QSAR-based toxicity classification and prediction for single and mixed aromatic compounds

A toxicity-based method for evaluating safety of reclaimed water for environmental reuses

A large quantity of toxic chemical pollutants possibly remains in reclaimed water due to the limited removal efficiency in traditional reclamation processes. It is not enough to guarantee the safety of reclaimed water using conventional water quality criteria. An integrated assessment method based on toxicity test is necessary to vividly depict the safety of reclaimed water for reuse. A toxicity test battery consisting of lethality, genotoxicity and endocrine disrupting effect was designed to screen the multiple biological effects of residual toxic chemicals in reclaimed water. The toxicity results of reclaimed water were converted into the equivalent concentrations of the corresponding positive reference substances (EQC). Simultaneously, the predicted no-effect concentration (PNEC) of each positive reference substance was obtained by analyzing the species sensitivity distribution (SSD) of toxicity data. An index "toxicity score" was proposed and valued as 1, 2, 3, or 4 depending on the ratio of the corresponding EQC to PNEC. For vividly ranking the safety of reclaimed water, an integrated assessment index "toxicity rank" was proposed, which was classified into A, B, C, or D rank with A being the safest. The proposed method was proved to be effective in evaluating reclaimed water samples in case studies.

QSAR modeling: where have you been? Where are you going to?

Quantitative structure-activity relationship modeling is one of the major computational tools employed in medicinal chemistry. However, throughout its entire history it has drawn both praise and criticism concerning its reliability, limitations, successes, and failures. In this paper, we discuss (i) the development and evolution of QSAR; (ii) the current trends, unsolved problems, and pressing challenges; and (iii) several novel and emerging applications of QSAR modeling. Throughout this discussion, we provide guidelines for QSAR development, validation, and application, which are summarized in best practices for building rigorously validated and externally predictive QSAR models. We hope that this Perspective will help communications between computational and experimental chemists toward collaborative development and use of QSAR models. We also believe that the guidelines presented here will help journal editors and reviewers apply more stringent scientific standards to manuscripts reporting new QSAR studies, as well as encourage the use of high quality, validated QSARs for regulatory decision making.

Evaluation of the ecotoxicity of pollutants with bioluminescent microorganisms

This chapter deals with the use of bioluminescent microorganisms in environmental monitoring, particularly in the assessment of the ecotoxicity of pollutants. Toxicity bioassays based on bioluminescent microorganisms are an interesting complement to classical toxicity assays, providing easiness of use, rapid response, mass production, and cost effectiveness. A description of the characteristics and main environmental applications in ecotoxicity testing of naturally bioluminescent microorganisms, covering bacteria and eukaryotes such as fungi and dinoglagellates, is reported in this chapter. The main features and applications of a wide variety of recombinant bioluminescent microorganisms, both prokaryotic and eukaryotic, are also summarized and critically considered. Quantitative structure-activity relationship models and hormesis are two important concepts in ecotoxicology; bioluminescent microorganisms have played a pivotal role in their development. As pollutants usually occur in complex mixtures in the environment, the use of both natural and recombinant bioluminescent microorganisms to assess mixture toxicity has been discussed. The main information has been summarized in tables, allowing quick consultation of the variety of luminescent organisms, bioluminescence gene systems, commercially available bioluminescent tests, environmental applications, and relevant references.

Toxicity cutoff of aromatic hydrocarbons for luminescence inhibition of Vibrio fischeri

Effects of individual petroleum hydrocarbons on the luminescence inhibition of Vibrio fischeri were evaluated according to a standard protocol to develop a quantitative structure-activity relationship and identify the apparent toxicity cutoff. Eighteen aromatic hydrocarbons, including benzene and its derivatives and polycyclic aromatic hydrocarbons (PAHs), were chosen as model compounds with their log K(ow) values between 2.7 and 6.4. The obtained values of 50 percent luminescence inhibition (EC50) showed a good linear correlation with log K(ow) up to ~5. However, toxic effects were not observed for more hydrophobic chemicals with log K(ow) value >5. The calculated chemical activities that caused EC50 were mostly between 0.01 and 0.1. This agrees with an earlier hypothesis concerning a chemical activity resulting the critical membrane concentration of aromatic hydrocarbons. The highest chemical activities for aromatic hydrocarbons with log K(ow) value >5 or melting point >100°C are <0.01 when they are spiked at their water solubility level according to the standard test protocol; this occurs for two primary reasons: (1) partitioning between organism and the test solution and (2) decreasing fugacity ratio with increasing melting point. Accordingly, luminescence inhibition by petroleum hydrocarbons is well explained by the baseline toxicity model. However, the apparent toxicity cutoff observed for single chemicals is not necessarily valid in a complex mixture, because baseline toxicity is regarded concentration additive.

Existing and Developing Approaches for QSAR Analysis of Mixtures

This review is devoted to the critical analysis of advantages and disadvantages of existing mixture descriptors and their usage in various QSAR/QSPR tasks. We describe good practices for the QSAR modeling of mixtures, data sources for mixtures, a discussion of various mixture descriptors and their application, recommendations about proper external validation specific for mixture QSAR modeling, and future perspectives of this field. The biggest problem in QSAR of mixtures is the lack of reliable data about the mixtures' properties. Various mixture descriptors are used for the modeling of different endpoints. However, these descriptors have certain disadvantages, such as applicability only to 1 : 1 binary mixtures, and additive nature. The field of QSAR of mixtures is still under development, and existing efforts could be considered as a foundation for future approaches and studies. The usage of non-additive mixture descriptors, which are sensitive to interaction effects, in combination with best practices of QSAR model development (e.g., thorough data collection and curation, rigorous external validation, etc.) will significantly improve the quality of QSAR studies of mixtures.