The double-stranded RNA-binding motif, a versatile macromolecular docking platform

The double-stranded RNA-binding motif (dsRBM) is an alphabetabetabetaalpha fold with a well-characterized function to bind structured RNA molecules. This motif is widely distributed in eukaryotic proteins, as well as in proteins from bacteria and viruses. dsRBM-containing proteins are involved in processes ranging from RNA editing to protein phosphorylation in translational control and contain a variable number of dsRBM domains. The structural work of the past five years has identified a common mode of RNA target recognition by dsRBMs and dissected this recognition into two functionally separated interaction modes. The first involves the recognition of specific moieties of the RNA A-form helix by two protein loops, while the second is based on the interaction between structural elements flanking the RNA duplex with the first helix of the dsRBM. The latter interaction can be tuned by other protein elements. Recent work has made clear that dsRBMs can also recognize non-RNA targets (proteins and DNA), and act in combination with other dsRBMs and non-dsRBM motifs to play a regulatory role in catalytic processes. The elucidation of functional networks coordinated by dsRBM folds will require information on the precise functional relationship between different dsRBMs and a clarification of the principles underlying dsRBM-protein recognition.     

Recent advances in RNA-protein recognition

The past few years have witnessed remarkable progress in knowledge of the structure and function of RNA-binding proteins and their RNA complexes. X-ray crystallography and NMR spectroscopy have provided structures for all major classes of RNA-binding proteins, both alone and complexed with RNA. New computational and experimental tools have provided unprecedented insight into the molecular basis of RNA recognition.     

Classifying RNA-binding proteins based on electrostatic properties

Protein structure can provide new insight into the biological function of a protein and can enable the design of better experiments to learn its biological roles. Moreover, deciphering the interactions of a protein with other molecules can contribute to the understanding of the protein's function within cellular processes. In this study, we apply a machine learning approach for classifying RNA-binding proteins based on their three-dimensional structures. The method is based on characterizing unique properties of electrostatic patches on the protein surface. Using an ensemble of general protein features and specific properties extracted from the electrostatic patches, we have trained a support vector machine (SVM) to distinguish RNA-binding proteins from other positively charged proteins that do not bind nucleic acids. Specifically, the method was applied on proteins possessing the RNA recognition motif (RRM) and successfully classified RNA-binding proteins from RRM domains involved in protein-protein interactions. Overall the method achieves 88% accuracy in classifying RNA-binding proteins, yet it cannot distinguish RNA from DNA binding proteins. Nevertheless, by applying a multiclass SVM approach we were able to classify the RNA-binding proteins based on their RNA targets, specifically, whether they bind a ribosomal RNA (rRNA), a transfer RNA (tRNA), or messenger RNA (mRNA). Finally, we present here an innovative approach that does not rely on sequence or structural homology and could be applied to identify novel RNA-binding proteins with unique folds and/or binding motifs.     

The RNA recognition motif, a plastic RNA-binding platform to regulate post-transcriptional gene expression

The RNA recognition motif (RRM), also known as RNA-binding domain (RBD) or ribonucleoprotein domain (RNP) is one of the most abundant protein domains in eukaryotes. Based on the comparison of more than 40 structures including 15 complexes (RRM-RNA or RRM-protein), we reviewed the structure-function relationships of this domain. We identified and classified the different structural elements of the RRM that are important for binding a multitude of RNA sequences and proteins. Common structural aspects were extracted that allowed us to define a structural leitmotif of the RRM-nucleic acid interface with its variations. Outside of the two conserved RNP motifs that lie in the center of the RRM beta-sheet, the two external beta-strands, the loops, the C- and N-termini, or even a second RRM domain allow high RNA-binding affinity and specific recognition. Protein-RRM interactions that have been found in several structures reinforce the notion of an extreme structural versatility of this domain supporting the numerous biological functions of the RRM-containing proteins.     

RNA-binding proteins: modular design for efficient function

Many RNA-binding proteins have modular structures and are composed of multiple repeats of just a few basic domains that are arranged in various ways to satisfy their diverse functional requirements. Recent studies have investigated how different modules cooperate in regulating the RNA-binding specificity and the biological activity of these proteins. They have also investigated how multiple modules cooperate with enzymatic domains to regulate the catalytic activity of enzymes that act on RNA. These studies have shown how, for many RNA-binding proteins, multiple modules define the fundamental structural unit that is responsible for biological function.     

Using RNA secondary structures to guide sequence motif finding towards single-stranded regions

RNA binding proteins recognize RNA targets in a sequence specific manner. Apart from the sequence, the secondary structure context of the binding site also affects the binding affinity. Binding sites are often located in single-stranded RNA regions and it was shown that the sequestration of a binding motif in a double-strand abolishes protein binding. Thus, it is desirable to include knowledge about RNA secondary structures when searching for the binding motif of a protein. We present the approach MEMERIS for searching sequence motifs in a set of RNA sequences and simultaneously integrating information about secondary structures. To abstract from specific structural elements, we precompute position-specific values measuring the single-strandedness of all substrings of an RNA sequence. These values are used as prior knowledge about the motif starts to guide the motif search. Extensive tests with artificial and biological data demonstrate that MEMERIS is able to identify motifs in single-stranded regions even if a stronger motif located in double-strand parts exists. The discovered motif occurrences in biological datasets mostly coincide with known protein-binding sites. This algorithm can be used for finding the binding motif of single-stranded RNA-binding proteins in SELEX or other biological sequence data.     

Constrained peptides mimic a viral suppressor of RNA silencing

The design of high-affinity, RNA-binding ligands has proven very challenging. This is due to the unique structural properties of RNA, often characterized by polar surfaces and high flexibility. In addition, the frequent lack of well-defined binding pockets complicates the development of small molecule binders. This has triggered the search for alternative scaffolds of intermediate size. Among these, peptide-derived molecules represent appealing entities as they can mimic structural features also present in RNA-binding proteins. However, the application of peptidic RNA-targeting ligands is hampered by a lack of design principles and their inherently low bio-stability. Here, the structure-based design of constrained α-helical peptides derived from the viral suppressor of RNA silencing, TAV2b, is described. We observe that the introduction of two inter-side chain crosslinks provides peptides with increased α-helicity and protease stability. One of these modified peptides (B3) shows high affinity for double-stranded RNA structures including a palindromic siRNA as well as microRNA-21 and its precursor pre-miR-21. Notably, B3 binding to pre-miR-21 inhibits Dicer processing in a biochemical assay. As a further characteristic this peptide also exhibits cellular entry. Our findings show that constrained peptides can efficiently mimic RNA-binding proteins rendering them potentially useful for the design of bioactive RNA-targeting ligands.     

Structure-based prediction of RNA-binding domains and RNA-binding sites and application to structural genomics targets

Mechanistic understanding of many key cellular processes often involves identification of RNA binding proteins (RBPs) and RNA binding sites in two separate steps. Here, they are predicted simultaneously by structural alignment to known protein-RNA complex structures followed by binding assessment with a DFIRE-based statistical energy function. This method achieves 98% accuracy and 91% precision for predicting RBPs and 93% accuracy and 78% precision for predicting RNA-binding amino-acid residues for a large benchmark of 212 RNA binding and 6761 non-RNA binding domains (leave-one-out cross-validation). Additional tests revealed that the method makes no false positive prediction from 311 DNA binding domains but correctly detects six domains binding with both DNA and RNA. In addition, it correctly identified 31 of 75 unbound RNA-binding domains with 92% accuracy and 65% precision for predicted binding residues and achieved 86% success rate in its application to SCOP RNA binding domain superfamily (Structural Classification Of Proteins). It further predicts 25 targets as RBPs in 2076 structural genomics targets: 20 of 25 predicted ones (80%) are putatively RNA binding. The superior performance over existing methods indicates the importance of dividing structures into domains, using a Z-score to measure relative structural similarity, and a statistical energy function to measure protein-RNA binding affinity.     

Themes in RNA-protein recognition.

Atomic resolution structures are now available for more than 20 complexes of proteins with specific RNAs. This review examines two main themes that appear in this set of structures. A "groove binder" class of proteins places a protein structure (alpha-helix, 310-helix, beta-ribbon, or irregular loop) in the groove of an RNA helix, recognizing both the specific sequence of bases and the shape or dimensions of the groove, which are sometimes distorted from the normal A-form. A second class of proteins uses beta-sheet surfaces to create pockets that examine single-stranded RNA bases. Some of these proteins recognize completely unstructured RNA, and in others RNA secondary structure indirectly promotes binding by constraining bases in an appropriate orientation. Thermodynamic studies have shown that binding specificity is generally a function of several factors, including base-specific hydrogen bonds, non-polar contacts, and mutual accommodation of the protein and RNA-binding surfaces. The recognition strategies and structural frameworks used by RNA binding proteins are not exotically different from those employed by DNA-binding proteins, suggesting that the two kinds of nucleic acid-binding proteins have not evolved independently.     

KH domains with impaired nucleic acid binding as a tool for functional analysis

In eukaryotes, RNA-binding proteins that contain multiple K homology (KH) domains play a key role in coordinating the different steps of RNA synthesis, metabolism and localization. Understanding how the different KH modules participate in the recognition of the RNA targets is necessary to dissect the way these proteins operate. We have designed a KH mutant with impaired RNA-binding capability for general use in exploring the role of individual KH domains in the combinatorial functional recognition of RNA targets. A double mutation in the hallmark GxxG loop (GxxG-to-GDDG) impairs nucleic acid binding without compromising the stability of the domain. We analysed the impact of the GDDG mutations in individual KH domains on the functional properties of KSRP as a prototype of multiple KH domain-containing proteins. We show how the GDDG mutant can be used to directly link biophysical information on the sequence specificity of the different KH domains of KSRP and their role in mRNA recognition and decay. This work defines a general molecular biology tool for the investigation of the function of individual KH domains in nucleic acid binding proteins.     

Recognition of diverse RNAs by a single protein structural framework

The coat proteins of different single-strand RNA phages utilize a common structural framework to recognize different RNA targets, making them suitable models for studies of RNA-protein recognition generally, especially for the class of proteins that bind RNA on a beta-sheet surface. Here we show that structurally distinct molecules are capable of satisfying the requirements for binding to Qbeta coat protein. Although the predicted secondary structures of the RNAs differ markedly, we contend that they are approximately equivalent structurally in their complexes with coat protein. Based on our prior observations that the RNA-binding specificities of Qbeta and MS2 coat proteins can be interconverted with as few as one amino acid substitution each, and taking into account details of the structures of complexes of MS2 coat protein with wild-type and aptamer RNAs, we propose a model for the Qbeta coat protein-RNA complex.     

RNA-protein complexes.

RNA-binding proteins are an extremely diverse group of proteins, reflecting the diverse functional requirements of cellular RNAs. Whereas the number of structures of RNA-binding proteins or modules is increasing at a reasonable rate, that of protein-RNA complexes increments by only a few each year. The recently determined structure of a complex from the U2 small nuclear ribonucleoprotein particle shows the subtleties of RNA stem-loop recognition by ribonucleoprotein modules. A second structure provides the first direct information on double-stranded RNA recognition by the double-stranded RNA-binding module that occurs in a variety of functionally distinct proteins. Another two new complexes concern proteins interacting with tRNA. The first is methionyl-tRNAf(Met) transformylase, which has to compete with elongation factor Tu for charged initiator tRNAMet and does so by recognising specific features of the acceptor stem of tRNAf(Met). The second is prolyl-tRNA synthetase, complexed with its cognate tRNA, that has to specifically recognise the two guanines common to all tRNA anticodons specific for proline.     

Design of RNA-binding proteins and ligands

The rapidly expanding database of RNA structures and protein complexes is beginning to lead to the successful design of specific RNA-binding molecules. Recent combinatorial and structure-based approaches have utilized known nucleic-acid-binding scaffolds from both proteins and small molecules to display a relatively small set of functional groups often used in protein--RNA recognition. Several studies have shown that the tethering of multiple binding modules can enhance RNA-binding affinity and specificity, a strategy also commonly used in DNA recognition.     

Function annotation for pseudoknot using structure similarity

Many raw biological sequence data have been generated by the human genome project and related efforts. The understanding of structural information encoded by biological sequences is important to acquire knowledge of their biochemical functions but remains a fundamental challenge. Recent interest in RNA regulation has resulted in a rapid growth of deposited RNA secondary structures in varied databases. However, a functional classification and characterization of the RNA structure have only been partially addressed. This article aims to introduce a novel interval-based distance metric for structure-based RNA function assignment. The characterization of RNA structures relies on distance vectors learned from a collection of predicted structures. The distance measure considers the intersected, disjoint, and inclusion between intervals. A set of RNA pseudoknotted structures with known function are applied and the function of the query structure is determined by measuring structure similarity. This not only offers sequence distance criteria to measure the similarity of secondary structures but also aids the functional classification of RNA structures with pesudoknots.     

Structural properties of carnation mottle virus p7 movement protein and its RNA-binding domain

Plant viral movement proteins (MPs) participate actively in the intra- and intercellular movement of RNA plant viruses to such an extent that MP dysfunction impairs viral infection. However, the molecular mechanism(s) of their interaction with cognate nucleic acids are not well understood, partly due to the lack of structural information. In this work, a protein dissection approach was used to gain information on the structural and RNA-binding properties of this class of proteins, as exemplified by the 61-amino acid residue p7 MP from carnation mottle virus (CarMV). Circular dichroism spectroscopy showed that CarMV p7 is an alpha/beta RNA-binding soluble protein. Using synthetic peptides derived from the p7 sequence, we have identified three distinct putative domains within the protein. EMSA showed that the central region, from residue 17 to 35 (represented by peptide p7(17-35)), is responsible for the RNA binding properties of CarMV p7. This binding peptide populates a nascent alpha-helix in water solution that is further stabilized in the presence of either secondary structure inducers, such as trifluoroethanol and monomeric SDS, or RNA (which also changes its conformation upon binding to the peptide). Thus, the RNA recognition appears to occur via an "adaptive binding" mechanism. Interestingly, the amino acid sequence and structural properties of the RNA-binding domain of p7 seem to be conserved among carmoviruses and some other RNA-binding proteins and peptides. The low conserved N terminus of p7 (peptide p7(1-16)) is unstructured in solution. In contrast, the highly conserved C terminus motif (peptide p7(40-61)) adopts a beta-sheet conformation in aqueous solution. Alanine scanning mutagenesis of the RNA-binding motif showed how selected positive charged amino acids are more relevant than others in the RNA binding process and how hydrophobic amino acid side chains would participate in the stabilization of the protein-RNA complex.     

RNA-binding strategies common to cold-shock domain- and RNA recognition motif-containing proteins

Numerous RNA-binding proteins have modular structures, comprising one or several copies of a selective RNA-binding domain generally coupled to an auxiliary domain that binds RNA non-specifically. We have built and compared homology-based models of the cold-shock domain (CSD) of the Xenopus protein, FRGY2, and of the third RNA recognition motif (RRM) of the ubiquitous nucleolar protein, nucleolin. Our model of the CSD_FRG–RNA complex constitutes the first prediction of the three-dimensional structure of a CSD–RNA complex and is consistent with the hypothesis of a convergent evolution of CSD and RRM towards a related single-stranded RNA-binding surface. Circular dichroism spectroscopy studies have revealed that these RNA-binding domains are capable of orchestrating similar types of RNA conformational change. Our results further show that the respective auxiliary domains, despite their lack of sequence homology, are functionally equivalent and indispensable for modulating the properties of the specific RNA-binding domains. A comparative analysis of FRGY2 and nucleolin C-terminal domains has revealed common structural features representing the signature of a particular type of auxiliary domain, which has co-evolved with the CSD and the RRM.