KNIME node development: Maven and Tycho

<p>In the <a href="https://3d-e-chem.github.io/">3D-e-Chem project</a> many KNIME workflow nodes where made, this presentation explains the build infrastructure behind them.</p

Kripo PDB Dec 2015

<p>KRIPO stands for Key Representation of Interaction in POckets.</p> <p>All fragments form all proteins-ligand complexes in PDB compared with all.<br> Data set contains PDB entries that where available at 23 December 2015.</p> <p>* Kripo.*.sqlite - Fragments sqlite database<br> * Distance matrix is too big to ship with VM so use http://3d-e-chem.vu-compmedchem.nl/kripodb webservice url to query.<br> * kripo_fingerprint_2015_*.fp.gz - Fragment fingerprints, see https://github.com/3D-e-Chem/kripodb/blob/master/README.md#create-distance-matrix-from-text-files for instructions how to convert to a distance matrix.</p> <p>Dataset was generated using http://dx.doi.org/10.5281/zenodo.53891</p> <p> </p

Modelling hybrid effects on the stiffness of aligned discontinuous composites with hybrid fibre-types

Hybrid discontinuous composites offer the possibility to tailor the composite properties for specific applications, improve their manufacturability, and reduce cost by introducing cheaper fibres. However, the mechanical behaviour of hybrid composites often shows hybrid effects which cannot be modelled by the rule-of-mixtures and are therefore challenging to predict and explain. This paper presents models to calculate the Young's modulus of different discontinuous hybrid composites, which is affected by such hybrid effects. The models are based on shear-lag and consider two types of hybrid discontinuous architectures: (i) a deterministic “brick-and-mortar” architecture consisting of perfectly staggered platelets with two different Young's moduli and thicknesses, and (ii) a stochastic architecture of aligned fibres with two different Young's moduli and diameters, with randomly allocated fibre-ends and random or organised intermingling. The models show good agreement with numerical and experimental validations; their results show that hybrid interactions between different types of fibres or platelets reduce the Young's modulus of hybrid discontinuous composites, which justifies the negative hybrid effects observed

<i>In Silico</i> Prediction and Automatic LC–MS^<i>n</i> Annotation of Green Tea Metabolites in Urine

The colonic breakdown and human biotransformation of small molecules present in food can give rise to a large variety of potentially bioactive metabolites in the human body. However, the absence of reference data for many of these components limits their identification in complex biological samples, such as plasma and urine. We present an <i>in silico</i> workflow for automatic chemical annotation of metabolite profiling data from liquid chromatography coupled with multistage accurate mass spectrometry (LC−MS<i>ⁿ</i>), which we used to systematically screen for the presence of tea-derived metabolites in human urine samples after green tea consumption. Reaction rules for intestinal degradation and human biotransformation were systematically applied to chemical structures of 75 green tea components, resulting in a virtual library of 27 245 potential metabolites. All matching precursor ions in the urine LC–MS^<i>n</i> data sets, as well as the corresponding fragment ions, were automatically annotated by <i>in silico</i> generated (sub)­structures. The results were evaluated based on 74 previously identified urinary metabolites and lead to the putative identification of 26 additional green tea-derived metabolites. A total of 77% of all annotated metabolites were not present in the Pubchem database, demonstrating the benefit of <i>in silico</i> metabolite prediction for the automatic annotation of yet unknown metabolites in LC–MS^<i>n</i> data from nutritional metabolite profiling experiments

Orchestration and Workflows in eScience: Problems, Standards, and Solutions

<p>The Netherlands eScience Center works in partnership with scientists from many different fields, from humanities to high energy physics. This gives us a unique overview of the problems in these fields. One common problem we see is the need for compute power, often for relatively independent tasks. In this paper, we will give an overview of the requirements for running these tasks. This list is relatively short, as we often encounter the same problems across projects. We argue that too often software to solve these problems is built from scratch, leading to a lot of duplicated effort.</p><p>Our approach is to re-use and contribute to existing solutions as much as possible, and above all else use standards whenever possible. Software changes quickly, standards hopefully last longer. We will discuss some of the (emerging) standards we use, including the Common Workflow Language (CWL) and Basic Model Interface (BMI) from the BioInformatics and Geosciences communities respectively. Using examples from projects, we will also discuss software we use.</p>We hope that the scientific community can come together to exchange knowledge on this topic: hopefully leading to a better overview standards related to workflows and orchestration, and more usage of some of the great software out there

A Prospective Cross-Screening Study on G-Protein-Coupled Receptors: Lessons Learned in Virtual Compound Library Design

We present the systematic prospective evaluation of a protein-based and a ligand-based virtual screening platform against a set of three G-protein-coupled receptors (GPCRs): the β-2 adrenoreceptor (ADRB2), the adenosine A_2A receptor (AA2AR), and the sphingosine 1-phosphate receptor (S1PR1). Novel bioactive compounds were identified using a consensus scoring procedure combining ligand-based (frequent substructure ranking) and structure-based (Snooker) tools, and all 900 selected compounds were screened against all three receptors. A striking number of ligands showed affinity/activity for GPCRs other than the intended target, which could be partly attributed to the fuzziness and overlap of protein-based pharmacophore models. Surprisingly, the phosphodiesterase 5 (PDE5) inhibitor sildenafil was found to possess submicromolar affinity for AA2AR. Overall, this is one of the first published prospective chemogenomics studies that demonstrate the identification of novel cross-pharmacology between unrelated protein targets. The lessons learned from this study can be used to guide future virtual ligand design efforts