New Plant Species Showing Antiprotozoian Activity.

The effects of extracts of ten plant species from Russia and five species from Vietnam on the growth and survival of ciliates Tetrahymena pyriformis were studied. T. pyriformis belongs to the subkingdom Protozoa, which also includes pathogens of protozoan infections. Extraction of dried plants was carried out with acidic and alkaline aqueous solutions, as well as with an aqueous ethanol. Various amounts of extracts were added to the ciliate cells, and the number of cells survived after incubation for 1 and 24 h was recorded. We found that our samples of several plants, including wormwood, harmala, and licorice, similarly to those studied earlier, exhibit antiprotozoal activity, which may indicate that the secondary metabolites are the same in plants from different regions. Using the ciliate T. pyriformis as a model organism, the presence of antiprotozoal activity in extracts of lilac, chondrilla, cinquefoil, hop, and elm was shown for the first time.

QSAR analysis of the acute toxicity of avermectins towards Tetrahymena pyriformis.

Avermectins have been effectively used in medicine, veterinary medicine, and agriculture as antiparasitic agents for many years. However, there are still no reliable data on the main ecotoxicological characteristics of most individual avermectins. Although many QSAR models have been proposed to describe the acute toxicity of organic compounds towards Tetrahymena pyriformis (T. pyriformis), avermectins are outside the applicability domain of these models. The influence of the molecular structures of various organic compounds on the acute toxicity towards T. pyriformis was studied using the OCHEM web platform (https://ochem.eu). A data set of 1792 toxicants was used to create models. The QSAR (Quantitative Structure-Activity Relationship) models were developed using the molecular descriptors Dragon, ISIDA, CDK, PyDescriptor, alvaDesc, and SIRMS and machine learning methods, such as Least Squares Support Vector Machine and Transformer Convolutional Neural Network. The HYBOT descriptors and Random Forest were used for a comparative QSAR investigation. Since the best predictive ability was demonstrated by the Transformer Convolutional Neural Network model, it was used to predict the toxicity of individual avermectins towards T. pyriformis. During a structural interpretation of the developed QSAR model, we determined the significant molecular transformations that increase and decrease the acute toxicity of organic compounds.

Assessment of the Cytotoxicity of Peptide Modifications of Doxorubicin on Tetrahymena pyriformis.

The cytotoxicity of doxorubicin (Dox) and its peptide modifications Z-Gly-Pro-Dox and Boc-Gly-Pro-Dox were studied. Tetrahymena pyriformis was used as a test system, which made it possible, due to the short life cycle and high reproduction rate of ciliates, to trace their response to the effects of toxicants over several generations. It was found that peptide modification of the Dox molecule markedly reduces its cytotoxic and cytostatic effect. The Z-Gly-Pro-Dox modification has less cytotoxic and cytostatic effect compared to Boc-Gly-Pro-Dox. When determining the ability of drugs (at a concentration of 100 µM) to prevent bacterial contamination of samples, it was shown that the smallest degree of overgrowth was recorded in the presence of Dox (OD600nm 81.1). Boc-Gly-Pro-Dox also had a bacteriostatic effect, though less pronounced (OD600nm 93.8). The degree of overgrowth in the presence of Z-Gly-Pro-Dox was close to that of distilled water. The results obtained on ciliates did not contradict the data obtained in similar studies on mice.

Cytoprotective effect of ethyl acetate fraction from Ephedra fragilis on H2O2-induced oxidative damage in Tetrahymena pyriformis.

The main purpose of the present study was to investigate the ability of ethyl acetate fraction (EAF) from Ephedra fragilis to function as a protective agent against hydrogen peroxide induced oxidative damage in Tetrahymena pyriformis. The cells were preincubated with EAF (50-200 µg/mL) or ascorbic acid (50 µg/mL) for 24 h, followed by incubation with 50% H2O2 inhibitory concentration for 48 h. Cell viability was assessed using trypan exclusion method. Cell morphology and mobility, antioxidant enzymes activities (catalase (CAT), superoxide dismutase (SOD) and glutathione reductase (GR)), malondialdehyde (MDA) and protein carbonyl (PCO) levels, DNA fragmentation and metabolic enzymes activities (succinate dehydrogenase (SDH) and NADPH-cytochrome c reductase (NCCR)) were investigated. Our results indicate that, pretreatment of T. pyriformis cells with EAF improved the cell viability, restored normal cell mobility and morphology, decreased the levels of both MDA and PCO level, prevent DNA fragmentation and enhanced the activity of antioxidant (CAT, SOD and GR) and metabolic (SDH and NCCR) enzymes in H2O2 damaged cells. In conclusion, these results suggest for the first time that E. fragilis is a promising source of natural antioxidants, that could offer protection against oxidative stress and should be further exploited for its use in clinical medicine.

Bacillus spp. metabolites are effective in eradicating Aedes aegypti (Diptera: Culicidae) larvae with low toxicity to non-target species.

The growing spread of dengue, chikungunya and Zika viruses demand the development of new and environmentally safe control methods for their vector, the mosquito Aedes aegypti. This study aims to find novel larvicidal agents from mutualistic (endophytic and rhizospheric) or edaphic bacteria that have no action against non-target organisms. Eleven out of the 254 bacterial strains tested were able to kill Ae. aegypti larvae. Larvicidal activity did not depend on presence of cells, since culture supernatants or crude lipopeptide extracts (CLEs) killed the larvae. Bacillus safensis BacI67 and Bacillus paranthracis C21 supernatants were the best performing supernatants, displaying the lowest lethal concentrations (LC50 = 31.11 µL/mL and 45.84 µL/mL, respectively). Bacillus velezensis B64a and Bacillus velezensis B15 produced the best performing CLEs (LC50 = 0.11 mg/mL and 0.12 mg/mL, respectively). Mass spectrometry analysis of CLEs detected a mixture of surfactins, iturins, and fengycins. The samples tested were weakly- or non-toxic to mammalian cells (RAW 264.7 macrophages and VERO cells) and non-target organisms (Caenorhabditis elegans, Galleria mellonella, Scenedesmus obliquus, and Tetrahymena pyriformis) - especially B. velezensis B15 CLE. The biosynthetic gene clusters related to secondary metabolism identified by whole genome sequencing of the four best performing bacteria strains revealed clusters for bacteriocin, beta-lactone, lanthipeptide, non-ribosomal peptide synthetases, polyketide synthases (PKS), siderophores, T3PKS, type 1 PKS-like, terpenes, thiopeptides, and trans-AT-PKS. Purification of lipopeptides may clarify the mechanisms by which these extracts kill Ae. aegypti larvae.

Modelling quantitative structure activity-activity relationships (QSAARs): auto-pass-pass, a new approach to fill data gaps in environmental risk assessment under the REACH regulation.

Reviewing the toxicological literature for over the past decades, the key elements of QSAR modelling have been the mechanisms of toxic action and chemical classes. As a result, it is often hard to design an acceptable single model for a particular endpoint without clustering compounds. The main aim here was to develop a Pass-Pass Quantitative Structure-Activity-Activity Relationship (PP QSAAR) model for direct prediction of the toxicity of a larger set of compounds, combing the application of an already predicted model for another species, and molecular descriptors. We investigated a large acute toxicity data set of five aquatic organisms, fish, Daphnia magna, and algae from the VEGA-Hub, as well as Tetrahymena pyriformis and Vibrio fischeri. The statistical quality of the models encouraged us to consider this alternative for the prediction of toxicity using interspecies extrapolation QSAAR models without regard to the toxicity mechanism or chemical class. In the case of algae, the use of activity values from a second species did not improve the models. This can be attributed to the weak interspecies relationships, due to different aquatic toxicity mechanisms in species.

Screening Snake Venoms for Toxicity to Tetrahymena Pyriformis Revealed Anti-Protozoan Activity of Cobra Cytotoxins.

Snake venoms possess lethal activities against different organisms, ranging from bacteria to higher vertebrates. Several venoms were shown to be active against protozoa, however, data about the anti-protozoan activity of cobra and viper venoms are very scarce. We tested the effects of venoms from several snake species on the ciliate Tetrahymena pyriformis. The venoms tested induced T. pyriformis immobilization, followed by death, the most pronounced effect being observed for cobra Naja sumatrana venom. The active polypeptides were isolated from this venom by a combination of gel-filtration, ion exchange and reversed-phase HPLC and analyzed by mass spectrometry. It was found that these were cytotoxins of the three-finger toxin family. The cytotoxins from several cobra species were tested and manifested toxicity for infusorians. Light microscopy revealed that, because of the cytotoxin action, the infusorians' morphology was changed greatly, from teardrop-like to an almost spherical shape, this alteration being accompanied by a leakage of cell contents. Fluorescence microscopy showed that the fluorescently labelled cytotoxin 2 from cobra N. oxiana was localized mainly at the membrane of killed infusorians, indicating that cytotoxins may kill T. pyriformis by causing membrane rupture. This work is the first evidence of the antiprotozoal activity of cobra venom cytotoxins, as demonstrated by the example of the ciliate T. pyriformis.

A Library of Thiazolidin-4-one Derivatives as Protein Tyrosine Phosphatase 1B (PTP1B) Inhibitors: An Attempt To Discover Novel Antidiabetic Agents.

Protein tyrosine phosphatase 1B (PTP1B) is an important target for the treatment of diabetes. A series of thiazolidin-4-one derivatives 8-22 was designed, synthesized and investigated as PTP1B inhibitors. The new molecules inhibited PTP1B with IC50 values in the micromolar range. 5-(Furan-2-ylmethylene)-2-(4-nitrophenylimino)thiazolidin-4-one (17) exhibited potency with a competitive type of enzyme inhibition. structure-activity relationship studies revealed various structural facets important for the potency of these analogues. The findings revealed a requirement for a nitro group-including hydrophobic heteroaryl ring for PTP1B inhibition. Molecular docking studies afforded good correlation with experimental results. H-bonding and π-π interactions were responsible for optimal binding and effective stabilization of virtual protein-ligand complexes. Furthermore, in-silico pharmacokinetic properties of test compounds predicted their drug-like characteristics for potential oral use as antidiabetic agents.Additionally, a binding site model demonstrating crucial pharmacophoric characteristics influencing potency and binding affinity of inhibitors has been proposed, which can be employed in the design of future potential PTP1B inhibitors.

An Electronic-structure Informatics Study on the Toxicity of Alkylphenols to Tetrahymena pyriformis.

Alkylphenols (APs) dissolved in water are known to be toxic to animals including humans. In this study, regression models describing the toxicity of the 33 AP molecules were investigated for reproducing and thereby making it possible to predict a quantitative structure-activity relationship (QSAR). For this purpose, we tried to derive regression models for the experimental IGC50 (growth inhibition concentration at 50 %) to Tetrahymena pyriformis by using various descriptor sets consisting of electronic and shape descriptors. By applying the multiple linear regression (MLR) analysis, it was successful to derive a quantitative regression model for the IGC50 values. In this analysis, the size parameters of the molecules were found important, suggesting that bulky molecules should be less toxic. We could also obtain, when the size descriptors were excluded, an MLR model indicating that the electron affinity (EA) should be important, which is consistent with the previous QSAR studies. Through the correlation analysis among the descriptors, it was shown that, in the present set of molecules, EA and a size parameter are highly correlated. Since EA was calculated to be negative, indicating that the related process would be energetically unfavourable, it was concluded that the size of the molecules should be a dominant factor determining IGC50 . This implies that a molecular recognition process would play a critical role in the mode of action for the toxicity.

Prediction of chemical toxicity to Tetrahymena pyriformis with four-descriptor models.

A quantitative structure-toxicity relationship (QSTR) model based on four descriptors was successfully developed for 1163 chemical toxicants against Tetrahymena pyriformis by applying general regression neural network (GRNN). The training set consisting of 600 organic compounds was used to train GRNN models that were evaluated with the test set of 563 compounds. For the optimal GRNN model, the training set possesses the coefficient of determination R2 of 0.86 and root mean square (rms) error of 0.41, and the test set has R2 of 0.80 and rms of 0.41. Investigated results indicate that the optimal GRNN model is accurate, although the GRNN model has only four descriptor and more samples in the test set.

Chlorination and bromination of 1,3-diphenylguanidine and 1,3-di-o-tolylguanidine: Kinetics, transformation products and toxicity assessment.

This works investigates the chlorination and bromination of two rubber and polymer related chemicals, which have emerged as relevant water contaminants, i.e. 1,3-di-o-tolylguanidine (DTG) and 1,3-diphenylguanidine (DPG). Kinetic constants at different pH values were obtained and modelled, taking into account the pKa values of DTG/DPG and HClO, showing that the maximum reaction rate (kapp > 104 M-1 s-1) is obtained at pH values 8.8 for DPG and 9.1 for DTG. Bromination is also very fast, although unlike chlorination, deviation from the model was observed at neutral pH, which was attributed to formation of metastable transformation product (TP). A total of 35 TPs, corresponding to halogenation, hydroxylation, formation of monophenylguanidine derivatives and cyclization reactions, were tentatively identified. Furthermore it was found that chloroform can be formed up to a 25% molar yield, while dichloroacetonitrile was formed into less than a 3% yield. Several ecotoxicological endpoints were predicted by quantitative structure-activity relationship models (QSAR) for the TPs, some of which were predicted to be more toxic than DPG/DTG. Also a chlorinated solution investigated by a Vibrio Fisheri acute toxicity test, confirmed that toxicity increases with chlorination.

Effects of Gonadotropin-Releasing Hormone (GnRH) and Its Analogues on the Physiological Behaviors and Hormone Content of Tetrahymena pyriformis.

The unicellular Tetrahymena distinguishes structure-related vertebrate hormones by its chemosensory reactions. In the present work, the selectivity of hormone receptors was evaluated by analyzing the effects of various gonadotropin-releasing hormone (GnRH) analogs (GnRH-I, GnRH-III) as well as truncated (Ac-SHDWKPG-NH2) and dimer derivatives ([GnRH-III(C)]2 and [GnRH-III(CGFLG)]2) of GnRH-III on (i) locomotory behaviors, (ii) cell proliferation, and (iii) intracellular hormone contents of Tetrahymena pyriformis. The migration, intracellular hormone content, and proliferation of Tetrahymena were investigated by microscope-assisted tracking analysis, flow cytometry, and a CASY TT cell counter, respectively. Depending on the length of linker sequence between the two GnRH-III monomers, the GnRH-III dimers had the opposite effect on Tetrahymena migration. [GnRH-III(CGFLG)]2 dimer had a slow, serpentine-like movement, while [GnRH-III(C)]2 dimer had a rather linear swimming pattern. All GnRH-III derivatives significantly induced cell growth after 6 h incubation. Endogenous histamine content was uniformly enhanced by Ac-SHDWKPG-NH2 and GnRH-III dimers, while some differences between the hormonal activities of GnRHs were manifested in their effects on intracellular levels of serotonin and endorphin. The GnRH peptides could directly affect Tetrahymena migration and proliferation in a structure-dependent manner, and they could indirectly regulate these reactions by paracrine/autocrine mechanisms. Present results support the theory that recognition ability and selectivity of mammalian hormone receptors can be deduced from a phylogenetically ancient level like the unicellular Tetrahymena.

Evaluation of phenylethylamine type entactogens and their metabolites relevant to ecotoxicology - a QSAR study.

The impact of the selected entactogens and their o-quinone metabolites on the environment was explored in QSAR studies by the use of predicted molecular descriptors, ADMET properties and environmental toxicity parameters, i.e., acute toxicity in Tetrahymena pyriformis (TOX_ATTP) expressed as Th_pyr_pIGC50/mmol L-1, acute toxicity in Pimephales promelas, the fathead minnow (TOX_FHM) expressed as Minnow LC50/mg L-1, the acute toxicity in Daphnia magna (TOX_DM) expressed as Daphnia LC50/mg L-1 and bioconcentration factor (BCF). The formation of corresponding o-quinones via benzo-dioxo-lone ring, O-demethylenation was predicted as the main metabolic pathway for all entactogens except for 1-(2,2-difluorobenzo[d][1,3]dioxol-5-yl)propan-2-amine (DiFMDA). The least favourable ADMET profile was revealed for N-(1-(benzo[d][1,3]dioxol-5-yl)propan-2-yl)-O-methylhydroxylamine (MDMEO). QSAR studies revealed significant linear correlations between MlogP of entactogens and MlogP of o-quinone metabolites (R = 0.99), and Th_pyr_pIGC50/mmol L-1 (R = 0.94), also their MlogPs with Minnow_LC50/mg L-1 (R = 0.80 and R = 0.78), BCF (R = 0.86 and R = 0.82) and percentage of o-quinones' yields (R = 0.73 and R = 0.80). Entactogens were predicted as non-biodegradable molecules, whereas the majority of their o-quinones were biodegradable.

A model of atomic compressibility and its application in QSAR domain for toxicological property prediction.

A model for computing the atomic compressibility (ß) based on two periodic descriptors, namely, absolute radius (r) and atomic electrophilicity index (ω), is proposed as[Formula: see text]The ansatz is invoked to compute compressibilities of atoms of 57 elements of the periodic table. The computed atomic data exhibits all sine qua non of periodic properties. Further, the concept group compressibility (Gß) is also established invoking additivity property using some molecules with different functional groups and consequently utilized in correlating with molecular polarizability. Since toxicity prediction is an imperative need of the hour, chemical reactivity descriptors are of paramount importance in the study of toxicological behaviour along with a lot of other molecular reactivity studies within a Quantitative Structure-Activity Relationship (QSAR) context. Hence, this quantity is applied in the modelling of toxicological property through QSAR and a comprehensive study is performed in an effort to investigate and validate the application of compressibility in determining its toxicological power. Consequently, varied 209 organic molecules are selected for studying the toxic effect on Tetrahymena pyriformis. A QSAR model is constructed in terms of compressibility which offers a superior prediction of toxicity independently without adopting additional descriptors or properties as in some other QSAR studies. Graphical abstract.

Effect of difenoconazole fungicide on physiological responses and ultrastructural modifications in model organism Tetrahymena pyriformis.

The continuous and extensive use of pesticides, particularly in the field of agriculture, leads to contamination of all ecosystems (water, soil, and atmosphere). Among pesticides, fungicides constitute a larger group whose impact on the environment are still poorly studied. Difenoconazole belongs to triazole group of fungicides having high photochemical stability and have low biodegradability, which makes them persistent in water bodies. The present study focuses on the physiological and cytotoxic impact of difenoconazole fungicide on ciliated protozoa, Tetrahymena pyriformis with reference to growth, morphology, behaviour and its generation time. Morphological studies showed changes in the shape and size of T. pyriformis. Our result showed an inhibitory effect on population growth of T. pyriformis and the IC50 concentration was found to be 6.8 µg mL-1.The numbers of generations decreased and generation time was found to be extended in a concentration and time dependent manner. Difenoconazole caused significant depletion in phagocytic activity and also ultra-structural changes were observed by Transmission electron microscopy (TEM) analysis. The results indicate that the Tetrahymena toxicity assay could be used as a complementary system to rapidly elucidate the cytotoxic potential of fungicide.

QSAR Models for Predicting Aquatic Toxicity of Esters Using Genetic Algorithm-Multiple Linear Regression Methods.

AIM AND OBJECTIVE: Esters are of great importance in industry, medicine, and space studies. Therefore, studying the toxicity of esters is very important. In this research, a Quantitative Structure-Activity Relationship (QSAR) model was proposed for the prediction of aquatic toxicity (log 1/IGC50) of aliphatic esters towards Tetrahymena pyriformis using molecular descriptors. MATERIALS AND METHODS: A data set of 48 aliphatic esters was separated into a training set of 34 compounds and a test set of 14 compounds. A large number of molecular descriptors were calculated with Dragon software. The Genetic Algorithm (GA) and Multiple Linear Regression (MLR) methods were used to select the suitable descriptors and to generate the correlation models that relate the chemical structural features to the biological activities. RESULTS: The predictive powers of the MLR models are discussed by using Leave-One-Out (LOO) cross-validation and external test set. The best QSAR model is obtained with R2 value of 0.899, Q2 LOO =0.928, F=137.73, RMSE=0.263. CONCLUSION: The predictive ability of the GA-MLR model with two selected molecular descriptors is satisfactory and it can be used for designing similar group and predicting of toxicity (log 1/IGC50) of ester derivatives.

Comparison of modes of action among different trophic levels of aquatic organisms for pesticides and medications based on interspecies correlations and excess toxicity: Theoretical consideration.

Pesticides and medications have adverse effects in non-target organisms that can lead to different modes of action (MOAs). However, no study has been performed to compare the MOAs between different levels of aquatic species. In this study, theoretical equations of interspecies relationship and excess toxicity have been developed and used to investigate the MOAs among fish, Daphnia magna, Tetrahymena pyriformis and Vibrio fischeri for pesticides and medications. The analysis on the interspecies correlation and excess toxicity suggested that fungicides, herbicides and medications share the similar MOAs among the four species. On the other hand, insecticides share different MOAs among the four species. Exclusion of insecticides from the interspecies correlation can significantly improve regression coefficient. Interspecies relationship is dependent not only on the difference in interaction of chemicals with the target receptor(s), but also on the difference in bio-uptake between two species. The difference in physiological structures will result in the difference in bioconcentration potential between two different trophic levels of organisms. Increasing of molecular size or hydrophobicity will increase the toxicity to higher level of aquatic organisms; on the other hand, chemical ionization will decrease the toxicity to higher level organisms. Hydrophilic compounds can more easily pass through cell membrane than skin or gill, leading to greater excess toxicity to Vibrio fischeri, but not to fish and Daphnia magna.

Estimation of the Toxicity of Different Substituted Aromatic Compounds to the Aquatic Ciliate Tetrahymena pyriformis by QSAR Approach.

Nowadays, quantitative structure⁻activity relationship (QSAR) methods have been widely performed to predict the toxicity of compounds to organisms due to their simplicity, ease of implementation, and low hazards. In this study, to estimate the toxicities of substituted aromatic compounds to Tetrahymena pyriformis, the QSAR models were established by the multiple linear regression (MLR) and radial basis function neural network (RBFNN). Unlike other QSAR studies, according to the difference of functional groups (−NO2, −X), the whole dataset was divided into three groups and further modeled separately. The statistical characteristics for the models are obtained as the following: MLR: n = 36, R² = 0.829, RMS (root mean square) = 0.192, RBFNN: n = 36, R² = 0.843, RMS = 0.167 for Group 1; MLR: n = 60, R² = 0.803, RMS = 0.222, RBFNN: n = 60, R² = 0.821, RMS = 0.193 for Group 2; MLR: n = 31 R² = 0.852, RMS = 0.192; RBFNN: n = 31, R² = 0.885, RMS = 0.163 for Group 3, respectively. The results were within the acceptable range, and the models were found to be statistically robust with high external predictivity. Moreover, the models also gave some insight on those characteristics of the structures that most affect the toxicity.

Development of thresholds of excess toxicity for environmental species and their application to identification of modes of acute toxic action.

The acute toxicity of organic pollutants to fish, Daphnia magna, Tetrahymena pyriformis, and Vibrio fischeri was investigated. The results indicated that the Toxicity Ratio (TR) threshold of log TR =1, which has been based on the distribution of toxicity data to fish, can also be used to discriminate reactive or specifically acting compounds from baseline narcotics for Daphnia magna and Vibrio fischeri. A log TR=0.84 is proposed for Tetrahymena pyriformis following investigation of the relationships between the species sensitivity and the absolute averaged residuals (AAR) between the predicted baseline toxicity and the experimental toxicity. Less inert compounds exhibit relatively higher toxicity to the lower species (Tetrahymena pyriformis and Vibrio fischeri) than the higher species (fish and Daphnia magna). A greater number of less inert compounds with log TR greater than the thresholds was observed for Tetrahymena pyriformis and Vibrio fischeri. This may be attributed to the hydrophilic compounds which may pass more easily through cell membranes than the skin or exoskeleton of organisms and have higher bioconcentration factors in the lower species, leading to higher toxicity. Most of classes of chemical associated with excess toxicity to one species also exhibited excess toxicity to other species, however, a few classes with excess toxicity to one species exhibiting narcotic toxicity to other species and thus may have different MOAs between species. Some ionizable compounds have log TR much lower than one because of the over-estimated log KOW. The factors that influence the toxicity ratio calculated from baseline level are discussed in this paper.

Prediction of aquatic toxicity of benzene derivatives using molecular descriptor from atomic weighted vectors.

Several descriptors from atom weighted vectors are used in the prediction of aquatic toxicity of set of organic compounds of 392 benzene derivatives to the protozoo ciliate Tetrahymena pyriformis (log(IGC50)-1). These descriptors are calculated using the MD-LOVIs software and various Aggregation Operators are examined with the aim comparing their performances in predicting aquatic toxicity. Variability analysis is used to quantify the information content of these molecular descriptors by means of an information theory-based algorithm. Multiple Linear Regression with Genetic Algorithms is used to obtain models of the structure-toxicity relationships; the best model shows values of Q2=0.830 and R2=0.837 using six variables. Our models compare favorably with other previously published models that use the same data set. The obtained results suggest that these descriptors provide an effective alternative for determining aquatic toxicity of benzene derivatives.