Large oligomeric complex structures can be computationally assembled by efficiently combining docked interfaces.

Macromolecular oligomeric assemblies are involved in many biochemical processes of living organisms. The benefits of such assemblies in crowded cellular environments include increased reaction rates, efficient feedback regulation, cooperativity and protective functions. However, an atom-level structural determination of large assemblies is challenging due to the size of the complex and the difference in binding affinities of the involved proteins.

SKINK: a web server for string kernel based kink prediction in α-helices.

Motivation: The reasons for distortions from optimal α-helical geometry are widely unknown, but their influences on structural changes of proteins are significant. Hence, their prediction is a crucial problem in structural bioinformatics. Here, we present a new web server, called SKINK, for string kernel based kink prediction.

Paleoproteomic study of the Iceman's brain tissue.

The Tyrolean Iceman, a Copper-age ice mummy, is one of the best-studied human individuals. While the genome of the Iceman has largely been decoded, tissue-specific proteomes have not yet been investigated. We studied the proteome of two distinct brain samples using gel-based and liquid chromatography-mass spectrometry-based proteomics technologies together with a multiple-databases and -search algorithms-driven data-analysis approach.

String kernels and high-quality data set for improved prediction of kinked helices in α-helical membrane proteins.

The reasons for distortions from optimal α-helical geometry are widely unknown, but their influences on structural changes of proteins are significant. Hence, their prediction is a crucial problem in structural bioinformatics. For the particular case of kink prediction, we generated a data set of 132 membrane proteins containing 1014 manually labeled helices and examined the environment of kinks.

Proteome analysis of Sorangium cellulosum employing 2D-HPLC-MS/MS and improved database searching strategies for CID and ETD fragment spectra.

Shotgun proteome analysis of the myxobacterial model strain for secondary metabolite biosynthesis Sorangium cellulosum was performed employing off-line two-dimensional high-pH reversed-phase HPLC x low-pH ion-pair reversed-phase HPLC and dual tandem mass spectrometry with collision-induced dissociation (CID) and electron transfer dissociation (ETD) as complementary fragmentation techniques. Peptide identification using database searching was optimized for ETD fragment spectra to obtain the maximum number of identifications at equivalent false discovery rates (1.0%) in the evaluation of both fragmentation techniques.

Revisiting automated G-protein coupled receptor modeling: the benefit of additional template structures for a neurokinin-1 receptor model.

The feasibility of automated procedures for the modeling of G-protein coupled receptors (GPCR) is investigated on the example of the human neurokinin-1 (NK1) receptor. We use a combined method of homology modeling and molecular docking and analyze the information content of the resulting docking complexes regarding the binding mode for further refinements. Moreover, we explore the impact of different template structures, the bovine rhodopsin structure, the human beta(2) adrenergic receptor, and in particular a combination of both templates to include backbone flexibility in the target conformational space.

GeneTrail--advanced gene set enrichment analysis.

We present a comprehensive and efficient gene set analysis tool, called 'GeneTrail' that offers a rich functionality and is easy to use. Our web-based application facilitates the statistical evaluation of high-throughput genomic or proteomic data sets with respect to enrichment of functional categories. GeneTrail covers a wide variety of biological categories and pathways, among others KEGG, TRANSPATH, TRANSFAC, and GO.