CAS Electrophile (El) Nucleophile (Nu) Parameter Unit Value Error log(Val) 818-61-1 2-Hydroxyethyl acrylate 4-Nitrobenzenethiol t1/2(NBT) min 2.45E-01 144-48-9 2-Iodoacetamide 4-Nitrobenzenethiol t1/2(NBT) min 1.83E-03 2682-20-4 2-Methyl-2H-isothiazolin-3-one 4-Nitrobenzenethiol t1/2(NBT) min 1.60E-03 25567-67-3 3-Chloro-1.2-dinitrobenzene 4-Nitrobenzenethiol t1/2(NBT) min 1.25E-02 2497-21-4 4-Hexen-3-one 4-Nitrobenzenethiol t1/2(NBT) min 2.77E-02 26172-55-4 5-Chloro-2-methyl-4-isothiazolin-3-one 4-Nitrobenzenethiol t1/2(NBT) min 5.83E-05 108-24-7 Acetic anhydride 4-Nitrobenzenethiol t1/2(NBT) min 9.83E-04 107-02-8 Acrolein 4-Nitrobenzenethiol t1/2(NBT) min 8.25E-02 100-39-0 Benzyl bromide 4-Nitrobenzenethiol t1/2(NBT) min 4.67E-05 57-57-8 beta-Propiolactone 4-Nitrobenzenethiol t1/2(NBT) min 1.62E-04 88-11-9 Diethylthiocarbamoyl chloride 4-Nitrobenzenethiol t1/2(NBT) min 1.52E-03 886-38-4 Diphenylcyclopropenone 4-Nitrobenzenethiol t1/2(NBT) min 1.05E-05 140-88-5 Ethyl acrylate 4-Nitrobenzenethiol t1/2(NBT) min 7.70E-01 50-00-0 Formaldehyde 4-Nitrobenzenethiol t1/2(NBT) min 1.25E-03 55965-84-9 Kathon CG 4-Nitrobenzenethiol t1/2(NBT) min 2.17E-04 124-63-0 Methyl sulfonyl chloride 4-Nitrobenzenethiol t1/2(NBT) min 7.67E-04 128-53-0 N-Ethylmaleimide 4-Nitrobenzenethiol t1/2(NBT) min 3.33E-04 Nitrobenzyl bromide 4-Nitrobenzenethiol t1/2(NBT) min 9.83E-06 15646-46-5 Oxazolone 4-Nitrobenzenethiol t1/2(NBT) min 9.00E-06 106-51-4 p-Benzoquinone 4-Nitrobenzenethiol t1/2(NBT) min 7.33E-06 1939-99-7 Phenylmethanesulfonyl chloride 4-Nitrobenzenethiol t1/2(NBT) min 6.00E-03 2892-51-5 Squaric acid 4-Nitrobenzenethiol t1/2(NBT) min 6.12E-02 584-84-9 Toluene 2.4-diisocyanate 4-Nitrobenzenethiol t1/2(NBT) min 4.50E-04 23726-91-2S2 Schwöbel et al.

P-glycoprotein (Pgp/ABCB1) both accounts for multidrug resistance (MDR) in chemotherapy and contributes to reduce oral bioavailability and brain distribution of drugs. Flavonoids, reported as potent Pgp inhibitors, are able to bind to the cytosolic ATP-binding site and a vicinal hydrophobic pocket. In order to explore the interaction forces governing the affinity of flavonoids towards Pgp, the 3D quantitative structure-activity relationship (QSAR) approach was used to analyze a set of flavonoid derivatives. The variation of affinity towards Pgp was investigated by VolSurf descriptors of Molecular Interaction Fields (MIFs) related to hydrophobic interaction forces, polarizability, and hydrogen-bonding capacity. The 3D linear solvation energy VolSurf model developed here identifies shape parameters and hydrophobicity as the major physicochemical parameters responsible for the affinity of flavonoid derivatives towards Pgp and hydrogen-bonding capacities as minor modulators of this activity. Furthermore, this predictive model (q(2) of 0.71) was also validated by use of an external set of 10 flavones.

Reactive toxicity encompasses important endpoints such as skin and respiratory sensitization, hepatotoxicity and elevated acute aquatic toxicity. These adverse effects are initiated by, among others, electrophilic chemicals and those transformed into electrophiles; i.e. non-reactive chemicals activated into reactive electrophilic species by either a biotransformation (pro-electrophiles) or abiotic mechanism (pre-electrophiles). The presence of pro- and pre-electrophiles is important when developing quantitative structure-activity relationships (QSARs). In this study, the reactivity of potential pre-electrophile polyphenolics was investigated using an in chemico assay based on glutathione (GSH) depletion; in addition, the toxicity to Tetrahymena pyriformis was determined. For pre-electrophiles, no direct relationship between toxic potency and reactivity to GSH was obtained. The structural determinants for the pre-electrophile domain were characterized qualitatively by assessing structure-activity relationships (SARs). From this analysis, structural alerts for the pre-Michael acceptor domain (i.e. non-reactive chemicals activated into Michael acceptors) were extracted from the in chemico GSH data. A series of 10 structural alerts corresponding to 1,2- and 1,4-hydroxy and amino-substituted aromatics was developed. The relevance of the alerts was assessed by investigating the aquatic toxicity of these compounds. The structural alerts should help to identify and group pre-Michael acceptors and thus potent reactive toxicants.

A number of toxic effects are brought about by the covalent interaction between the toxicant and biological macromolecules. In chemico assays are available that attempt to identify reactive compounds. These approaches have been developed independently for pharmaceuticals and for other non-pharmaceutical compounds. The assays vary widely in terms of the macromolecule (typically a peptide) and the analytical technique utilised. For both sets of methods, there are great opportunities to capture in chemico information by using in silico methods to provide computational tools for screening purposes. In order to use these in chemico and in silico methods, integrated testing strategies are required for individual toxicity endpoints. The potential for the use of these approaches is described, and a number of recommendations to improve this extremely useful technique, in terms of implementing the Three Rs in toxicity testing, are presented.