Industrial Organic Chemicals Research Articles

Comparative QSAR and q-RASAR modeling for aquatic toxicity of organic chemicals to three trout species: O. Clarkii, S. Namaycush, and S. Fontinalis

Oncorhynchus clarkii, Salvelinus fontinalis, and Salvelinus namaycush are vital trout species in North America, crucial for maintaining ecological balance, economic stability, and human health. These species thrive in cold, unpolluted waters and are highly vulnerable to contaminants. Given the rapid proliferation of industrial organic chemicals, traditional in vivo toxicity testing methods are inadequate to ensure timely and comprehensive risk assessments. Therefore, we employed in silico tools, namely Quantitative Structure-Activity Relationship (QSAR) and Quantitative Read-Across Structure-Activity Relationship (q-RASAR), to efficiently predict the aquatic toxicity of chemicals. Utilizing acute median lethal concentration (LC50) data from the US EPA’s ToxValDB, we developed the first-ever species-specific QSAR and q-RASAR models. The q-RASAR models outperformed traditional QSAR models by achieving higher internal and external statistical quality for each species. Key toxicity-determining descriptors included electrotopological state indices, autocorrelation descriptors, and similarity-based RASAR descriptors. For O. clarkii, the presence of chlorine atoms and rotatable bonds significantly influenced toxicity. S. fontinalis toxicity was strongly affected by polarizability, and van der Waals volumes, while S. namaycush showed sensitivity to weak hydrogen bond acceptors and topological complexity. The models predicted the toxicity of 1172 external compounds, identifying the most and least toxic chemicals for each species. This study not only offers the first comprehensive q-RASAR models for predicting trout species-specific toxicity but also provides novel insights into species-specific toxicological modes of action. The results contribute significantly to chemical screening and prioritization in aquatic risk assessments, effectively filling critical data gaps and advancing predictive modeling techniques.

Separation of phenolic compounds from oil mixtures using environmentally benign biological reagents based on Brønsted acid-Lewis base interaction

Phenolic compounds, which are widely used in producing synthetic fibers, engineering plastics, and other industrial organic chemicals, can be obtained from oil mixtures before further processing or applications by separation. Based on Lewis/Brønsted acid-base theory, we proposed the separation of phenolic compounds from oil mixtures using some environmentally benign biological reagents (BRs, including 1,3-dimethylxanthine-DMX, isonicotinamide-INA, and L-lysine-LYS). The effects of stirring time, temperature, initial phenol concentration, and BR:phenol mole ratio on phenol removal were studied in detail. LYS, INA and DMX show phenol removal efficiencies of 98.4%, 82.2%, and 66.6% from toluene at BR:phenol mole ratios of 1.6, 1.4, and 0.4, respectively, and those of 99.1%, 91.8%, and 74.6% from n-hexane at BR:phenol mole ratios of 2.20, 1.60, and 0.80, respectively, at room temperature. The BRs were regenerated with an anti-extraction method for four cycles without significant changes in separation efficiency and their properties. In addition, it is found that there is little toluene entrained in the biological reagents, which is as low as 2.3 wt% of separated phenol, indicating high purities of products. These BRs show the advantages of easy biodegradation, no corrosion to the equipment and containers, and no pollution to the environment.

Production of lignofuels and electrofuels by extremely thermophilic microbes

Extreme thermophiles are microorganisms that grow optimally at elevated temperatures (≥ 70°C). They could play an important role in the emerging renewable energy landscape by exploiting thermophily to produce liquid transportation fuels. For example, Caldicellulosiruptor species can grow on unpretreated plant biomass near 80°C utilizing novel multi-domain glycoside hydrolases. Through metabolic engineering, advanced biofuels compatible with existing infrastructure liquid biofuels, so-called lignofuels, could be produced to establish consolidated bioprocessing at high temperatures. In another case, a new paradigm, electrofuels, addresses the inefficiency of biofuel production through the direct synthesis of advanced fuels from carbon dioxide using hydrogen gas as the electron carrier. This requires coupling of biological electron utilization to carbon dioxide fixation and ultimately to fuel synthesis. Using a hyperthermophilic host Pyrococcus furiosus and synthetic metabolic pathways comprised of genes from less thermophilic sources, temperature-regulated biosynthesis of industrial organic chemicals and liquid fuel molecules are possible. Herein, we review recent progress towards the synthesis of lignofuels and electrofuels by extremely thermophilic microorganisms.

Industrial Organic Chemicals. Von H. A. Wittcoff, B. G. Reuben, J. S. Plotkin

Industrial Organic Chemicals. Von H. A. Wittcoff, B. G. Reuben, J. S. Plotkin

Risk assessment based prioritization of 200 organic micropollutants in 4 Iberian rivers

The use of chemicals is continuously growing both in total amount as well as in a number of different substances, among which organic chemicals play a major role. Owing to the growing public awareness on the need of protecting both ecosystems and human health from the risks related to chemical pollution, an increasing attention has been drowned to risk assessment and prioritization of organic pollutants. In this context, the aims of this study were (a) to perform an environmental risk assessment for 200 organic micropollutants including both regulated and emerging contaminants (pesticides, alkylphenols, pharmaceuticals, hormones, personal care products, perflourinated compounds and various industrial organic chemicals) monitored in four rivers located in the Mediterranean side of the Iberian Peninsula, namely, the Ebro, Llobregat, Júcar and Guadalquivir rivers; and (b) to prioritize them for each of the four river basins studied, taking into account their observed concentration levels together with their ecotoxicological potential. For this purpose, a prioritization approach has been developed and a resulting ranking index (RI) associated with each compound. Ranking index is based on the measured concentrations of the chemical in each river and its ecotoxicological potential (EC50 values for algae, Daphnia sp. and fish). Ten compounds were identified as most important for the studied rivers: pesticides chlorpyriphos, chlorfenvinphos, diazinon, dichlofenthion, prochloraz, ethion carbofuran and diuron and the industrial organic chemicals nonylphenol and octylphenol that result from the biodegration of polyethoxylated alkyphenol surfactants. Also, further research into chronic toxicity of emerging contaminants is advocated.

Experimental verification of structural alerts for the protein binding of sulfur-containing compounds

As often noted by Dr. Gilman Veith, a major barrier to advancing any model is defining its applicability domain. Sulfur-containing industrial organic chemicals can be grouped into several chemical classes including mercaptans (RSH), sulfides (RSR’), disulfides (RSSR’), sulfoxides (RS(=O)R’), sulfones (RS(=O)(=O)R’), sulfonates (ROS(=O)(=O)R’) and sulfates (ROS(=O)(=O)OR’). In silico expert systems that predict protein binding reactions from 2D structure sub-divide these chemical classes into a variety of chemical reactive mechanisms and reactions which have toxic consequences. Using the protein binding profilers in version 3.1 of the OECD QSAR Toolbox, a series of sulfur-containing chemicals were profiled for protein binding potential. From these results it was hypothesized which sulfur-containing chemicals would be reactive or non-reactive in an in chemico glutathione assay and whether if reactive they would exhibit toxicity in excess of baseline in the Tetrahymena pyriformis population growth impairment assay. Subsequently, these hypotheses were tested experimentally. The in chemico data show that the in silico profiler predictions were generally correct for all chemical categories, where testing was possible. Mercaptans could not be assessed for GSH reactivity because they react directly with the chromophore 5,5’-dithiobis-(2-nitrobenzoic acid). With some exceptions, the major being disulfides, the in vitro toxicity data supported the in chemico findings.

Industrial organic chemicals

Industrial organic chemicals

High Affinity Membranes for Cellulase Enzyme Detection in Subterranean Termites

ABSTRACTThe United States dependence on fossil fuels has become mandatory over the past few decades. The fuel shortage during the 1970s and after Hurricane Katrina has catalyzed a need for creating alternative energy sources, improving the efficacy of these alternative energy sources, and enhancing energy sustainability. The U.S. Department of Energy has set goals to replace 30% of the liquid petroleum transportation fuel with biofuels and to replace 25% of industrial organic chemicals with biomass-derived chemicals by 2025. In the southeast United States, subterranean termites are prevalent and microbes in their gut degrade wood based materials such as cellulose which produce simple sugars that can be used to produce bioethanol. Upon seasonal change, subterranean termites undergo less enzymatic activity and wood-eating capability limiting the amount of sugars that may be produced. This limited activity sparks an interest to investigate this poorly understood phenomenon of how temperature may affect the enzymatic activity in subterranean termites’ guts. In this study, we report the development thermoresponsive biomaterial nanofiber mats containing cellulose to model cellulase activity. Using electrospinning techniques, poly(N-vinylcaprolactam) celluose fiber mats have been prepared via alkaline hydrolysis and labeled with fluorescent tags. Subterranean termites (reticulitermes species) were feed fiber mats for 10 consecutive days to assess enzyme mapping and kinetics. Fluorescent microscopy images confirmed spatial and temporal localization of cellulase enzyme throughout the termite gut upon time and temperature change. These novel high affinity enzyme detection membranes show promise towards future biofuel production.

The influence of modes of action and physicochemical properties of chemicals on the correlation between in vitro and acute fish toxicity data

New EU legislation is providing an impetus for research aimed at replacing acute fish toxicity testing with in vitro alternatives. In line with such research, the objective of this study was to determine what factors influence the correlation between in vitro and fish toxicity data. Basal cytotoxicity (IC 50) and acute toxicity data from fathead minnow (LC 50) of 82 industrial organic chemicals were obtained from the Halle Registry of Cytotoxicity and the US EPA Fathead Minnow Database. A good correlation between IC 50 with LC 50 data was found ( r 0.84). Yet, IC 50 data were less sensitive than LC 50 data by an order of magnitude. Using multiple regression analysis, the octanol–water partition coefficient ( K OW ) and the Henry’s Law Constant ( H) were found to significantly explain the low absolute sensitivity. The mode of action (MOA) of the chemical was found to significantly explain the general variation in the log IC 50/log LC 50 regression line. These results support the notion that (a) the bioavailability of hydrophobic (high K OW ) and volatile (high H) chemicals is significantly lower in in vitro assays than in the fish bioassay and (b) multiple cell types and endpoints should be included to mimic the modes of action possible in the whole organism.

Integrated fuzzy concentration addition–independent action (IFCA–IA) model outperforms two-stage prediction (TSP) for predicting mixture toxicity

Mixture toxicities were determined for 12 industrial organic chemicals bearing four different modes of toxic action (MOAs) to Vibrio fischeri, to compare the predictability of the integrated fuzzy concentration addition–independent action (IFCA–IA) model and the two-stage prediction (TSP) model. Three mixtures were designed: The first and second mixtures were based on the ratios of each component at the 1% and 50% effect concentrations (EC 1 and EC 50), respectively; and the third mixture contained an equimolar ratio of individual components. For the EC 1, EC 50 and equimolar ratio, prediction errors from the IFCA–IA model at the 50% experimental mixture effects were 0.3%, 6% and 0.6%, respectively; while for the TSP model, the corresponding errors were 2.8%, 19% and 24%, respectively. Thus, the IFCA–IA model performed better than the TSP model. The IFCA–IA model calculated two weight coefficients from the molecular structural descriptors, which weigh the relation between concentration addition (CA) and independent action (IA) through the fuzzy membership functions. Thus, MOAs are not pre-requisites for mixture toxicity prediction by the IFCA–IA approach, implying the practicability of this method in toxicity assessment of mixtures.

Causes of water toxicity to Hyalella azteca in the New River, California, USA

The New River (CA, USA) was created in 1905 to 1907 when the Colorado River washed out diversionary works and flowed into the Salton Basin, creating the Salton Sea. Approximately 70% of the river's current flow is agricultural wastewater from the Imperial Valley. The river is contaminated with pesticides, industrial organic chemicals, metals, nutrients, bacteria, and silt. Monitoring for the State of California Surface Water Ambient Monitoring Program has indicated persistent water column toxicity to the epibenthic amphipod Hyalella azteca. Four toxicity identification evaluations (TIEs), along with chemical analyses, were performed, and the results indicated multiple and varying causes of toxicity. The first two TIEs characterized the causes of toxicity as a combination of metals and organics, but only the second sample contained enough total copper to contribute to toxicity. The third TIE used an emerging method for characterizing and identifying toxicity caused by pyrethroid pesticides. This TIE characterized organics as the cause of toxicity, and a carboxylesterase enzyme treatment further identified the cause of toxicity as pyrethroids. The final TIE used the enzyme and Phase II procedures to identify cypermethrin as the cause of toxicity. The TIE results demonstrate the evolving causes of toxicity in the New River and should assist regulators with implementing the total maximum daily load process for pesticides, particularly pyrethroids. Further research will determine if pyrethroids and other New River contaminants are having an impact on the Salton Sea.

Time Dependence in Mixture Toxicity with Soft Electrophiles: 1. Combined Effects of Selected SN2- and SNAr-Reactive Agents with a Nonpolar Narcotic

Frequently the toxicity of an organic chemical mixture is close to dose-additive, even when the agents are thought to induce toxicity at different molecular sites of action. These findings appear to conflict with the hypothesis that a strictly dose-additive combined effect will be observed for agents sharing a single molecular site of toxic action within the organism. In this study, several SN2-reactive (alpha-halogen) or S(N)Ar-reactive (halogenated dinitrobenzene) soft electrophiles were tested with a model nonpolar narcotic (NPN) to determine the toxicity of the combinations. A sham combination of the model NPN (3-methyl-2-butanone) was also tested as a positive control. The study design incorporated time-dependent toxicity (TDT) determinations at 15, 30, and 45 minutes using a Microtox (Vibrio fischeri) protocol that included testing seven duplicated concentrations for each single agent and mixture per combination. Additionally, in chemico reactivity was determined for each compound using thiol in glutathione as a model nucleophile. The model NPN alone lacked reactivity and TDT. The SN2-reactive agents individually showed varying levels of both reactivity and TDT alone, while the SNAr-reactive chemicals alone were reactive and had toxicity that was fully time-dependent between 15 and 45 minutes of exposure. Data analyses indicated that the sham combination was dose additive, as expected, whereas three of four SN2:NPN combinations showed effects close to that predicted for dose addition but with some differences. The fourth SN2:NPN combination, which included an alpha-halogen with full TDT, showed a less-than-dose-additive combined effect as did both of the SNAr:NPN pairings. By incorporating TDT values, shapes of the dose-response curves, chemical reactivity data with thiol, reactive mechanisms for the soft electrophiles, and quantitative structure activity relationship information on whether the toxicity of the individual soft electrophiles did or did not exceeded that predicted for baseline narcosis, the results suggested that the alpha-halogens elicited two toxic effects at the concentrations tested (reactivity and narcotizing effects), whereas toxicity induced by the halogenated dinitrobenzenes was essentially limited to reactive effects. Collectively, these results provide experimental evidence consistent with previous explanations as to why binary mixtures of industrial organic chemicals often show combined effects that are close to dose additive, even when the chemicals are thought to induce toxicity at different molecular sites of action.

Biorefineries–Industrial Processes and Products: Status Quo and Future Directions

Biorefineries–Industrial Processes and Products: Status Quo and Future Directions

Are endocrine disrupting compounds a health risk in drinking water?

There has been a great deal of international discussion on the nature and relevance of endocrine disrupting compounds in the environment. Changes in reproductive organs of fish and mollusks have been demonstrated in rivers downstream of sewage discharges in Europe and in North America, which have been attributed to estrogenic compounds in the effluent. The anatomical and physiological changes in the fauna are illustrated by feminization of male gonads. The compounds of greatest hormonal activity in sewage effluent are the natural estrogens 17Beta-estradiol, estrone, estriol and the synthetic estrogen ethinylestradiol. Androgens are also widely present in wastewaters. Investigations of anthropogenic chemical contaminants in freshwaters and wastewaters have shown a wide variety of organic compounds, many of which have low levels of estrogenic activity. In many highly populated countries the drinking water is sourced from the same rivers and lakes that are the recipients of sewage and industrial discharge. The River Thames which flows through London, England, has overall passed through drinking water and sewage discharge 5 times from source to mouth of the river. Under these types of circumstance, any accumulation of endocrine disrupting compounds from sewage or industry potentially affects the quality of drinking water. Neither basic wastewater treatment nor basic drinking water treatment will eliminate the estrogens, androgens or detergent breakdown products from water, due to the chemical stability of the structures. Hence a potential risk to health exists; however present data indicate that estrogenic contamination of drinking water is very unlikely to result in physiologically detectable effects in consumers. Pesticide, detergent and industrial contamination remain issues of concern. As a result of this concern, increased attention is being given to enhanced wastewater treatment in locations where the effluent is directly or indirectly in use for drinking water. In some places at which heavy anthropogenic contamination of drinking water sources occurs, advanced drinking water treatment is increasingly being implemented. This treatment employs particle removal, ozone oxidation of organic material and activated charcoal adsorption of the oxidation products. Such processes will remove industrial organic chemicals, pesticides, detergents, pharmaceutical products and hormones. Populations for which only basic wastewater and drinking water treatment are available remain vulnerable.

Estrogenicity and acute toxicity of selected anilines using a recombinant yeast assay

Suspected estrogen modulators include industrial organic chemicals (i.e., xenoestrogens), and have been shown to consist of alkylphenols, bisphenols, biphenylols, and some hydroxy-substituted polycyclic aromatic hydrocarbons. The most prominent structural feature identified to be important for estrogenic activity is a polar group capable of donating hydrogen bonds (i.e., hydroxyl) on an aromatic system. The present study was undertaken to explore the estrogenic activity and acute toxicity of chemicals containing a weaker hydrogen bond donor group on aromatic systems, i.e., the amino substituent. There is a great deal of chemical similarity between aromatic amines (anilines) and aromatic alcohols (phenols). The chemicals chosen for the current study contained an amino-substituted benzene ring with hydrophobic constituents varying in size and shape. Thus, 37 substituted aromatic amines were assayed for estrogenic activity EC 50 and acute toxicity LC 50 using the Saccharomyces cerevisiae recombinant yeast assay. While the EC 50 of 17-β-estradiol occurs at the 10 −10 range, the aniline with the greatest activity had an EC 50 of 10 −6 M. Thus, anilines, in general, are capable only of very weak estrogenic activity in this assay. A comparison of estrogenic potency between the present group of anilines and a set of previously tested analogous phenols indicated that anilines are consistently less estrogenic than phenols. A comparison of hazard indices (EC 50/LC 50) of these chemicals revealed that, for the vast majority of anilines, the EC 50 and LC 50 were in the same order of magnitude. More specifically, estrogenic activity of para-substituted alkylanilines increases with alkyl group size up to 5 carbons in length, after which the acute toxicity of the larger alkyl-substituents precluded the ability of the compound to induce the estrogenic response.

The present status of QSAR in toxicology

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.

Health-effects related structure–toxicity relationships: a paradigm for the first decade of the new millennium

Prediction of the effects of industrial chemicals to humans will be an area of increasing concern in the next century. The role of quantitative structure–activity relationships (QSARs) is to aid in the prediction of effects by determination of the limits of variation in structure that are consistent with the production of a specific toxic effect and define the ways in which alterations in structure influences toxicity. The paradigm followed in the development of QSARs for ecotoxic-endpoints has been successful as a direct result of the availability of in vivo toxicity data in which to build initial QSARs and validate surrogate test systems. However, the lack of quantitative in vivo toxicity data means this paradigm cannot be used in the prediction of human health-effect endpoints. Therefore, a new paradigm, which provides guidance in the use of predictive QSARs for health-effects that serves to circumvent the problems associated with the lack of whole-mammal toxicity data must be established. A scenario is given that provides for the development, standardization, and validation of health-effects related QSARs in the first decade of the 21st century. Due to the structural diversity and sheer number of industrial organic chemicals, assays used to garner health-effects data must be based on quantifiable, rapid, reliable, and inexpensive surrogate endpoints. New ‘biotools’ developed using modern molecular techniques will aid in the circumvention of in vivo health-effects data and provide measurable endpoints, which can be used as surrogates for health-effects endpoints. This has particular application in receptor-mediated toxicity and gene expression. The lack of whole-mammal health-effects data means that the standardization and validation, of these endpoints will be accomplished in novel ways. Databases garnered using modern biotools will allow the derivation of QSARs developed for validated surrogate health-effect endpoints. If QSARs are to be useful in bridging gaps in health-effects data, they must be based on accurate, reproducible data for a robust series of non-congeneric chemicals. The latter applies to both toxicity and descriptor values. Because health-effects are often the result of metabolic activation, if these new QSARs are to be meaningful, validated software for predicting metabolite formation must be incorporated. Lastly, once QSARs and software are developed and validated, they will need to be linked into some type of expert system.

Industrial Organic Chemicals. Starting Materials and Intermediates

The encyclopedia of Industrial Organic Chemicals brings together around 200 detailed and thoroughly edited articles on organic starting materials and intermediates.[...]

Prediction of microbial toxicity of industrial organic chemicals

Aqueous solubility is evaluated as a predictor of microbial toxicity. Experimental toxicity data for activated sludge, methanogens, nitrobacter, and two commercial cultures, Polytox and Microtox were correlated with experimental solubility data for over 70 organic chemicals of diverse molecular structures and congeneric families. The database covered over 8 log units of aqueous solubility and over 6 log units of IC50 values. Statistically significant correlations were found between log (IC50) and log (solubility) for all the microorganisms, with coefficients of correlation ranging from 0.70 to 0.76 at a level of significance of p = 0.0001. An overall correlation was found to be log (IC50, mM/l) = 0.68 log (Solubility, mM/l) - 0.25, with an r2 = 0.756 for nearly 200 data points.

Prediction of microbial toxicity of industrial organic chemicals

Aqueous solubility is evaluated as a predictor of microbial toxicity. Experimental toxicity data for activated sludge, methanogens, nitrobacter, and two commercial cultures, Polytox and Microtox were correlated with experimental solubility data for over 70 organic chemicals of diverse molecular structures and congeneric families. The database covered over 8 log units of aqueous solubility and over 6 log units of IC50 values. Statistically significant correlations were found between log (IC50) and log (solubility) for all the microorganisms, with coefficients of correlation ranging from 0.70 to 0.76 at a level of significance of p = 0.0001. An overall correlation was found to be log (IC50, mM/l) = 0.68 log (Solubility, mM/l) — 0.25, with an r2 = 0.756 for nearly 200 data points.