Structure-toxicity relationships of selected nitrogenous heterocyclic compounds II. Dinitrogen molecules

From data point timelines to a well curated data set, data mining of experimental data and chemical structure data from scientific articles, problems and possible solutions

The scientific literature is important source of experimental and chemical structure data. Very often this data has been harvested into smaller or bigger data collections leaving the data quality and curation issues on shoulders of users. The current research presents a systematic and reproducible workflow for collecting series of data points from scientific literature and assembling a database that is suitable for the purposes of high quality modelling and decision support. The quality assurance aspect of the workflow is concerned with the curation of both chemical structures and associated toxicity values at (1) single data point level and (2) collection of data points level. The assembly of a database employs a novel "timeline" approach. The workflow is implemented as a software solution and its applicability is demonstrated on the example of the Tetrahymena pyriformis acute aquatic toxicity endpoint. A literature collection of 86 primary publications for T. pyriformis was found to contain 2,072 chemical compounds and 2,498 unique toxicity values, which divide into 2,440 numerical and 58 textual values. Every chemical compound was assigned to a preferred toxicity value. Examples for most common chemical and toxicological data curation scenarios are discussed.

Chemical and biological characterization of wastewater generated from hydrothermal liquefaction of Spirulina

Hydrothermal liquefaction (HTL) is an attractive method for converting wet biomass into petroleum-like biocrude oil that can be refined to make petroleum products. This approach is advantageous for conversion of low-lipid algae, which are promising feedstocks for sustainable large-scale biofuel production. As with natural petroleum formation, the water in contact with the produced oil contains toxic compounds. The objectives of this research were to: (1) identify nitrogenous organic compounds (NOCs) in wastewater from HTL conversion of Spirulina; (2) characterize mammalian cell cytotoxicity of specific NOCs, NOC mixture, and the complete HTL wastewater (HTL-WW) matrix; and (3) investigate mitigation measures to reduce toxicity in HTL-WW. Liquid-liquid extraction and nitrogen-phosphorus detection was used in conjunction with gas chromatography-mass spectrometry (GC-MS), which detected hundreds of NOCs in HTL-WW. Reference materials for nine of the most prevalent NOCs were used to identify and quantify their concentrations in HTL-WW. Mammalian cell cytotoxicity of the nine NOCs was quantified using a Chinese hamster ovary (CHO) cell assay, and the descending rank order for cytotoxicity was 3-dimethylamino-phenol > 2,2,6,6-tetramethyl-4-piperidone > 2,6-dimethyl-3-pyridinol > 2-picoline > pyridine > 1-methyl-2-pyrrolidinone > σ-valerolactam > 2-pyrrolidinone > ε-caprolactam. The organic mixture extracted from HTL-WW expressed potent CHO cell cytotoxic activity, with a LC(50) at 7.5% of HTL-WW. Although the toxicity of HTL-WW was substantial, 30% of the toxicity was removed biologically by recycling HTL-WW back into algal cultivation. The remaining toxicity of HTL-WW was mostly eliminated by subsequent treatment with granular activated carbon.

Structure-toxicity relationships for aminoalkanols: a comparison with alkanols and alkanamines

The relative toxicity (log IGC50(-1)) of 49 selected aliphatic amines and aminoalkanols was evaluated in the static Tetrahymena pyriformis population growth impairment assay. Excess toxicity, indicated by potency greater than predicted for non-polar narcotic alkanols, was associated with both classes of test chemicals. Moreover, the aminoalkanols were found to be more toxic than the corresponding alkanamines. A high quality 1-octanol/water partition coefficient (log K(ow)) dependent quantitative structure-activity relationship (QSAR), logIGC50(-1) = 0.78 (log K(ow)) - 1.42; r2 = 0.934, was developed for alkanamines. This QSAR represented the amine narcosis mechanism of toxic action. No quality QSAR was developed for the aminoalkanols. However, several structure-toxicity features were observed for this class of chemicals. Two-amino-1-hydroxy derivatives being more toxic than the corresponding derivatives, where the amino and hydroxy moieties were separated by methylene groups. Hydrocarbon branching next to the amino moiety resulted in decreased toxicity. Aminoalkanol alters lipid metabolism in T. pyriformis.

A novel QSAR approach for estimating toxicity of phenols

Toxicity values (log IGC50(-1)) for 60 phenols tested in the 2-d static population growth inhibition assay with the ciliate Tetrahymena pyriformis were tabulated. Each chemical was selected so the series formed uniform coverage of the hydrophobicity/ionization surface. A high quality hydrophobicity-dependent (log Kow) structure-toxicity relationship (log IGC50(-1) = 0.741 (log Kow)-1.433; n = 17; r2 = 0.970; s = 0.134; F = 486.55; Pr > F = 0.0001) was developed for phenols with pKa values > 9.8. Similarly, separate hydrophobicity-dependent relationships were developed for phenols with pKa values of 4.0, 5.1, 6.3, 7.5, and 8.7. Comparisons of intercepts and slopes, respectively, revealed phenols with pKa values of 6.3 to be the most toxic and the least influenced by hydrophobicity. These relationships were reversed for the more acidic and basic phenols. Plots of toxicity versus pKa for nitro-substituted phenols and phenols with log Kow values of either 1.75 or 2.50 further demonstrated bilinearity between toxicity and ionization. In an effort to more accurately model the relationship between toxicity and ionization, the absolute value function [6.3-pKa] was used to model ionization affects for derivatives with pKa values between 0 and 9.8. For derivatives with pKa value > 9.8, a value of 3.50 was used to quantitate ionization effects. The use of log Kow in conjunction with this modified pKa (delta pKa) resulted in the structure-toxicity relationship (log IGC(50)-1 = 0.567 (log Kow)-0.226 (delta pKa)-0.079; n = 54; r2 = 0.926; s = 0.215; F = 321.06; Pr > F = 0.0001). Derivatives with a nitro group in the 4-position typically did not model well with the above equation.

Quantitative structure-toxicity relationships and volume fraction analyses for selected esters

The acute toxicity of aliphatic and aromatic mono and diesters in two eucaryotic organisms was compared. The test systems were the static 2-d Tetrahymena pyriformis 50% population growth impairment (IGC50(-1)) assay, and the flow-through 4-d Pimephales promelas 50% mortality (LC50(-1)) assay. In ciliates, esters act via the nonpolar narcosis mechanism of toxic action. This was indicated by: the high quality 1-octanol/water partition coefficient (log Kow) dependent quantitative structure-activity relationship (QSAR), log IGC50(-1) = 0.79 (log Kow) - 1.93, n = 15, r2 = 0.945, s = 0.22, f = 222.37 Pr > f = 0.001); volume fraction (Vf) (0.8e-02); and "a" coefficient (0.3) which are not different from other nonpolar narcotics. In vivo hydrolysis in Tetrahymena appears to be insignificant. However, in fish, presumably because of more active esterases, in vivo hydrolysis is significant and leads to greater toxicity of esters than observed for nonpolar narcotics. Moreover, it leads to a unique high quality QSAR, log LC50(-1) = 0.64 (log Kow) - 0.64, n = 14, r2 = 0.945, s = 0.22, f = 207.08, Pr > f = 0.0001). Due to in vivo hydrolysis, a nonreducing concentration gradient is formed between water and fish. Therefore, the fish take up more toxicant as compared to a situation that leads to thermodynamic equilibrium. Additional information about the mechanism of ester toxicity in fish was gained by applying corrections for hydrolysis in volume fraction analyses. The corrected Vf (0.6e-02) is very close to the one found for nonpolar narcotics (0.7e-02).(ABSTRACT TRUNCATED AT 250 WORDS)

Structure-toxicity relationships for alkanones and alkenones

The relative toxicity (log IGC-1(50)) of 54 selected alkanones, both aliphatic and aromatic, as well as, alkenones and alkynones was evaluated in the static Tetrahymena pyriformis population growth assay. Excess toxicity, an indicator of bioreactivity, was associated only with the alpha-beta unsaturated alkenones and alkynones. Moreover, the alkynones were found to be more toxic than corresponding alkenones. A high quality 1-octanol/water partition coefficient (log Kow) dependent structure-toxicity relationship, log IGC-1(50) = 0.86 (log Kow) - 2.27; r2 = 0.955, was developed for alkanones. This QSAR represented the nonpolar narcosis mechanism of toxic action. Toxicity of alkenones was predicted by the highest-occupied-molecular-orbital energy (HOMO), log IGC-1(50) = -3.474 (HOMO) -35.357; r2 = 0.897, and the difference between HOMO and the lowest-unoccupied-molecular-orbital energy (LUMO), log IGC-1(50) = -3.559 (HOMO-LUMO gap) - 36.106; r2 = 0.903. The alpha-beta unsaturated ketones are considered soft electrophiles. Moreover, the toxicity of the aliphatic alkanones and alkenones was predicted by log Kow and LUMO, log IGC-1(50) = 0.69 (log Kow) - 2.55 (LUMO) + 0.05; r2 = 0.852.

Structure activity relationships of selected naphthalene derivatives

Twenty-two derivatives of naphthalene were assayed under an acute static regime with biological activity being monitored as population growth of Tetrahymena pyriformis. Activity varied over one log unit. Substituent constant structure-activity analyses revealed the model, log BR = 0.282Ha + 0.352 pi + 0.692F + 0.3341Xvsub - 0.326R + 0.027, to be best and to account for 85% of the variation in log BR (BR, biological response; Ha, hydrogen acceptance; pi, hydrophobic substituent constant; F, polar electronic substituent constant, 1Xvsub, substituent molar connectivity index; R, resonance electronic substituent constant). The Ha and pi parameters are the most important, accounting for 71% of the log BR variability.