Posters

This poster describes a section of BioFocus’s screening workfolow where mosquito X1 is integrated with a RapidStak plate stacker (Thermo Scientific) using TTP LabTech’s CherryPicker software. This allows the mosquito X1 to work unattended for extended periods. The CherryPicker software drives the system automatically by converting pick lists provided by BioFocus’ LIMS system into mosquito protocols, and feeding appropriate plates via the RapidStak.

A proprietary and structurally diverse fragment library has been created and screened for a variety of Gprotein coupled receptors (GPCRs) and a number of other drug targets. The data allows for a fragment-based chemogenomics study to interrogate the interactions of GPCRs and their ligands.

Characterizing metabolite structures and metabolic pathways is essential to understanding the potential biological implications of compounds in drug discovery.

Characterizing metabolite structures and metabolic pathways is essential to understanding the potential biological implications of compounds in drug discovery.

Residues 261-273 of type II collagen bound to the MHC class II allele HLA-DR4 play a crucial role in rheumatoid arthritis. The protein–protein interactions between TCR and CII-MHCII complex may therefore serve as targets for the development of new drugs against RA. The aim of this study is to develop a pharmacophore virtual screening followed by molecular docking and dynamics calculations leading to the identification of new TCR/CII-MHCII inhibitors.

The majority of marketed drugs are natural compounds or derivatives thereof. The compounds availability is often unclear. Therefore we have compiled a database of ~50,000 natural compounds. Starting point for in silico screenings are about 2,500 well-known, classified natural compounds or imported molecules. Possible medical applications can be detected and about three million conformers computed to account for the flexibility during usage of the 3D-superposition algorithm.

In the post acqusition analysis of comprehensive -omics data the pre-processing pipe-line is crucial to extract the maximum possible amount of information from the data. Here we show a processing pipe-line for (1D)H-NMR and (2D)X/MS data comprising; feature detection, inter-sample feature alignment and internal-standard free normalization that outperforms today’s state-of-the-art processing schemes.

In metabolic profiling, multivariate data analysis techniques are used to interpret 1D 1H–NMR data. Multivariate data analysis techniques require that peaks are located in the same variables in every spectrum – this requirement is not met in native NMR spectra. Current state-of-the-art alignment algorithms are unable to align peaks when the spatial order of the peaks changes. We present the Fuzzy Generalized Hough Transform alignment which solves the alignment problem.

NMR can be used for the quantification of minute quantities of standard compounds. The high specificity of NMR signals permits absolute quantifications independent of the presence of impurities. The feasibility and limits of NMR application are demonstrated through the analysis of algal toxins and polar substances in butter.