Tertiary structure prediction of RNA-RNA complexes using a secondary structure and fragment-based method

RNAapt3D: RNA aptamer 3D-structural modeling database

RNA aptamers are oligonucleotides with high binding affinity and specificity for target molecules and are expected to be a new generation of therapeutic molecules and targeted delivery materials. The tertiary structure of RNA molecules and RNA-protein interaction sites are increasingly important as potential targets for new drugs. The pathological mechanisms of diseases must be understood in detail to guide drug design. In developing RNA aptamers as drugs, information about the interaction mechanisms and structures of RNA aptamer-target protein complexes are useful. We constructed a database, RNA aptamer 3D-structural modeling (RNAapt3D), consisting of RNA aptamer data that are potential drug candidates. The database includes RNA sequences and computationally predicted RNA tertiary structures based on secondary structures and implements methods that can be used to predict unknown structures of RNA aptamer-target molecule complexes. RNAapt3D should enable the design of RNA aptamers for target molecules and improve the efficiency and productivity of candidate drug selection. RNAapt3D can be accessed at https://rnaapt3d.medals.jp.

IL1B Increases Intestinal Tight Junction Permeability by Up-regulation of MIR200C-3p, Which Degrades Occludin mRNA

BACKGROUND & AIMS

Defects in the epithelial tight junction (TJ) barrier contribute to development of intestinal inflammation associated with diseases. Interleukin 1 beta (IL1B) increases intestinal permeability in mice. We investigated microRNAs that are regulated by IL1B and their effects on expression of TJ proteins and intestinal permeability.

METHODS

We used Targetscan to identify microRNAs that would bind the 3' untranslated region (3'UTR) of occludin mRNA; regions that interacted with microRNAs were predicted using the V-fold server and Assemble2, and 3-dimensional models were created using UCSF Chimera linked with Assemble2. Caco-2 cells were transfected with vectors that express microRNAs, analyzed by immunoblots and real-time polymerase chain reaction (PCR), and grown as monolayers; permeability in response to IL1B was assessed with the marker inulin. Male C57BL/6 mice were given intraperitoneal injections of IL1B and intestinal recycling perfusion was measured; some mice were given dextran sodium sulfate to induce colitis and/or gavage with an antagonist to MIR200C-3p (antagomiR-200C) or the nonspecific antagomiR (control). Intestinal tissues were collected from mice and analyzed by histology and real-time PCR; enterocytes were isolated by laser capture microdissection. We also analyzed colon tissues and organoids from patients with and without ulcerative colitis.

RESULTS

Incubation of Caco-2 monolayers with IL1B increased TJ permeability and reduced levels of occludin protein and mRNA without affecting the expression of other transmembrane TJ proteins. Targetscan identified MIR122, MIR200B-3p, and MIR200C-3p, as miRNAs that might bind to the occludin 3'UTR. MIR200C-3p was rapidly increased in Caco-2 cells incubated with IL1B; the antagomiR-200c prevented the IL1B-induced decrease in occludin mRNA and protein and reduced TJ permeability. Administration of IL1B to mice increased small intestinal TJ permeability, compared with mice given vehicle; enterocytes isolated from mice given IL1B had increased expression of MIR200C-3p and decreased levels of occludin messenger RNA (mRNA) and protein. Intestinal tissues from mice with colitis had increased levels of IL1B mRNA and MIR200C-3p and decreased levels of occludin mRNA; gavage of mice with antagomiR-200C reduced levels of MIR200C-3p and prevented the decrease in occludin mRNA and the increase in colonic permeability. Colon tissues and organoids from patients with ulcerative colitis had increased levels of IL1B mRNA and MIR200C-3p compared with healthy controls. Using 3-dimensional molecular modeling and mutational analyses, we identified the nucleotide bases in the occluding mRNA 3'UTR that interact with MIR200C-3p.

CONCLUSIONS

Intestine tissues from patients with ulcerative colitis and mice with colitis have increased levels of IL1B mRNA and MIR200C-3p, which reduces expression of occludin by enterocytes and thereby increases TJ permeability. Three-dimensional modeling of the interaction between MIR200C-3p and the occludin mRNA 3'UTR identified sites of interaction. The antagomiR-200C prevents the decrease in occludin in enterocytes and intestine tissues of mice with colitis, maintaining the TJ barrier.

Structure folding of RNA kissing complexes in salt solutions: predicting 3D structure, stability, and folding pathway

RNA kissing complexes are essential for genomic RNA dimerization and regulation of gene expression, and their structures and stability are critical to their biological functions. In this work, we used our previously developed coarse-grained model with an implicit structure-based electrostatic potential to predict three-dimensional (3D) structures and stability of RNA kissing complexes in salt solutions. For extensive RNA kissing complexes, our model shows great reliability in predicting 3D structures from their sequences, and our additional predictions indicate that the model can capture the dependence of 3D structures of RNA kissing complexes on monovalent/divalent ion concentrations. Moreover, the comparisons with extensive experimental data show that the model can make reliable predictions on the stability for various RNA kissing complexes over wide ranges of monovalent/divalent ion concentrations. Notably, for RNA kissing complexes, our further analyses show the important contribution of coaxial stacking to the 3D structures and stronger stability than the corresponding kissing-interface duplexes at high salts. Furthermore, our comprehensive analyses for RNA kissing complexes reveal that the thermally folding pathway for a complex sequence is mainly determined by the relative stability of two possible folded states of kissing complex and extended duplex, which can be significantly modulated by its sequence.

Determination of an effective scoring function for RNA-RNA interactions with a physics-based double-iterative method

RNA–RNA interactions play fundamental roles in gene and cell regulation. Therefore, accurate prediction of RNA–RNA interactions is critical to determine their complex structures and understand the molecular mechanism of the interactions. Here, we have developed a physics-based double-iterative strategy to determine the effective potentials for RNA–RNA interactions based on a training set of 97 diverse RNA–RNA complexes. The double-iterative strategy circumvented the reference state problem in knowledge-based scoring functions by updating the potentials through iteration and also overcame the decoy-dependent limitation in previous iterative methods by constructing the decoys iteratively. The derived scoring function, which is referred to as DITScoreRR, was evaluated on an RNA–RNA docking benchmark of 60 test cases and compared with three other scoring functions. It was shown that for bound docking, our scoring function DITScoreRR obtained the excellent success rates of 90% and 98.3% in binding mode predictions when the top 1 and 10 predictions were considered, compared to 63.3% and 71.7% for van der Waals interactions, 45.0% and 65.0% for ITScorePP, and 11.7% and 26.7% for ZDOCK 2.1, respectively. For unbound docking, DITScoreRR achieved the good success rates of 53.3% and 71.7% in binding mode predictions when the top 1 and 10 predictions were considered, compared to 13.3% and 28.3% for van der Waals interactions, 11.7% and 26.7% for our ITScorePP, and 3.3% and 6.7% for ZDOCK 2.1, respectively. DITScoreRR also performed significantly better in ranking decoys and obtained significantly higher score-RMSD correlations than the other three scoring functions. DITScoreRR will be of great value for the prediction and design of RNA structures and RNA–RNA complexes.

ToGo-WF: prediction of RNA tertiary structures and RNA-RNA/protein interactions using the KNIME workflow

Recent progress in molecular biology has revealed that many non-coding RNAs regulate gene expression or catalyze biochemical reactions in tumors, viruses and several other diseases. The tertiary structure of RNA molecules and RNA–RNA/protein interaction sites are of increasing importance as potential targets for new medicines that treat a broad array of human diseases. Current RNA drugs are split into two groups: antisense RNA molecules and aptamers. In this report, we present a novel workflow to predict RNA tertiary structures and RNA–RNA/protein interactions using the KNIME environment, which enabled us to assemble a combination of RNA-related analytical tools and databases. In this study, three analytical workflows for comprehensive structural analysis of RNA are introduced: (1) prediction of the tertiary structure of RNA; (2) prediction of the structure of RNA–RNA complexes and analysis of their interactions; and (3) prediction of the structure of RNA–protein complexes and analysis of their interactions. In an RNA–protein case study, we modeled the tertiary structure of pegaptanib, an aptamer drug, and performed docking calculations of the pegaptanib-vascular endothelial growth factor complex using a fragment of the interaction site of the aptamer. We also present molecular dynamics simulations of the RNA–protein complex to evaluate the affinity of the complex by mutating bases at the interaction interface. The results provide valuable information for designing novel features of aptamer-protein complexes.