Structural and functional modules in RNA interference.
Ontology highlight
ABSTRACT:
SUBMITTER: Nowotny M
PROVIDER: S-EPMC2721689 | biostudies-literature | 2009 Jun
REPOSITORIES: biostudies-literature
Publications
Structural and functional modules in RNA interference.
Current opinion in structural biology 20090526 3
RNA interference (RNAi) uses small RNA molecules to regulate transcriptional and post-transcriptional gene expression. In recent years, a number of structural studies provided insights into the molecular architecture and mechanism of functional modules of RNAi. Mechanisms of nucleic acid recognition and cleavage have been revealed by structural studies of proteins and their nucleic acid complexes involved in RNA biogenesis, for example, Argonaute, PIWI, RNase III, Dicer, Drosha, and DGCR8. While ...[more]
Similar Datasets
Project description:Virtually all animals and plants utilize small RNA molecules to control protein expression during different developmental stages and in response to viral infection. Structural and mechanistic studies have begun to illuminate three fundamental aspects of these pathways: small RNA biogenesis, formation of RNA-induced silencing complexes (RISCs), and targeting of complementary mRNAs. Here we review exciting recent progress in understanding how regulatory RNAs are produced and how they trigger specific destruction of mRNAs during RNA interference (RNAi).
| S-EPMC2855239 | biostudies-literature
Project description:Natural stable RNAs fold and assemble into complex three-dimensional architectures by relying on the hierarchical formation of intricate, recurrent networks of noncovalent tertiary interactions. These sequence-dependent networks specify RNA structural modules enabling orientational and topological control of helical struts to form larger self-folding domains. Borrowing concepts from linguistics, we defined an extended structural syntax of RNA modules for programming RNA strands to assemble into complex, responsive nanostructures under both thermodynamic and kinetic control. Based on this syntax, various RNA building blocks promote the multimolecular assembly of objects with well-defined three-dimensional shapes as well as the isothermal folding of long RNAs into complex single-stranded nanostructures during transcription. This work offers a glimpse of the limitless potential of RNA as an informational medium for designing programmable and functional nanomaterials useful for synthetic biology, nanomedicine, and nanotechnology.
| S-EPMC6363482 | biostudies-literature
Project description:Large-scale, cooperative rearrangements underlie the functions of RNA in RNA-protein machines and gene regulation. To understand how such rearrangements are orchestrated, we used high-throughput chemical footprinting to dissect a seemingly concerted rearrangement in P5abc RNA, a paradigm of RNA folding studies. With mutations that systematically disrupt or restore putative structural elements, we found that this transition reflects local folding of structural modules, with modest and incremental cooperativity that results in concerted behavior. First, two distant secondary structure changes are coupled through a bridging three-way junction and Mg2+-dependent tertiary structure. Second, long-range contacts are formed between modules, resulting in additional cooperativity. Given the sparseness of RNA tertiary contacts after secondary structure formation, we expect that modular folding and incremental cooperativity are generally important for specifying functional structures while also providing productive kinetic paths to these structures. Additionally, we expect our approach to be useful for uncovering modularity in other complex RNAs.
| S-EPMC5894117 | biostudies-literature
Project description:Human Tudor-SN is involved in the degradation of hyper-edited inosine-containing microRNA precursors, thus linking the pathways of RNA interference and editing. Tudor-SN contains four tandem repeats of staphylococcal nuclease-like domains (SN1-SN4) followed by a tudor and C-terminal SN domain (SN5). Here, we showed that Tudor-SN requires tandem repeats of SN domains for its RNA binding and cleavage activity. The crystal structure of a 64-kD truncated form of human Tudor-SN further shows that the four domains, SN3, SN4, tudor and SN5, assemble into a crescent-shaped structure. A concave basic surface formed jointly by SN3 and SN4 domains is likely involved in RNA binding, where citrate ions are bound at the putative RNase active sites. Additional modeling studies provide a structural basis for Tudor-SN's preference in cleaving RNA containing multiple I.U wobble-paired sequences. Collectively, these results suggest that tandem repeats of SN domains in Tudor-SN function as a clamp to capture RNA substrates.
| S-EPMC2441809 | biostudies-literature
Project description:While small interfering RNA (siRNA) and microRNA (miRNA) have attracted extensive attention and showed significant promise for the study, diagnosis and treatment of human cancers, delivering siRNA or miRNA specifically and efficiently into tumor cells in vivo remains a great challenge. Delivery barriers, which arise mainly from the routes of administration associated with complex physiochemical microenvironments of the human body and the unique properties of RNAs, hinder the development of RNA-interference (RNAi)-based therapeutics in clinical practice. However, in available delivery systems, non-viral nanoparticle-based gene/RNA-delivery vectors, or nanovectors, are showing powerful delivery capacities and huge potential for improvements in functional nanomaterials, including novel fabrication approaches which would greatly enhance delivery performance. In this review, we summarize the currently recognized RNAi delivery barriers and the anti-barrier requirements related to vectors' properties. Recent efforts and achievements in the development of novel nanomaterials, nanovectors fabrication methods, and delivery approaches are discussed. We also review the outstanding needs in the areas of material synthesis and assembly, multifunction combinations, proper delivery and assisting approaches that require more intensive investigation for the comprehensive and effective delivery of RNAi by non-viral nanovectors.
| S-EPMC3092671 | biostudies-literature
Project description:Structured RNAs fold through multiple pathways, but we have little understanding of the molecular features that dictate folding pathways and determine rates along a given pathway. Here, we asked whether folding of a complex RNA can be understood from its structural modules. In a two-piece version of the Tetrahymena group I ribozyme, the separated P5abc subdomain folds to local native secondary and tertiary structure in a linked transition and assembles with the ribozyme core via three tertiary contacts: a kissing loop (P14), a metal core-receptor interaction, and a tetraloop-receptor interaction, the first two of which are expected to depend on native P5abc structure from the local transition. Native gel, NMR, and chemical footprinting experiments showed that mutations that destabilize the native P5abc structure slowed assembly up to 100-fold, indicating that P5abc folds first and then assembles with the core by conformational selection. However, rate decreases beyond 100-fold were not observed because an alternative pathway becomes dominant, with nonnative P5abc binding the core and then undergoing an induced-fit rearrangement. P14 is formed in the rate-limiting step along the conformational selection pathway but after the rate-limiting step along the induced-fit pathway. Strikingly, the assembly rate along the conformational selection pathway resembles that of an isolated kissing loop similar to P14, and the rate along the induced-fit pathway resembles that of an isolated tetraloop-receptor interaction. Our results indicate substantial modularity in RNA folding and assembly and suggest that these processes can be understood in terms of underlying structural modules.
| S-EPMC5048535 | biostudies-literature
Project description:Recent progress in predicting RNA structure is moving towards filling the 'gap' in 2D RNA structure prediction where, for example, predicted internal loops often form non-canonical base pairs. This is increasingly recognized with the steady increase of known RNA 3D modules. There is a general interest in matching structural modules known from one molecule to other molecules for which the 3D structure is not known yet. We have created a pipeline, metaRNAmodules, which completely automates extracting putative modules from the FR3D database and mapping of such modules to Rfam alignments to obtain comparative evidence. Subsequently, the modules, initially represented by a graph, are turned into models for the RMDetect program, which allows to test their discriminative power using real and randomized Rfam alignments. An initial extraction of 22 495 3D modules in all PDB files results in 977 internal loop and 17 hairpin modules with clear discriminatory power. Many of these modules describe only minor variants of each other. Indeed, mapping of the modules onto Rfam families results in 35 unique locations in 11 different families. The metaRNAmodules pipeline source for the internal loop modules is available at http://rth.dk/resources/mrm.
| S-EPMC3905863 | biostudies-literature
Project description:Modular organization in biological networks has been suggested as a natural mechanism by which a cell coordinates its metabolic strategies for evolving and responding to environmental perturbations. To understand how this occurs, there is a need for developing computational schemes that contribute to integration of genomic-scale information and assist investigators in formulating biological hypotheses in a quantitative and systematic fashion. In this work, we combined metabolome data and constraint-based modeling to elucidate the relationships among structural modules, functional organization, and the optimal metabolic phenotype of Rhizobium etli, a bacterium that fixes nitrogen in symbiosis with Phaseolus vulgaris. To experimentally characterize the metabolic phenotype of this microorganism, we obtained the metabolic profile of 220 metabolites at two physiological stages: under free-living conditions, and during nitrogen fixation with P. vulgaris. By integrating these data into a constraint-based model, we built a refined computational platform with the capability to survey the metabolic activity underlying nitrogen fixation in R. etli. Topological analysis of the metabolic reconstruction led us to identify modular structures with functional activities. Consistent with modular activity in metabolism, we found that most of the metabolites experimentally detected in each module simultaneously increased their relative abundances during nitrogen fixation. In this work, we explore the relationships among topology, biological function, and optimal activity in the metabolism of R. etli through an integrative analysis based on modeling and metabolome data. Our findings suggest that the metabolic activity during nitrogen fixation is supported by interacting structural modules that correlate with three functional classifications: nucleic acids, peptides, and lipids. More fundamentally, we supply evidence that such modular organization during functional nitrogen fixation is a robust property under different environmental conditions.
| S-EPMC3469419 | biostudies-literature
Project description:HIV-1 drug therapies can prevent disease progression but cannot eliminate HIV-1 viruses from an infected individual. While there is hope that elimination of HIV-1 can be achieved, several approaches to reach a functional cure (control of HIV-1 replication in the absence of drug therapy) are also under investigation. One of these approaches is the transplant of HIV-1 resistant cells expressing anti-HIV-1 RNAs, proteins or peptides. Small RNAs that use RNA interference pathways to target HIV-1 replication have emerged as competitive candidates for cell transplant therapy and have been included in all gene combinations that have so far entered clinical trials. Here, we review RNA interference pathways in mammalian cells and the design of therapeutic small RNAs that use these pathways to target pathogenic RNA sequences. Studies that have been performed to identify anti-HIV-1 RNA interference therapeutics are also reviewed and perspectives on their use in combination gene therapy to functionally cure HIV-1 infection are provided.
| S-EPMC5795421 | biostudies-literature
Project description:Biological systems can be modeled as complex network systems with many interactions between the components. These interactions give rise to the function and behavior of that system. For example, the protein-protein interaction network is the physical basis of multiple cellular functions. One goal of emerging systems biology is to analyze very large complex biological networks such as protein-protein interaction networks, metabolic networks, and regulatory networks to identify functional modules and assign functions to certain components of the system. Network modules do not occur by chance, so identification of modules is likely to capture the biologically meaningful interactions in large-scale PPI data. Unfortunately, existing computer-based clustering methods developed to find those modules are either not so accurate or too slow.We devised a new methodology called SCAN (Structural Clustering Algorithm for Networks) that can efficiently find clusters or functional modules in complex biological networks as well as hubs and outliers. More specifically, we demonstrated that we can find functional modules in complex networks and classify nodes into various roles based on their structures. In this study, we showed the effectiveness of our methodology using the budding yeast (Saccharomyces cerevisiae) protein-protein interaction network. To validate our clustering results, we compared our clusters with the known functions of each protein. Our predicted functional modules achieved very high purity comparing with state-of-the-art approaches. Additionally the theoretical and empirical analysis demonstrated a linear running-time of the algorithm, which is the fastest approach for networks.We compare our algorithm with well-known modularity based clustering algorithm CNM. We successfully detect functional groups that are annotated with putative GO terms. Top-10 clusters with minimum p-value theoretically prove that newly proposed algorithm partitions network more accurately then CNM. Furthermore, manual interpretations of functional groups found by SCAN show superior performance over CNM.
| S-EPMC2537570 | biostudies-literature