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WIREs Comput Mol Sci
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Predictions of protein–RNA interactions

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Ribonucleoprotein interactions play important roles in a wide variety of cellular processes, ranging from transcriptional and posttranscriptional regulation of gene expression to host defense against pathogens. High throughput experiments to identify RNA–protein interactions provide information about the complexity of interaction networks, but require time and considerable efforts. Thus, there is need for reliable computational methods for predicting ribonucleoprotein interactions. In this review, we discuss a number of approaches that have been developed to predict the ability of proteins and RNA molecules to associate. © 2012 John Wiley & Sons, Ltd.

This article is categorized under:

  • Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods
Figure 1.

Predictions of RNA associations with protein classes. The catRAPID method is used to calculate the ability of proteins to interact with ncRNAs.13 (a) RNA‐binding, ribonucleo‐ and DNA‐binding proteins show higher propensities to bind to RNA than anionic‐, cation‐, and non‐nucleic‐acid binding proteins.12 (b) In Homo sapiens, The Suppressor of Zeste Homolog Suz12 is predicted to interact with HOTAIR 5′ (NCBI entry NR_003716.2 nucleotides 56–355; discriminative power 76%), which is in agreement with experimental evidence.15 RNA‐binding sites correspond to the C terminal VEFS‐Box, which contains a Zinc finger domain, as well as amino acids 150–200 and 210–250, which are rich in positively charged residues; (c) indoleglycerol Phosphate Synthase (pdb code 1A53) belongs to the class non‐nucleic‐acid binding proteins (NNBP)12 and shows negligible propensity to bind to HOTAIR 5′ (discriminative power 0%).11,12 (d) Suz12 does not bind to HOTAIR 3′ (nucleotides 1553‐2198; discriminative power 0%), as shown by experiments carried out in HeLa cells.15

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Figure 2.

RNAse P. In Escherichia coli, RNase P is composed of a large catalytic molecule of RNA (M1 RNA) and a small protein subunit (C5 protein). This complex is required to process precursor tRNAs in functional tRNAs molecules. C5 protein enhances substrate recognition and helps catalysis by discriminating between substrate and product through the binding to the 5′ leader sequence of pre‐tRNA.18 The C5 RNA‐binding domain spans the entire protein sequence. High interactions are predicted between C5 and several pre‐tRNA molecules.19 (a) High interaction propensity is predicted between C5 and Ser pre‐tRNA (E. coli K12 2816667–2816575 nt; discriminative power 80%). The predicted binding site is located at the 5′ leader, in agreement with experimental evidence19; (b) randomization of Ser pre‐tRNA sequence results in strong reduction of the C5 binding ability (discriminative power 0%); (c) C5 and Ser pre‐tRNA are predicted to have higher interaction propensities than a random pool of 104 associations with same protein and RNA lengths (interaction strength 99%, marked as blue area under the distribution curve). (d) We predict strong interaction propensities for all the pre‐tRNA molecules reported to interact with C5.19 More specifically, we find that 80 pre‐tRNAs (i.e., 92% of the RNA set) have interaction strengths (IS) > 50% with average interaction strength = 82%.

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Figure 3.

The CsrA‐CsrB system. The central component of the calcium storage regulator system, CsrA, is a 61‐amino‐acid RNA‐binding protein. This small protein, whose RNA‐binding domain spans the entire polypeptide sequence, inhibits glycogen biosynthesis and catabolism, gluconeogenesis, and biofilm formation, whereas it activates glycolysis, acetate metabolism, motility, and flagellum biosynthesis.20,21 A second component of the CSR system is untranslated CsrB RNA (fRNAdb code: FR283968), which binds to a number CsrA subunits, forming a large globular ribonucleoprotein complex (Erwinia carotovora). (a) In agreement with previous observations, CsrB is predicted to contact CsrA (discriminative power 88%)13 and shows binding regions in the 5′ and central region of the transcript in correspondence to the repeated motifs CAGGATG, CAGGAAG, AAGGAAA, and AGGGAT.23 (b) Very strong interaction is predicted for the CsrA–CsrB system with respect to a random pool of 104 protein–RNA associations (interaction strength 97%, marked as blue area under the distribution curve).

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