Spliceosomal SL1 RNA binding to U1-70K: the role of the extended RRM

The RNA recognition motif (RRM) occurs widely in RNA-binding proteins, but does not always by itself support full binding. For example, it is known that binding of SL1 RNA to the protein U1-70K in the U1 spliceosomal particle is reduced when a region flanking the RRM is truncated. How the RRM flanking regions that together with the RRM make up an ‘extended RRM’ (eRRM) contribute to complex stability and structural organization is unknown. We study the U1-70K eRRM bound to SL1 RNA by thermal dissociation and laser temperature jump kinetics; long-time molecular dynamics simulations interpret the experiments with atomistic resolution. Truncation of the helix flanking the RRM on its N-terminal side, ‘N-helix,’ strongly reduces overall binding, which is further weakened under higher salt and temperature conditions. Truncating the disordered region flanking the RRM on the C-terminal side, ‘C-IDR’, affects the local binding site. Surprisingly, all-atom simulations show that protein truncation enhances base stacking interactions in the binding site and leaves the overall number of hydrogen bonds intact. Instead, the flanking regions of the eRRM act in a distributed fashion via collective interactions with the RNA when external stresses such as temperature or high salt mimicking osmotic imbalance are applied.     

Protein-RNA interactions: a structural analysis

A detailed computational analysis of 32 protein–RNA complexes is presented. A number of physical and chemical properties of the intermolecular interfaces are calculated and compared with those observed in protein–double-stranded DNA and protein–single-stranded DNA complexes. The interface properties of the protein–RNA complexes reveal the diverse nature of the binding sites. van der Waals contacts played a more prevalent role than hydrogen bond contacts, and preferential binding to guanine and uracil was observed. The positively charged residue, arginine, and the single aromatic residues, phenylalanine and tyrosine, all played key roles in the RNA binding sites. A comparison between protein–RNA and protein–DNA complexes showed that whilst base and backbone contacts (both hydrogen bonding and van der Waals) were observed with equal frequency in the protein–RNA complexes, backbone contacts were more dominant in the protein–DNA complexes. Although similar modes of secondary structure interactions have been observed in RNA and DNA binding proteins, the current analysis emphasises the differences that exist between the two types of nucleic acid binding protein at the atomic contact level.     

Npl3 functions in mRNP assembly by recruitment of mRNP components to the transcription site and their transfer onto the mRNA

RNA-binding proteins (RBPs) control every RNA metabolic process by multiple protein–RNA and protein–protein interactions. Their roles have largely been analyzed by crude mutations, which abrogate multiple functions at once and likely impact the structural integrity of the large ribonucleoprotein particles (RNPs) these proteins function in. Using UV-induced RNA–protein crosslinking of entire cells, protein complex purification and mass spectrometric analysis, we identified >100 in vivo RNA crosslinks in 16 nuclear mRNP components in Saccharomyces cerevisiae. For functional analysis, we chose Npl3, which displayed crosslinks in its two RNA recognition motifs (RRMs) and in the connecting flexible linker region. Both RRM domains and the linker uniquely contribute to RNA recognition as revealed by NMR and structural analyses. Interestingly, mutations in these regions cause different phenotypes, indicating distinct functions of the different RNA-binding domains. Notably, an npl3-Linker mutation strongly impairs recruitment of several mRNP components to chromatin and incorporation of other mRNP components into nuclear mRNPs, establishing a so far unknown function of Npl3 in nuclear mRNP assembly. Taken together, our integrative analysis uncovers a specific function of the RNA-binding activity of the nuclear mRNP component Npl3. This approach can be readily applied to RBPs in any RNA metabolic process.     

Structural predictions of protein–DNA binding: MELD-DNA

Structural, regulatory and enzymatic proteins interact with DNA to maintain a healthy and functional genome. Yet, our structural understanding of how proteins interact with DNA is limited. We present MELD-DNA, a novel computational approach to predict the structures of protein–DNA complexes. The method combines molecular dynamics simulations with general knowledge or experimental information through Bayesian inference. The physical model is sensitive to sequence-dependent properties and conformational changes required for binding, while information accelerates sampling of bound conformations. MELD-DNA can: (i) sample multiple binding modes; (ii) identify the preferred binding mode from the ensembles; and (iii) provide qualitative binding preferences between DNA sequences. We first assess performance on a dataset of 15 protein–DNA complexes and compare it with state-of-the-art methodologies. Furthermore, for three selected complexes, we show sequence dependence effects of binding in MELD predictions. We expect that the results presented herein, together with the freely available software, will impact structural biology (by complementing DNA structural databases) and molecular recognition (by bringing new insights into aspects governing protein–DNA interactions).     

ETR-3 and CELF4 protein domains required for RNA binding and splicing activity in vivo

Members of the CUG-BP and ETR-3 like factor (CELF) protein family bind within conserved intronic elements (called MSEs) flanking the cardiac troponin T (cTNT) alternative exon 5 and promote exon inclusion in vivo and in vitro. Here we use a comparative deletion analysis of two family members (ETR-3 and CELF4) to identify separate domains required for RNA binding and splicing activity in vivo. CELF proteins contain two adjacent RNA binding domains (RRM1 and RRM2) near the N-terminus and one RRM (RRM3) near the C-terminus, which are separated by a 160–230 residue divergent domain of unknown function. Either RRM1 or RRM2 of CELF4 are necessary and sufficient for binding MSE RNA and RRM2 plus an additional 66 amino acids of the divergent domain are as effective as full-length protein in activating MSE-dependent splicing in vivo. Non-overlapping N- and C-terminal regions of ETR-3 containing either RRM1 and RRM2 or RRM3 plus segments of the adjacent divergent domain activate MSE-dependent exon inclusion demonstrating an unusual functional redundancy of the N- and C-termini of the protein. These results identify specific regions of ETR-3 and CELF4 that are likely targets of protein–protein interactions required for splicing activation.     

Fragment-based modelling of single stranded RNA bound to RNA recognition motif containing proteins

Protein-RNA complexes are important for many biological processes. However, structural modeling of such complexes is hampered by the high flexibility of RNA. Particularly challenging is the docking of single-stranded RNA (ssRNA). We have developed a fragment-based approach to model the structure of ssRNA bound to a protein, based on only the protein structure, the RNA sequence and conserved contacts. The conformational diversity of each RNA fragment is sampled by an exhaustive library of trinucleotides extracted from all known experimental protein–RNA complexes. The method was applied to ssRNA with up to 12 nucleotides which bind to dimers of the RNA recognition motifs (RRMs), a highly abundant eukaryotic RNA-binding domain. The fragment based docking allows a precise de novo atomic modeling of protein-bound ssRNA chains. On a benchmark of seven experimental ssRNA–RRM complexes, near-native models (with a mean heavy-atom deviation of <3 Å from experiment) were generated for six out of seven bound RNA chains, and even more precise models (deviation < 2 Å) were obtained for five out of seven cases, a significant improvement compared to the state of the art. The method is not restricted to RRMs but was also successfully applied to Pumilio RNA binding proteins.     

Visualization and characterization of RNA–protein interactions in living cells

RNA–protein interactions are the structural and functional basis of significant numbers of RNA molecules. RNA–protein interaction assays though, still mainly depend on biochemical tests in vitro. Here, we establish a convenient and reliable RNA fluorescent three-hybrid (rF3H) method to detect/interrogate the interactions between RNAs and proteins in cells. A GFP tagged highly specific RNA trap is constructed to anchor the RNA of interest to an artificial or natural subcellular structure, and RNA–protein interactions can be detected and visualized by the enrichment of RNA binding proteins (RBPs) at these structures. Different RNA trapping systems are developed and detection of RNA–protein complexes at multiple subcellular structures are assayed. With this new toolset, interactions between proteins and mRNA or noncoding RNAs are characterized, including the interaction between a long noncoding RNA and an epigenetic modulator. Our approach provides a flexible and reliable method for the characterization of RNA–protein interactions in living cells.     

A new hydrogen-bonding potential for the design of protein-RNA interactions predicts specific contacts and discriminates decoys

RNA-binding proteins play many essential roles in the regulation of gene expression in the cell. Despite the significant increase in the number of structures for RNA–protein complexes in the last few years, the molecular basis of specificity remains unclear even for the best-studied protein families. We have developed a distance and orientation-dependent hydrogen-bonding potential based on the statistical analysis of hydrogen-bonding geometries that are observed in high-resolution crystal structures of protein–DNA and protein–RNA complexes. We observe very strong geometrical preferences that reflect significant energetic constraints on the relative placement of hydrogen-bonding atom pairs at protein–nucleic acid interfaces. A scoring function based on the hydrogen-bonding potential discriminates native protein–RNA structures from incorrectly docked decoys with remarkable predictive power. By incorporating the new hydrogen-bonding potential into a physical model of protein–RNA interfaces with full atom representation, we were able to recover native amino acids at protein–RNA interfaces.     

The role of positively charged amino acids and electrostatic interactions in the complex of U1A protein and U1 hairpin II RNA

Previous kinetic investigations of the N-terminal RNA recognition motif (RRM) domain of spliceosomal protein U1A, interacting with its RNA target U1 hairpin II, provided experimental evidence for a ‘lure and lock’ model of binding in which electrostatic interactions first guide the RNA to the protein, and close range interactions then lock the two molecules together. To further investigate the ‘lure’ step, here we examined the electrostatic roles of two sets of positively charged amino acids in U1A that do not make hydrogen bonds to the RNA: Lys20, Lys22 and Lys23 close to the RNA-binding site, and Arg7, Lys60 and Arg70, located on ‘top’ of the RRM domain, away from the RNA. Surface plasmon resonance-based kinetic studies, supplemented with salt dependence experiments and molecular dynamics simulation, indicate that Lys20 predominantly plays a role in association, while nearby residues Lys22 and Lys23 appear to be at least as important for complex stability. In contrast, kinetic analyses of residues away from the RNA indicate that they have a minimal effect on association and stability. Thus, well-positioned positively charged residues can be important for both initial complex formation and complex maintenance, illustrating the multiple roles of electrostatic interactions in protein–RNA complexes.     

Anatomy of noncovalent interactions between the nucleobases or ribose and π-containing amino acids in RNA–protein complexes

A set of >300 nonredundant high-resolution RNA–protein complexes were rigorously searched for π-contacts between an amino acid side chain (W, H, F, Y, R, E and D) and an RNA nucleobase (denoted π–π interaction) or ribose moiety (denoted sugar–π). The resulting dataset of >1500 RNA–protein π-contacts were visually inspected and classified based on the interaction type, and amino acids and RNA components involved. More than 80% of structures searched contained at least one RNA–protein π-interaction, with π–π contacts making up 59% of the identified interactions. RNA–protein π–π and sugar–π contacts exhibit a range in the RNA and protein components involved, relative monomer orientations and quantum mechanically predicted binding energies. Interestingly, π–π and sugar–π interactions occur more frequently with RNA (4.8 contacts/structure) than DNA (2.6). Moreover, the maximum stability is greater for RNA–protein contacts than DNA–protein interactions. In addition to highlighting distinct differences between RNA and DNA–protein binding, this work has generated the largest dataset of RNA–protein π-interactions to date, thereby underscoring that RNA–protein π-contacts are ubiquitous in nature, and key to the stability and function of RNA–protein complexes.     

The role of disorder in RNA binding affinity and specificity

Most RNA-binding modules are small and bind few nucleotides. RNA-binding proteins typically attain the physiological specificity and affinity for their RNA targets by combining several RNA-binding modules. Here, we review how disordered linkers connecting RNA-binding modules govern the specificity and affinity of RNA–protein interactions by regulating the effective concentration of these modules and their relative orientation. RNA-binding proteins also often contain extended intrinsically disordered regions that mediate protein–protein and RNA–protein interactions with multiple partners. We discuss how these regions can connect proteins and RNA resulting in heterogeneous higher-order assemblies such as membrane-less compartments and amyloid-like structures that have the characteristics of multi-modular entities. The assembled state generates additional RNA-binding specificity and affinity properties that contribute to further the function of RNA-binding proteins within the cellular environment.     

Specific protein domains mediate cooperative assembly of HuR oligomers on AU-rich mRNA-destabilizing sequences

The RNA-binding factor HuR is a ubiquitously expressed member of the Hu protein family that binds and stabilizes mRNAs containing AU-rich elements (AREs). Hu proteins share a common domain organization of two tandemly arrayed RNA recognition motifs (RRMs) near the N terminus, followed by a basic hinge domain and a third RRM near the C terminus. In this study, we engineered recombinant wild-type and mutant HuR proteins lacking affinity tags to characterize their ARE-binding properties. Using combinations of electrophoretic mobility shift and fluorescence anisotropy-based binding assays, we show that HuR can bind ARE substrates as small as 13 nucleotides with low nanomolar affinity, but forms cooperative oligomeric protein complexes on ARE substrates of at least 18 nucleotides in length. Analyses of deletion mutant proteins indicated that RRM3 does not contribute to high affinity recognition of ARE substrates, but is required for cooperative assembly of HuR oligomers on RNA. Finally, the hinge domain between RRM2 and RRM3 contributes significant binding energy to HuR.ARE complex formation in an ARE length-dependent manner. The hinge does not enhance RNA-binding activity by increased ion pair formation despite extensive positive charge within this region, and it does not thermodynamically stabilize protein folding. Together, the results define distinct roles for the HuR hinge and RRM3 domains in formation of cooperative HuR.ARE complexes in solution.     

Insights into structure, dynamics and hydration of locked nucleic acid (LNA) strand-based duplexes from molecular dynamics simulations

Locked nucleic acid (LNA) is a chemically modified nucleic acid with its sugar ring locked in an RNA-like (C3′-endo) conformation. LNAs show extraordinary thermal stabilities when hybridized with DNA, RNA or LNA itself. We performed molecular dynamics simulations on five isosequential duplexes (LNA–DNA, LNA–LNA, LNA–RNA, RNA–DNA and RNA–RNA) in order to characterize their structure, dynamics and hydration. Structurally, the LNA–DNA and LNA–RNA duplexes are found to be similar to regular RNA–DNA and RNA–RNA duplexes, whereas the LNA–LNA duplex is found to have its helix partly unwound and does not resemble RNA–RNA duplex in a number of properties. Duplexes with an LNA strand have on average longer interstrand phosphate distances compared to RNA–DNA and RNA–RNA duplexes. Furthermore, intrastrand phosphate distances in LNA strands are found to be shorter than in DNA and slightly shorter than in RNA. In case of induced sugar puckering, LNA is found to tune the sugar puckers in partner DNA strand toward C3′-endo conformations more efficiently than RNA. The LNA–LNA duplex has lesser backbone flexibility compared to the RNA–RNA duplex. Finally, LNA is less hydrated compared to DNA or RNA but is found to have a well-organized water structure.     

The structure and selectivity of the SR protein SRSF2 RRM domain with RNA

SRSF2 is a prototypical SR protein which plays important roles in the alternative splicing of pre-mRNA. It has been shown to be involved in regulatory pathways for maintaining genomic stability and play important roles in regulating key receptors in the heart. We report here the solution structure of the RNA recognition motifs (RRM) domain of free human SRSF2 (residues 9-101). Compared with other members of the SR protein family, SRSF2 structure has a longer L3 loop region. The conserved aromatic residue in the RNP2 motif is absent in SRSF2. Calorimetric titration shows that the RNA sequence 5'AGCAGAGUA3' binds SRSF2 with a K(d) of 61 ± 1 nM and a 1:1 stoichiometry. NMR and mutagenesis experiments reveal that for SFSF2, the canonical β1 and β3 interactions are themselves not sufficient for effective RNA binding; the additional loop L3 is crucial for RNA complex formation. A comparison is made between the structures of SRSF2-RNA complex with other known RNA complexes of SR proteins. We conclude that interactions involving the L3 loop, N- and C-termini of the RRM domain are collectively important for determining selectivity between the protein and RNA.     

RNA recognition and self-association of CPEB4 is mediated by its tandem RRM domains

Cytoplasmic polyadenylation is regulated by the interaction of the cytoplasmic polyadenylation element binding proteins (CPEB) with cytoplasmic polyadenylation element (CPE) containing mRNAs. The CPEB family comprises four paralogs, CPEB1–4, each composed of a variable N-terminal region, two RNA recognition motif (RRM) and a C-terminal ZZ-domain. We have characterized the RRM domains of CPEB4 and their binding properties using a combination of biochemical, biophysical and NMR techniques. Isothermal titration calorimetry, NMR and electrophoretic mobility shift assay experiments demonstrate that both the RRM domains are required for an optimal CPE interaction and the presence of either one or two adenosines in the two most commonly used consensus CPE motifs has little effect on the affinity of the interaction. Both the single RRM1 and the tandem RRM1–RRM2 have the ability to dimerize, although representing a minor population. Self-association does not affect the proteins’ ability to interact with RNA as demonstrated by ion mobility–mass spectrometry. Chemical shift effects measured by NMR of the apo forms of the RRM1–RRM2 samples indicate that the two domains are orientated toward each other. NMR titration experiments show that residues on the β-sheet surface on RRM1 and at the C-terminus of RRM2 are affected upon RNA binding. We propose a model of the CPEB4 RRM1–RRM2–CPE complex that illustrates the experimental data.     

A Compare-and-Contrast NMR Dynamics Study of Two Related RRMs: U1A and SNF

The U1A/U2B″/SNF family of small nuclear ribonucleoproteins uses a phylogenetically conserved RNA recognition motif (RRM1) to bind RNA stemloops in U1 and/or U2 small nuclear RNA (snRNA). RRMs are characterized by their α/β sandwich topology, and these RRMs use their β-sheet as the RNA binding surface. Unique to this RRM family is the tyrosine-glutamine-phenylalanine (YQF) triad of solvent-exposed residues that are displayed on the β-sheet surface; the aromatic residues form a platform for RNA nucleobases to stack. U1A, U2B″, and SNF have very different patterns of RNA binding affinity and specificity, however, so here we ask how YQF in Drosophila SNF RRM1 contributes to RNA binding, as well as to domain stability and dynamics. Thermodynamic double-mutant cycles using tyrosine and phenylalanine substitutions probe the communication between those two residues in the free and bound states of the RRM. NMR experiments follow corresponding changes in the glutamine side-chain amide in both U1A and SNF, providing a physical picture of the RRM1 β-sheet surface. NMR relaxation and dispersion experiments compare fast (picosecond to nanosecond) and intermediate (microsecond-to-millisecond) dynamics of U1A and SNF RRM1. We conclude that there is a network of amino acid interactions involving Tyr-Gln-Phe in both SNF and U1A RRM1, but whereas mutations of the Tyr-Gln-Phe triad result in small local responses in U1A, they produce extensive microsecond-to-millisecond global motions throughout SNF that alter the conformational states of the RRM.     

A study of collective atomic fluctuations and cooperativity in the U1A-RNA complex based on molecular dynamics simulations

Cooperative interactions play an important role in recognition and binding in macromolecular systems. In this study, we find that cross-correlated atomic fluctuations can be used to identify cooperative networks in a protein–RNA system. The dynamics of the RRM-containing protein U1A–stem loop 2 RNA complex have been calculated theoretically from a 10 ns molecular dynamics (MD) simulation. The simulation was analyzed by calculating the covariance matrix of all atomic fluctuations. These matrix elements are then presented in the form of a two-dimensional grid, which displays fluctuations on a per residue basis. The results indicate the presence of strong, selective cross-correlated fluctuations throughout the RRM in U1A–RNA. The atomic fluctuations correspond well with previous biophysical studies in which a multiplicity of cooperative networks have been reported and indicate that the various networks identified in separate individual experiments are fluctuationally correlated into a hyper-network encompassing most of the RRM. The calculated results also correspond well with independent results from a statistical covariance analysis of 330 aligned RRM sequences. This method has significant implications as a predictive tool regarding cooperativity in the protein–nucleic acid recognition process.