A predictive toolset for the identification of degradation pattern and toxic hazard estimation of multimeric hazardous compounds persists in water bodies

Laccase-based biocatalytic systems application in sustainable degradation of pharmaceutically active contaminants

The outflow of pharmaceutically active chemicals (PhACs) exerts a negative impact on biological systems even at extremely low concentrations. For instance, enormous threats to human and aquatic species have resulted from the widespread use of antibiotics in ecosystems, which stimulate the emergence and formation of antibiotic-resistant bacterial species and associated genes. Additionally, it is challenging to eliminate these PhACs by employing conventional physicochemical water treatment techniques. Enzymatic approaches, including laccase, have been identified as a promising alternative to eliminate a broad array of PhACs from water matrices. However, their application in environmental bioremediation is hindered by several factors, including the enzyme's stability and its location in the aqueous environment. Such obstacles may be surmounted by employing laccase immobilization, which enables enhanced stability (including inactivation caused by the substrate), and thus improved catalysis. This review emphasizes the potential hazards of PhACs to aquatic organisms within the detection concentration range of ngL-1 to µgL-1, as well as the deployment of laccase-based multifunctional biocatalytic systems for the environmentally friendly mitigation of anticancer drugs, analgesics/NSAIDs, antibiotics, antiepileptic agents, and beta blockers as micropollutants. This approach could reduce the underlying toxicological consequences. In addition, current developments, potential applications, and viewpoints have focused on computer-assisted investigations of laccase-PhACs binding at enzyme cavities and degradability prediction.

SwissADME studies and Density Functional Theory (DFT) approaches of methyl substituted curcumin derivatives

Research suggests curcumin's safety and efficacy, prompting interest in its use for treating and preventing various human diseases. The current study aimed to predict drag ability of methyl substituted curcumin derivatives (BL1 to BL4) using SwissADME and Density Functional Theory (DFT) approaches. The curcumin derivatives investigated mostly adhere to Lipinski's rule of five, with molecular properties including MW, F. Csp3, nHBA, nHBD, and TPSA falling within acceptable limits. The compounds demonstrating high lipophilicity while poor water solubility. The pharmacokinetic evaluation revealed favorable gastrointestinal absorption and blood-brain barrier permeation while none were identified as substrates for P-glycoprotein, however, revealed inhibitory actions against various cytochrome P450 enzymes. Additionally, all derivatives exhibited a consistent bioavailability score of 0.55. Similarly, the DFT computations of the compounds of the curcumin derivatives were conducted at B3LYP/6-311 G** level to predict and then assess the key electronic characteristics underlying the bioactivity. Accordingly, the BL4 molecule (ΔEgap= 4.105 eV) would prefer to interact with the external molecular system more than the other molecules due to having the biggest energy gap. The ΔNmax (2.328 eV) and Δεback-donat. (-0.446 eV) scores implied that BL1 would have more charge transfer capability and the lowest stability via back donation among the compounds. In short, the derivative (BL1 to BL4) exhibited strong extrinsic therapeutic properties and therefore stand eligible for further in vitro and in vivo studies.

Engineering non-conservative substrate recognition sites of extradiol dioxygenase: Computation guided design to diversify and accelerate degradation of aromatic compounds

Extradiol dioxygenases (EDOs) catalyzing meta-cleavage of catecholic compounds promise an effective way to detoxify aromatic pollutants. This work reported a novel scenario to engineer our recently identified Type I EDO from Tcu3516 for a broader substrate scope and enhanced activity, which was based on 2,3-dihydroxybiphenyl (2,3-DHB)-liganded molecular docking of Tcu3516 and multiple sequence alignment with other 22 Type I EDOs. 11 non-conservative residues of Tcu3516 within 6 Å distance to the 2,3-DHB ligand center were selected as potential hotspots and subjected to semi-rational design using 6 catecholic analogues as substrates; the mutants V186L and V212N returned with progressive evolution in substrate scope and catalytic activity. Both mutants were combined with D285A for construction of double mutants and final triple mutant V186L/V212N/D285A. Except for 2,3-DHB (the mutant V186L/D285A gave the best catalytic performance), the triple mutant prevailed all other 5 catecholic compounds for their degradation; affording the catalytic efficiency kcat/Km value increase by 10-30 folds, protein Tm (structural rigidity) increase by 15 °C and the half-life time enhancement by 10 times compared to the wild type Tcu3516. The molecular dynamic simulation suggested that a stabler core and a more flexible entrance are likely accounting for enhanced catalytic activity and stability of enzymes.

Prediction of molecular-specific mutagenic alerts and related mechanisms of chemicals by a convolutional neural network (CNN) model based on SMILES split

Structural alerts (SAs) are essential to identify chemicals for toxicity evaluation and health risk assessment. We constructed a novel SMILES split-based deep learning model (SSDL) that was trained and verified with 5850 chemicals from the ISSSTY database and 384 external test chemicals from published papers. The training accuracy was above 0.90 and the evaluation metrics (precision, recall and F1-score) all reached 0.78 or above on both internal and external test chemicals. In this model, the molecular-specific fragment importance of chemicals was first quantified independently. Then, the SA identification method based on the importance of these fragments was statistically analyzed and verified with the ISSSTY test and external test chemicals containing one of 28 typical SAs, and most of the performances were better than that of expert rules. Furthermore, a mutagenicity mechanism prediction method was developed using 237 chemicals with four known mutagenic mechanisms based on molecular similarity calibrated by the SSDL method and fragment importance, which significantly improved accuracy in three mechanisms and had comparable accuracy in the other one compared to traditional methods. Overall, the SSDL model quantifying fragment toxicity within molecules would be a novel potentially powerful tool in the determination and visualization of molecular-specific SAs and the prediction of mutagenicity mechanisms for environmental or industrial compounds and drugs.

Assessment of the Presence of Transformation Products of Certain Pharmaceutical Products (Psychotropic Family) by Suspect and Non-Targeted HRMS Screening in Wastewater Treatment Plants

Aquatic environments are the final receptors of human emissions and are therefore contaminated by molecules, such as pharmaceuticals. After use, these compounds and their metabolites are discharged to wastewater treatment plants (WWTPs). During wastewater treatment, compounds may be eliminated or degraded into transformation products (TPs) or may be persistent. The aim of this study was to develop an analytical method based on high resolution mass spectrometry (HRMS) for the identification of six psychotropic drugs that are widely consumed in France and present in WWTPs, as well as their potential associated metabolites and TPs. Four out of six psychotropic drugs and between twenty-five and thirty-seven potential TPs were detected in wastewater, although this was based on full scan data. TPs not reported in the literature and specific to the study sites and therefore to the wastewater treatment processes were tentatively identified. For the selected drugs, most known and present TPs were identified, such as desmethylvenlafaxine or norcitalopram. Moreover, the short fragmentation study led rather to the identification of several TPs of carbamazepine as ubiquitous persistent TPs.

Structural insights, biocatalytic characteristics, and application prospects of lignin-modifying enzymes for sustainable biotechnology

Lignin modifying enzymes (LMEs) have gained widespread recognition in depolymerization of lignin polymers by oxidative cleavage. LMEs are a robust class of biocatalysts that include lignin peroxidase (LiP), manganese peroxidase (MnP), versatile peroxidase (VP), laccase (LAC), and dye-decolorizing peroxidase (DyP). Members of the LMEs family act on phenolic, non-phenolic substrates and have been widely researched for valorization of lignin, oxidative cleavage of xenobiotics and phenolics. LMEs implementation in the biotechnological and industrial sectors has sparked significant attention, although its potential future applications remain underexploited. To understand the mechanism of LMEs in sustainable pollution mitigation, several studies have been undertaken to assess the feasibility of LMEs in correlating to diverse pollutants for binding and intermolecular interactions at the molecular level. However, further investigation is required to fully comprehend the underlying mechanism. In this review we presented the key structural and functional features of LMEs, including the computational aspects, as well as the advanced applications in biotechnology and industrial research. Furthermore, concluding remarks and a look ahead, the use of LMEs coupled with computational framework, built upon artificial intelligence (AI) and machine learning (ML), has been emphasized as a recent milestone in environmental research.

Assessing chemical hazard and unraveling binding affinity of priority pollutants to lignin modifying enzymes for environmental remediation

Lignin-modifying enzymes (LMEs) are impactful biocatalysts in environmental remediation applications. However, LMEs-assisted experimental degradation neglects the molecular basis of pollutant degradation. Furthermore, throughout the remediation process, the inherent hazards of environmental pollutants remain untapped for in-depth toxicological endpoints. In this investigation, a predictive toxicological framework and a computational framework adopting LMEs were employed to assess the hazards of Priority Pollutants (PP) and its possible LMEs-assisted catalytic screening. The potential hazardous outcomes of PP were assessed using Quantitative structure-activity relationship (QSARs)-based techniques including Toxtree, ECOSAR, and T.E.S.T. tools. Toxicological findings revealed positive outcomes in a multitude of endpoints for all PP. The PP compound 2,3,7,8-TCDD (dioxin) was found to exhibit the lowest concentration of aquatic toxicity implementing aquatic model systems; LC50 as 0.01, 0.01, 0.04 (mg L-1) for Fish (96 H), Daphnid (48 H), Green algae (96 H) respectively. T.E.S.T. results revealed that chloroform, and 2-chlorophenol both seem to be developmental toxicants. Subsequently, LMEs-assisted docking procedure was employed in predictive mitigation of PP. The docking approach as predicted degradation revealed the far lowest docking energy score for Versatile peroxidase (VP)- 2,3,7,8-TCDD docked complex with a binding energy of -9.2 (kcal mol-1), involved PHE-46, PRO-139, PRO-141, ILE-148, LEU-165, HIS-169, LEU-228, MET-262, and MET-265 as key interacting amino acid residues. Second most ranked but lesser than VP, Lignin peroxidase (LiP)- 2,3,7,8-TCDD docked complex exhibited a rather lower binding affinity score (-8.8 kcal mol-1). Predictive degradation screening employing comparative docking revealed varying binding affinities, portraying that each LMEs member has independent feasibility to bind PP as substrate. Predictive findings endorsed the hazardous nature of associated PP in a multitude of endpoints, which could be attenuated by undertaking LMEs as a predictive approach to protect the environment and implement it in regulatory considerations.

Synthesis, Characterization, and Pharmacokinetic Studies of Thiazolidine-2,4-Dione Derivatives

Various derivatives of thiazolidine-2,4-dione (C1–C5) were designed and synthesized by chemical reaction with 4-nitrobenzaldehyde using Knoevenagel reaction conditions which results in the reduction of nitro group to amine and further modification results in target compounds. The chemical structures of all the 2,4-thiazolidinedione derivatives have been elucidated by 1H and 13C NMR spectroscopy. These compounds were further characterized by in silico ADME (absorption, distribution, metabolism, and excretion) studies. The pharmacokinetic properties were assessed by SwissADME software. The in silico ADME (absorption, distribution, metabolism, and excretion) assessment reveals that all derivatives (C1 to C5) have 5 to 7 rotatable bonds. Lipophilicity and water solubility showed that C1, C2, and C4 are water soluble except for C3 and C5 which are moderately soluble. All the compounds have high GI absorption except C3. None of the derivatives are blood-brain barrier permeant. Drug metabolism of TZDs derivatives showed that C3 was identified as an inhibitor of CYP2C9 and C5 as an inhibitor of CYP1A2 and CYP2C19. Drug likeness properties indicate that C1 has only one violation of the Ghose rule while C3 has violations in the Ghose and Egan rules. The in silico pharmacokinetic studies revealed high GI absorption and the inability to pass blood-brain barrier which can be further assessed by in vitro and in vivo antihyperglycemic activity. This study will contribute to providing TZDs derivatives with an improved pharmacokinetic profile and decreased toxicity.

Thermodynamic valorisation of lignocellulosic biomass green sorbents for toxic pollutants removal

Various toxic heavy metals have become hazardous to human health as well as the environment. This research has been focused on a biosorption/bioremoval process of chromium (III), copper (II) and lead (II) ions from an aqueous solution by utilizing lignocellulosic biomass of Citrus limon peel (CLP) powder. CLP powder biomass was selected based on dietary fibre components having greater potential to remove target heavy metal ions in order to purify wastewater by following the eco-friendly biosorption method. At optimum conditions, the observed maximum removal efficiency of 97.47, 87.13 and 95.71% for Cr, Cu and Pb ions, respectively, was observed. An investigation has been made as a work of pH, CLP amount and temperature. The presented bio-removal processes by prepared CLP biosorbent manifested as a temperature-independent. Langmuir isotherm model was found an excellent fit of the isotherm data for tested systems with the calculated biosorption capacities of 111.11 (Cr), 76.92 (Cu) and 100 (Pb) mg/g. The positive ΔH values for selected target heavy metal ions, except lead ions, confirmed that the reaction was spontaneous and endothermic. A cooperative mechanism of second-order and intraparticle diffusion models during the adsorption processes of all three target ions was established with a higher coefficient of determination and more closely anticipated take-up (adsorption capacity). Furthermore, the interaction of -OH and -COOH functional groups of CLP that have a major role in the removal of Cr, Cu and Pb ions from single-ion aqueous solution and/or a surface biosorption was confirmed based on the results presented by SEM-EDS and FTIR analysis. Analysis from XRD revealed peak corresponding to amorphous cellulose type I as observed by FT-IR analysis.