Extrapolation of in vitro structural alerts for mutagenicity to the in vivo endpoint.

As part of the hazard and risk assessment of chemicals in man, it is important to assess the ability of a chemical to induce mutations in vivo. Because of the commonalities in the molecular initiating event, mutagenicity in vitro can correlate well to the in vivo endpoint for certain compound classes; however, the difficulty lies in identifying when this correlation holds true. In silico alerts for in vitro mutagenicity may therefore be used as the basis for alerts for mutagenicity in vivo where an expert assessment is carried out to establish the relevance of the correlation. Taking this into account, a data set of publicly available transgenic rodent gene mutation assay data, provided by the National Institute of Health Sciences of Japan, was processed in the expert system Derek Nexus against the in vitro mutagenicity endpoint. The resulting predictivity was expertly reviewed to assess the validity of the observed correlations in activity and mechanism of action between the two endpoints to identify suitable in vitro alerts for extension to the in vivo endpoint. In total, 20 alerts were extended to predict in vivo mutagenicity, which has significantly improved the coverage of this endpoint in Derek Nexus against the data set provided. Updating the Derek Nexus knowledge base in this way led to an increase in sensitivity for this data set against this endpoint from 9% to 66% while maintaining a good specificity of 89%.

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.

Using in vitro structural alerts for chromosome damage to predict in vivo activity and direct future testing.

While the in vivo genotoxicity of a compound may not always correlate well with its activity in in vitro test systems, for certain compound classes a good overlap may exist between the two endpoints. The difficulty, however, lies in establishing the cases where this relationship holds true and selecting the most appropriate protocol to highlight any potential in vivo hazard. With this in mind, a project was initiated in which existing structural alerts for in vitro chromosome damage in the expert system Derek Nexus were assessed for their relevance to in vivo activity by assessing their predictivity against an in vivo chromosome damage data set. An expert assessment was then made of selected alerts. Information regarding the findings from specific in vivo tests was added to the alert along with any significant correlations between activity and test protocol or mechanism. A total of 32 in vitro alerts were updated using this method resulting in a significant improvement in the coverage of in vivo chromosome damage in Derek Nexus against a data set compiled by the mammalian mutagenicity study group of Japan. The detailed information relating to in vivo activity and protocol added to the alerts in combination with the mechanistic information provided will prove useful in directing the further testing of compounds of interest.

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.

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.

HuskinDB, a database for skin permeation of xenobiotics.

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 https://doi.org/10.7303/syn21998881 .

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.

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.

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.