Messenger RNAs interact with a number of different molecules that determine the fate of each transcript and contribute to the overall pattern of gene expression. These interactions are governed by specific mRNA signals, which in principle could represent a special mRNA recognition 'code'. Both, small molecules and proteins demonstrate a diversity of mRNA binding modes often dependent on the structural context of the regions surrounding specific target sequences. In this review, we have highlighted recent structural studies that illustrate the diversity of recognition principles used by mRNA binders for timely and specific targeting and processing of the message.
"Over the past few years, there has been an increasing interest in RNA biology and RNA binding proteins. Structural studies of protein–RNA complexes are therefore needed if we want to understand how proteins recognise specifically their RNA targets and to derive a general code for RNA recognition [55,56]. The intrinsic properties of such complexes, however, make them difficult to study structurally. "
[Show abstract][Hide abstract] ABSTRACT: In the past few years, RNA molecules have been revealed to be at the center of numerous biological processes. Long considered as passive molecules transferring genetic information from DNA to proteins, it is now well established that RNA molecules play important regulatory roles. Associated with that, the number of identified RNA binding proteins (RBP) has increased considerably and mutations in RNA molecules or RBP have been shown to cause various diseases, such as cancers. It is therefore crucial to understand at the molecular level how these proteins specifically recognize their RNA targets in order to design new generation drug therapies targeting protein-RNA complexes. Nuclear Magnetic Resonance (NMR) is a particularly well-suited technique to study such protein-RNA complexes at the atomic level and can provide valuable information for new drug discovery programs. In this chapter, we describe the NMR strategy that we and other laboratories use for screening optimal conditions necessary for structural studies of protein-single stranded RNA complexes, using two proteins, Sam68 and T-STAR, as examples.
"Folding upon binding represents an extreme class of conformational change, but it may be an option for high-confidence predictions . Another challenge in the computational analysis of RNP interactome is that many RNA-binding proteins recognize just RNA sequences that are in single-stranded regions (Extended Discussion, 3; Agostini et al., 2013; Goodarzi et al., 2012; Serganov and Patel, 2008; Shulman-Peleg et al., 2008). An inherent limitation of using only solved structures is that many of these are protein domains, not full-length proteins. "
[Show abstract][Hide abstract] ABSTRACT: RNA-protein (RNP) interactions generally are required for RNA function. At least 5% of human genes code for RNA-binding proteins. Whereas many approaches can identify the RNA partners for a specific protein, finding the protein partners for a specific RNA is difficult. We present a machine-learning method that scores a protein's binding potential for an RNA structure by utilizing the chemical context profiles of the interface from known RNP structures. Our approach is applicable even when only a single RNP structure is available. We examined 801 mammalian proteins and find that 37 (4.6%) potentially bind transfer RNA (tRNA). Most are enzymes involved in cellular processes unrelated to translation and were not known to interact with RNA. We experimentally tested six positive and three negative predictions for tRNA binding in vivo, and all nine predictions were correct. Our computational approach provides a powerful complement to experiments in discovering new RNPs.
"Still, a few smRNA target sites do appear in UTRs, and these can be used to assess trends in target-site conservation without the confounding effects of conservation related to protein encoding. Although post-transcriptional processes are sometimes mediated by RNA secondary structure, most mRNA-specific interactions require a primary nucleotide sequence component (Rabani et al. 2008; Serganov and Patel 2008; Gilligan et al. 2011). The conservation of such primary sequence elements is typically easier to interpret because similarity in secondary structure is often a result of nucleotide composition (Rivas and Eddy 2000) and, even when constrained structure can be identified via covariance, these structures are difficult to generalize across the genes that harbor them (McGuire and Galagan 2008; Rabani et al. 2008). "
[Show abstract][Hide abstract] ABSTRACT: The sequence elements that mediate post-transcriptional gene regulation often reside in the 5' and 3' untranslated regions (UTRs) of mRNAs. Using six different families of dicotyledonous plants, we developed a comparative transcriptomics pipeline for the identification and annotation of deeply conserved regulatory sequences in the 5' and 3' UTRs. Our approach was robust to confounding effects of poor UTR alignability and rampant paralogy in plants. In the 3' UTR, motifs resembling PUMILIO-binding sites form a prominent group of conserved motifs. Additionally, Expansins, one of the few plant mRNA families known to be localized to specific subcellular sites, possess a core conserved RCCCGC motif. In the 5' UTR, one major subset of motifs consists of purine-rich repeats. A distinct and substantial fraction possesses upstream AUG start codons. Half of the AUG containing motifs reveal hidden protein-coding potential in the 5' UTR, while the other half point to a peptide-independent function related to translation. Among the former, we added four novel peptides to the small catalog of conserved-peptide uORFs. Among the latter, our case studies document patterns of uORF evolution that include gain and loss of uORFs, switches in uORF reading frame, and switches in uORF length and position. In summary, nearly three hundred post-transcriptional elements show evidence of purifying selection across the eudicot branch of flowering plants, indicating a regulatory function spanning at least 70 million years. Some of these sequences have experimental precedent, but many are novel and encourage further exploration.
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