Ovanes G. Mekenyan

QSARs for photoinduced toxicity: I. Acute lethality of polycyclic aromatic hydrocarbons to Daphnia magna

Research with a variety of aquatic species has shown that while polycyclic aromatic hydrocarbons (PAHs) are generally not acutely toxic in conventional laboratory tests, many are extremely toxic in the presence of sunlight. In an effort to develop a model for predicting which PAHs may exhibit photo-induced toxicity, Newsted and Giesy (1987) reported a parabolic relationship between the toxicity and the energy of the triplet state of a variety of PAHs. We have reexamined these data and propose a more mechanistic explanation for the prediction of photo-induced PAH toxicity. Photo-induced toxicity is the result of competing processes such as stability and light absorbance which interact to produce a complex, multilinear relationship between toxicity and chemical structure. We sought a molecular descriptor which could be computed from structure rather than measured empirically. We found that a measure of the energy stabilization of the toxicant in the form of the HOMO-LUMO (Highest Occupied Molecular Orbital - Lowest Unoccupied Molecular Orbital) gap provided a useful index to explain the persistence, light absorption, and photo-induced toxicity of PAHs. The model clearly shows, for example, why phenanthrene and tetracene are not toxic while anthracene is highly phototoxic. Those PAHs exhibiting photo-induced toxicity were consistently within HOMO-LUMO gap “window” of 7.2 ± 0.4 eV.

A QSAR analysis of substituent effects on the photoinduced acute toxicity of PAHs

Photoinduced toxicity of polycyclic aromatic hydrocarbons (PAHs) is a result of competing effects including stability and light absorbance of the molecules as well as irradiation parameters. The energy difference between the Highest Occupied Molecular Orbital and the Lowest Unoccupied Molecular Orbital (HOMO-LUMO gap), which can be computed directly from structure, was found to be the molecular descriptor that best distinguishes phototoxic chemicals from non-phototoxic chemicals. Aromatic chemicals that are phototoxic in sunlight have HOMO-LUMO gap energies that fall in the range of 6.7 to 7.5 eV. This study showed that the effect of most substituents on the HOMO-LUMO gap was negligible, and that phototoxicity in an aromatic chemical is likely only if the parent aromatic structure is phototoxic. Exceptions included substituents that add to delocalization (nitro and alkenyl) which could shift some chemicals with a HOMO-LUMO gap just above 7.5 eV into the domain of photoinduced toxicity.

A new development of the oasis computer system for modeling molecular properties

Abstract A description of the new version of the OASIS system for computer assisted quantitative structure-property analysis is presented. The newly developed system is much more flexible and versatile than the version recently introduced. The most significant changes are the amendments within the input module. The originally developed line notion system is described in detail. The routine for an exhaustive generation of all stereo, optical and torsional isomers should also be emphasized here. The input module provides a database management for a library with three-dimensional molecular models, including substructure search. The list of the calculated topological, steric and electronic indices is extended by physicochemical parameters such as partition coefficient, molecular refraction, van der Waals volume and surface, etc. The basic advantages of the system are delineated. Some numerical data on the performance of the improved OASIS method are presented.

QSAR Estimates of Excited States and Photoinduced Acute Toxicity of Polycyclic Aromatic Hydrocarbons

Abstract Direct calculation of the energy of excited states for polycyclic aromatic hydrocarbons using semi-empirical methods on a supercomputer were inadequate in explaning spectrosopic data or measured phototoxicity. The energy difference between frontier orbitals HOMO-LUMO gap of “average” excited state structures of the PAHs correlated with the measured excited state energies and their observed photoinduced toxicity. The multi-linear relationship between phototoxicity and hypothetical triplet state HOMO-LUMO gap is similar to that based on ground state structures. This molecular descriptor discriminated phototoxic PAHs into a narrow range of approximately 6.2+ mn;0.4 eV. Chemicals with a HOMO-LUMO gap in the triplet state greater than 7.1 eV were not phototoxic in simulated sunlight. Chemicals with gaps less than 5.8 eV are likely to be unstable in water and degrade too rapidly to enable determination of photoinduced potency to aquatic organisms. Several preliminary structure-phototoxicity relationshi...

QSARs for Photoinduced Toxicity of Aromatic Compounds

Abstract This paper reviews the results of a series of efforts to develop QSAR models for aromatic chemicals whose toxicity is enhanced by the ultraviolet radiation present in sunlight. Photoinduced toxicity of polycyclic aromatic hydrocarbons (PAHs) was found to be a result of competing factors: structural (such as molecular stability and light absorbance) and external (irradiation energy and intensity). These two factors interact, producing a complex, multilinear relationship between toxicity and electronic structure. The HOMO-LUMO gap provided a useful ground-state index to explain the persistence, light absorption, and eventually, the photoinduced toxicity of PAHs. The derived QSAR clearly distinguished phototoxic differences between pairs of structurally similar PAHs, such as phenanthrene and anthracene, benzo [a] anthracene and tetracene, et cetera. Those PAHs exhibiting photoinduced toxicity were consistently within a specific range of the electronic parameter. Further modeling revealed a significa...

Simulation of chemical metabolism for fate and hazard assessment. I. Approach for simulating metabolism

Information regarding the metabolism of xenobiotic chemicals plays a central role in regulatory risk assessments. In regulatory programmes where metabolism studies are required, the studies of metabolic pathways are often incomplete and the identification of activated metabolites and important degradation products are limited by analytical methods. Because so many more new chemicals are being produced than can be assessed for potential hazards, setting assessment priorities among the thousands of untested chemicals requires methods for predictive hazard identification which can be derived directly from chemical structure and their likely metabolites. In a series of papers we are sharing our experience in the computerized management of metabolic data and the development of simulators of metabolism for predicting the environmental fate and (eco)toxicity of chemicals. The first paper of the series presents a knowledge-based formalism for the computer simulation of non-intermediary metabolism for untested chemicals, with an emphasis on qualitative and quantitative aspects of modelling metabolism.

In silico modelling of hazard endpoints: current problems and perspectives

Major scientific hurdles in the acceptance of quantitative structure–activity relationships (QSAR) for regulatory purposes have been identified. First, when quantifying important features of chemical structure complexities of molecular structure have often been ignored. More mechanistic modelling of chemical structure should proceed on two fronts: by developing a more in-depth understanding and representation of the multiple states possible for a single chemical by achieving greater rigor in understanding of conformational flexibility of chemicals; and, by considering families of activated metabolites that are derived in biological systems from an initial chemical substrate. Second, QSAR research is severely limited by the lack of systematic databases for important risk assessment endpoints, and despite many decades of research, the ability to cluster reactive chemicals by common toxicity pathways is in its infancy. Finally, computational tools are lacking for defining where a specific QSAR is applicable within the domain (universe) of chemical structures that are to be regulated. This paper describes some of the approaches being taken to address these needs. Applications of some of these new approaches are demonstrated for the prediction of chemical mutagenicity, where considerations of both molecular flexibility and metabolic activation improved the QSAR predictability and interpretations. Lastly, the applicability domain for a specific QSAR predicting estrogen receptor binding is presented in the context of a mechanistically-defined chemical structure space for large heterogeneous chemical datasets of regulatory concern. A strategic approach is discussed to selecting chemicals for model improvement and validation until regulatory acceptance criteria for risk assessment applications are met.

'Dynamic' QSAR for semicarbazide-induced mortality in frog embryos

The conventional quantitative–structure–activity relationship (QSAR) provides only a single three‐dimensional (3D) model for a given two‐dimensional (2D) item in the modeling process. However, in complex reaction environments with solvents of different polarity, especially biological systems, the molecules can take the form of different conformers depending on the particular interaction. Therefore, chemical behavior, e.g. toxicity, may be considered the integral effect of a set of conformers rather than the property of a single 3D isomer. The ‘dynamic’ QSAR method is unique in that it provided for the calculation of a set of conformers for 2D representation of each chemical of the series under investigation. Moreover, these conformers can be selected interactively according to the hypothesized mechanism of toxic action.

POPs: A QSAR System for Developing Categories for Persistent, Bioacculative and Toxic Chemicals and their Metabolites

This paper presents the framework of a QSAR-based decision support system which provides a rapid screening of potential hazards, classification of chemicals with respect to risk management thresholds, and estimation of missing data for the early stages of risk assessment. At the simplest level, the framework is designed to rank hundreds of chemicals according to their profile of persistence, bioaccumulation potential and toxicity often called the persistent organic pollutant (POP) profile or the PBT (persistent bioaccumulative toxicant) profile. The only input data are the chemical structure. The POPs framework enables decision makers to introduce the risk management thresholds used in the classification of chemicals under various authorities. Finally, the POPs framework advances hazard identification by integrating a metabolic simulator that generates metabolic map for each parent chemical. Both the parent chemicals and plausible metabolites are systematically evaluated for metabolic activation and POPs profile.

SAR Models for Futile Metabolism: One-Electron Reduction of Quinones, Phenols and Nitrobenzenes

Abstract Benzoquinones, naphthoquinones and aziridinylbenzoquinones, can be reduced by flavoproteins to semiquinones that react with molecular oxygen to form superoxide anion with the subsequent regeneration of the parent compounds. This redox cycling, a form of futile metabolism, produces reactive oxygen species and depletes the reducing equivalents of cells without concomitant energy production. The ability of a toxicant to redox cycle is related to its one-electron reduction potential, and this study attempted to estimate reduction potential from structure using semi-empirical quantum chemical models for a diverse set of chemicals. The results of this study suggest that one-electron reduction potentials, within structural classes of benzoquinones, naphthoquinones, phenols and nitrobenzenes, can be estimated from local and global electronic indices that are related to delocalization. Smaller absolute charge on the carbonyl carbon in the quinone moiety correlated with more positive one-electron reduction...