A Double-Activity (Green Algae Toxicity and Bacterial Genotoxicity) 3D-QSAR Model Based on the Comprehensive Index Method and Its Application in Fluoroquinolones' Modification

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.

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.

Toxicity Rank Order (TRO) As a New Approach for Toxicity Prediction by QSAR Models

Quantitative Structure-Activity Relationship (QSAR) models are commonly used for risk assessment of emerging contaminants. The objective of this study was to use a toxicity rank order (TRO) as an integrating parameter to improve the toxicity prediction by QSAR models. TRO for each contaminant was calculated from collected toxicity data including acute toxicity concentration and no observed effect concentration. TRO values associated with toxicity mechanisms were used to classify pollutants into three modes of action consisting of narcosis, transition and reactivity. The selection principle of parameters for QSAR models was established and verified. It showed a reasonable prediction of toxicities caused by organophosphates and benzene derivatives, especially. Compared with traditional procedures, incorporating TRO showed an improved correlation coefficient of QSAR models by approximately 10%. Our study indicated that the proposed procedure can be used for screening modeling parameter data and improve the toxicity prediction by QSAR models, and this could facilitate prediction and evaluation of environmental contaminant toxicity.

Multi-Dimensional Elimination of β-Lactams in the Rural Wetland: Molecule Design and Screening for More Antibacterial and Degradable Substitutes

Restricted economic conditions and limited sewage treatment facilities in rural areas lead to the discharge of small-scale breeding wastewater containing higher values of residual beta-lactam antibiotics (β-lactams), which seriously threatens the aquatic environment. In this paper, molecular docking and a comprehensive method were performed to quantify and fit the source modification for the combined biodegradation of β-lactams. Using penicillin (PNC) as the target molecule, combined with contour maps for substitute modification, a three-dimensional quantitative structure-activity relationship (3D-QSAR) model was constructed for the high-performance combined biodegradation of β-lactams. The selected candidate with better environmental friendliness, functionality, and high performance was screened. By using the homology modeling algorithms, the mutant penicillin-binding proteins (PBPs) of Escherichia coli were constructed to have antibacterial resistance against β-lactams. The molecular docking was applied to obtain the target substitute by analyzing the degree of antibacterial resistance of β-lactam substitute. The combined biodegradation of β-lactams and substitute in the constructed wetland (CW) by different wetland plant root secretions was studied using molecular dynamics simulations. The result showed a 49.28% higher biodegradation of the substitutes than PNC when the combined wetland plant species of Eichhornia crassipes, Phragmites australis, and Canna indica L. were employed.

Design Two Novel Tetrahydroquinoline Derivatives against Anticancer Target LSD1 with 3D-QSAR Model and Molecular Simulation

Lysine-specific demethylase 1 (LSD1) is a histone-modifying enzyme, which is a significant target for anticancer drug research. In this work, 40 reported tetrahydroquinoline-derivative inhibitors targeting LSD1 were studied to establish the three-dimensional quantitative structure-activity relationship (3D-QSAR). The established models CoMFA (Comparative Molecular Field Analysis (q² = 0.778, Rpred2 = 0.709)) and CoMSIA (Comparative Molecular Similarity Index Analysis (q² = 0.764, Rpred2 = 0.713)) yielded good statistical and predictive properties. Based on the corresponding contour maps, seven novel tetrahydroquinoline derivatives were designed. For more information, three of the compounds (D1, D4, and Z17) and the template molecule 18x were explored with molecular dynamics simulations, binding free energy calculations by MM/PBSA method as well as the ADME (absorption, distribution, metabolism, and excretion) prediction. The results suggested that D1, D4, and Z17 performed better than template molecule 18x due to the introduction of the amino and hydrophobic groups, especially for the D1 and D4, which will provide guidance for the design of LSD1 inhibitors.

Research on the anti-tumor activity of a novel aminopeptidase inhibitor based on 3D QSAR model

Background:

Aminopeptidase N (APN) is a type II transmembrane zinc ion-dependent metalloprotease. It is closely related to many processes of tumor occurrence and development, such as the formation of new blood vessels and tumor metastasis. Recent studies have shown that APN is a member of the family of surface markers of liver cancer stem cells. Therefore, APN small molecule inhibitors may have multiple compound functions, exerting multiple anti-tumor effects at multiple stages of cancer occurrence and development.

Methods:

Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) approaches.

Results:

Both internal and external cross-validation were conducted to obtain high predictive and satisfactory CoMFA model (q2 = 0.627, r2 =0.995, SEE = 0.043) and CoMSIA model (q2 = 0.575, r2 = 0.998, SEE = 0.031). The statistical results obtained from CoMFA and CoMSIA models were full of credibility and remarkable predictive power.

Conclusion:

The results of 3D-QSAR are reliable and significant with high predictive (q2) ability, and a lower value of the standard error of estimation indicates a good correlation between predicted and observed activity. All these results revealed many useful structural insights to improve the activity of the newly designed APN small molecule inhibitors.

Theoretical design and process control of neonicotinoids insecticides suitable for synergistic degradation with the rubisco enzyme from rhizobia and carbon-fixing bacteria in soil

In this study, we studied and developed the modification schemes of environmentally friendly substitutes of neonicotinoid insecticides (NNIs) along with the regulatory measures that effectively enhanced the synergistic degradation of NNIs by soil rhizobia and carbon-fixing bacteria. Firstly, the binding ability of NNIs to the two key proteins was characterized by molecular docking; secondly, the mean square deviation decision method, which is a comprehensive evaluation method, was used to investigate the binding ability of NNI molecules with the two Rubisco rate-limiting enzymes. The three-dimensional quantitative structure-activity relationship (3D-QSAR) model was established for the synergistic degradation and single effect of rhizobia and carbon-fixing bacteria. Finally, after combining the 3D-QSAR model with a contour map analysis of the synergistic degradation effect of soil rhizobia and carbon-fixing bacteria, 102 NNI derivatives were designed. Flonicamid-36 and other four NNI derivatives passed the functional and environmentally friendly evaluation. Taguchi orthogonal experiment and factorial experiment-assisted molecular dynamics method were used to simulate the effects of 32 regulation schemes on the synergistic degradation of NNIS and its derivatives by rhizobia and carbon fixing bacteria. The synergistic degradation capacity of soil rhizobia and carbon-fixing bacteria was increased to 33.32% after right nitrogen supplementation. This indicated that supplementing the correct amount of nitrogen in the soil environment was beneficial to the microbial degradation of NNIs and their derivatives.

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.

Establishment of a CoMFA Model Based on the Combined Activity of Bioconcentration, Long-Range Transport, and Highest Infrared Signal Intensity and Molecular Design of Environmentally Friendly PBB Derivatives

In the current study, a comparative molecular field analysis (CoMFA) model with the combined activity of polybrominated biphenyls (PBBs) bioconcentration, long-range transport, and the highest infrared signal intensity (weight ratio of 5:4:1) was constructed based on the threshold method and was further evaluated and analyzed. PBB-153 derivatives with improved combined activity values of bioconcentration, long-range transport, and the highest infrared signals intensity were designed based on contour maps of the CoMFA model. The environmental stability and functionality of the derivatives were also evaluated. The constructed model showed good prediction ability, fitting ability, stability, and external prediction ability. The contribution rates of electrostatic and steric fields to the combined activity of PBBs were 53.4% and 46.6%, respectively. Four PBB-153 derivatives with significantly improved bioconcentration, long-range transport and the highest infrared signal intensity (the combined activity value of these three parameters decreased) were screened with good environmental stability and functionality. Results validated the accuracy and reliability, and ability of the generated model to realize the simultaneous modification of the three activities of the target molecule. The binding ability of the designed derivatives to food chain biodegradation enzymes increased, thereby verifying the improvement in the bioconcentration. The half-lives of the derivatives in air and their ability to be absorbed by the plants significantly improved compared to the target molecule, further showing that the long-range transport of derivatives was reduced. In addition, the introduction of the –NO group caused the N =O stretching vibration of the derivatives to increase the infrared signal intensity. The present model provides a theoretical design method for the molecular modification of environmentally friendly PBBs.

Environmentally Friendly Quinolones Design for a Two-Way Choice between Biotoxicity and Genotoxicity through Double-Activity 3D-QSAR Model Coupled with the Variation Weighting Method

Quinolone (QN) antibiotics are widely used, which lead to their accumulation in soil and toxic effects on ryegrass in pasture. In this study, we employed ryegrass as the research object and selected the total scores of 29 QN molecules docked with two resistant enzyme structures, superoxide dismutase (SOD, PDB ID: 1B06) and proline (Pro, PPEP-2, PDB ID: 6FPC), as dependent variables. The structural parameters of QNs were used as independent variables to construct a QN double-activity 3D-QSAR model for determining the biotoxicity on ryegrass by employing the variation weighting method. This model was constructed to determine modification sites and groups for designing QNs molecules. According to the 3D contour map of the model, by considering enrofloxacin (ENR) and sparfloxacin (SPA) as examples, 23 QN derivatives with low biotoxicity were designed, respectively. The functional properties and environmental friendliness of the QN derivatives were predicted through a two-way selection between biotoxicity and genotoxicity before and after modification; four environmentally friendly derivatives with low biotoxicity and high genotoxicity were screened out. Mixed toxicity index and molecular dynamics methods were used to verify the combined toxicity mechanism of QNs on ryegrass before and after modification. By simulating the combined pollution of ENR and its derivatives in different soils (farmland, garden, and woodland), the types of combined toxicity were determined as partial additive and synergistic. Binding energies were calculated using molecular dynamics. The designed QN derivatives with low biotoxicity, high genotoxicity, and environmental friendliness can highly reduce the combined toxicity on ryegrass and can be used as theoretic reserves to replace QN antibiotics.

Environmentally Friendly Fluoroquinolone Derivatives with Lower Plasma Protein Binding Rate Designed Using 3D-QSAR, Molecular Docking and Molecular Dynamics Simulation

Comparative molecular similarity index analysis (CoMSIA) was used to establish a three-dimensional quantitative structure–activity relationship (3D-QSAR) model with structural parameters of quinolones as the independent variables and plasma protein binding rate (logf_b) as the dependent variable to predict the logf_b values of remaining quinolones in this study. In addition, the mono-substituted and bis-substituted reaction schemes that significantly influenced the plasma protein binding rate of quinolones were determined through an analysis of the 3D-QSAR contour maps. It was found that the replacement of small groups, hydrophobic groups, electronegative groups, or hydrogen bond acceptor groups at the substitution sites significantly reduce the logf_b values of quinolone derivatives. Furthermore, the mechanism of decrease in binding rate between trovafloxacin (TRO) derivatives and plasma protein was revealed qualitatively and quantitatively based on molecular docking and molecular dynamics simulation. After modification of the target molecule, 11 TRO derivatives with low plasma protein binding rates were screened (reduced by 0.50–24.18%). Compared with the target molecule, the molecular genotoxicity and photodegradability of the TRO derivatives was higher (genotoxicity increased by 4.89–21.36%, and photodegradability increased by 9.04–20.56%), and their bioconcentration was significantly lower (by 36.90–61.41%).