KnowTox: pipeline and case study for confident prediction of potential toxic effects of compounds in early phases of development.

Risk assessment of newly synthesised chemicals is a prerequisite for regulatory approval. In this context, in silico methods have great potential to reduce time, cost, and ultimately animal testing as they make use of the ever-growing amount of available toxicity data. Here, KnowTox is presented, a novel pipeline that combines three different in silico toxicology approaches to allow for confident prediction of potentially toxic effects of query compounds, i.

The cytochrome bc complex inhibitor Ametoctradin has an unusual binding mode.

Ametoctradin is an agricultural fungicide that selectively inhibits the cytochrome bc complex of oomycetes. Previous spectrophotometric studies using the purified cytochrome bc complex from Pythium sp. showed that Ametoctradin binds to the Q-site of the enzyme.

In silico target prediction for elucidating the mode of action of herbicides including prospective validation.

The rapid emergence of pesticide resistance has given rise to a demand for herbicides with new mode of action (MoA). In the agrochemical sector, with the availability of experimental high throughput screening (HTS) data, it is now possible to utilize in silico target prediction methods in the early discovery phase to suggest the MoA of a compound via data mining of bioactivity data. While having been established in the pharmaceutical context, in the agrochemical area this approach poses rather different challenges, as we have found in this work, partially due to different chemistry, but even more so due to different (usually smaller) amounts of data, and different ways of conducting HTS.

Binding of the respiratory chain inhibitor ametoctradin to the mitochondrial bc1 complex.

Background: Ametoctradin is an agricultural fungicide that inhibits the mitochondrial bc1 complex of oomycetes. The bc1 complex has two quinone binding sites that can be addressed by inhibitors. Depending on their binding sites and binding modes, the inhibitors show different degrees of cross-resistance that need to be considered when designing spray programmes for agricultural fungicides.

Structure-activity relationships of thiostrepton derivatives: implications for rational drug design.

The bacterial ribosome is a major target of naturally occurring thiopeptides antibiotics. Studying thiopeptide (e.g.

Generalized workflow for generating highly predictive in silico off-target activity models.

Chemical structure data and corresponding measured bioactivities of compounds are nowadays easily available from public and commercial databases. However, these databases contain heterogeneous data from different laboratories determined under different protocols and, in addition, sometimes even erroneous entries. In this study, we evaluated the use of data from bioactivity databases for the generation of high quality in silico models for off-target mediated toxicity as a decision support in early drug discovery and crop-protection research.

A chip-calorimetric approach to the analysis of Ag nanoparticle caused inhibition and inactivation of beads-grown bacterial biofilms.

With the increasing complexity of model systems for the investigation of antibacterial effects of nanoparticles, the demands on appropriate analysis methods are rising. In case of biofilms grown on small particles, the high inhomogeneity of the samples represents a major challenge for traditional biofilm analysis. For this purpose, we developed a new calorimetric method which allows non-invasive and real-time investigation of the effects of nanoparticles on beads-grown biofilms which meets the requirements for an increased sample throughput.

Influence of thiostrepton binding on the ribosomal GTPase associated region characterized by molecular dynamics simulation.

The thiostrepton antibiotic inhibits bacterial protein synthesis by binding to a cleft formed by the ribosomal protein L11 and 23S's rRNA helices 43-44 on the 70S ribosome. It was proposed from crystal structures that the ligand restricts L11's N-terminal movement and thus prevents proper translation factor binding. An exact understanding of thiostrepton's impact on the binding site's dynamics at atomistic resolution is still missing.

Principal component and clustering analysis on molecular dynamics data of the ribosomal L11·23S subdomain.

With improvements in computer speed and algorithm efficiency, MD simulations are sampling larger amounts of molecular and biomolecular conformations. Being able to qualitatively and quantitatively sift these conformations into meaningful groups is a difficult and important task, especially when considering the structure-activity paradigm. Here we present a study that combines two popular techniques, principal component (PC) analysis and clustering, for revealing major conformational changes that occur in molecular dynamics (MD) simulations.

Potentials and limitations of miniaturized calorimeters for bioprocess monitoring.

In theory, heat production rates are very well suited for analysing and controlling bioprocesses on different scales from a few nanolitres up to many cubic metres. Any bioconversion is accompanied by a production (exothermic) or consumption (endothermic) of heat. The heat is tightly connected with the stoichiometry of the bioprocess via the law of Hess, and its rate is connected to the kinetics of the process.

PLIO: an ontology for formal description of protein-ligand interactions.

Motivation: Biomedical ontologies have proved to be valuable tools for data analysis and data interoperability. Protein-ligand interactions are key players in drug discovery and development; however, existing public ontologies that describe the knowledge space of biomolecular interactions do not cover all aspects relevant to pharmaceutical modelling and simulation.

Results: The protein--ligand interaction ontology (PLIO) was developed around three main concepts, namely target, ligand and interaction, and was enriched by adding synonyms, useful annotations and references.

In silico drug discovery approaches on grid computing infrastructures.

The first step in finding a "drug" is screening chemical compound databases against a protein target. In silico approaches like virtual screening by molecular docking are well established in modern drug discovery. As molecular databases of compounds and target structures are becoming larger and more and more computational screening approaches are available, there is an increased need in compute power and more complex workflows.

DockFlow - a prototypic PharmaGrid for virtual screening integrating four different docking tools.

In this paper we present DockFlow, a prototypic version of a PharmaGrid. DockFlow is supporting pharmaceutical research through enabling virtual screening on the Grid. The system was developed in the course of the BRIDGE project funded by the European Commission.

Design of new plasmepsin inhibitors: a virtual high throughput screening approach on the EGEE grid.

Though different species of the genus Plasmodium may be responsible for malaria, the variant caused by P. falciparum is often very dangerous and even fatal if untreated. Hemoglobin degradation is one of the key metabolic processes for the survival of the Plasmodium parasite in its host.

Alternative to consensus scoring--a new approach toward the qualitative combination of docking algorithms.

Since the development of the first docking algorithm in the early 1980s a variety of different docking approaches and tools has been created in order to solve the docking problem. Subsequent studies have shown that the docking performance of most tools strongly depends on the considered target. Thus it is hard to choose the best algorithm in the situation at hand.

Glutamate release by neurons evokes a purinergic inhibitory mechanism of osmotic glial cell swelling in the rat retina: activation by neuropeptide Y.

Glial cell swelling is a central cause of ischemic edema in the brain and retina; however, the regulation of glial cell volume by endogenous factors in situ is largely unknown. In slices of the postischemic retina of the rat, the somata of glial (Müller) cells swell upon hypotonic stress that is not observed in slices of control retinas. We describe an endogenous signaling pathway that leads to inhibition of the osmotic glial cell swelling, and that is evoked by the release of glutamate from retinal neurons upon application of neuropeptide Y.

The glucocorticoid triamcinolone acetonide inhibits osmotic swelling of retinal glial cells via stimulation of endogenous adenosine signaling.

The glucocorticoid triamcinolone acetonide is clinically used for the treatment of macular edema. However, the edema-resolving mechanisms of triamcinolone are incompletely understood. Since cell swelling is a central cause of cytotoxic edema in the brain and retina, we determined the effects of triamcinolone acetonide on the swelling of retinal ganglion and Müller glial cells in acutely isolated retinas from rats and guinea pigs in situ.