N-(Iodoacetyl)-N'-(anthraquinon-2-oyl)-ethylenediamine (IAED): a new heterobifunctional reagent for the preparation of biochips

Design and synthesis of a new heterobifunctional reagent, N-(iodoacetyl)-N'-(anthraquinon-2-oyl)-ethylenediamine (IAED), have been described for the preparation of oligonucleotide-based biochips. The performance of the featured reagent is probed by the immobilization of thiolated and thiophosphorylated oligonucleotides on modified glass microslides via two routes (routes A and B). The immobilization procedure was accelerated by performing a chemical reaction between thiolated oligomers and the iodoacetyl moiety of the reagent under microwaves (MW), where it is completed in just 10 min. The quality of the constructed oligonucleotide microarrays was tested by performing a hybridization assay with a complementary target and subsequently used for the detection of base mismatches. The immobilized probes were found to be thermally stable.     

3D structure generation,virtual screening and docking of human Ras-associated binding (Rab3A) protein involved in tumourigenesis

Rab3A is expressed predominantly in brain and synaptic vesicles. Rab3A is involved specifically in tethering and docking of synaptic vesicles prior to fusion which is a critical step in regulated release of neurotransmitters. The precise function of Rab3A is still not known. However, up-regulation of Rab3A has been reported in malignant neuroendocrine and breast cancer cells. In the present study, the structure of Rab3A protein was generated using MODELLER 9v8 software. The modeled protein structure was validated and subjected to molecular docking analyses. Docking with GTP was carried out on the binding site of Rab3A using GOLD software. The Rab3A-GTP complex has best GOLD fitness value of 77.73. Ligplot shows hydrogen bondings (S16, S17, V18, G19, K20, T21, S22, S31, T33, A35, S38, T39 and G65) and hydrophobic interacting residues (F25, F32, P34, F36, V37, D62 and A64) with the GTP ligands in the binding site of Rab3A protein. Here, the ligand molecules of NCI diversity set II from the ZINC database against the active site of the Rab3A protein were screened. For this purpose, the incremental construction algorithm of GLIDE and the genetic algorithm of GOLD were used. Docking results were analyzed for top ranking compounds using a consensus scoring function of X-Score to calculate the binding affinity and Ligplot was used to measure protein–ligand interactions. Five compounds which possess good inhibitory activity and may act as potential high affinity inhibitors against Rab3A active site were identified. The top ranking molecule (ZINC13152284) has a Glide score of ?6.65 kcal/mol, X-Score of ?3.02 kcal/mol and GOLD score of 64.54 with 03 hydrogen bonds and 09 hydrophobic contacts. This compound is thus a good starting point for further development of strong inhibitors.     

miRPlant: an integrated tool for identification of plant miRNA from RNA sequencing data

Background

Small RNA sequencing is commonly used to identify novel miRNAs and to determine their expression levels in plants. There are several miRNA identification tools for animals such as miRDeep, miRDeep2 and miRDeep*. miRDeep-P was developed to identify plant miRNA using miRDeep’s probabilistic model of miRNA biogenesis, but it depends on several third party tools and lacks a user-friendly interface. The objective of our miRPlant program is to predict novel plant miRNA, while providing a user-friendly interface with improved accuracy of prediction.

Result

We have developed a user-friendly plant miRNA prediction tool called miRPlant. We show using 16 plant miRNA datasets from four different plant species that miRPlant has at least a 10% improvement in accuracy compared to miRDeep-P, which is the most popular plant miRNA prediction tool. Furthermore, miRPlant uses a Graphical User Interface for data input and output, and identified miRNA are shown with all RNAseq reads in a hairpin diagram.

Conclusions

We have developed miRPlant which extends miRDeep* to various plant species by adopting suitable strategies to identify hairpin excision regions and hairpin structure filtering for plants. miRPlant does not require any third party tools such as mapping or RNA secondary structure prediction tools. miRPlant is also the first plant miRNA prediction tool that dynamically plots miRNA hairpin structure with small reads for identified novel miRNAs. This feature will enable biologists to visualize novel pre-miRNA structure and the location of small RNA reads relative to the hairpin. Moreover, miRPlant can be easily used by biologists with limited bioinformatics skills.miRPlant and its manual are freely available at http://www.australianprostatecentre.org/research/software/mirplant or http://sourceforge.net/projects/mirplant/.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-275) contains supplementary material, which is available to authorized users.     

Integrative approach to pain genetics identifies pain sensitivity loci across diseases

Identifying human genes relevant for the processing of pain requires difficult-to-conduct and expensive large-scale clinical trials. Here, we examine a novel integrative paradigm for data-driven discovery of pain gene candidates, taking advantage of the vast amount of existing disease-related clinical literature and gene expression microarray data stored in large international repositories. First, thousands of diseases were ranked according to a disease-specific pain index (DSPI), derived from Medical Subject Heading (MESH) annotations in MEDLINE. Second, gene expression profiles of 121 of these human diseases were obtained from public sources. Third, genes with expression variation significantly correlated with DSPI across diseases were selected as candidate pain genes. Finally, selected candidate pain genes were genotyped in an independent human cohort and prospectively evaluated for significant association between variants and measures of pain sensitivity. The strongest signal was with rs4512126 (5q32, ABLIM3, P = 1.3×10⁻¹⁰) for the sensitivity to cold pressor pain in males, but not in females. Significant associations were also observed with rs12548828, rs7826700 and rs1075791 on 8q22.2 within NCALD (P = 1.7×10⁻⁴, 1.8×10⁻⁴, and 2.2×10⁻⁴ respectively). Our results demonstrate the utility of a novel paradigm that integrates publicly available disease-specific gene expression data with clinical data curated from MEDLINE to facilitate the discovery of pain-relevant genes. This data-derived list of pain gene candidates enables additional focused and efficient biological studies validating additional candidates.