SPOT-Seq-RNA: Predicting protein-RNA complex structure and RNA-binding function by fold recognition and binding affinity prediction

RNA-binding proteins (RBPs) play key roles in RNA metabolism and post-transcriptional regulation. Computational methods have been developed separately for prediction of RBPs and RNA-binding residues by machine-learning techniques and prediction of protein-RNA complex structures by rigid or semiflexible structure-to-structure docking. Here, we describe a template-based technique called SPOT-Seq-RNA that integrates prediction of RBPs, RNA-binding residues, and protein-RNA complex structures into a single package. This integration is achieved by combining template-based structure-prediction software, SPARKS X, with binding affinity prediction software, DRNA. This tool yields reasonable sensitivity (46 %) and high precision (84 %) for an independent test set of 215 RBPs and 5,766 non-RBPs. SPOT-Seq-RNA is computationally efficient for genome-scale prediction of RBPs and protein-RNA complex structures. Its application to human genome study has revealed a similar sensitivity and ability to uncover hundreds of novel RBPs beyond simple homology. The online server and downloadable version of SPOT-Seq-RNA are available at http://sparks-lab.org/server/SPOT-Seq-RNA/

RNA secondary structure prediction from multi-aligned sequences

It has been well accepted that the RNA secondary structures of most functional non-coding RNAs (ncRNAs) are closely related to their functions and are conserved during evolution. Hence, prediction of conserved secondary structures from evolutionarily related sequences is one important task in RNA bioinformatics; the methods are useful not only to further functional analyses of ncRNAs but also to improve the accuracy of secondary structure predictions and to find novel functional RNAs from the genome. In this review, I focus on common secondary structure prediction from a given aligned RNA sequence, in which one secondary structure whose length is equal to that of the input alignment is predicted. I systematically review and classify existing tools and algorithms for the problem, by utilizing the information employed in the tools and by adopting a unified viewpoint based on maximum expected gain (MEG) estimators. I believe that this classification will allow a deeper understanding of each tool and provide users with useful information for selecting tools for common secondary structure predictions.Comment: A preprint of an invited review manuscript that will be published in a chapter of the book `Methods in Molecular Biology'. Note that this version of the manuscript may differ from the published versio

Quantitative Response of IMS Detector for Mixtures Containing Two Active Components

This study describes the relationship between the output signal of the ion mobility spectrometry (IMS) detector and the concentrations of two compounds being simultaneously introduced into the reaction section. Investigations were performed for three pairs of compounds, that is, dimethyl methylphosphonate (DMMP) and acetone, methyl <i>tert</i>-butyl ether (MTBE), and acetone, as well as trimethylamine (TMA) and <i>n</i>-nonylamine (NA). Vapors of the investigated compounds were produced in a two-channel generator with permeation sources and a dilution system based on mass-flow controllers. The generator design and the method of concentration determination are discussed in this paper. It was found that admixture can differently influence detection of an analyte. The presence of acetone does not effect the signal corresponding to dimer ions of DMMP. For pairs MTBE + acetone and TMA + NA characteristic peaks of analyte ions diminish with growing concentration of admixture, however, the detection based on the peak of the asymmetric dimer containing proton-bound molecules of both compounds is effective. For the detection of TMA in the presence of NA, the signal generated by the asymmetric dimer ions is meaningfully higher than the signals of monomer or dimer TMA ions measured without the NA admixture. The course of calibration dependencies was analyzed on the basis of a simple mathematical model of the reaction region. This model provided an estimation of the intensity of the signal for a given ionic species for definite concentration of analyte

Toxicity of clove essential oil and its ester eugenyl acetate against Artemia salina

Abstract The production of compounds via enzymatic esterification has great scientific and technological interest due to the several inconveniences related to acid catalysis, mainly by these systems do not fit to the concept of “green chemistry”. Besides, natural products as clove oil present compounds with excellent biological potential. Bioactives compounds are often toxic at high doses. The evaluation of lethality in a less complex animal organism can be used to a monitoring simple and rapid, helping the identification of compounds with potential insecticide activity against larvae of insect vector of diseases. In this sense, the toxicity against Artemia salina of clove essential oil and its derivative eugenyl acetate obtained by enzymatic esterification using Novozym 435 as biocatalyst was evaluated. The conversion of eugenyl acetate synthesis was 95.6%. The results about the evaluation of toxicity against the microcrustacean Artemia salina demonstrated that both oil (LC50= 0.5993 µg.mL–1) and ester (LC50= 0.1178 µg.mL–1) presented high toxic potential, being the eugenyl acetate almost 5 times more toxic than clove essential oil. The results reported here shows the potential of employing clove oil and eugenyl acetate in insecticide formulations