T. Wayne Schultz

Pitfalls in QSAR

Abstract There are no formal guidelines for the development of quantitative structure–activity relationships (QSARs). However, there are a number of practices that should be avoided. This paper describes the pitfalls in QSAR, and problems that can arise if they occur. The emphasis of this paper is particularly for the development of QSARs for toxicity for environmental endpoints and drugs, but is equally applicable to pharmacological endpoints. Problems may arise from all three areas of the QSAR, namely the biological activity, physico-chemical and/or structural descriptors, and the use of a statistical technique. Biological data for use in a QSAR should be of a known (and preferably high) quality. Physico-chemical descriptors and statistical processes should be appropriate for the endpoint being modelled. They should allow for the development of a clear, transparent and mechanistically interpretable QSAR. To have any practical utility, QSARs should be validated by means of an external testing set.

Quantitative structure–activity relationships (QSARs) in toxicology: a historical perspective

Abstract The history of the use of quantitative structure–activity relationships (QSARs) in toxicology, both for environmental, and human health effects is described. A particular emphasis is made on the science in response to the United States Toxic Substance Control Act of 1976. Specifically, the basic concepts and objectives of QSARs for toxicity are reviewed. QSARs for environmental and human health effects are discussed separately. Environmental, and more specifically, ecotoxicity, QSARs have focused historically on modeling congeneric series and non-specific effects in aquatic organisms through the use of the logarithm of the 1-octanol/water partition coefficient to describe hydrophobicity, and hence uptake. Compounds that do not fit these QSARs (namely the outliers) have been explained by differences in mechanism of acute toxicity, especially as a result of electro(nucleo)philic interactions. In light of this, mechanisms of acute toxicity are discussed. QSAR approaches to receptor-mediated effects, such as those exhibited by environmental estrogens, and competitive binding to the estrogen receptor, are different from those typically applied to model acute toxic endpoints. Several of these approaches, including three-dimensional QSAR techniques, are reviewed. Human health effects include both local and systemic effects. Local effects (e.g. corrosivity and skin sensitization) are often modeled by multivariate QSAR methods such as linear regression and discriminant analysis. The prediction of systemic effects such as mutagenesis and carcinogenesis requires consideration of the endpoint and a more mechanistic basis for modeling. Approaches to predict these endpoints include the use of expert systems.

Use of Saccharomyces cerevisiae BLYES expressing bacterial bioluminescence for rapid, sensitive detection of estrogenic compounds

ABSTRACT An estrogen-inducible bacterial lux-based bioluminescent reporter was developed in Saccharomyces cerevisiae for applications in chemical sensing and environmental assessment of estrogen disruptor activity. The strain, designated S. cerevisiae BLYES, was constructed by inserting tandem estrogen response elements between divergent yeast promoters GPD and ADH1 on pUTK401 (formerly pUA12B7) that constitutively express luxA and luxB to create pUTK407. Cotransformation of this plasmid with a second plasmid (pUTK404) containing the genes required for aldehyde synthesis (luxCDE) and FMN reduction (frp) yielded a bioluminescent bioreporter responsive to estrogen-disrupting compounds. For validation purposes, results with strain BLYES were compared to the colorimetric-based estrogenic assay that uses the yeast lacZ reporter strain (YES). Strains BLYES and YES were exposed to 17β-estradiol over the concentration range of 1.2 × 10−8 through 5.6 × 10−12 M. Calculated 50% effective concentration values from the colorimetric and bioluminescence assays (n = 7) were similar at (4.4 ± 1.1) × 10−10 and (2.4 ± 1.0) × 10−10 M, respectively. The lower and upper limits of detection for each assay were also similar and were approximately 4.5 × 10−11 to 2.8 × 10−9 M. Bioluminescence was observed in as little as 1 h and reached its maximum in 6 h. In comparison, the YES assay required a minimum of 3 days for results. Strain BLYES fills the niche for rapid, high-throughput screening of estrogenic compounds and has the ability to be used for remote, near-real-time monitoring of estrogen-disrupting chemicals in the environment.

Guidelines for developing and using quantitative structure-activity relationships

Numerous quantitative structure-activity relationships (QSARs) have been developed to predict properties, fate, and effects of mostly discrete organic chemicals. As the demand for different types of regulatory testing increases and the cost of experimental testing escalates, there is a need to evaluate the use of QSARs and provide some guidance to avoid their misuse, especially as QSARs are being considered for regulatory purposes. This paper provides some guidelines that will promote the proper development and use of QSARs. While this paper uses examples of QSARs to predict toxicity, the proposed guidelines are applicable to QSARs used to predict physical or chemical properties, environmental fate, ecological effects and health effects.

The present status of QSAR in toxicology

Abstract The current status of the use of Quantitative Structure–Activity Relationships (QSARs) in toxicology, both environmental (i.e. ecotoxicology) and human health effects, are described with a particular emphasis on the science since 1995. Discussions of ecotoxicity QSARs focus on recent information that relates to separation of effects based on modes of toxic action. Particular attention is given to the response-surface approach to modeling toxic potency of baseline and non-specific soft electrophiles (i.e. the majority of industrial organic chemicals) and the development of rules-based expert systems to aid in the selection of the most appropriate QSAR. In addition the more recent application self-organizing dynamical algorithms such as artificial neural networks to ecotoxicity data is described. Recent QSAR modeling of estrogenicity, an example of receptor-mediated effects, are described with particular emphasis on 2D structural alerts as screening tools and QSARs developed with data for the recombinant yeast assay. In addition the current status of modeling human health effects include mutagenesis and carcinogenesis, developmental toxicity, skin sensitization, and skin and eye irritation is described.

Overview of data and conceptual approaches for derivation of quantitative structure-activity relationships for ecotoxicological effects of organic chemicals

The use of quantitative structure-activity relationships (QSARs) in assessing potential toxic effects of organic chemicals on aquatic organisms continues to evolve as computational efficiency and toxicological understanding advance. With the ever-increasing production of new chemicals, and the need to optimize resources to assess thousands of existing chemicals in commerce, regulatory agencies have turned to QSARs as essential tools to help prioritize tiered risk assessments when empirical data are not available to evaluate toxicological effects. Progress in designing scientifically credible QSARs is intimately associated with the development of empirically derived databases of well-defined and quantified toxicity endpoints, which are based on a strategic evaluation of diverse sets of chemical structures, modes of toxic action, and species. This review provides a brief overview of four databases created for the purpose of developing QSARs for estimating toxicity of chemicals to aquatic organisms. The evolution of QSARs based initially on general chemical classification schemes, to models founded on modes of toxic action that range from nonspecific partitioning into hydrophobic cellular membranes to receptor-mediated mechanisms is summarized. Finally, an overview of expert systems that integrate chemical-specific mode of action classification and associated QSAR selection for estimating potential toxicological effects of organic chemicals is presented.

Structure–toxicity relationships for selected halogenated aliphatic chemicals

Toxicity to the ciliate Tetrahymena pyriformis (log(IGC(50)(-1))) for 39 halogen-substituted alkanes, alkanols, and alkanitriles were obtained experimentally. Log(IGC(50)(-1)) along with the hydrophobic term, logK(ow) (1-octanol/water partition coefficient) and the electrophilic parameter, E(lumo) (the energy of the lowest unoccupied molecular orbital) were used to develop quantitative structure-activity relationships (QSARs). Two strong hydrophobic dependent relationships were obtained: one for the haloalkanes and a second for the haloalcohols. The relationship for the haloalkanes [log(IGC(50)(-1))=0.92 (logK(ow))-2.58; n=4, r(2)=0.993, s=0.063, f=276, Pr>f=0.0036] was not different from baseline toxicity. With the rejection of 1,3-dibromo-2-propanol as a statistical outlier, the relationship [log(IGC(50)(-1))=0.63(logK(ow))-1.18; n=19, r(2)=0.860, s=0.274, f=104, Pr>f=0.0001] was observed for the haloalcohols. No hydrophobicity-dependent model (r(2)=0.165) was observed for the halonitriles. However, an electrophilicity-dependent model [log(IGC(50)(-1))=-1.245(E(lumo))+0.73; n=15, r(2)=0.588, s=0.764, F=18.6, Pr>f=0.0009] was developed for the halonitriles. Additional analysis designed to examine surface-response modeling of all three chemical classes met with some success. Following rejection of statistical outliers, the plane [log(IGC(50)(-1))=0.60(logK(ow))-0.747(E(lumo))-0.37; n=34, r(2)=0.915, s=0.297, F=162, Pr>F=0.0001] was developed. The halogenated alcohols and nitriles tested all had observed toxicity in excess of non-reactive baseline toxicity (non-polar narcosis). This observation along with the complexity of the structure-toxicity relationships developed in this study suggests that the toxicity of haloalcohols and halonitriles is by multiple and/or mixed mechanisms of action which are electro(nucleo)philic in character.

Observations on the preferential biodegradation of selected components of polyaromatic hydrocarbon mixtures

The capacity of the naphthalene degrading enzyme (NAH) system of Pseudomonas fluorescens 5R and a number of other NAH system bacterial isolates to degrade mixtures of polyaromatic hydrocarbons (PAHs) and heterocyclic compounds were examined. It was found that all the examined organisms displayed similar patterns of preferential compound degradation when presented with the same mixture. Using strains that possess portions of the NAH system, this preferential degradation was localized to the activity of naphthalene dioxygenase. Comparisons of the first-order rates of compound degradation with the structures of the mixture components indicated that increased deviation from the base structure of naphthalene led to slower disappearance. Structural features that were found to decrease the rate of compound degradation include an increase in the number of methyl substituents and an increase in the size of a substituent.

Saccharomyces cerevisiae BLYAS, a New Bioluminescent Bioreporter for Detection of Androgenic Compounds

ABSTRACT A Saccharomyces cerevisiae strain, capable of autonomous bioluminescence, was engineered to respond to androgenic chemicals. The strain, S. cerevisiae BLYAS, contains the human androgen receptor in the chromosome and was constructed by inserting a series of androgen response elements between divergent yeast promoters GPD and ADH1 on pUTK401 that constitutively expressed luxA and luxB to create pUTK420. Cotransformation of this plasmid with a second plasmid (pUTK404), containing the genes required for aldehyde synthesis (luxCDE) and FMN reduction (frp), yielded a bioluminescent bioreporter responsive to androgenic chemicals. Using dihydrotestosterone (DHT) as a standard, the response time and the 50% effective concentration values were 3 to 4 h and (9.7 ± 4.6) × 10−9 M, respectively. The lower limit of detection in response to DHT was 2.5 × 10−9 M, and in response to testosterone it was 2.5 × 10−10 M. This strain is suitable for high-throughput screening of chemicals with potential for remote environmental monitoring systems because of the assay speed, sensitivity, and self-containment.

Structure-toxicity relationships for selected weak acid respiratory uncouplers

Abstract The relative biological response (log BR) for each of 30 select substituted phenols and anilines was evaluated using the 48-h Tetrahymena pyriformis population growth test system. Simple linear regression analysis of log BR versus log Kow (1-octanol/water partition coefficient) was used to formulate a quantitative structure-activity relationship (QSAR). The equation, log BR = 0.438 (log Kow) + 0.157; n=27, r2 =0.933, s = 0.151, f=348.02, is a highly predictive model. An evaluation of data on fathead minnow mortality for these same compounds shows a similar QSAR, log LC50= −0.590 (log Kow)− 3.247; n = 11, r2 = 0.917, s = 0.287, f=99.04. These relationships are the respective QSARs for the respiratory uncoupling mechanism of action of selected weak acids. Moreover, the toxic response in the two systems are highly correlated (r2 = 0.915).