Quantitative structure-activity relationships (QSARs) for inhibitors and substrates of CYP2B enzymes: importance of compound lipophilicity in explanation of potency differences

The results of quantitative structure-activity relationship (QSAR) studies on inhibitors and substrates of cytochrome P450 2B (CYP2B) subfamily enzymes are reported. It was found that lipophilicity (in the form of log P) is the most important property for explaining the variations in inhibitory activity, and there are similarities between QSARs for both substrates and inhibitors for CYP2B6 (human), and also between those of other CYP2B enzymes, such as CYP2B1 (rat) and CYP2B4 (rabbit). Both linear and quadratic lipophilicity relationships are evidenced in human and other mammalian species, and the particular type of expression found is probably due to the nature of the compounds under investigation, as it is usually the homologous series which tend to show quadratic relationships in log P. The findings from QSAR studies can be rationalized by molecular modelling of the active site interactions with both P450 crystal structures and homology models of CYP2B subfamily enzymes.     

Quantitative relationships between structure and antimicrobial activity of new “Soft” bisquaternary ammonium salts

New surface-active bisquaternary ammonium salts derived from bis-(2-dimethylaminoethyl) ester of glutaric acid are highly effective against representatives of Gram-positive, Gram-negative bacteria and yeasts. Relationships between structure, lipophilicity and antimicrobial effectiveness were demonstrated by quantitative structure-activity methodology. The nonlinear dependence of biological activity on the structure as well as lipophilicity (expressed as critical micelle concentration—CMC) was shown using Kubinyi’s bilinear model. The most effective compounds were those with the alkyl chain of 11–12 carbon atoms and with the CMC values around 0.7−1.0 mmol/L. These derivatives possessed higher antimicrobial activity particularly to Gram-negative bacteria. Part 45 of the seriesQuaternary Ammonium Salts; part 44: Brádlerová A.et al., Pharmazie, in press.     

2-(Aryl)-3-furan-2-ylmethyl-thiazolidin-4-ones as selective HIV-RT inhibitors

A series of 4-thiazolidinones were evaluated as selective inhibitors of the HIV-RT enzyme. Our attempt in correlating the derived physicochemical properties with the HIV-RT inhibitory activity resulted in some statistically significant QSAR models with good predictive ability. The QSAR studies indicated the role of lipophilicity, dipole moment and out-of-plane potential energy of the compounds in rationalizing the activity. One of the compounds, 1, inhibited the enzyme at 0.204 μM concentration with minimal toxicity to MT-4 cells.     

Opioid analgetics retention-pharmacologic activity models using biopartitioning micellar chromatography

Opioids are drugs used in medicine for pain control. In this paper, retention-pharmacokinetics and retention-pharmacodynamics relationships of opioids are proposed and statistically validated. These models are based on the compound retention in the biopartitioning micellar chromatography system (BMC), a new methodology which has successfully been used to develop QRAR models for many other families of compounds. The obtained results are compared to the traditional QSAR models using lipophilicity data. The adequacy of QRAR models is due to the fact that the characteristics of the compounds such as the hydrophobicity, electronic charge and steric effects determine both their retention in BMC and their pharmacokinetic and pharmacodynamic behavior.     

Development and validation of a robust QSAR model for prediction of carcinogenicity of drugs

Carcinogenicity is one of the toxicological endpoints causing the highest concern. Also, the standard bioassays in rodents used to assess the carcinogenic potential of chemicals and drugs are extremely long, costly and require the sacrifice of large numbers of animals. For these reasons, we have attempted development of a global quantitative structure-activity relationship (QSAR) model using a data set of 1464 compounds (the Galvez data set available from http://www.uv.es/-galvez/tablevi.pdf), including many marketed drugs for their carcinogenesis potential. Though experimental toxicity testing using animal models is unavoidable for new drug candidates at an advanced stage of drug development, yet the developed global QSAR model can in silico predict the carcinogenicity of new drug compounds to provide a tool for initial screening of new drug candidate molecules with reduced number of animal testing, money and time. Considering large number of data points with diverse structural features used for model development (n(training) = 732) and model validation (n(test) = 732), the model developed in this study has an encouraging statistical quality (leave-one-out Q2 = 0.731, R2pred = 0.716). Our developed model suggests that higher lipophilicity values and conjugated ring systems, thioketo and nitro groups contribute positively towards drug carcinogenicity. On the contrary, tertiary and secondary nitrogens, phenolic, enolic and carboxylic OH fragments and presence of three-membered rings reduce the carcinogenicity. Branching, size and shape are found to be crucial factors for drug-induced carcinogenicity. One may consider all these points to reduce carcinogenic potential of the molecules.     

Chromatographic evaluation of the toxicity in fish of pesticides

Ecotoxicity assessment is essential before placing new chemical substances on the market. An investigation of the use of the chromatographic retention (log k) in biopartitioning micellar chromatography (BMC) as an in vitro approach to evaluate the toxicity in fish of pesticides (acute toxicity levels as pLC(50)) is proposed. A heterogeneous data set of 85 pesticides from six chemical families with available experimental fish toxicity data (ECOTOX database from U.S. Environmental Protection Agency (EPA)) was used. For pesticides exhibiting non-polar narcosis mechanism in fish (non-specific toxicity), more reliable models and precise pLC(50) estimations are obtained from log k (quantitative retention-activity relationships, QRAR) than from log P (quantitative structure-activity relationships, QSAR) or ECOSAR (ECOSAR program from U.S. EPA).