3D-QSAR studies on the toxicity of substituted benzenes to Tetrahymena pyriformis: CoMFA, CoMSIA and VolSurf approaches

Classification Model of Pesticide Toxicity in Americamysis bahia Based on Quantum Chemical Descriptors

A set of quantum chemical descriptors (molecular polarization, heat capacity, entropy, Mulliken net charge of the most positive hydrogen atom, APT charge of the most negative atom and APT charge of the most positive atom with hydrogen summed into heavy atoms) was successfully used to establish the classification models for the toxicity pLC50 of pesticides in Americamysis bahia. The optimal random forest model (Class Model A) yielded predictive accuracy of 100% (training set of 217 pesticides), 95.8% (test set of 72 pesticides) and 99.0% (total set of 289 pesticides), which were very satisfactory, compared with previous classification models reported for the toxicity of compounds in aquatic organisms. Therefore, it is reasonable to apply the quantum chemical descriptors associated with molecular structural information on molecular bulk, chemical reactivity and weak interactions, to develop classification models for the toxicity pLC50 of pesticides in A. bahia.

Risk mitigation strategy and mechanism analysis of neonicotinoid pesticides on earthworms

Neonicotinoid insecticides (NNIs) are a new class of widely used insecticides with certain risks to non-target organisms, like earthworms. The gray correlation method was used to calculate the comprehensive risk effect value of acute toxicity (LC50) and bioaccumulation (logKow) of NNIs on earthworms. A comprehensive effects three-dimensional quantitative structure-activity relationship (3D-QSAR) model was constructed, using NNIs molecular structures and the comprehensive effect value as the independent and dependent variables, respectively. One of the representatives guadipyr (GUA) was selected as the template molecule for the molecular design and modification. A total of 63 NNIs alternatives were designed with a reduced comprehensive value higher than 10%, and as high as 42%. After screening, 15 NNIs alternatives were screened with decreased acute toxicity to earthworms, bioaccumulation effects and improved functional property. The calculated primary acute risk quotient of earthworms shows that the designed NNIs alternatives have lower earthworm risks (reduction of 70.48-99.99%). Results also found that the electronic, geometric and topological parameters of NNIs are the key descriptors that affect NNIs alternatives' toxicity. The number of hydrophobic interaction amino acid residues in NNIs molecules also contributes to the acute toxicity and the bioaccumulation of NNIs alternatives on earthworms. This study aims to design and screen functionally improved and environmentally friendly NNIs alternatives that have low risk to earthworms and provide theoretical methods and new ideas for the risk control and development of pesticides represented by NNIs.

Multi-process regulation of novel brominated flame retardants: Environmentally friendly substitute design, screening and environmental risk regulation

Novel brominated flame retardants (NBFRs), one of the most widely used synthetic flame-retardant materials, have been considered as a new group of pollutants that potentially affect human health. To overcome the adverse effects of NBFRs, a systematic approach for molecular design, screening, and performance evaluation was developed to generate environmentally friendly NBFR derivatives with unaltered functionality. In the present study, the features of NBFRs (long-distance migration, biotoxicity, bioenrichment, and environmental persistence) were determined and characterized by the multifactor comprehensive characterization method with equal weight addition, and the similarity index analysis (CoMSIA) model was constructed. Based on the three-dimensional equipotential diagram of the target molecule 2-ethylhexyl tetrabromobenzoic acid (TBB), 23 TBB derivatives were designed. Of these, 22 derivatives with decreased environmental impact and unaltered functional properties (i.e., flame retardancy and stability) were selected using 3D-QSAR models and density functional theory methods. The health risks of these derivatives to humans were assessed by toxicokinetic analysis; the results narrowed down the number of candidates to three (Derivative-7, Derivative-10, and Derivative-15). The environmental impact of these candidates was further evaluated and regulated in the real-world environment by using molecular dynamics simulation assisted by the Taguchi experimental design method. The relationship between the binding effects and the nonbonding interaction resultant force (TBB derivatives-receptor proteins) was also studied, and it was found that the larger the modulus of the binding force, the stronger the binding ability of the two. This finding indicated that the environmental impact of the designed NBFR derivatives was decreased. The present study aimed to provide a new idea and method for designing NBFR substitutes and to provide theoretical support for restraining the potential environmental risks of NBFRs.

Molecular design of environment-friendly chlorophenol (CP) derivatives based on 3D-QSAR assisted with a comprehensive evaluation method combining bioaccumulation and degradation

In this study, a chlorophenol (CP) 3D-QSAR model with a double activity (bioaccumulation and degradation) combination was established. 19 CPs were divided into a training set and test set according to the ratio of 4:1. The cross-validation coefficient (q2) and non-cross-validation coefficient (R2) of the model were 0.803 (> 0.5) and 0.925 (> 0.9), respectively, indicating a good stability and predictive ability of the 3D-QSAR. 2,4,6-trichlorophenol (2,4,6-TCP) was used as a target molecule, and 46 derivatives with low comprehensive effects were designed. Out of the 46 derivatives, 11 derivatives were screened to have the good insecticidal and preservative properties. From the perspective of the toxicity of zebrafish, 4 out of the 11 derivatives were found to have lower aquatic toxicity effects. Through the food chain simulation of cyanobacteria-daphnia-swamp-mandarin fish, it was found that the bioaccumulation effect of the four derivatives was lower than that of 2,4, 6-TCP. Finally, molecular dynamics simulation was conducted using 2-CH2NH2 substituted derivatives, and it was found that the degradation effect by laccase (white rot fungi) was significantly improved in the presence of violuric acid, hydroxybenzotriazole, and syringaldehyde. This study can provide theoretical support for the development of environment-friendly technology for emerging pollutants.

Bidirectional selection of the functional properties and environmental friendliness of organophosphorus (OP) pesticide derivatives: Design, screening, and mechanism analysis

Organophosphorus pesticides (OPs) are widely used in agricultural production, but the resulting pollution and drug resistance have sparked widespread concern. Therefore, this paper built a model to design OP substitute molecules with high functionality and environmental friendliness, as well as conducted various human health and ecological environment evaluations, synthetic accessibility screening, and easy detection screening. The functionality of the two OP substitute molecules, DIM-100 and DIM-164, increased by 22.79 % and 22.18 %, respectively, and the environmental friendliness increased by 18.07 % and 24.02 %, respectively. The human health risk and ecological, environmental risks were significantly reduced. Both molecules are easy to synthesize, and their detection sensitivity is 9.85 % and 11.24 % higher than that of the target molecule, respectively. Furthermore, significant changes in the distribution of electrons and holes near the C8 and S1 atoms of the OP substitute molecule resulted in easier breakage of the C8-S1 bond, enhancing its photodegradation ability. The charge transfer ability between the atoms of the molecule (as increasing the electron-withdrawing group led to an increase in charge of the P atom) and the volume of the cholinesterase active pocket both affect the functionality of the DIM substitute molecule. That is, the volume of the cholinesterase active pocket of the bee is smaller than that of the brown planthopper and is more affected by the volume of the OP molecule. Furthermore, the mutual verification analysis of the bidirectional selectivity effect of OP substitute molecules between the BayesianRidge model and the 3D-QS(A² + ∀³)R model reveals that the overall charge transfer degree of DIM substitute molecules is the main reason for the increase in the bidirectional selectivity effect.

Deciphering the toxicity mechanism of haloquinolines on Chlorella pyrenoidosa using QSAR and metabolomics approaches

The hazardous potential of haloquinolines (HQLs) is becoming an issue of great concern due to its wide and long-term usage in many personal care products. We examined the growth inhibition, structure-activity relationship, and toxicity mechanism of 33 HQLs on Chlorella pyrenoidosa using the 72-h algal growth inhibition assay, three-dimensional quantitative structure-activity relationship (3D-QSAR), and metabolomics. We found that the IC₅₀ (half maximal inhibitory concentration) values for 33 compounds ranged from 4.52 to > 150 mg·L^-1, most tested compounds were toxic (1 mg·L^-1 < IC₅₀ < 10 mg·L^-1) or harmful (10 mg·L^-1 < IC₅₀ < 100 mg·L^-1) for the aquatic ecosystem. Hydrophobic properties of HQLs dominate their toxicity. Halogen atoms with large volume appear at the 2, 3, 4, 5, 6, and 7-positions of the quinoline ring to significantly increase the toxicity. In algal cells, HQLs can block diverse carbohydrates, lipids, and amino acid metabolism pathways, thereby resulting in energy usage, osmotic pressure regulation, membrane integrity, oxidative stress disorder, thus fatally damaging algal cells. Therefore, our results provide insight into the toxicity mechanism and ecological risk of HQLs.

Triazine Herbicides Risk Management Strategies on Environmental and Human Health Aspects Using In-Silico Methods

As an effective herbicide, 1, 3, 5-Triazine herbicides (S-THs) are used widely in the pesticide market. However, due to their chemical properties, S-THs severely threaten the environment and human health (e.g., human lung cytotoxicity). In this study, molecular docking, Analytic Hierarchy Process—Technique for Order Preference by Similarity to the Ideal Solution (AHP-TOPSIS), and a three-dimensional quantitative structure-active relationship (3D-QSAR) model were used to design S-TH substitutes with high herbicidal functionality, high microbial degradability, and low human lung cytotoxicity. We discovered a substitute, Derivative-5, with excellent overall performance. Furthermore, Taguchi orthogonal experiments, full factorial design of experiments, and the molecular dynamics method were used to identify three chemicals (namely, the coexistence of aspartic acid, alanine, and glycine) that could promote the degradation of S-THs in maize cropping fields. Finally, density functional theory (DFT), Estimation Programs Interface (EPI), pharmacokinetic, and toxicokinetic methods were used to further verify the high microbial degradability, favorable aquatic environment, and human health friendliness of Derivative 5. This study provided a new direction for further optimizations of novel pesticide chemicals.

Virtual screening and structure-activity relationship study of novel BTK inhibitors in Traditional Chinese Medicine for the treatment of rheumatoid arthritis

Bruton tyrosine kinase (BTK) is a known drug target for the treatment of autoimmune diseases, including rheumatoid arthritis (RA). In this study, a series of 1-amino-1H-imidazole-5-carboxamide derivatives with good inhibitory activity against BTK were selected to explore the structure-activity relationships of these BTK inhibitors (BTKIs). Furthermore, we concentrated on 182 prescriptions of Traditional Chinese Medicine with therapeutic effects on RA. 54 herbs with a frequency of ≥10 were counted to establish a database containing 4027 ingredients for virtual screening. Five compounds with relatively higher docking scores and better absorption, distribution, metabolism, elimination and toxicity (ADMET) parameters were then selected for higher precision docking. The results demonstrated that the potentially active molecules form hydrogen bond interactions with the hinge region residues Met477, Glu475, glycine-rich P-loop residue Val416, Lys430 and DFG motif Asp539. In particular, they also interact with the key residues Thr474 and Cys481 of BTK. The molecular dynamics (MD) results demonstrated that all five compounds above could bind with BTK stably as its cognate ligand in dynamic conditions. This work identified several potential BTKIs using a computer-aided drug design approach and may provide crucial information for developing novel BTKIs.Communicated by Ramaswamy H. Sarma.

Dermal exposure to synthetic musks: Human health risk assessment, mechanism, and control strategy

Synthetic musks (SMs) have been widely used as odor additives in personal care products (PCPs). Dermal exposure to SMs is the main pathway of the accumulation of these chemicals in human kerateins and poses potential health risks. In this study, in silico methods were established to reduce the human health risk of SMs from dermal exposure by investigating the risk mechanisms, designing lower bioaccumulation ability SMs and suggesting proper PCP ingredients using molecular docking, molecular dynamics simulation, and quantitative structure-activity relationship (QSAR) models. The binding energy, a parameter reflecting the binding ability of SMs and human keratin protein (4ZRY), was used as the indicator to assess the human health risk of SMs. According to the mechanism analysis, total energy was found as the most influential molecular structural feature influencing the bioaccumulation ability of a SM, and as one of the main factors influencing the function (i.e., odor sensitivity) of an SM. The 3D-QSAR models were constructed to control the human health risk of SMs by designing lower-risk SMs derivatives. The phantolide (PHAN)- 58 was determined to be the optimum SM derivative with lower bioaccumulation ability (reduced 17.25%) and improved odor sensitivity (increased 7.91%). A further reduction of bioaccumulation ability of PHAN-58 was found when adding proper body wash ingredients (i.e., alkyl ethoxylate sulfate (AES), dimethyloldimethyl (DMDM), EDTA-Na4, ethylene glycol distearate (EGDS), hydroxyethyl cellulose (HEC), lemon yellow and octyl glucose), leading to a significant reduction of the bioaccumulation ability (42.27%) compared with that of PHAN. Results demonstrated that the proposed theoretical mechanism and control strategies could effectively reduce the human health risk of SMs from dermal exposure.

Inhalation and ingestion of Synthetic musks in pregnant women: In silico spontaneous abortion risk evaluation and control

Synthetic musks (SMs) are odor additives commonly used in the personal care products. Their wide existence in the environment and the recently reported adverse impact on the production and activity of progesterone and estrogen have raised pregnancy red flags and even lead to a pregnancy loss. Apart from the suggestion of limiting SM contact and exposure, effective abortion risk control measures for SMs remain to be blank. Facing the above challenges, this study tried to establish a new theoretical circumvention strategy to reduce the abortion risk of SMs to pregnant women by designing the supplementary diet plan and environmentally friendly SMs derivatives using molecular docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) models. According to the supplementary diet plan, the diet combination of vitamin E, vitamin B₂, niacin, vitamin A, and vitamin B₆ were confirmed to not only provide essential nutrients for human health, but also reduce the abortion risk in pregnant women in daily life. The multi-activity (binding ability of SMs with progesterone-estrogen) 3D-QSAR model was constructed to screen SMs derivatives. The LibDock score, a parameter reflecting the binding ability between SMs' Derivative-24 with progesterone-estrogen, decreased as much as 137.67% compared with its precursor galaxolide (HHCB). The 3D-QSAR models assisted screening indicated that Derivative-24 had lower environmental impacts (i.e., bioconcentration and mobility) and improved functional properties (odor stability, musky scent, and odor intensity). The integration of the optimum candidate, Derivative-24, with optimum three supplementary diet plans exhibited a much lower abortion risk than HHCB, demonstrating the effectiveness of the proposed theoretical circumvention strategy as a comprehensive abortion risk control measure. It also shed light on the design of new pharmaceutical and personal care products using advanced computing tools.

Molecular design of high-efficacy and high drug safety Fluoroquinolones suitable for a variety of aerobic biodegradation bacteria

The present study attempted to improve the biodegradation removal rate of Fluoroquinolones (FQs) in sewage treatment plants. The similarity index analysis (CoMSIA) model for combined biodegradability was constructed, and 33 kinds of molecular derivatives of FQs suitable for a variety of aerobic biodegradation microorganisms were designed. Further, derivative-20 and derivative-28, with high drug efficiency, drug safety, and environmental friendliness were selected through pharmacokinetics (ADMET), toxicokinetics (TOPKAT), FQs functional characteristics, and environmental friendliness evaluations. Compared with the target molecules, the combined biodegradability of the above two FQ-derivative molecules were increased by 193.57 % and 205.07 %, respectively, while their environment-friendly characteristics were improved to a certain degree. Through molecular docking and molecular dynamic simulation analysis, it showed that van der Waals force (decreased by 2.73 %-61.74 %) was the main factor influencing the binding ability of the modified FQ molecules to the receptor proteins. In addition, the relationship among the non-bonding interaction resultant force, the binding effect of the FQ-derivative molecules, and the receptor protein-related amino acid residues were studied for the first time. It was observed that the higher the value of the non-bonding interaction resultant force, the better was the binding effect, which demonstrating the significantly improved biodegradability of the designed FQ-derivative molecules.

Strategies to Control Human Health Risks Arising from Antibiotics in the Environment: Molecular Modification of QNs for Enhanced Plant-Microbial Synergistic Degradation

In the present work, a comprehensive screening and evaluation system was established to improve the plant-microbial synergistic degradation effects of QNs. The study included the construction of a 3D-QSAR model, the molecular modification, environmental friendliness and functional evaluation of drugs, degradation pathway simulation, and human health risk assessment. Molecular dynamics was applied to quantify the binding capacity of QNs toward the plant degradation enzyme (peroxidase) and microbial degradation enzymes (manganese peroxidase, lignin peroxidase, and laccase). The fuzzy comprehensive evaluation method was used in combination with the weighted average method for normalization and assigning equal weights to the plant and microbial degradation effect values of the QNs. Considering the synergistic degradation effect value as the dependent variable and the molecular information of the QNs as the independent variable, a 3D-QSAR model was constructed for the plant-microbial synergistic degradation effect of QNs. The constructed model was then employed to conduct the molecular modification, environmental friendliness and functional evaluation, degradation pathway simulation, and human health risk assessment of transformation products using pharmacokinetics and toxicokinetics. The results revealed that the synergistic degradation effect 3D-QSAR (CoMSIA) model exhibited good internal and external prediction ability, fitting ability, stability, and no overfitting phenomenon. Norfloxacin (NOR) was used as the target molecule in the molecular modification. A total of 35 NOR derivatives with enhanced plant-microbial synergistic degradation effect (1.32-21.51%) were designed by introducing small-volume, strongly electronegative, and hydrophobic hydrogen bond receptor groups into the active group of the norfloxacin structure. The environment-friendliness and the functionality of NOR were evaluated prior to and after the modification, which revealed seven environment-friendly FQs derivatives exhibiting moderate improvement in stability and bactericidal efficacy. The simulation of the NOR plant and microbial degradation pathways prior to and after the modification and the calculation of the reaction energy barrier revealed Pathway A (D-17 to D-17-2) and Pathway B (D-17 to D-17-4) as the most prone degradation pathways in plants and Pathway A (D-17 to D-17-1) and Pathway B (D-17 to D-17-4) as the most prone degradation pathways in microorganisms. This demonstrated that the degradation of the modified NOR derivatives was significantly enhanced, with the hydroxylation and piperazine ring substitution reaction playing an important role in the degradation process. Finally, the parameters, including hepatotoxicity, mutagenicity, and rodent carcinogenicity, among others, predicted using the pharmacokinetics and toxicokinetics analyses revealed a significant reduction in the human health risk associated with the modified NOR, along with a considerable reduction in the toxicity of its transformation products, implying that the human health risk associated with the transformation products was reduced remarkably. The present study provides a theoretical basis for novel ideas and evaluation programs for improving the plant-microbial synergistic degradation of the QNs antibiotics for source control and drug design, thereby reducing the residues of these antibiotics and the associated hazard in the complex plant-soil environment, ultimately decreasing the potential risks to human health.

Functional modification of HHCB: Strategy for obtaining environmentally friendly derivatives

Galaxolide (HHCB), one of the most widely used synthetic musks in personal care products (PCPs), has been recognized as an emerging contaminant with potential human health concerns. To overcome such adverse effects, a systematic molecular design, screening and performance evaluation approach was developed to generate functionally improved and environmentally friendly HHCB derivatives. Among the 90 designed HHCB derivatives, 15 were screened with improved functional properties (i.e., odor stability and intensity) and less environmental impacts (i.e., lower bio-toxicity, bio-accumulation ability, and mobility) using 3D-QSAR models and density functional theory methods. Their human health risks were then assessed by toxicokinetic analysis, which narrowed the candidates to four. Derivative 7, the designed molecule with the least dermal adsorption potential, was evaluated for its interaction with other PCPs additives (i.e., anti-photosensitivity materials and moisturizer) and such impacts on human health risks using molecular docking and molecular dynamic simulation. The environmental fate of Derivative 7 after transformation (i.e., photodegradation, biotransformation, and chlorination) was also discussed. Biotransformation and chlorination were recognized as optimum options for Derivative 7 mitigation. This study provided the theoretical basis for the design of functionally improved and environmentally friendly HHCB alternatives and advanced the understanding of their environmental behaviors and health risks.

Effects of Phthalate Esters (PAEs) on Cell Viability and Nrf2 of HepG2 and 3D-QSAR Studies

Phthalate esters (PAEs) are a widespread environmental pollutant, and their ecological and environmental health risks have gradually attracted attention. To reveal the toxicity characteristics of these compounds, ten PAEs were selected as research objects to establish a cell model. CCK-8 was used to determine cell viability, Western blots were used to determine the content of Nrf₂ in HepG2, and the LD₅₀ collected for the 13 PAEs administered to rats. On this basis, 3D-QSAR models of IC₅₀, LD₅₀ and Nrf2 were established. The experimental results showed that as the time of PAEs exposure increased (24, 48 and 72 h), cell viability gradually decreased. The test concentration (62.5 /125/250 μM) of PAEs exposed for 48 h could significantly increase the content of Nrf2, and the 1000 μM PAEs could inhibit the content of Nrf2. The model is relatively stable and predicts well that the introduction of large and hydrophobic groups may significantly affect the toxic effects of PAEs on cells. The present study provided a potential tool for predicting the LD50 and Nrf2 of new PAEs, and provide a reference for the design of new less toxic PAEs in the future.

Mitigating the Adverse Effects of Polychlorinated Biphenyl Derivatives on Estrogenic Activity via Molecular Modification Techniques

The aim of this paper is to explore the mechanism of the change in oestrogenic activity of PCBs molecules before and after modification by designing new PCBs derivatives in combination with molecular docking techniques through the constructed model of oestrogenic activity of PCBs molecules. We found that the weakened hydrophobic interaction between the hydrophobic amino acid residues and hydrophobic substituents at the binding site of PCB derivatives and human oestrogen receptor alpha (hERα) was the main reason for the weakened binding force and reduced anti-oestrogenic activity. It was consistent with the information that the hydrophobic field displayed by the 3D contour maps in the constructed oestrogen activity CoMSIA model was one of the main influencing force fields. The hydrophobic interaction between PCB derivatives and oestrogen-active receptors was negatively correlated with the average distance between hydrophobic substituents and hydrophobic amino acid residues at the hERα-binding site, and positively correlated with the number of hydrophobic amino acid residues. In other words, the smaller the average distance between the hydrophobic amino acid residues at the binding sites between the two and the more the number of them, and the stronger the oestrogen activity expression degree of PCBS derivative molecules. Therefore, hydrophobic interactions between PCB derivatives and the oestrogen receptor can be reduced by altering the microenvironmental conditions in humans. This reduces the ability of PCB derivatives to bind to the oestrogen receptor and can effectively modulate the risk of residual PCB derivatives to produce oestrogenic activity in humans.

An adjusted 3D-QSAR model for the combined activity of fluoroquinolones photodegradation and microbial degradation assisted by dynamic simulation and its application in molecular modification

This study developed a comprehensive characterization method for the combined degradation effect of modified fluoroquinolones (FQs) photodegradation and microbial degradation. A combination of revised 3D-QSAR model, molecular docking, path simulation inference, pharmacokinetics, molecular dynamics (MD) simulation and toxicokinetics simulation was used to construct a systematic environment-friendly drug screening system. Five derivatives were screened with significantly improved combined degradation effect (over 20%) and functional characteristics and human health parameters through combined model verification, functional and human health risk assessment. The simulation path of photo- and microbial-degradation of gatifloxacin and new gatifloxacin molecules was derived, and the reaction energy barrier was also calculated. The ratio of the total rate-determining steps change rate of the decreased energy barrier (14.10%:26.30%) was consistent with the ratio of the increased degradation performance predicted by the model (22.87%:19.77%), demonstrating the reliability of revised 3D-QSAR model and it could be applied in molecular modification. MD and toxicokinetics simulation were used to predict the binding energy and aquatic toxicity between photo- and microbial-degradation products and the degradation enzymes, which further to screen the degradation pathways with low potential environmental risks. The findings will be helpful to screen environment-friendly drug and develop appropriate strategies for its risk management.

Aquatic toxicity (Pre)screening strategy for structurally diverse chemicals: global or local classification tree models?

With an ever-increasing number of synthetic chemicals being manufactured, it is unrealistic to expect that they will all be subjected to comprehensive and effective risk assessment. A shift from conventional animal testing to computer-aided methods is therefore an important step towards advancing the environmental risk assessments of chemicals. The aims of this study are two-fold: firstly, it examines the relationships between structural and physicochemical features of a diverse set of organic chemicals, and their acute aquatic toxicity towards Daphnia magna and Oryzias latipes using a classification tree approach. Secondly, it compares the efficiency and accuracy of the predictions of two modeling schemes: local models that are inherently restricted to a smaller subset of structurally-related substances, and a global model that covers a wider chemical space and a number of modes of toxic action. The classification tree-based models differentiate the organic chemicals into either 'highly toxic' or 'low to non-toxic' classes, based on internal and external validation criteria. These mechanistically-driven models, which demonstrate good performance, reveal that the key factors driving acute aquatic toxicity are lipophilicity, electrophilic reactivity, molecular polarizability and size. A comparative analysis of the performance of the two modeling schemes indicates that the local models, trained on homogeneous data sets, are less error prone, and therefore superior to the global model. Although the global models showed worse performance metrics compared to the local ones, their applicability domain is much wider, thereby significantly increasing their usefulness in practical applications for regulatory purposes. This demonstrates their advantage over local models and shows they are an invaluable tool for modeling heterogeneous chemical data sets.

Changes in cognitive function and related brain regions in chronic benzene poisoning: a case report

To discuss the changes in cognitive function and related brain regions in patients with chronic benzene poisoning. Few studies have explored the damage to cognitive function that occurs in benzene toxic encephalopathy. It is important to identify early in the course of disease whether cognitive dysfunction is caused by benzene poisoning so that disease prognosis and appropriate treatment can be determined. We reported on the chronic benzene poisoning of a 41-year-old Han Chinese woman. The patient had graduated from primary school, and she had a cheerful and diligent personality. She had performed painting work for more than five years, and her primary work involved painting swivel chairs. The primary reasons she attended the psychiatric clinic were loss of appetite, she had experienced fatigue for more than 2 months, and she had had memory loss for a month. These symptoms seriously impacted the patient’s daily life and ability to work. The patient’s husband expressed concern that she could not recognize acquaintances, could not find her way home, and had lost approximately 5 kg per month over two months. We analyzed changes in this chronic benzene poisoning patient’s cognitive function with cognitive function assessments and magnetic resonance imaging (MRI). Measurements were taken on presentation to hospital, during the patient’s hospitalization, and three months following discharge. Long-term exposure to benzene can damage the central nervous system. However, it is difficult to recognize when cognitive impairment is caused by chronic benzene poisoning, as it rarely presents with a decline in cognitive function as the primary clinical manifestation. Atypical symptoms, such as decreased immune function and gastrointestinal issues, may be the first symptoms to appear, and these atypical symptoms are difficult to detect in the early stages of disease. Regular screening of high-risk groups is required to significantly reduce the incidence of systemic damage caused by benzene poisoning.

'Ideal correlations' for the predictive toxicity to Tetrahymena pyriformis

OBJECTIVES

Predictive models for toxicity to Tetrahymena pyriformis are an important component of natural sciences. The present study aims to build up a predictive model for the endpoint using the so-called index of ideality of correlation (IIC). Besides, the comparison of the predictive potential of these models with the predictive potential of models suggested in the literature is the task of the present study.

METHODS

The Monte Carlo technique is a tool to build up the predictive model applied in this study. The molecular structure is represented via a simplified molecular input-line entry system (SMILES). The IIC is a statistical characteristic sensitive to both the correlation coefficient and mean absolute error. Applying of the IIC to build up quantitative structure-activity relationships (QSARs) for the toxicity to Tetrahymena pyriformis improves the predictive potential of those models for random splits into the training set and the validation set. The calculation was carried out with CORAL software (http://www.insilico.eu/coral).

RESULTS

The statistical quality of the suggested models is incredibly good for the external validation set, but the statistical quality of the models for the training set is modest. This is the paradox of ideal correlation, which is obtained with applying the IIC.

CONCLUSIONS

The Monte Carlo technique is a convenient and reliable way to build up a predictive model for toxicity to Tetrahymena pyriformis. The IIC is a useful statistical criterion for building up predictive models as well as for the assessment of their statistical quality.

Enhanced Biodegradation of Phthalic Acid Esters' Derivatives by Plasticizer-Degrading Bacteria (Burkholderia cepacia, Archaeoglobus fulgidus, Pseudomonas aeruginosa) Using a Correction 3D-QSAR Model

A phthalic acid ester’s (PAEs) comprehensive biodegradability three-dimensional structure-activity relationship (3D-QSAR) model was established, to design environmentally friendly PAE derivatives, which could be simultaneously degraded by plasticizer-degrading bacteria, such as Burkholderia cepacia, Archaeoglobus fulgidus, and Pseudomonas aeruginosa. Only three derivatives of diethyl phthalate (DEP (DEP-27, DEP-28 and DEP-29)) were suited for their functionality and environmental friendliness, which had an improved stability in the environment and improved the characteristics (bio-toxicity, bioaccumulation, persistence, and long-range migration) of the persistent organic pollutants (POPs). The simulation inference of the microbial degradation path before and after DEP modification and the calculation of the reaction energy barrier exhibited the energy barrier for degradation being reduced after DEP modification and was consistent with the increased ratio of comprehensive biodegradability. This confirmed the effectiveness of the comparative molecular similarity index analysis (CoMSIA) model of the PAE’s comprehensive biodegradability. In addition, a molecular dynamics simulation revealed that the binding of the DEP-29 derivative with the three plasticizer-degradation enzymes increased significantly. DEP-29 could be used as a methyl phthalate derivative that synergistically degrades with microplastics, providing directional selection and theoretical designing for plasticizer replacement.

When global and local molecular descriptors are more than the sum of its parts: Simple, But Not Simpler?

In this report, we introduce a set of aggregation operators (AOs) to calculate global and local (group and atom type) molecular descriptors (MDs) as a generalization of the classical approach of molecular encoding using the sum of the atomic (or fragment) contributions. These AOs are implemented in a new and free software denominated MD-LOVIs ( http://tomocomd.com/md-lovis ), which allows for the calculation of MDs from atomic weights vector and LOVIs (local vertex invariants). This software was developed in Java programming language and employed the Chemical Development Kit (CDK) library for handling chemical structures and the calculation of atomic weights. An analysis of the complexities of the algorithms presented herein demonstrates that these aspects were efficiently implemented. The calculation speed experiments show that the MD-LOVIs software has satisfactory behavior when compared to software such as Padel, CDKDescriptor, DRAGON and Bluecal software. Shannon's entropy (SE)-based variability studies demonstrate that MD-LOVIs yields indices with greater information content when compared to those of popular academic and commercial software. A principal component analysis reveals that our approach captures chemical information orthogonal to that codified by the DRAGON, Padel and Mold2 software, as a result of the several generalizations in MD-LOVIs not used in other programs. Lastly, three QSARs were built using multiple linear regression with genetic algorithms, and the statistical parameters of these models demonstrate that the MD-LOVIs indices obtained with AOs yield better performance than those obtained when the summation operator is used exclusively. Moreover, it is also revealed that the MD-LOVIs indices yield models with comparable to superior performance when compared to other QSAR methodologies reported in the literature, despite their simplicity. The studies performed herein collectively demonstrated that MD-LOVIs software generates indices as simple as possible, but not simpler and that use of AOs enhances the diversity of the chemical information codified, which consequently improves the performance of traditional MDs.

Fuzzy risk assessment of modified polychlorinated naphthalenes for enhanced degradation

The three-dimensional quantitative structure-activity relationship (3D-QSAR) model is established for polychlorinated naphthalenes (PCNs) using the biological degradability (total score) results to modify CN-56 to design 37 new derivatives with higher degradability (increased by 14.55-38.79%). Furthermore, five new CN-56 derivatives are selected through evaluation of their persistent organic pollutant properties (toxicity, bioconcentration, long-range transport) and practicability (stability, insulativity, flame retardancy) using 3D-QSAR, density functional theory (DFT) and molecular docking methods. Environmental and health-based risk assessments are conducted using the multimedia fugacity model and fuzzy theory for complete screening of the new CN-56 derivatives. Whereas CN-56 is classed as high risk, three new derivatives can be classed as medium risk. The biodegradability mechanism analysis of the PCNs indicates that the electrostatic property is the main factor that affects the degradability, which provides a favorable theoretical reference to obtain environmentally friendly fire retardant and insulating materials.

Biological enrichment prediction of polychlorinated biphenyls and novel molecular design based on 3D-QSAR/HQSAR associated with molecule docking

Based on the experimental data of octanol-water partition coefficients (Kow, represents bioaccumulation) for 13 polychlorinated biphenyl (PCB) congeners, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used to establish 3D-QSAR models, combined with the hologram quantitative structure-activity relationship (HQSAR), the substitution sites (mono-substituted and bis-substituted) and substituent groups (electron-withdrawing hydrophobic groups) that significantly affect the octanol-water partition coefficients values of PCBs were identified, a total of 63 monosubstituted and bis-substituted were identified. Compared with using 3D-QSAR model alone, the coupling of 3D-QSAR and HQSAR models greatly increased the number of newly designed bis-substituted molecules, and the logKow reduction in newly designed bis-substituted molecules was larger than that of monosubstituted molecules. This was established to predict the Kow values of 196 additional PCBs and carry out a modification of target molecular PCB-207 to lower its Kow (biological enrichment) significantly, simultaneously maintaining the flame retardancy and insulativity after calculation by using Gaussian09. Simultaneously, molecular docking could further screen out three more environmental friendly low biological enrichment newly designed PCB-207 molecules (5-methyl-PCB-207, 5-amino-PCB-207, and 4-amino-5-ethyl-PCB-207).

Combined QSAR/QSPR and molecular docking study on fluoroquinolones to reduce biological enrichment

With the aim of reducing the adverse effects of fluoroquinolones in the environment, a complete design and screening system for the low biological enrichment and high photodegradabilities of 29 fluoroquinolones was established through a three-dimensional quantitative structure-activity relationship (3D-QSAR) model and molecular docking. The interaction mechanisms of the fluoroquinolones with Gram-negative bacteria (DNA gyrase in Escherichia coli) and Gram-positive bacteria (Topoisomerase IV in Staphylococcus aureus) were also evaluated. Consequently, the 3D-QSAR model showed that the 3- and 18-positions of the fluoroquinolones strongly affected their biological enrichment, and that the introduction of electropositive or hydrophobic groups at these positions reduced the logarithm of the octanol-water partition coefficient. Using nadifloxacin as a template, 23 derivatives with lower biological enrichment than nadifloxacin (decreased by 30.12%-94.18%) were designed. Meanwhile, the photodegradabilities of 15 derivatives were increased compared with nadifloxacin. Finally, the further screening by molecular docking of nadifloxacin and the above 15 derivatives with DNA gyrase and Topoisomerase IV showed that 13 of the derivatives had lower biological enrichment (decreased by 0.30%-16.76%) than nadifloxacin in the bacteria.

Environmentally friendly polychlorinated naphthalenes (PCNs) derivatives designed using 3D-QSAR and screened using molecular docking, density functional theory and health-based risk assessment

A complete design and screening system for environmental-friendly polychlorinated naphthalene (PCN) derivatives was established through three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, density functional theory (DFT) methods and health-based risk assessment based on dynamic multimedia fugacity model. Two types of 3D-QSAR models were established for PCNs using the experimental biological toxicity (logEC₅₀) of 14 PCNs to carry out a modification to lower the logEC₅₀ of CN-70. Consequently, 67 new monosubstituted and disubstituted derivatives with a lower biological toxicity than CN-70 were designed. Furthermore, 21 new CN-70 derivatives were selected through the evaluation of their persistent organic pollutant properties (biological toxicity, bio-concentration, long-range transport potential, biodegradability) and practicability (stability, insulativity, flame retardancy) using 3D-QSAR, molecular docking and DFT methods. Finally, the non-carcinogenic and carcinogenic risks of 19 new CN-70 derivatives in different exposure pathways were reduced, and 5 derivatives with a significant decrease both in biological toxicity (amplitude reduction: 12.73%-32.51%) and risk (amplitude reduction: 32.18%-59.19%) were selected as environmental-friendly PCN derivatives, which had been screened using the health-based risk assessment system associated with dynamic multimedia fugacity model. This study provides a theoretical basis for the design of environmental-friendly flame retardants and insulating materials.

Modified neonicotinoid insecticide with bi-directional selective toxicity and drug resistance

A three-dimensional quantitative structure-activity relationship (3D-QSAR) model was established based on the molecular structures and the negative logarithm of experimental lethal concentration 50 values (pLC₅₀) of neonicotinoid insecticides. Then, the mechanisms of bi-directional selective toxic effects and drug resistance were determined using homology modeling and molecular docking analyses. The results of the model showed that the 1-, 2-, 4-, and 12- positions of neonicotinoid insecticides strongly affected their toxicity, and that the introduction of bulky or electropositive groups at these positions could increase the pLC₅₀ values. Using Compound 19 as a template, we designed 37 derivatives with greater toxicity (increased by 0.04-11.45%). Among them, 20 derivatives had bioconcentrations lower than that of Compound 19 (reduced by 0.38-147.88%). Further screening of Compound 19 and the 20 derivatives mentioned above by homology modeling and acetylcholine receptors (AChRs) molecular docking analyses showed that 10 derivatives had bi-directional selective toxic effects against pests and bees. Further docking analyses of Compound 19 and these 10 derivatives identified that Derivative-33 showed decreased docking with superoxide dismutase (SOD) and glutathione S transferase (GST) in pests and enhanced docking with these enzymes in bees, indicating bi-directional selective resistance for pests and bees. Accordingly, Derivative-33 was selected as a new insecticide with high toxicity to pests and low toxicity to bees (bi-directional selective toxicity), low resistance in pest populations, and high resistance in bee populations. This study provides valuable reference data and will be useful for the development of strategies to produce new environmentally friendly pesticides.

Modification of Hexachlorobenzene to Molecules with Lower Long-Range Transport Potentials Using 3D-QSAR Models with a Full Factor Experimental Design

In this study, the hexachlorobenzene molecule was modified by three-dimensional quantitative structure-activity relationship (3D-QSAR) models and a full factor experimental design to obtain new hexachlorobenzene molecules with low migration ability. The 3D-QSAR models (comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA)) were constructed by SYBLY-X 2.0 software, using experimental data of octanol-air partition coefficients (K_OA) for 12 chlorobenzenes (CBs) congeners as the dependent variable, and the structural parameters of CBs as independent variables, respectively. A target molecule (hexachlorobenzene; HCB: its long-distance migration capability leads to pollution of the marine environment in Antarctic and Arctic) was modified using the 3D-QSAR contour maps associated with resolution V of the 2^10-3 full-factorial experimental design method, and 11 modified HCB molecules were produced with a single chlorine atom (-Cl₂) and three chlorine atoms (-Cl₁, -Cl₃, and -Cl₅) replaced with electropositive groups (-COOH, -CN, -CF₃, -COF, -NO₂, -F, -CHF₂, -ONO₂, and -SiF₃) to increase the logK_OA. The new molecules had essentially similar biological enrichment functions and toxicities as HCB but were found to be more easily degraded. A 2D-QSAR model and molecular docking technology indicated that both dipole moments and highest occupied orbital energies of the substituents markedly affected migration and degradation of the new molecules. The abilities of the compounds to undergo long distance migration were assessed. The modified HCB molecules (i.e. 2-CN-HCB, 2-CF₃-HCB, 1-F-3-COOH-5-NO₂-HCB, 1-NO₂-3-CN-5-CHF₂-HCB and 1-CN-3-F-5-NO₂-HCB) moved from a long-range transport potential of the modified molecules to a relatively low mobility class, and the transport potentials of the remaining modified HCB molecules (i.e. 2-COOH-HCB, 2-COF-HCB, 1-COF-3-ONO₂-5-NO2-HCB, 1-F-3-CN-5-SiF₃-HCB, 1-F-3-COOH-5-SiF₃-HCB and 1-CN-3-SiF₃-5-ONO₂-HCB) also significantly decreased. These results provide a basic theoretical basis for designing environmentally benign molecules based on HCB.

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.

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.

Building up a QSAR model for toxicity toward Tetrahymena pyriformis by the Monte Carlo method: A case of benzene derivatives

Data on toxicity toward Tetrahymena pyriformis is indicator of applicability of a substance in ecologic and pharmaceutical aspects. Quantitative structure-activity relationships (QSARs) between the molecular structure of benzene derivatives and toxicity toward T. pyriformis (expressed as the negative logarithms of the population growth inhibition dose, mmol/L) are established. The available data were randomly distributed three times into the visible training and calibration sets, and invisible validation sets. The statistical characteristics for the validation set are the following: r(2)=0.8179 and s=0.338 (first distribution); r(2)=0.8682 and s=0.341 (second distribution); r(2)=0.8435 and s=0.323 (third distribution). These models are built up using only information on the molecular structure: no data on physicochemical parameters, 3D features of the molecular structure and quantum mechanics descriptors are involved in the modeling process.

Cyto- and enzyme toxicities of ionic liquids modelled on the basis of VolSurf+ descriptors and their principal properties

Five in silico principal properties (PPs) for 218 heterocyclic cations and four PPs for 38 organic and inorganic anionic counterparts of ionic liquids (ILs) were derived by the VolSurf+ approach. VolSurf+ physicochemical descriptors take into account several cationic structural features of ILs such as heterocyclic aromatic and non-aromatic cationic cores, alkyl chain length, presence of oxygen atoms in the substituents as well as the properties of a wide variety of inorganic and organic anions. Combination of these cation and anion PPs can provide descriptors for over 8000 ILs, thus allowing the development of QSPR models for IL cytotoxicity (IPC-81 rat cell line) and enzyme toxicity (acetylcholinesterase inhibition). The adoption of a Partial Least Squares approach, relating PPs and toxicities, provided affordable predictions for ILs in both learning and external validation sets, implying the possibility to extend the predictive model to a set of 520 ILs. This allows us to establish priorities in selecting ILs for experimental hazard assessment as required by the REACH regulation.

Prediction of octanol-air partition coefficients for polychlorinated biphenyls (PCBs) using 3D-QSAR models

Based on the experimental data of octanol-air partition coefficients (KOA) for 19 polychlorinated biphenyl (PCB) congeners, two types of QSAR methods, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), are used to establish 3D-QSAR models using the structural parameters as independent variables and using logKOA values as the dependent variable with the Sybyl software to predict the KOA values of the remaining 190 PCB congeners. The whole data set (19 compounds) was divided into a training set (15 compounds) for model generation and a test set (4 compounds) for model validation. As a result, the cross-validation correlation coefficient (q(2)) obtained by the CoMFA and CoMSIA models (shuffled 12 times) was in the range of 0.825-0.969 (>0.5), the correlation coefficient (r(2)) obtained was in the range of 0.957-1.000 (>0.9), and the SEP (standard error of prediction) of test set was within the range of 0.070-0.617, indicating that the models were robust and predictive. Randomly selected from a set of models, CoMFA analysis revealed that the corresponding percentages of the variance explained by steric and electrostatic fields were 23.9% and 76.1%, respectively, while CoMSIA analysis by steric, electrostatic and hydrophobic fields were 0.6%, 92.6%, and 6.8%, respectively. The electrostatic field was determined as a primary factor governing the logKOA. The correlation analysis of the relationship between the number of Cl atoms and the average logKOA values of PCBs indicated that logKOA values gradually increased as the number of Cl atoms increased. Simultaneously, related studies on PCB detection in the Arctic and Antarctic areas revealed that higher logKOA values indicate a stronger PCB migration ability. From CoMFA and CoMSIA contour maps, logKOA decreased when substituents possessed electropositive groups at the 2-, 3-, 3'-, 5- and 6- positions, which could reduce the PCB migration ability. These results are expected to be beneficial in predicting logKOA values of PCB homologues and derivatives and in providing a theoretical foundation for further elucidation of the global migration behaviour of PCBs.

Nano-QSAR: Model of mutagenicity of fullerene as a mathematical function of different conditions

The experimental data on the bacterial reverse mutation test (under various conditions) on C60 nanoparticles for the cases (i) TA100, and (ii) WP2uvrA/pkM101 are examined as endpoints. By means of the optimal descriptors calculated with the Monte Carlo method a mathematical model of these endpoints has been built up. The models are a mathematical function of eclectic data such as (i) dose (g/plate); (ii) metabolic activation (i.e. with mix S9 or without mix S9); and (iii) illumination (i.e. darkness or irradiation). The eclectic data on different conditions were represented by so-called quasi-SMILES. In contrast to the traditional SMILES which are representation of molecular structure, the quasi-SMILES are representation of conditions by sequence of symbols. The calculations were carried out with the CORAL software, available on the Internet at http://www.insilico.eu/coral. The main idea of the suggested descriptors is the accumulation of all available eclectic information in the role of logical and digital basis for building up a model. The computational experiments have shown that the described approach can be a tool to build up models of mutagenicity of fullerene under different conditions.

Global and local QSPR models to predict supercooled vapour pressure for organic compounds

In this study, a quantitative structure-property relationship (QSPR) approach was used for estimation of logarithmic values of supercooled liquid vapour pressure (log P_L) of a large set of structurally diverse organic compounds. This set includes 12 local sets of aromatic and aliphatic hydrocarbons, polychlorinated biphenyls, ethers, polychlorinated and brominated diphenylethers, polychlorinated naphthalenes and alcohols. Some simple models based on the linear relationship between log P_L and VolSurf descriptors were developed as global models, and a general equation as a simple way to calculate the supercooled liquid vapour pressure of organic chemicals was provided. A descriptor representing the hydrophilic regions (WO₁) of organic chemicals showed the highest correlation with log P_L and resulted in a one-parameter global model characterized by satisfactory statistical performance; calibration (r²_c) and prediction (r²_p) correlation coefficient of 0.84 and 0.85, respectively. Moreover, local QSPR models were also developed for each subset of organic compounds and, as expected, the statistical results obtained from these models were better than the global one. From the descriptors involved in the models, it is concluded that the hydrophilic and hydrophobic regions at different energy levels and polarizability usually determine the variation of supercooled liquid vapour pressure of organic compounds.