Prediction of michael-type acceptor reactivity toward glutathione.

A model has been developed to predict the kinetic rate constants (k(GSH)) of α,ß-unsaturated Michael acceptor compounds for their reaction with glutathione (GSH). The model uses the local charge-limited electrophilicity index ω(q) [Wondrousch, D., et al. (2010) J. Phys. Chem. Lett. 1, 1605-1610] at the ß-carbon atom as a descriptor of reactivity, a descriptor for resonance stabilization of the transition state, and one for steric hindrance at the reaction sites involved. Overall, the Michael addition model performs well (r² = 0.91; rms = 0.34). It includes various classes of compounds with double and triple bonds, linear and cyclic systems, and compounds with and without substituents in the α-position. Comparison of experimental and predicted rate constants demonstrates even better performance of the model for individual classes of compounds (e.g., for aldehydes, r² = 0.97 and rms = 0.15; for ketones, r² = 0.95 and rms = 0.35). The model also allows for the prediction of the RC50 values from the Schultz chemoassay, the accuracy being close to the interlaboratory experimental error. Furthermore, k(GSH) and associated RC50 values can be predicted in cases where experimental measurements are not possible or restricted, for example, because of low solubility or high volatility. The model has the potential to provide information to assist in the assessment and categorization of toxicants and in the application of integrated testing strategies.

COSMOperm: Mechanistic Prediction of Passive Membrane Permeability for Neutral Compounds and Ions and Its pH Dependence.

We present a new and entirely mechanistic COSMOperm method to predict passive membrane permeabilities for neutral compounds, as well as anions and cations. The COSMOperm approach is based on compound-specific free energy profiles within a membrane of interest from COSMO-RS (conductor-like screening model for realistic solvation) calculations. These are combined with membrane layer-specific diffusion coefficients, for example, in the water phase, the polar head groups, and the alkyl tails of biochemical phospholipid bilayers. COSMO-RS utilizes first-principle quantum chemical structures and physically sound intermolecular interactions (electrostatic, hydrogen bond, and van der Waals). For this reason, it is unbiased toward different application scenarios, such as in cosmetics and industrial chemical or pharmaceutical industries. A fully predictive calculation of passive permeation through phospholipid bilayer membranes results in a performance of r2 = 0.92; rmsd = 0.90 log10 units for neutral compounds and anions, as compared to gold standard black lipid membrane experiments. It will be demonstrated that new membrane types can be generated by the related COSMOplex method and directly used for permeability studies by COSMOperm.

Application of a computational model for Michael addition reactivity in the prediction of toxicity to Tetrahymena pyriformis.

A computational model to predict acute aquatic toxicity to the ciliate Tetrahymena pyriformis has been developed. A general prediction of toxicity can be based on three consecutive steps: 1. Identification of a potential reactive mechanism via structural alerts; 2. Confirmation and quantification of (bio)chemical reactivity; 3. Establishing a relationship between calculated reactivity and toxicity. The method described herein uses a combination of a reactive toxicity (RT) model, including computed kinetic rate constants for adduct formation (log k) via a Michael acceptor mechanism of action, and baseline toxicity (BT), modelled by hydrophobicity (octanol-water partition coefficient). The maximum of the RT and BT values defines acute toxicity for a particular compound. The reactive toxicity model is based on site-specific steric and quantum chemical ground state electronic properties. The performance of the model was examined in terms of predicting the toxicity of 106 potential Michael acceptor compounds covering several classes of compounds (aldehydes, ketones, esters, heterocycles). The advantages of the computational method are described. The method allows for a closer and more transparent mechanistic insight into the molecular initiating events of toxicological endpoints.

Modelling acute oral mammalian toxicity. 1. Definition of a quantifiable baseline effect.

Quantitative structure-activity relationships (QSARs) provide a useful tool to define a relationship between chemical structure and toxicity and allow for the prediction of the toxicity of untested chemicals. QSAR models based upon an anaesthetic or narcosis mechanism represent a baseline, or minimum, toxicity, i.e. unless a chemical acts by another, more specific, mechanism, its toxicity will be predicted by such models. The aim of this investigation was to develop baseline models for the acute toxicity of chemicals to mammals (rat and mouse) following the oral route of administration. The availability of such baseline toxicity models for mammalian species can provide a probe for testing new chemicals with respect to their molecular mechanism of toxicity. Multiple-regression type structure-toxicity relationships were derived . (i.e., from oral log LD(50)(-1) data for mammalian species (rat and mouse) and the 1-octanol/water partition coefficient (log P) of classic non-polar narcotics). Subsequently, these models were used to distinguish between reactive chemicals of different mechanistic domains and baseline toxic chemicals. Comparison of measured toxicity data for oral rat and mouse LD(50) with predictions from baseline QSAR provides a means of identifying mechanistic categories and for categorising more specific acute mechanisms.