A comprehensive spectroscopic study of the polymorphs of diflunisal and their phase transformations

Understanding phase transitions in pharmaceutical materials is of vital importance for drug manufacturing, processing and storage. In this paper we have carried out comprehensive high-resolution spectroscopic studies on the polymorphs of the non-steroidal anti-inflammatory drug diflunisal that has four known polymorphs, forms I-IV (FI-FIV), three of which have known crystal structures. Phase transformations during milling, heating, melt-quenching and exposure to high relative humidity were investigated using Raman and terahertz spectroscopy in combination with differential scanning calorimetry and X-ray powder diffraction. The observed phase transformations indicate the stability order FIII>FI>FII, FIV. Furthermore, crystallization experiments from the gas phase and from solution by fast evaporation of different solvents were carried out. Fast evaporation of an ethanolic solution below 70°C was identified as a reliable and convenient method to obtain the somewhat elusive FII in bulk quantities.This work was supported by Science Foundation Ireland under Grant No. [12/RC/2275] as part of the Synthesis and Solid State Pharmaceutical Centre (SSPC). ARP would like to acknowledge ICHEC, Irish HPC system for computing time on the condominium access (nuig02). ARP also acknowledges the RIA Charlemont grant for financial support of a research visit to the University of Cambridge

SocialLink: exploiting graph embeddings to link DBpedia entities to Twitter profiles

SocialLink is a project designed to match social media profiles on Twitter to corresponding entities in DBpedia. Built to bridge the vibrant Twitter social media world and the Linked Open Data cloud, SocialLink enables knowledge transfer between the two, both assisting Semantic Web practitioners in better harvesting the vast amounts of information available on Twitter and allowing leveraging of DBpedia data for social media analysis tasks. In this paper, we further extend the original SocialLink approach by exploiting graph-based features based on both DBpedia and Twitter, represented as graph embeddings learned from vast amounts of unlabeled data. The introduction of such new features required to redesign our deep neural network-based candidate selection algorithm and, as a result, we experimentally demonstrate a significant improvement of the performances of SocialLink

Sulfamerazine:understanding the influence of slip-planes in polymorphic phase-transformation through X-ray crystallographic studies and <i>ab initio</i> lattice dynamics

Understanding the polymorphism exhibited by organic active-pharmaceutical ingredients (APIs), in particular the relationships between crystal structure and the thermodynamics of polymorph stability, is vital for the production of more stable drugs and better therapeutics, and for the economics of the pharmaceutical industry in general. In this article, we report a detailed study of the structure–property relationships among the polymorphs of the model API, Sulfamerazine. Detailed experimental characterization using synchrotron radiation is complemented by computational modeling of the lattice dynamics and mechanical properties, in order to study the origin of differences in millability and to investigate the thermodynamics of the phase equilibria. Good agreement is observed between the simulated phonon spectra and mid-infrared and Raman spectra. The presence of slip planes, which are found to give rise to low-frequency lattice vibrations, explains the higher millability of Form I compared to Form II. Energy/volume curves for the three polymorphs, together with the temperature dependence of the thermodynamic free energy computed from the phonon frequencies, explains why Form II converts to Form I at high temperature, whereas Form III is a rare polymorph that is difficult to isolate. The combined experimental and theoretical approach employed here should be generally applicable to the study of other systems that exhibit polymorphism

The RNA workbench: best practices for RNA and high-throughput sequencing bioinformatics in Galaxy

RNA-based regulation has become a major research topic in molecular biology. The analysis of epigenetic and expression data is therefore incomplete if RNA-based regulation is not taken into account. Thus, it is increasingly important but not yet standard to combine RNA-centric data and analysis tools with other types of experimental data such as RNA-seq or ChIP-seq. Here, we present the RNA workbench, a comprehensive set of analysis tools and consolidated workflows that enable the researcher to combine these two worlds. Based on the Galaxy framework the workbench guarantees simple access, easy extension, flexible adaption to personal and security needs, and sophisticated analyses that are independent of command-line knowledge. Currently, it includes more than 50 bioinformatics tools that are dedicated to different research areas of RNA biology including RNA structure analysis, RNA alignment, RNA annotation, RNA-protein interaction, ribosome profiling, RNA-seq analysis and RNA target prediction. The workbench is developed and maintained by experts in RNA bioinformatics and the Galaxy framework. Together with the growing community evolving around this workbench, we are committed to keep the workbench up-to-date for future standards and needs, providing researchers with a reliable and robust framework for RNA data analysis. Availability: The RNA workbench is available at https://github.com/bgruening/galaxy-rna-workbench

StreptomeDB:a resource for natural compounds isolated from <i>Streptomyces</i> species

Bacteria from the genus Streptomyces are very important for the production of natural bioactive compounds such as antibiotic, antitumour or immunosuppressant drugs. Around two-thirds of all known natural antibiotics are produced by these bacteria. An enormous quantity of crucial data related to this genus has been generated and published, but so far no freely available and comprehensive database exists. Here, we present StreptomeDB (http://www.pharmaceutical-bioinformatics.de/streptomedb/). To the best of our knowledge, this is the largest database of natural products isolated from Streptomyces. It contains >2400 unique and diverse compounds from >1900 different Streptomyces strains and substrains. In addition to names and molecular structures of the compounds, information about source organisms, references, biological role, activities and synthesis routes (e.g. polyketide synthase derived and non-ribosomal peptides derived) is included. Data can be accessed through queries on compound names, chemical structures or organisms. Extraction from the literature was performed through automatic text mining of thousands of articles from PubMed, followed by manual curation. All annotated compound structures can be downloaded from the website and applied for in silico screenings for identifying new active molecules with undiscovered properties

Designing organometallic compounds for catalysis and therapy

Bioorganometallic chemistry is a rapidly developing area of research. In recent years organometallic compounds have provided a rich platform for the design of effective catalysts, e.g. for olefin metathesis and transfer hydrogenation. Electronic and steric effects are used to control both the thermodynamics and kinetics of ligand substitution and redox reactions of metal ions, especially Ru II. Can similar features be incorporated into the design of targeted organometallic drugs? Such complexes offer potential for novel mechanisms of drug action through incorporation of outer-sphere recognition of targets and controlled activation features based on ligand substitution as well as metal- and ligand-based redox processes. We focus here on η 6-arene, η 5-cyclopentadienyl sandwich and half-sandwich complexes of Fe II, Ru II, Os II and Ir III with promising activity towards cancer, malaria, and other conditions. © 2012 The Royal Society of Chemistry

The RNA workbench: Best practices for RNA and high-throughput sequencing bioinformatics in Galaxy

RNA-based regulation has become a major research topic in molecular biology. The analysis of epigenetic and expression data is therefore incomplete if RNA-based regulation is not taken into account. Thus, it is increasingly important but not yet standard to combine RNA-centric data and analysis tools with other types of experimental data such as RNA-seq or ChIP-seq. Here, we present the RNA workbench, a comprehensive set of analysis tools and consolidated workflows that enable the researcher to combine these two worlds. Based on the Galaxy framework the workbench guarantees simple access, easy extension, flexible adaption to personal and security needs, and sophisticated analyses that are independent of command-line knowledge. Currently, it includes more than 50 bioinformatics tools that are dedicated to different research areas of RNA biology including RNA structure analysis, RNA alignment, RNA annotation, RNA-protein interaction, ribosome profiling, RNA-seq analysis and RNA target prediction. The workbench is developed and maintained by experts in RNA bioinformatics and the Galaxy framework. Together with the growing community evolving around this workbench, we are committed to keep the workbench up-to-date for future standards and needs, providing researchers with a reliable and robust framework for RNA data analysis

Does congenital deafness affect the structural and functional architecture of primary visual cortex?

Deafness results in greater reliance on the remaining senses. It is unknown whether the cortical architecture of the intact senses is optimized to compensate for lost input. Here we performed widefield population receptive field (pRF) mapping of primary visual cortex (V1) with functional magnetic resonance imaging (fMRI) in hearing and congenitally deaf participants, all of whom had learnt sign language after the age of 10 years. We found larger pRFs encoding the peripheral visual field of deaf compared to hearing participants. This was likely driven by larger facilitatory center zones of the pRF profile concentrated in the near and far periphery in the deaf group. pRF density was comparable between groups, indicating pRFs overlapped more in the deaf group. This could suggest that a coarse coding strategy underlies enhanced peripheral visual skills in deaf people. Cortical thickness was also decreased in V1 in the deaf group. These findings suggest deafness causes structural and functional plasticity at the earliest stages of visual cortex