Characterisation of data resources for in silico modelling: benchmark datasets for ADME properties.

Introduction: The cost of in vivo and in vitro screening of ADME properties of compounds has motivated efforts to develop a range of in silico models. At the heart of the development of any computational model are the data; high quality data are essential for developing robust and accurate models. The characteristics of a dataset, such as its availability, size, format and type of chemical identifiers used, influence the modelability of the data. Areas covered: This review explores the usefulness of publicly available ADME datasets for researchers to use in the development of predictive models. More than 140 ADME datasets were collated from publicly available resources and the modelability of 31selected datasets were assessed using specific criteria derived in this study. Expert opinion: Publicly available datasets differ significantly in information content and presentation. From a modelling perspective, datasets should be of adequate size, available in a user-friendly format with all chemical structures associated with one or more chemical identifiers suitable for automated processing (e.g. CAS number, SMILES string or InChIKey). Recommendations for assessing dataset suitability for modelling and publishing data in an appropriate format are discussed

Quantification and characterization of the phenolic compounds of kenaf leaves

Dissertation for the Master Degree in Technology and Food SecurityIn the food industry is necessary to bring new ways to improve the taste and quality of food and add health benefits for the consumer, some herbs and plants are a good natural source of antioxidants having the ability to protect the human system from many chronicle diseases, such as Parkinson and inflammatory processes. Combining these two worlds there is a way to acquire a new product. To know if the plant chosen is suitable to be a future add to a certain food it’s necessary to study the components of the plant and determinate the quantitative and qualitative composition of the metabolite group of interest, in this case phenolic compounds. The plant of interest was Hibiscus cannabinus L. (Kenaf), from Malvaceae family that it’s known for its fibres but it is also used as an infusion or condimental herb and in traditional medicine as an antidote to poisoning with chemicals and venomous mushrooms, it’s known in Asia and Africa but still barely approached by European countries. In order to separate and identify the phenolic compounds a liquid extraction with a polar solvent was the first step, it was chosen MeOH/H2O and MeOH (80% w/w; 100%). Was determinate the antioxidant capacity and the quantification of the phenolic content of the plant samples, for Everglades 41 the DPPH value of Ec50 was 27,33, The ORAC value was 1273,7 (μmol Trolox/mg sample) and the Folin-Ciocalteu 26,40 EAG (mg)/Sample (g)). For the Tainung 2 type was 43,00, 307.54 and 18,67, respectively. The final step was the identification of the compounds by liquid chromatography followed by mass spectrometry with time of fly analyzer and quadrupole time of fly (HPLC-ESI-MS), were obtained 47 compounds for Everglades leaf and 37 for Tainung 2

Interaction and Transport of Actinides in Natural Clay Rock with Consideration of Humic Substances and Clay Organic Compounds. (KIT Scientific Reports ; 7633)

The present report summarizes the progress and the results obtained within the BMWi financed Joint Research Project Interaction and Transport of Actinides in Natural Clay Rock with Consideration of Humic Substances and Clay Organic Compounds. The basic approach of the work was to obtain a fundamental process understanding on the molecular level of complexation and sorption reactions as well as diffusion processes. The experimental findings are supported by quantum mechanical modeling