A surprisingly complex aqueous chemistry of the simplest amino acid. A pulse radiolysis and theoretical study on H/D kinetic isotope effects in the reaction of glycine anions with hydroxyl radicals.

A pulse radiolysis study was carried out of the reaction rate constants and kinetic isotope effects of hydroxyl-radical-induced H/D abstraction from the most-simple alpha-amino acid glycine in its anionic form in water. The rate constants and yields of three predominantly formed radical products, glycyl (NH2-*CH-CO2-), aminomethyl (NH2-*CH2), and aminyl (*NH-CH2-CO2-) radicals, as well as of their partially or fully deuterated analogs, were found to be of comparable magnitude. The primary, secondary, and primary/secondary H/D kinetic isotope effects on the rate constants were determined with respect to each of the three radicals. The unusual variety of products for such an elementary reaction between two small and simple species indicates a complex mechanism with several reactions taking place simultaneously. Thus, a theoretical modeling of the reaction mechanism and kinetics in the gas- and aqueous phase was performed by using the unrestricted density functional theory with the BB1K functional (employing the polarizable continuum model for the aqueous phase), unrestricted coupled cluster UCCSD(T) method, and improved canonical variational theory. Several hydrogen-bonded prereaction complexes and transition states were detected. In particular, the calculations pointed to a significant mechanistic role of the three-electron two-orbital (sigma/sigma* N therefore O) hemibonded prereaction complexes in the aqueous phase. A good agreement with the experimental rate constants and kinetic isotope effects was achieved by downshifting the calculated reaction barriers by 3 kcal mol(-1) and damping the NH(D) stretching frequency by a factor of 0.86.

Reliable QSAR for estimating Koc for persistent organic pollutants: correlation with molecular connectivity indices.

Several recent studies have shown that n-octanol/water partition coefficients may not be a good predictor for estimating soil sorption coefficients of persistent organic pollutants (POPs), defined here as chemicals with log Kow greater than 5. Thus, an alternative QSAR model was developed that seems to provide reliable estimates for the soil sorption coefficients of persistent organic pollutants. This model is based on a set of calculated molecular connectivity indices and evaluated soil sorption data for 18 POPs. The chemical's size and shape, quantified by 1chi, 3chiC and 4chiC(v) indices, have a dominant effect on the soil sorption process of POPs. The developed QSAR model was rationalized in terms of potential hydrophobic interactions between persistent organic pollutants and soil organic matrix. Its high predictive power has been verified by an extensive internal and external validation procedure.

QSAR models for estimating properties of persistent organic pollutants required in evaluation of their environmental fate and risk.

The molecular connectivity indices (MCIs) have been successfully used for over 20 years in quantitative structure activity relationships (QSAR) modelling in various areas of physics, chemistry, biology, drug design, and environmental sciences. With this review, we hope to assist present and future QSAR practitioners to apply MCIs more wisely and more critically. First, we have described the methods of calculation and systematics of MCIs. This section should be helpful in rational selection of MCIs for QSAR modelling. Then we have presented our long-term experience in the application of MCIs through several characteristic and successful QSAR models for estimating partitioning and chromatographic properties of persistent organic pollutants (POPs). We have also analysed the trends in calculated MCIs and discussed their physical interpretation. In conclusion, several practical recommendations and warnings, based on our research experience, have been given for the application of MCIs in the QSAR modelling.

Applications of experts' judgement to derive structure-biodegradation relationships.

The experts' judgement data on microbial degradation were used to develop the first general QSAR biodegradability model (Boethling and Sabljic, 1989) which is composed of a set of structural descriptors and a set of quantitative rules. Its evaluation and validation with experimental biodegradation data clearly show that the developed model gives a realistic and reliable account of structurebiodegradability relationship for organic chemicals. The same set of experts judgement data was used to develop structure-biodegradation rule by the application of an inductive machine learning method. An improved structure-biodegradation rule was derived from a larger training set of 160 chemicals, i.e. the combined experts' judgement and evaluated experimental biodegradation data. This rule has good predictive ability and discloses logical dependencies between structural features that have a strong influence on biodegradation of organic chemicals. Thus, the understanding of biodegradation processes will benefit from developed rule.

Predicting tropospheric degradation of chemicals: from estimation to computation.

For the majority of commercial chemicals present in the troposphere, the reaction with OH radicals during the day and with NO3 radicals at night are the most important abiotic pathways for their degradation and removal from the troposphere. Today, there are only a couple of methods available for estimating the reactivity of commercial chemicals with tropospheric radicals, which are not class specific, he Atkinson fragment contribution method and QSAR models, based on a linear correlation of OH (NO3) radical reactivity with the corresponding ionization energies, allow a rapid estimation of the rate constants of OH or NO3 radicals for various classes of organic compounds. Both methods are described and their limitations are discussed. A lot of work has been done to develop QSAR models for tropospheric degradation of commercial chemicals that will be based on calculated quantum chemical descriptors. This fast expanding area of QSAR research is presented and evaluated. Particular emphasis is given to the precision of various methods as well as to the latest results from our laboratory. The recent dramatic development in computing technology enables to precisely calculate energy profiles of tropospheric reactions with OH radicals. The semiempirical and ab initio molecular orbital calculations have been performed for hydrogen abstraction reactions for several classes of tropospheric pollutants. The best results of the high-level ab initio molecular orbital calculations are presented and discussed.

Assessment of QSARS for Predicting Fate and Effects of Chemicals in the Environment: An International European Project.

Abstract In 1993, an international project on QSAR has been started with funding from the Commission of the European Union. The first part of the project is focused on preparing an overview of existing models for the prediction of environmental parameters such as bioconcentration, sorption, degradation and ecotoxicity. Emphasis will be given to defining the limitations of the models. Since all models, including QSARs, have their limitations, it is important that these limitations are known in case QSARs are actually used and applied within the risk assessment context. The second part of the project is directed towards experimental research on new developments with emphasis on the use of multivariate techniques and quantum chemical properties. In this short paper, a general outline of the project will be given, as well as some first results. Results of experimental work within this project will be published in the proceedings of the 6th International Workshop on QSAR in Environmental Sciences and will appear in this same journal.

Chemical topology and ecotoxicology.

The experimental determination of environmental parameters (e.g. soil sorption, bioconcentration, biodegradation and biotransformation, toxic effects, etc.) of commercial chemicals is a costly and time-consuming process. Since there is a large number of chemicals currently in common use (approximately 100,000) and new chemicals are registered at a very high rate (1000/year) it is obvious that our human and material resources are insufficient to obtain experimentally even basic information on environmental fate and effects for all those chemicals. Thus, it is necessary to develop quantitative models that will accurately and rapidly predict environmental behaviour for large sets of chemicals. Thus far, molecular connectivity indices have been shown to be the most successful structural property for describing and predicting soil sorption coefficients, association with dissolved humic substances, Henry's law constants, bioconcentration factors in aquatic organisms and vegetation, biodegradation, and acute toxicity. We describe and discuss the most recent results on modelling environmental fate of organic pollutants by the application of molecular connectivity indices. Two sections describe the usefulness of environmental QSAR models based on n-octanol/water coefficients and the systematics and possible physical interpretation of molecular connectivity indices. Some practical and theoretical weaknesses and pitfalls are discussed concerning the use of n-octanol/water partition coefficients in environmental QSAR research.

Expert systems survey on biodegradation of xenobiotic chemicals.

To determine the feasibility of developing an expert system for biodegradability assessment, a survey was conducted in which biodegradation experts were asked to estimate rates and products of degradation for 50 chemicals. These chemicals, which varied widely in structure, were considered representative of the spectrum of premanufacture notice chemicals subject to EPA review under the Toxic Substances Control Act. There was substantial agreement among the 22 experts on both sites of initial attack and rates of degradation. The approximate order in which various groups were viewed as contributing to aerobic biodegradability is as follows: ester, amide, anhydride greater than hydroxyl greater than carboxyl, epoxide, site of unsaturation greater than benzene ring, methyl, methylene. Hydrolyzable groups, azo bonds, halogens, and nitro groups were preferred sites of anaerobic attack. Among the negative influences on aerobic biodegradability were molecular mass, branching, halogenation, and nitrogen heterocycles. Results also indicate that estimates of removal by biodegradation in aerobic wastewater treatment and time for aerobic ultimate and primary degradation were well correlated, and that the predictive value of such correlations could be improved using correction factors for certain classes of chemicals. The results lend support to existing rules of thumb, but also offer additional insight that will prove useful in designing a prototype system.

Quantitative modeling of soil sorption for xenobiotic chemicals.

Experimentally determining soil sorption behavior of xenobiotic chemicals during the last 10 years has been costly, time-consuming, and very tedious. Since an estimated 100,000 chemicals are currently in common use and new chemicals are registered at a rate of 1000 per year, it is obvious that our human and material resources are insufficient to experimentally obtain their soil sorption data. Much work is being done to find alternative methods that will enable us to accurately and rapidly estimate the soil sorption coefficients of pesticides and other classes of organic pollutants. Empirical models, based on water solubility and n-octanol/water partition coefficients, have been proposed as alternative, accurate methods to estimate soil sorption coefficients. An analysis of the models has shown (a) low precision of water solubility and n-octanol/water partition data, (b) varieties of quantitative models describing the relationship between the soil sorption and above-mentioned properties, and (c) violations of some basic statistical laws when these quantitative models were developed. During the last 5 years considerable efforts were made to develop nonempirical models that are free of errors imminent to all models based on empirical variables. Thus far molecular topology has been shown to be the most successful structural property for describing and predicting soil sorption coefficients. The first-order molecular connectivity index was demonstrated to correlate extremely well with the soil sorption coefficients of polycyclic aromatic hydrocarbons (PAHs), alkylbenzenes, chlorobenzenes, chlorinated alkanes and alkenes, heterocyclic and heterosubstituted PAHs, and halogenated phenols. The average difference between predicted and observed soil sorption coefficients is only 0.2 on the logarithmic scale (corresponding to a factor of 1.5). A comparison of the molecular connectivity model with the empirical models described earlier shows that the former is superior in accuracy, performance, and range of applicability. It is possible to extend this model, with the addition of a single, semiempirical variable, to take care of polar and ionic compounds and to accurately predict the soil sorption coefficients for almost 95% of all organic chemicals whose coefficients have been reported. No empirical or nonempirical models have ever predicted the soil sorption coefficients to such a high degree of accuracy on such a broad selection of structurally diverse compounds. An additional advantage of the molecular connectivity model is that it is sufficient to know the structural formulas to make predictions about soil sorption coefficients.(ABSTRACT TRUNCATED AT 400 WORDS)

Calculation of retention indices by molecular topology. Chlorinated benzenes.

A comparative study was undertaken to test the ability of several different topological indices to predict the retention indices of chlorinated benzenes on polar and non-polar stationary phases using both correlation coefficients and correctly predicted elution sequences as criteria of fit. The test was performed on three topological indices: connectivity indices, Wiener numbers, and Balaban indices. The regression analyses showed that the molecular connectivity model predicted the retention indices of chlorinated benzenes more successfully than either Wiener numbers or Balaban indices. The results also demonstrated that the major structural property controlling chromatographic behavior was the size of the chlorinated benzene. In addition, the use of the new non-empirical heteroatom parameterization scheme in the calculation of Wiener numbers and Balaban indices was successfully tested for the first time.

Calculation of retention indices by molecular topology: chlorinated alkanes.

This study was undertaken to test the ability of the molecular connectivity model to predict retention indices using both statistical correlation coefficients and correctly predicted elution sequences as criteria of fit. The test was performed on three groups of chloroalkanes. Regression analyses show that the molecular connectivity model successfully predicts the retention indices of chlorinated alkanes on polar and non-polar stationary phases. However, first-order molecular connectivity indices alone are not sufficient, higher order indices are demonstrated to be necessary. The results also indicate that different structural features determine the retention index values of mono- and dichlorides. For monochlorides the major factor is the size of the alkyl chain, while for dichlorides the major factor is the topological relation between the two chlorine atoms. The comparison of the results obtained with the molecular connectivity model and the empirical additive scheme reveals several important advantages of the molecular connectivity approach.

Molecular connectivity: a novel method for prediction of bioconcentration factor of hazardous chemicals.

Bioconcentration factor (BCF) is the concentration of a chemical in an organism divided by the concentration in water and it is one of the most important indicators for the fate of chemicals in the environment. Present methods for a preliminary estimation of concentration of hazardous chemicals in biota are based on empirical parameters, like water solubility (WS) and octanol-water partition coefficient (Kow). The accuracy of these methods is very low and experimental determination of empirical parameters can be very costly and time consuming. Thus, a novel, practical and efficient, method for prediction of BCFs of hazardous chemicals has been proposed. Molecular connectivity indices, based on molecular topology (number and type of atoms and chemical bonds), are purely non-empirical data and their calculation is quite simple. Second-order valence molecular connectivity indices were found to correlate extremely well with the BCFs in fish, obtained from the flowing water method, for various halocarbons (hydrocarbons, benzenes, biphenyls and diphenyloxides). Several well known and extensively used pesticides (DDT, DDD, DDE, heptachlor and dieldrin) have been chosen to test the predictive ability of the equation describing parabolic relationship between second-order valence molecular connectivity indices and BCFs.