Structure-Activity Relationships for Para-Substituted Phenols

Schultz, T.W.; Riggin, G.W.; Wesley, S K

doi:10.1007/978-94-009-3937-0_25

Cited by 10 publications

(10 citation statements)

References 14 publications

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“…However, the inhibition generated by an organic compound may also depend on the specific transport system used by the microorganisms. Such a simple model works well for non-ionic molecules, which are the case of alkyl phenols at pH 7.0 [17].…”

Section: Biodegradability Assays With Phenol-acclimated Granular Sludgementioning

confidence: 98%

Inhibition of the acetoclastic methanogenic activity by phenol andalkylphenols

Olguín-Lora

Puig-Grajales

Razo-Flores

2003

Environmental Technology

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Chemical and petrochemical industries are important sources of aromatic pollutants. Petrochemical processes like caustic washing of middle distillates produce the spent caustic liquors highly concentrated in phenol and alkyl phenols. The anaerobic technology is considered a feasible strategy for petrochemical wastewater pre-treatment although high concentrations of phenol could limit its efficiency. The goal of this work was to determine the toxicity of both selected alkyl phenols and a synthetic "spent-caustic phenols mixture" on the acetoclastic Specific Methanogenic Activity (SMA) of unadapted and phenol-adapted granular sludge. Alkyl phenols were responsible for 50% (IC50) and 100% (IC100) inhibition of the SMA at concentrations ranging from 1.6 to 5.0 mM and from 4.1 to 27.5 mM, respectively, for un-adapted granular sludge. In the case of phenol-adapted granular sludge, the inhibitory concentrations ranged from 1.7 to 14.9 mM and from 4.0 to 83.0 for IC50 and IC100, respectively, highlighting the impact of sludge acclimation. The inhibition produced by 2-ethylphenol was more acute compared to phenol and was not reduced by the phenol acclimation process. The IC50 and IC100 values obtained for the synthetic "spent-caustic phenols mixture" were 9.5 mM and 88.4 mM, respectively. The inhibitory concentrations of phenol compounds were closely correlated with compound apolarity (log P), indicating that the lipophilic character of the tested compounds was responsible for their methanogenic toxicity. An inhibition model is confirmed to estimate the IC50 and IC100.

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Section: Biodegradability Assays With Phenol-acclimated Granular Sludgementioning

confidence: 98%

Inhibition of the acetoclastic methanogenic activity by phenol andalkylphenols

Olguín-Lora

Puig-Grajales

Razo-Flores

2003

Environmental Technology

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“…When such a plot (Fig. 3) is made for chemicals that we tested with phenol (Narcosis I1 reference toxicant), however, it is apparent that some physical chemical property such as the ionization term pK,, the Hammett sigma electronic substituent constant (@), or other orthogonal electronic descriptor, in addition to log P , is needed to segregate those chemicals that are and are not additive with phenol, and thus act as polar narcotics [34,48]. A similar situation was observed for those chemicals tested in binary mixtures with 2,4-DNP.…”

Section: Qsarsmentioning

confidence: 99%

Use of Joint Toxic Response to Define the Primary Mode of Toxic Action for Diverse Industrial Organic Chemicals

Broderius

Kahl²,

Hoglund³

1995

Environ Toxicol Chem

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An important aspect of understanding how multiple toxicants jointly act involves defining the primary mode of toxic action for the chemicals of interest. We have explored the use of 96-h acute toxicity tests with juvenile fathead minnows and primarily binary chemical mixtures to define the primary acute mode of toxic action for diverse industrial organic chemicals. Our investigation mainly considered the two special cases of noninteractive joint action known as concentration (simple similar) and response (independent) addition. The different forms of joint toxicity with binary mixtures were graphically illustrated by isoboie diagrams. Designated as the mode of action-specific reference toxicants were 1-octanol, phenol, and 2,4-dinitrophenol. It was observed from binary isobole diagrams that a chemical with a similar primary mode of toxic action to that of a reference toxicant would display a concentration-addition type of joint action with the reference toxicant over the entire mixture ratio range. Dissimilar chemicals with very steep concentration-response curves generally showed an interaction that was less-thanconcentration additive, but consistently demonstrated a joint toxicity that was greater than predicted by the response-addition model. The more-than-concentration additive and complex isoboles that are indicative of interactive toxicity were not commonly observed in our experiments.

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“…As an example of the limitations of their application, Sinks et al [14] showed Characteristics of QSARs Environ. One of the early examples of such optimization was the study of Schultz et al [15] where efforts were made to maximize the structure diversity or, more specifically, the physiochemical space of the dataset while at the same time limiting the number of compounds tested. Chem.…”

Section: Dataset Should Be Both Structurally and Potency Diversementioning

confidence: 99%

“…Toxicol. The net result was a high statistical fitted QSAR (r 2 ϭ 0.911) based on data for 29 para-substituted phenols, which revealed hydrophobicity, electrophilicity, and hydrogen bonding were the important properties in modeling the ecotoxicity (T. pyriformis population growth impairment) of phenols [15]. 22, 2003 601 that QSARs based on either a congeneric series of saturated alcohols or saturated primary amines were not able to predict the toxic potency of aminoalkanols accurately.…”

Section: Dataset Should Be Both Structurally and Potency Diversementioning

confidence: 99%

“…Outliers from a QSAR are chemicals that do not fit the model or are poorly predicted by it [17]. In the example of the phenols [15], the azophenyl-derivative, a known weak acid respiratory uncoupler [18], was an outlier, as was the carboxylderivative of which toxicity was unduly impacted by ionization [19]. There are several potential reasons for a chemical being an outlier from a QSAR.…”

Section: Dataset Should Be Both Structurally and Potency Diversementioning

confidence: 99%

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Essential and Desirable Characteristics of Ecotoxicity Quantitative Structure–activity Relationships

Schultz¹,

Cronin²

2003

Environ Toxicol Chem

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Quantitative structure-activity relationships (QSAR) developed and applied in the prediction of ecotoxic potencies far out number those in other areas, such as health effects. There are yet to be any formal guidelines for the development of ecotoxicological QSARs. Despite this, the depth and breadth of our knowledge of QSARs as they apply to ecotoxicology, especially short-term aquatic toxicity, allow for the formulation of characteristics that appear to be essential and/or desirable for high-quality QSARs. The three components of a QSAR are the biological activity, the property/structural descriptors, and the statistical methodology. Problems may arise from all three components and may be compounded by interactions between them. In an effort to minimize any tribulations associated with development and application of ecotoxic QSARs, a number of essential or desirable characteristics have been identified. Ecotoxicological data used in formulating the QSAR must be reliable, of high quality, and reflect a well-defined and continuous endpoint; this dataset should be diverse both in terms of potency and chemical structure (i.e., property). Descriptors used in formulating the QSAR should be of high quality, reproducible, of a number and type consistent with the endpoint being modeled, and when possible allow for a mechanistic interpretation of the QSAR. The statistical process used in formulating a QSAR should be as rigorous as possible, appropriate for the endpoint being modeled, and allow for the development of as easily interpretable (i.e., transparent) QSARs as possible. The resultant QSAR should be validated, only used within the descriptor space and chemical domain of the model, and relied on in relation to the total weight of evidence; precision of the QSAR and expectations from its application need to be related to the error in the original ecotoxicological and descriptor measurements. Finally, development of QSARs should be through the interaction of a group of multidisciplinary experts.

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Structure-Activity Relationships for Para-Substituted Phenols

Cited by 10 publications

References 14 publications

Inhibition of the acetoclastic methanogenic activity by phenol andalkylphenols

Inhibition of the acetoclastic methanogenic activity by phenol andalkylphenols

Use of Joint Toxic Response to Define the Primary Mode of Toxic Action for Diverse Industrial Organic Chemicals

Essential and Desirable Characteristics of Ecotoxicity Quantitative Structure–activity Relationships

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