temperature-dependent and especially at lower temperatures they reach timescales that are biologically not accessible. To overcome this problem, RNA chaperones have evolved. However, the precise molecular mechanism of how these proteins accelerate RNA refolding reactions remains enigmatic. Here we show how the RNA chaperone StpA of Escherichia coli leads to an acceleration of a bistable RNA’s refolding kinetics through the selective destabilization of key base pairing interactions. We find in laser assisted real-time NMR experiments on photocaged bistable RNAs that the RNA chaperone leads to a two-fold increase in refolding rates at low temperatures due to reduced stability of ground state conformations. Further, we can show that upon interaction with StpA, base pairing interactions in the bistable RNA are modulated to favor refolding through the dominant pseudoknotted transition pathway. Our results shed light on the molecular mechanism of the interaction between RNA chaperones and bistable RNAs and are the first step into a functional classification of chaperones dependent on their biophysical mode of operation.

The Role of Ionic Strength and Ion Valence in RNA Collapse and Folding

The Impact of Gene Expression Regulation on Evolution of Extracellular Signaling Pathways

The solvent of membrane proteins is the membrane lipids in which they are embedded. Therefore, the nature of the lipids that surround membrane proteins impacts their dynamics and interactions. Unfortunately, how membrane proteins dynamically interact is difficult to study, and little is experimentally known how membrane proteins interplay in a membrane at the molecular scale. Herein, high‐speed atomic force microscopy (HS‐AFM) is used to dynamically image a well‐controlled bottom‐up system consisting of two aquaporin‐fold membrane proteins, pentameric FocA and tetrameric GlpF, that interact in membranes composed of varying amounts of 1,2‐dioleoyl‐sn‐glycero‐3‐phosphocholine (DOPC) and E. coli lipids. It is found that the lipid environment significantly influences membrane protein mobility and interaction, where increased E. coli lipid content reduces protein movement, while DOPC‐rich environments promote mobility. Furthermore, the supramolecular structures of the membrane proteins and protomer interactions in clusters are also lipid modulated, where E. coli lipids favor specific protein–protein interactions, whereas greater interaction variability is found in DOPC. These findings highlight the role of lipids in regulating protein diffusion and interactions and suggest that lipid–protein interaction energetics play a significant role in controlling membrane protein interactions and supramolecular assembly.

Dissecting the Contribution of Diffusion and Interactions to the Mobility of Nuclear Proteins

Proteins are generally organized into molecular complexes, in which multiple interaction partners collaborate to carry out cellular processes. Thus, techniques to map protein-protein interactions have become pivotal for biological studies of as yet uncharacterized proteins. Investigation of interaction partners of membrane proteins is of special interest, as they play a major role in cellular processes and are often directly linked to human diseases. Owing to their hydrophobic nature, however, it has proven difficult to study their interaction partners. To circumvent this problem, a yeast-based genetic technology for the in vivo detection of membrane protein interactions, the split-ubiquitin membrane yeast two-hybrid (MYTH) system, has been developed. MYTH allows for detection of both stable and transient interactions and can be applied to large- and small-scale screens. It uses the split-ubiquitin approach, in which the reconstitution of two ubiquitin halves is mediated by a specific protein-protein interaction. Briefly, the bait membrane protein is fused to the C-terminal half of ubiquitin and an artificial transcription factor. The mutated N-terminal moiety of ubiquitin is fused to the prey protein. Upon interaction of bait and prey proteins, ubiquitin is reconstituted and further recognized by ubiquitin-specific proteases, which subsequently cleave off the transcription factor, thus resulting in reporter gene activation. To date, MYTH has been successfully applied to study interactions of membrane proteins from various organisms and has only recently been adapted for the identification of interaction partners of mammalian receptor tyrosine kinases.

Demonstrating direct interactions between host and virus proteins during infection is a major goal and challenge for the field of virology. Most protein interactions are not binary or easily amenable to structural determination. Using infectious preparations of a polerovirus (Potato leafroll virus [PLRV]) and protein interaction reporter (PIR), a revolutionary technology that couples a mass spectrometric-cleavable chemical cross-linker with high-resolution mass spectrometry, we provide the first report of a host-pathogen protein interaction network that includes data-derived, topological features for every cross-linked site that was identified. We show that PLRV virions have hot spots of protein interaction and multifunctional surface topologies, revealing how these plant viruses maximize their use of binding interfaces. Modeling data, guided by cross-linking constraints, suggest asymmetric packing of the major capsid protein in the virion, which supports previous epitope mapping studies. Protein interaction topologies are conserved with other species in the Luteoviridae and with unrelated viruses in the Herpesviridae and Adenoviridae. Functional analysis of three PLRV-interacting host proteins in planta using a reverse-genetics approach revealed a complex, molecular tug-of-war between host and virus. Structural mimicry and diversifying selection-hallmarks of host-pathogen interactions-were identified within host and viral binding interfaces predicted by our models. These results illuminate the functional diversity of the PLRV-host protein interaction network and demonstrate the usefulness of PIR technology for precision mapping of functional host-pathogen protein interaction topologies. The exterior shape of a plant virus and its interacting host and insect vector proteins determine whether a virus will be transmitted by an insect or infect a specific host. Gaining this information is difficult and requires years of experimentation. We used protein interaction reporter (PIR) technology to illustrate how viruses exploit host proteins during plant infection. PIR technology enabled our team to precisely describe the sites of functional virus-virus, virus-host, and host-host protein interactions using a mass spectrometry analysis that takes just a few hours. Applications of PIR technology in host-pathogen interactions will enable researchers studying recalcitrant pathogens, such as animal pathogens where host proteins are incorporated directly into the infectious agents, to investigate how proteins interact during infection and transmission as well as develop new tools for interdiction and therapy.

A recently discovered common trait of all eukaryotic organisms is a high prevalence of mobile genetic elements in their genome. From yeast to man, transposable elements are mostly represented by retroelements, which account for about half of the genome content in mammals and replicate by means of an obligatory RNA intermediate. According to the “RNA world” hypothesis, one step of the “prebiotic life” would correspond to populations of small RNA molecules forming increasingly complex RNA networks generating and piling up information. To reach this organizational level, RNA molecules probably needed to interact with small basic peptides, thus forming the backbone of ribonucleoparticles (RNPs). Aggregation and condensation of diverse RNA populations by basic peptides can generate arrays of large RNPs in which a drastic increase in RNA concentration leads to a crowding phenomenon facilitating RNA-RNA, RNA-peptide and peptide-peptide interactions and biochemical reactions. In addition, small basic peptides can have critical properties, known as RNA chaperoning, whereby the most stable structure of RNA molecules is rapidly reached and RNA-RNA annealing reactions can take place in a highly dynamic fashion. Thus, RNA chaperoning provided by basic peptides within highly crowded RNA populations may actively create novel information essential for the basic mechanisms of life. Simple retroelements from yeast to man encode such simple basic peptides with the RNA binding and chaperoning properties that are needed for their replication. Here we will briefly review RNA chaperones of retroelements and their mode of action, whereby these intrinsically flexible proteins can interact with many different partners to establish networks required for the replication of retroelements. We will also consider some mechanisms thought to regulate amplification of retroelements to control their invasion of and damage to eukaryotic genomes.

This article investigates the phase-locked loop (PLL) synchronization transient stability (PLL-STS) issue of grid-tied multiple voltage source converters (MVSCs) systems, specifically focusing on transient stability evaluation and transient interaction analysis. First, a novel PLL-STS assessment method for MVSCs systems has been proposed, which considers angular frequency jumps, nonlinear damping, and transient interactions among VSCs. Compared with previous studies, this method can accurately evaluate PLL-STS of MVSCs system since the acceleration and deceleration areas of VSCs can be accurately determined by combining equal-area criterion and numerical integration method. Moreover, it can identify the dominant converters which lead to transient instability. Second, by introducing static and dynamic interaction coefficients, influence of static and dynamic interaction on the transient stability of individual converters is quantitatively analyzed. Finally, the theoretical analysis results are verified by PSCAD/ EMTDC time-domain simulation results and RT-LAB hardware-in-the-loop experimental results.

The journey to the end of the chromosome: delivering active telomerase to telomeres in plants.

Protein-protein interactions (PPIs) are fundamental to biology. While experimental PPI detection is crucial, it is often expensive, error-prone, and struggles with transient interactions. Computational, especially structure-based, methods offer valuable alternatives, their reliance on experimentally determined structures has historically restricted their applicability. AlphaFold has transformed PPI prediction by providing accurate protein structure predictions, even without experimental data, thereby overcoming a major bottleneck in PPI research. This review examines the transformative impact of AlphaFold-based methods - including AlphaFold2, AlphaFold-Multimer, and AlphaFold3 - on PPI prediction, categorizing their contributions into six methodological domains. These methods utilize AlphaFold's capabilities to directly predict interacting protein complex structures, employing enhanced metrics for accuracy and sensitivity in PPI detection based on predicted interface features .The combination of AlphaFold-generated structures with computational techniques such as machine learning and network analysis is also considered to further improve prediction reliability and coverage. Furthermore, the critical role of the AlphaFold Database (AFDB) is highlighted in facilitating large-scale PPI studies by providing access to millions of predicted structures, enabling researchers to explore interaction networks and binding interfaces at an unprecedented scale. The review also surveys databases that provide critical information on protein interactions, sequences, structures, as PPI research hinges on the effective utilization and integration of these databases.