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.

Solid-phase methodology for synthesis of O-alkylated aromatic oligoamide inhibitors of α-helix-mediated protein-protein interactions.

Rapid access to rigid rods: A method is described for the synthesis of 3-O-alkylated aromatic oligobenzamide foldamers that could be used for assembly of libraries of α-helix mimetic inhibitors of protein-protein interactions (see scheme; Fmoc=9-fluorenylmethoxycarbonyl).

N-alkylated oligoamide alpha-helical proteomimetics.

Generic approaches for the design and synthesis of small molecule inhibitors of protein-protein interactions (PPIs) represent a key objective in modern chemical biology. Within this context, the alpha-helix mediated PPIs have received considerable attention as targets for inhibition using small molecules, foldamers and proteomimetics. This manuscript describes a novel N-alkylated aromatic oligoamide proteomimetic scaffold and its solid-phase synthesis--the first time such an approach has been used for proteomimetics. The utility of these scaffolds as proteomimetics is exemplified through the identification of potent microM inhibitors of the p53-hDM2 helix mediated PPI--a key oncogenic target.

A Semi-automated Approach to Create Purposeful Mechanistic Datasets from Heterogeneous Data: Data Mining Towards the in silico Predictions for Oestrogen Receptor Modulation and Teratogenicity.

The need to find an alternative to costly animal studies for developmental and reproductive toxicity testing has shifted the focus considerably to the assessment of in vitro developmental toxicology models and the exploitation of pharmacological data for relevant molecular initiating events. We hereby demonstrate how automation can be applied successfully to handle heterogeneous oestrogen receptor data from ChEMBL. Applying expert-derived thresholds to specific bioactivities allowed an activity call to be attributed to each data entry. Human intervention further improved this mechanistic dataset which was mined to develop structure-activity relationship alerts and an expert model covering 45 chemical classes for the prediction of oestrogen receptor modulation. The evaluation of the model using FDA EDKB and Tox21 data was quite encouraging. This model can also provide a teratogenicity prediction along with the additional information it provides relevant to the query compound, all of which will require careful assessment of potential risk by experts.

Shape-selective fluorescent sensing ensemble using a tweezer-type metalloreceptor.

[reaction: see text] A fluorescent sensing ensemble for pyridine-derived compounds is described. The receptor portion of the ensemble is prepared from a bisimidazole pyridine which coordinates copper to form a well-defined cavity. Small heteroaromatic guests such as adenine bind strongly in the cavity. The fluorescent response is provided by a dye which is coordinated to the receptor and quenched by the metal ion. The dye is released upon guest binding providing up to 25-fold fluorescence increases.

Trivalent Gd-DOTA reagents for modification of proteins.

The development of novel protein-targeted MRI contrast agents crucially depends on the ability to derivatise suitable targeting moieties with a high payload of relaxation enhancer (e.g., gadolinium(iii) complexes such as Gd-DOTA), without losing affinity for the target proteins. Here, we report robust synthetic procedures for the preparation of trivalent Gd-DOTA reagents with various chemical handles for site-specific modification of biomolecules. The reagents were shown to successfully label proteins through isothiocyanate ligation or through site-specific thiol-maleimide ligation and strain-promoted azide-alkyne cycloaddition.

A rigid cavity containing tetra-cobalt(III) [2 x 2] grid complex.

The synthesis and structure of a rigid, cavity containing tetra-cobalt(III) [2 x 2] grid complex using an unusual bis(bipyridine)dimethoxynaphthyridine ligand is described.

Oligobenzamide proteomimetic inhibitors of the p53-hDM2 protein-protein interaction.

Oligobenzamide inhibitors of the p53-hDM2 protein-protein interaction are described.