Combined 2D-QSAR, Principal Component Analysis and Sensitivity Analysis Studies on Fluoroquinolones' Genotoxicity

An in silico study on human carcinogenicity mechanism of polybrominated biphenyls exposure

Polybrominated biphenyls (PBBs) are associated with an increased risk of thyroid cancer; however, relevant mechanistic studies are lacking. In this study, we investigated the mechanisms underlying PBB-induced human thyroid cancer. Molecular docking and molecular dynamics methods were employed to investigate the metabolism of PBBs by the cytochrome P450 enzyme under aryl hydrocarbon receptor mediation into mono- and di-hydroxylated metabolites. This was taken as the molecular initiation event. Subsequently, considering the interactions of PBBs and their metabolites with the thyroxine-binding globulin protein as key events, an adverse outcome pathway for thyroid cancer caused by PBBs exposure was constructed. Based on 2D quantitative structure activity relationship (2D-QSAR) models, the contribution of amino acid residues and binding energy were analyzed to understand the mechanism underlying human carcinogenicity (adverse effect) of PBBs. Hydrogen bond and van der Waals interactions were identified as key factors influencing the carcinogenic adverse outcome pathway of PBBs. Analysis of non-bonding forces revealed that PBBs and their hydroxylation products were predominantly bound to the thyroxine-binding globulin protein through hydrophobic and hydrogen bond interactions. The key amino acids involved in hydrophobic interactions were alanine 330, arginine 381 and lysine 270, and the key amino acids involved in hydrogen bond interactions were arginine 381 and lysine 270. This study provides valuable insights into the mechanisms underlying human health risk associated with PBBs exposure.

In silico degradation of fluoroquinolones by a microalgae-based constructed wetland system

Fluoroquinolone antibiotics (FQs) have been used worldwide due to their extended antimicrobial spectrum. However, the overuse of FQs leads to frequent detection in the environment and cannot be efficiently removed. Microalgae-based constructed wetland systems have been proven to be a relatively proper method to treat FQs, mainly by microalgae, plants, microorganisms, and sediments. To improve the removal efficiency of microalgae-constructed wetland, a systematic molecular design, screening, functional, and risk evaluation method was developed using three-dimensional quantitative structure-activity relationship models, molecular dynamics simulation, molecular docking, and TOPKAT approaches. Five designed ciprofloxacin alternatives with improved bactericidal effects and lower human health risks were found to be more easily degraded by microalgae (16.11-167.88 %), plants (6.72-58.86 %), microorganisms (9.10-15.02 %), and sediments (435.83 %-1763.51 %) compared with ciprofloxacin. According to the mechanism analysis, the removal effect of the FQs can be affected via changes in the number, bond energy, and molecular descriptors of favorable and unfavorable amino acids. To the best of our knowledge, this is the first comprehensive study of improving the microalgae, plants, microorganisms, and sediment removal efficiency of FQs in constructed wetlands, which provides theoretical support for the treatment of FQ pollution.

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.

Synthesis of environmentally friendly neonicotinoid insecticide with proper functional properties by theoretical methodologies

Modern insecticide substitutes using acetylcholine receptors (nAChR) as biochemical targets, such as neonicotinoid insecticides (NNIs), have been extensively researched. Only 12 compounds have been experimentally realized since the initial discovery of imidacloprid. Increasingly, the bottleneck in this field is to rapidly determine the synthesizability of NNI substitutes. Here, we designed a coupled evaluation system for synthesis prediction and validation, including the synthesis probability, reaction path difficulty, and electron transfer characteristics of NNIs and their substitutes. Firstly, a total of 1475 eigenvalues were generated and 52 critical eigenvalues were screened out through the Pearson's correlation coefficient. The positive and unlabeled (PU) machine learning was constructed using the critical eigenvalues NNIs, including 12 experimentally synthesized NNIs (positive samples) and 73 unsynthesized NNI substitutes (unlabeled samples). Results identified 3 NNI substitutes that were highly promising candidates for synthesis (synthesis probability > 0.5). The results of density functional theory demonstrated the ranking of their reaction ease was UN-1 (31.4 kcal/mol) > UN-2 (81.6 kcal/mol) > UN-3 (3.35 ×103 kcal/mol). Time-dependent density functional theory revealed that changes in the electron distribution and electron excitation type were critical factors affecting their synthesizability, and the local excitation type was more favorable for the synthesizability of NNI substituents. The findings provide significant guidance for NNIs synthesis, reducing the possible space of unlabeled samples to 95.89% of their original size, while also minimizing the cost of research on subsequent NNI substitutes.

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.

Biodegradability analysis of Dioxins through in silico methods: Model construction and mechanism analysis

The biodegradation treatment of dioxins has long been of interest due to its good ecological and economic effects. In this study, the biodegradability of polychlorinated dibenzo-p-dioxins (PCDDs) were investigated by constructing machine learning and multiple linear regression models. The maximum chlorine atomic charge (qHirshfeldCl+), which characterizes the biodegradation ability of PCDDs, was used as the response value. The random forest model was used to rank the importance on the 1471 descriptors of PCDDs, and the BCUTp-1 h, QXZ, JGI4, ATSC8c, VE3_Dt, topoShape, and maxwHBa were screened as the important descriptors by Pearson's correlation coefficient method. A quantitative structure-activity relationship (QSAR) model was constructed to predict the biodegradability of PCDDs. In addition, the extreme gradient boosting (XGBoost) and random forest model were also constructed and proved the good predictability of QSAR model. The biodegradability of polychlorinated dibenzofurans (PCDFs) can also be predicted by the constructed three models from a certain level after adjusting some model parameters, which further proved the versatility of the models. Besides, the sensitivity analysis of the QSAR model and a 3D-QSAR model was developed to investigate the biodegradability mechanisms of PCDDs. Results showed that the descriptors BCUTp-1 h, JGI4, and maxwHBa were the key descriptors in the biodegradability effect by the sensitivity analysis of the QSAR model. Coupled with the results of PCDDs biodegradability 3D-QSAR model, BCUTp-1 h, JGI4, and maxwHBa were confirmed as the main descriptors that affect the biodegradability of dioxins. This study provides a novel theoretical perspective for the research of the biodegradation of both PCDDs and PCDFs dioxins.

Reduced bacterial resistance antibiotics with improved microbiota tolerance in human intestinal: Molecular design and mechanism analysis

Antibiotic selectivity and bacterial resistance are critical global public health issues. We constructed a multi-class machine learning model to study antibiotic effects on human intestinal microbiota abundance and identified key features. Binding energies of β-lactam antibiotics with Escherichia coli PBP3 mutant protein were calculated, and a 2D-QSAR model for bacterial resistance was established. Sensitivity analysis identified key features affecting bacterial resistance. By coupling key features from the machine learning model and 2D-QSAR model, we designed ten flucloxacillin (FLU) substitutes that improved intestinal microbiota tolerance and reduced antibiotic bacterial resistance. Concurrently, the substitutes exhibited superior degradability in soil, aquatic environments, and under photolytic conditions, coupled with a reduced environmental toxicity compared to the FLU. Evaluations under combined medication revealed significant improvements in functionality and bacterial resistance for 80% of FLU substitutes, with 50% showing more than a twofold increase. Mechanistic analysis demonstrated enhanced binding to target proteins and increased biodegradability for FLU substitutes due to more concentrated surface charges. Reduced solvent hindrance and increased cell membrane permeability of FLU substitutes, mainly due to enhanced interactions with phospholipid bilayers, contributed to their functional selectivity. This study aims to address poor antibiotic selectivity and strong bacterial resistance, providing guidance for designing antibiotic substitutes.

Quantitative structure activity relationship (QSAR) modeling study of some novel thiazolidine 4-one derivatives as potent anti-tubercular agents

This study aims to develop a QSAR model for Antitubercular activity. The quantitative structure-activity relationship (QSAR) approach predicted the thiazolidine-4-ones derivative's Antitubercular activity. For the QSAR study, 53 molecules with Antitubercular activity on H37Rv were collected from the literature. Compound structures were drawn by ACD/Labs ChemSketch. The energy minimization of the 2D structure was done using the MM2 force field in Chem3D pro. PaDEL Descriptor software was used to construct the molecular descriptors. QSARINS software was used in this work to develop the 2D QSAR model. A series of thiazolidine 4-one with MIC data were taken from the literature to develop the QSAR model. These compounds were split into a training set (43 compounds) and a test set (10 compounds). The PaDEL software calculated 2300 descriptors for this series of thiazolidine 4-one derivatives. The best predictive Model 4, which has R2 of 0.9092, R2adj of 0.8950 and LOF parameter of 0.0289 identify a preferred fit. The QSAR study resulted in a stable, predictive, and robust model representing the original dataset. In the QSAR equation, the molecular descriptor of MLFER_S, GATSe2, Shal, and EstateVSA 6 positively correlated with Antitubercular activity. While the SpMAD_Dzs 6 is negatively correlated with Antitubercular activity. The high polarizability, Electronegativities, Surface area contributions and number of Halogen atoms in the thiazolidine 4-one derivatives will increase the Antitubercular activity.

Overview of Side-Effects of Antibacterial Fluoroquinolones: New Drugs versus Old Drugs, a Step Forward in the Safety Profile?

Antibacterial fluoroquinolones (FQs) are frequently used in treating infections. However, the value of FQs is debatable due to their association with severe adverse effects (AEs). The Food and Drug Administration (FDA) issued safety warnings concerning their side-effects in 2008, followed by the European Medicine Agency (EMA) and regulatory authorities from other countries. Severe AEs associated with some FQs have been reported, leading to their withdrawal from the market. New systemic FQs have been recently approved. The FDA and EMA approved delafloxacin. Additionally, lascufloxacin, levonadifloxacin, nemonoxacin, sitafloxacin, and zabofloxacin were approved in their origin countries. The relevant AEs of FQs and their mechanisms of occurrence have been approached. New systemic FQs present potent antibacterial activity against many resistant bacteria (including resistance to FQs). Generally, in clinical studies, the new FQs were well-tolerated with mild or moderate AEs. All the new FQs approved in the origin countries require more clinical studies to meet FDA or EMA requirements. Post-marketing surveillance will confirm or infirm the known safety profile of these new antibacterial drugs. The main AEs of the FQs class were addressed, highlighting the existing data for the recently approved ones. In addition, the general management of AEs when they occur and the rational use and caution of modern FQs were outlined.

A comprehensive evaluation of liposome/water partition coefficient prediction models based on the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method: Challenges from different descriptor dimension reduction methods and machine learning algorithms

The liposome/water partition coefficient (K_lip/w) is a key parameter to evaluate the bioaccumulation potential of pollutants. Considering that it is difficult to determine the K_lip/w values of all pollutants through experiments, researchers gradually developed models to predict it. However, there is currently no research on how to comprehensively evaluate prediction models and recommend a compelling optimal modeling method. To remedy the defect of single parameters in a traditional model comparison, the TOPSIS evaluation method, based on entropy weight, was first proposed. We use this method to comprehensively evaluate models from multiple angles in this study. Thirty QSPR models, including 3 descriptor dimension reduction methods and 10 algorithms (belonging to 4 tribes), were used to predict K_lip/w and verify the effectiveness of the comprehensive assessment method. The results showed that RF (descriptor dimension reduction method), symbolism (tribes) and RF (algorithm) exhibited significant advantages in establishing the K_lip/w value prediction model. At present, the application of TOPSIS in environmental model evaluations is almost absent. We hope that the proposed TOPSIS evaluation method can be applied to more chemical datasets and provide a more systematic and comprehensive basis for the application of the QSPR model in environmental studies and other fields.

Synthesis of Synthetic Musks: A Theoretical Study Based on the Relationships between Structure and Properties at Molecular Scale

Synthetic musks (SMs), as an indispensable odor additive, are widely used in various personal care products. However, due to their physico-chemical properties, SMs were detected in various environmental media, even in samples from arctic regions, leading to severe threats to human health (e.g., abortion risk). Environmentally friendly and functionally improved SMs have been theoretically designed in previous studies. However, the synthesizability of these derivatives has barely been proven. Thus, this study developed a method to verify the synthesizability of previously designed SM derivatives using machine learning, 2D-QSAR, 3D-QSAR, and high-throughput density functional theory in order to screen for synthesizable, high-performance (odor sensitivity), and environmentally friendly SM derivatives. In this study, three SM derivatives (i.e., D52, D37, and D25) were screened and recommended due to their good performances (i.e., high synthesizability and odor sensitivity; low abortion risk; and bioaccumulation ability in skin keratin). In addition, the synthesizability mechanism of SM derivatives was also analyzed. Results revealed that high intramolecular hydrogen bond strength, electrostatic interaction, qH⁺ value, energy gap, and low E_HOMO would lead to a higher synthesizability of SMs and their derivatives. This study broke the synthesizability bottleneck of theoretically designed environment-friendly SM derivatives and advanced the mechanism of screening functional derivatives.

A new perspective to improve the treatment of Lianhuaqingwen on COVID-19 and prevent the environmental health risk of medication

Lianhuaqingwen (LH), one traditional Chinese medicine (TCM), has been used to treat the coronavirus disease 2019 (COVID-19), but its ecotoxicity with potential human health security has not been well investigated. To overcome such adverse effects and improve its medication efficacy, an intelligent multi-method integrated dietary scheme, screening, and performance evaluation approach was developed. Thirteen LH compounds were selected, and the main protease (Mpro) was used as the potential drug target. Resulted information showed that the more compounds of LH added, the higher medication efficacy obtained using multi-method integrated screening system, expert consultation method, and molecular dynamics simulation. Pharmacodynamic mechanism analysis showed that low total energy and polar surface area of LH active compound (i.e., β-sitosterol) will contribute to the best therapeutic effect on COVID-19 using quantitative structure-activity relationships (QSAR) and sensitivity models. Additionally, when mild COVID-19 patients take LH with the optimum dietary scheme (i.e., β-lactoglobulin, α-lactalbumin, vitamin A, vitamin B, vitamin C, carotene, and vitamin E), the medication efficacy were significantly improved (23.58%). Pharmacokinetics and toxicokinetics results showed that LH had certain human health risks and ecotoxicity. This study revealed the multi-compound interaction mechanism of LH treatment on COVID-19, and provided theoretical guidance for improving therapeutic effect, evaluating TCM safety, and preventing human health risk.

Coupling strategies for ecotoxicological assessment of neonicotinoid insecticides based on their selective lethal effects: Design, screening, and regulation

The recently recognized adverse environmental and toxic effects of neonicotinoid insecticides (NNIs) on non-target organisms are alarming. A comprehensive design, screening, and regulatory system was developed to generate NNI derivatives and mutant receptors with selective-ecotoxicological effects to overcome such adverse effects. For ligand design, taking ACE-09 derivative as an example, the toxicity on non-target animals (aboveground: bees; underground: earthworms), plant absorption, and soil absorption decreased by 4.80% and 13.7%, 10.0%, and 121%, while the toxicity on target animals (aboveground: aphids; underground: B. odoriphagas), plant metabolism, and soil degradation increased by 70.2% and 51.7%, 5.08%, and 8.28%. For receptor modification, the ability of mutants to absorb ACE-09 derivative decreased by 31.0%, while the ability of mutants to metabolize ACE-09 derivative increased by 28.0% in scenario 2 (mainly plant selectivity); the ability of mutants to degrade ACE-09 derivative increased by 11.6% in scenario 3 (mainly soil selectivity). The above results indicated that the selective-ecotoxicological effects of ligand design and receptor modification were both improved. Additionally, the combined effects of the ACE-09 derivative on plant absorption and metabolic mutants improved by 31.1% and 31.4% in scenario 2, respectively, while the effect on microbial degradation mutant improved by 14.9%, indicating that there was a synergistic effect between ligand design and receptor modification. Finally, based on the interaction between the ACE-09 derivative and mutants, the optimal environmental factors that improved the selectivity of their ecotoxicological effects were determined. For example, alternate application of nitrogen and phosphorus fertilizers effectively reduced the oxidative damage to plants caused by NNI residues. The novel ligand-receptor joint modification method, combined with the regulation of environmental factors under multiple scenarios, can biochemically address the ecotoxicological concern and highlight the harmful effects of pesticides on the environment and non-target organisms.

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.

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.

Application of a 2D-QSAR with a sine normalization method for the biodegradation of fluoroquinolones to poison cyanobacteria

Cyanobacteria are photosynthetic autotrophic aquatic prokaryotes. One of the methods for controlling cyanobacterial blooms is to destroy the phycobiliproteins required for photosynthesis. In this study, to improve the biodegradation of the fluoroquinolones through inhibit cyanobacteria, the molecular docking scores of 32 fluoroquinolones (FQs) with four categories of phycobiliproteins from cyanobacteria were calculated after sine normalization to characterize the binding ability between them. A two-dimensional quantitative structure-activity relationship (2D-QSAR) model was constructed based on the comprehensive scores. Danofloxacin (DAN) with the highest comprehensive score was chosen for molecular modification. When docking with four categories of phycobiliproteins from cyanobacteria, the docking values of DAN-11 and DAN-16 were increased up to 35.75%. Moreover, their functional characteristics and environmentally friendly predictive values were improved. When the DAN-11 and DAN-16 molecules docked with the other cyanobacterial phycobiliproteins, indicating that the designed DAN derivatives had general applicability to poison cyanobacteria, the weak interaction forces might increase the binding ability between the DAN derivatives and the receptor phycobiliprotein compared with the target molecule.

Combined toxicity characteristics and regulation of residual quinolone antibiotics in water environment

In this study, the mixture toxicity index method was used to evaluate the combined toxicity of residual Quinolones (QNs) on algae in twelve groups of water environment reported in the literature. The selected three sets of data (II, Ⅺ, and Ⅻ) combined with full factorial design method were used to analyze the significance of the combined toxicity. Subsequently, molecular docking was used to reveal the significant mechanism of the primary effect of the combined toxicity. Finally, based on the sensitivity analysis method, the acid-base conditions affecting the combined toxicity were screened, and molecular dynamics simulation was used to control the combined toxicity in the water environment. The results of the mixture toxicity index method showed that the combined toxicity in all the twelve groups of water environments was synergistic. The full factorial design method revealed that ciprofloxacin, norfloxacin, enrofloxacin, lomefloxacin, and their binary combinations from the combined toxicity system of QNs, were the significant factors that caused the synergistic toxicity of QN_S on algae. Molecular docking confirmed that the total number of amino acids, the number of significant amino acids, and hydrogen bonds of QNs toxic targets were significantly related to the synergistic effect of the combined toxicity. In addition, the molecular dynamics simulation showed that the binding energy of residual QNs and toxic targets changes with the acid-base conditions of the water environment. Thus, the combined toxicity can be slowed down or reduced by adequately adjusting the acid-base condition of the water.

Exploring QSAR models for assessment of acute fish toxicity of environmental transformation products of pesticides (ETPPs)

Environmental transformation products of pesticides (ETPPs) have a great deal of ecological impact owing to their ability to cause toxicity to the aquatic organisms, which can then be translated to the humans. The limited experimental data on biochemical and toxic effects of ETPPs, the high test costs together with regulatory limitations and the international push to reduce animal testing encourage greater dependence on predictive in silico techniques like quantitative structure-activity relationship (QSAR) models. The aim of the present work was to explore the key structural features, which regulate the toxicity towards fishes, for 85 ETPPs using a partial least squares (PLS) regression based chemometric model developed according to Organisation for Economic Co-operation and Development (OECD) guidelines. The model was extensively validated using both internal and external validation metrics, and the results so obtained justify the reliability and usefulness of the developed model (Q² = 0.648, R²_pred or Q²_F1 = 0.734 and Q²_F2 = 0.733). From the developed model, we can conclude that lipophilicity, polarity, presence of branching and the functional form of O-atom in the transformed structures of pesticides are the important features that are to be considered during ecotoxicity assessment of ETPPs. The information obtained from the descriptors of the developed model could be utilized in the future for assessing ETPPs with the benefit of providing an early warning of their potentially detrimental effect on fishes for regulatory purposes.

Highly biodegradable fluoroquinolone derivatives designed using the 3D-QSAR model and biodegradation pathways analysis

A three-dimensional quantitative structure-activity relationship (3D-QSAR) model was established based on molecular structures and docking scores (representing the biodegradability); the scores were obtained for 23 fluoroquinolones (FQs) and the oxidoreductase (PDB ID: 1YZP) of Phanerochaete chrysosporium in the aerobic process of municipal wastewater treatment plants. In the Comparative Molecular Field Analysis (CoMFA) model, q² was 0.516 and r²_pred was 0.727, which showed that the model was reliable and robust. The modification information obtained by the contour maps showed that introducing electronegative, bulky or electropositive groups at different active sites could increase the biodegradability of fluoroquinolone derivatives. Using levofloxacin (LEV) as a modified molecule, 35 fluoroquinolone derivatives with higher biodegradability than LEV were designed. After the evaluation of genotoxicity, bioconcentration and photodegradation, Derivative-15, with higher biodegradability (increased by 27.85%), higher genotoxicity, higher photodegradation and lower bioconcentration, was identified as the most environmentally friendly fluoroquinolone derivative. The 2D-QSAR model of FQ biodegradability was established through the quantization parameters, and q⁺ was identified as the main parameter affecting the biodegradability of FQs through sensitivity analysis. In addition, the docking results of LEV and Derivative-15 with the oxidoreductase in P. chrysosporium showed that the electrostatic field force between Derivative-15 and the amino acid residues promoted the binding of the donor to the receptor protein, thereby increasing the biodegradability of Derivative-15. Additionally, molecular dynamics simulations revealed that the enhancement of the electrostatic field force with Derivative-15 could promote the binding of the ligand to the receptor, which was basically consistent with the conclusion of molecular docking. Finally, the three microbial degradation pathways of LEV and Derivative-15 were also proposed. The total energy barrier value of the pathway with the lowest total energy barrier of biodegradation was reduced by 32.07%, which was basically consistent with the enhancement of biodegradability of Derivative-15.

The synthesis and biological evaluation of virtually designed fluoroquinolone analogs against fluoroquinolone-resistantEscherichia coliintended for UTI treatment

Synthesis and evaluvate the supercoiling activity of the virtually screened novel fluoroquinolone analogs against fluoroquinolone-resistantEscherichia colifor the treatment of urinary tract infections (UTIs).