The catalytic asymmetric synthesis of planar chiral ferrocenes and P-stereogenic phosphines and bisphosphines (important classes of chiral ligands for metal-catalyzed asymmetric processes) is successfully demonstrated using n-BuLi or s-BuLi in combination with substoichiometric quantities (0.1-0.5 equiv) of (-)-sparteine or the (+)-sparteine surrogate.

An 8-step, gram-scale synthesis of the (-)-sparteine surrogate (22 % yield, with just 3 chromatographic purifications) and a 10-step, gram-scale synthesis of (-)-sparteine (31 % yield) are reported. Both syntheses proceed with complete diastereocontrol and allow access to either antipode. Since the syntheses do not rely on natural product extraction, our work addresses long-term supply issues relating to these widely used chiral ligands.

A comparison between phosphine boranes and sulfides in their catalytic asymmetric deprotonation using organolithiums and sub-stoichiometric amounts of (-)-sparteine has revealed superior catalytic efficiency in the phosphine sulfide deprotonation.

Skin permeation is an essential biological property of small organic compounds our body is exposed to, such as drugs in topic formulations, cosmetics, and environmental toxins. Despite the limited availability of experimental data, there is a lack of systematic analysis and structure. We present a novel resource on skin permeation data that collects all measurements available in the literature and systematically structures experimental conditions. Besides the skin permeation value kp, it includes experimental protocols such as skin source site, skin layer used, preparation technique, storage conditions, as well as test conditions such as temperature, pH as well as the type of donor and acceptor solution. It is important to include these parameters in the assessment of the skin permeation data. In addition, we provide an analysis of physicochemical properties and chemical space coverage, laying the basis for applicability domain determination of insights drawn from the collected data points. The database is freely accessible under https://huskindb.drug-design.de or 10.7303/syn21998881.

A new protocol for the catalytic asymmetric deprotonation of a phosphine borane using s-BuLi and substoichiometric quantities of chiral diamines is reported. The method involves three sequential additions of s-BuLi, and use of (-)-sparteine or the (+)-sparteine surrogate facilitates access to P-stereogenic phosphines with opposite configuration. The method is exemplified by the catalytic asymmetric synthesis of each enantiomer of precursors to QuinoxP*, trichickenfootphos, and Mini-PHOS.

Dermal contact with chemicals may lead to an inflammatory reaction known as allergic contact dermatitis. Consequently, it is important to assess new and existing chemicals for their skin sensitizing potential and to mitigate exposure accordingly. There is an urgent need to develop quantitative non-animal methods to better predict the potency of potential sensitizers, driven largely by European Union (EU) Regulation 1223/2009, which forbids the use of animal tests for cosmetic ingredients sold in the EU. A Nearest Neighbours in silico model was developed using an in-house dataset of 1096 murine local lymph node (LLNA) studies. The EC3 value (the effective concentration of the test substance producing a threefold increase in the stimulation index compared to controls) of a given chemical was predicted using the weighted average of EC3 values of up to 10 most similar compounds within the same mechanistic space (as defined by activating the same Derek skin sensitization alert). The model was validated using previously unseen internal (n = 45) and external (n = 103) data and accuracy of predictions assessed using a threefold error, fivefold error, European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC) and Globally Harmonized System of Classification and Labelling of Chemicals (GHS) classifications. In particular, the model predicts the GHS skin sensitization category of compounds well, predicting 64% of chemicals in an external test set within the correct category. Of the remaining chemicals in the previously unseen dataset, 25% were over-predicted (GHS 1A predicted: GHS 1B experimentally) and 11% were under-predicted (GHS 1B predicted: GHS 1A experimentally). Copyright © 2017 John Wiley & Sons, Ltd.

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