Gram-Scale Synthesis of the (-)-Sparteine Surrogate and (-)-Sparteine.

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 quantitative in silico model for predicting skin sensitization using a nearest neighbours approach within expert-derived structure-activity alert spaces.

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.

Predicting skin sensitisation using a decision tree integrated testing strategy with an in silico model and in chemico/in vitro assays.

There is a pressing need for non-animal methods to predict skin sensitisation potential and a number of in chemico and in vitro assays have been designed with this in mind. However, some compounds can fall outside the applicability domain of these in chemico/in vitro assays and may not be predicted accurately. Rule-based in silico models such as Derek Nexus are expert-derived from animal and/or human data and the mechanism-based alert domain can take a number of factors into account (e.g. abiotic/biotic activation). Therefore, Derek Nexus may be able to predict for compounds outside the applicability domain of in chemico/in vitro assays. To this end, an integrated testing strategy (ITS) decision tree using Derek Nexus and a maximum of two assays (from DPRA, KeratinoSens, LuSens, h-CLAT and U-SENS) was developed. Generally, the decision tree improved upon other ITS evaluated in this study with positive and negative predictivity calculated as 86% and 81%, respectively. Our results demonstrate that an ITS using an in silico model such as Derek Nexus with a maximum of two in chemico/in vitro assays can predict the sensitising potential of a number of chemicals, including those outside the applicability domain of existing non-animal assays.

Establishing Good Computer Modelling Practice (GCMP) in the Prediction of Chemical Toxicity.

This paper suggests guidelines for good computer modelling practice (GCMP) when predicting chemical toxicity, with similar purposes to those for Good Laboratory Practice (GLP). The purpose of GCMP is not to specify what should be delivered with models or predictions but to set out what must be done to ensure that work can be audited, on site, in a way analogous to the auditing of studies conforming to GLP; it is intended to confirm that work has been done properly, as distinct from providing advice on how to do it. Comments are made on the guidelines and how they might be followed, based on practical experience with the implementation of such a scheme in the development of knowledge-based and quantitative structure activity relationship models. It is hoped that publication of this paper will encourage wider discussion of the subject leading to adoption of measures to ensure the trustworthiness of computer modelling work that is carried out in connection with regulatory submissions.

One-ligand catalytic asymmetric deprotonation of a phosphine borane: synthesis of P-stereogenic bisphosphine ligands.

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.

Catalytic asymmetric deprotonation of phosphine boranes and sulfides as a route to P-stereogenic compounds.

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.

Catalytic asymmetric synthesis of ferrocenes and P-stereogenic bisphosphines.

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.