An evaluation of the implementation of the Cramer classification scheme in the Toxtree software

Investigation of ritonavir analogs antiretroviral natural compounds against SARS-CoV-2 envelope protein

Since the pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported from Wuhan, China, there has been a surge in scientific research to find a permanent cure for the disease. The main challenge in effective drug discovery is the continuously mutating nature of the SARS-CoV-2 virus. Thus, we have used the I-TASSER modeling to predict the structure of the SARS-CoV-2 viral envelope protein followed by combinatorial computational assessment to predict its putative potential small molecule inhibitors. As early treatment with ritonavir in combination was associated with faster time to clinical improvement and/or virological clearance, we aimed to retrieve analogs of ritonavir to find ideal inhibitors for SARS-CoV-2 viral envelope protein. The collected ligands were screened against the predicted binding pocket of viral envelope protein using extra precision (XP) docking protocol and the first four best-docked compounds were studied for complex stability using 300 ns all-atom molecular dynamics simulations embedding within the cellular membrane. Among the selected compounds, ZINC64859171 and ZINC1221429 showed considerable stability and interactions by comparison to the reference compound, i.e., Ritonavir (ZINC3944422). Moreover, the post-simulation analysis suggested the considerable binding affinity and induced conformation changes in the respective docked complexes against Ritonavir. Altogether, the obtained results demonstrated the putative potential of screened ritonavir analogs, i.e., ZINC64859171, against the envelope protein of SARS-CoV-2 and can be considered for further drug development in the treatment of the COVID-19 pandemic.Communicated by Ramaswamy H. Sarma.

Establishment of a threshold of toxicological concern for pharmaceutical intermediates based on historical repeat-dose data and its application in setting health based exposure limits

Availability of toxicological data for pharmaceutical intermediates (IMs) used in the manufacture of small molecules is often limited. Scarcity of data - in particular, repeat-dose toxicity (RDT) - renders the calculation of health-based exposure limits (HBELs) problematic. Establishment of HBELs, including occupational exposure limits (OELs) and permitted daily exposures (PDEs) facilitating worker and patient safety respectively, is however essential. Historic 28-day oral rodent toxicity data was analysed for 103 GSK isolated IMs. No-observed (adverse) effect levels (NO(A)ELs) and critical effects were extracted. The 5th percentile (p05) of the NO(A)EL distribution was 15 mg/kg/day. Substance specific HBELs were calculated, selecting the NO(A)EL as the Point of Departure (PoD); 99% of IMs (n = 102) were assigned an oral PDE ≥1000 μg/day and OEL ≥100 μg/m3. A default oral PDE of 1000 μg/day and OEL of 100 μg/m3 is thus proposed for IMs. Evaluation of an additional PoD - benchmark dose lower confidence limit (BMDL) - further supported the default HBELs. The default oral PDE can also serve as a threshold of toxicological concern (TTC) for IMs. Default limits can aid in setting HBELs for novel data-poor IMs, as well as supporting waiving of RDT in the future through read-across.

Molecular docking and in silico analysis of the pharmacokinetics, toxicological profile and differential gene expression of bioactive compounds from Cyrtopodium glutiniferum

The genus Cyrtopodium, from the Orchidaceae family, is widely used for its therapeutic properties in the treatment of tuberculosis, abscesses, urinary infection, and colds. C. glutiniferum, one of the species of this genus, is endemic in Brazil and largely used in herbal medicine. Thus, it is of great interest to recognize its composition, the properties of the molecules found in it. This study aimed to perform the in silico analysis of the main compounds from C. glutiniferum, on the platforms pKCSM, SwissADME, LAZAR, CLC-pred, ToxTree, DIGEPred, STRING, and Cytoscape. Further than this, the molecular docking was performed. The compounds present in the aqueous extract of C. glutiniferum were identified by UHPLC-MS/MS, finding Arbutin, Caffeic acid 4-O-glucoside, and Dihydroformononetin as the three most abundant molecules. The evaluation of the gastrointestinal absorption of Dihydroformononetin is given as high, also managing to cross the blood-brain barrier, while Arbutin can only be absorbed by the gastrointestinal tract and Caffeic acid 4-O-glucoside had very low absorption. Further analysis showed that Arbutin and Dihydroformononetin are possible leading molecules for drug synthesis, according to the prediction. Toxicological aspects were analysed, and no adverse effects were noted, but there were divergences in the mutagenic prediction of Arbutin and Dihydroformononetin, having different results in the used platforms, demonstrating that a cautious analysis and data insertion is needed in these tools to optimize them. The analysis of the differentially expressed genes predicted that the compounds can regulate several genes, including some genes associated with carcinogenesis and inflammation. The Molecular docking analysis showed high binding affinities of the molecules with different proteins. Therefore, C. glutiniferum demonstrates the potential to be used as a phytotherapeutic. The same was given through the in silico analysis of the three compounds found in the orchid, that show good individual potential.

A Novel Machine Learning Model and a Web Portal for Predicting the Human Skin Sensitization Effects of Chemical Agents

Skin sensitization is a significant concern for chemical safety assessments. Traditional animal assays often fail to predict human responses accurately, and ethical constraints limit the collection of human data, necessitating a need for reliable in silico models of skin sensitization prediction. This study introduces HuSSPred, an in silico tool based on the Human Predictive Patch Test (HPPT). HuSSPred aims to enhance the reliability of predicting human skin sensitization effects for chemical agents to support their regulatory assessment. We have curated an extensive HPPT database and performed chemical space analysis and grouping. Binary and multiclass QSAR models were developed with Bayesian hyperparameter optimization. Model performance was evaluated via five-fold cross-validation. We performed model validation with reference data from the Defined Approaches for Skin Sensitization (DASS) app. HuSSPred models demonstrated strong predictive performance with CCR ranging from 55 to 88%, sensitivity between 48 and 89%, and specificity between 37 and 92%. The positive predictive value (PPV) ranged from 84 to 97%, versus negative predictive value (NPV) from 22 to 65%, and coverage was between 75 and 93%. Our models exhibited comparable or improved performance compared to existing tools, and the external validation showed the high accuracy and sensitivity of the developed models. HuSSPred provides a reliable, open-access, and ethical alternative to traditional testing for skin sensitization. Its high accuracy and reasonable coverage make it a valuable resource for regulatory assessments, aligning with the 3Rs principles. The publicly accessible HuSSPred web tool offers a user-friendly interface for predicting skin sensitization based on chemical structure.

Data-driven toxicity prediction in drug discovery: Current status and future directions

Early toxicity assessment plays a vital role in the drug discovery process on account of its significant influence on the attrition rate of candidates. Recently, constant upgrading of information technology has greatly promoted the continuous development of toxicity prediction. To give an overview of the current state of data-driven toxicity prediction, we reviewed relevant studies and summarized them in three main respects: the features and difficulties of toxicity prediction, the evolution of modeling approaches, and the available tools for toxicity prediction. For each part, we expound the research status, existing challenges, and feasible solutions. Finally, several new directions and suggestions for toxicity prediction are also put forward.

Evaluating the consistency of judgments derived through both in silico and expert application of the Cramer classification scheme

The Cramer classification scheme has emerged as one of the most extensively-adopted predictive toxicology tools, owing in part to its employment for chemical categorisation within threshold of toxicological concern evaluation. The characteristics of several of its rules have contributed to inconsistencies with respect to degree of hazard attributed to common (particularly food-relevant) substances. This investigation examines these discrepancies, and their origins, raising awareness of such issues amongst users seeking to apply and/or adapt the rule-set. A dataset of over 3000 compounds was assembled, each with Cramer class assignments issued by up to four groups of industry and academic experts. These were complemented by corresponding outputs from in silico implementations of the scheme present within Toxtree and OECD QSAR Toolbox software, including a working of a "Revised Cramer Decision Tree". Consistency between judgments was assessed, revealing that although the extent of inter-expert agreement was very high (≥97%), general concordance between expert and in silico calls was more modest (∼70%). In particular, 22 chemical groupings were identified to serve as prominent sources of disagreement, the origins of which could be attributed either to differences in subjective interpretation, to software coding anomalies, or to reforms introduced by authors of the revised rules.

Exploring the Artificial Intelligence and Its Impact in Pharmaceutical Sciences: Insights Toward the Horizons Where Technology Meets Tradition

The technological revolutions in computers and the advancement of high-throughput screening technologies have driven the application of artificial intelligence (AI) for faster discovery of drug molecules with more efficiency, and cost-friendly finding of hit or lead molecules. The ability of software and network frameworks to interpret molecular structures' representations and establish relationships/correlations has enabled various research teams to develop numerous AI platforms for identifying new lead molecules or discovering new targets for already established drug molecules. The prediction of biological activity, ADME properties, and toxicity parameters in early stages have reduced the chances of failure and associated costs in later clinical stages, which was observed at a high rate in the tedious, expensive, and laborious drug discovery process. This review focuses on the different AI and machine learning (ML) techniques with their applications mainly focused on the pharmaceutical industry. The applications of AI frameworks in the identification of molecular target, hit identification/hit-to-lead optimization, analyzing drug-receptor interactions, drug repurposing, polypharmacology, synthetic accessibility, clinical trial design, and pharmaceutical developments are discussed in detail. We have also compiled the details of various startups in AI in this field. This review will provide a comprehensive analysis and outline various state-of-the-art AI/ML techniques to the readers with their framework applications. This review also highlights the challenges in this field, which need to be addressed for further success in pharmaceutical applications.

Physicochemical Stability of Doravirine (Pifeltro®): Characterization of Main Degradation Products and Assessment of Stability of Tablets Repackaged in Single-Dose Unit Containers

Doravarine (DOR) is an antiviral drug with a marketed authorization for the management of occupational blood and body fluid exposure. The currently existing packaging, consisting of multiple unit bottles comprising 30 tablets, is not fully appropriate for daily nominative dispensing at the hospital. This study aims at assessing the impact of the change in packaging on the key attributes of the drug: assay, impurity profile, and dissolution. As the first step, which is not fully depicted in the literature, the main potential impurities that could appear during storage (i.e., degradation products (DPs) of DOR) were characterized using a forced degradation protocol followed by an LC-MS/MS analysis. These results paved the way for in silico toxicological assessment and targeted degradation product profiling. Based on this study, the assessment of the implication of repackaging on the formation of DOR's degradation products should be a primary focus.

Deriving a Continuous Point of Departure for Skin Sensitization Risk Assessment Using a Bayesian Network Model

Regulations of cosmetic ingredients and products have been the most advanced in embracing new approach methodologies (NAMs). Consequently, the cosmetic industry has assumed a forerunner role in the development and implementation of animal-free next-generation risk assessment (NGRA) that incorporates defined approaches (DAs) to assess the skin sensitization potency of ingredients. A Bayesian network DA predicting four potency categories (SkinSens-BN) was constructed against reference Local Lymph Node Assay data for a total of 297 substances, achieving a predictive performance similar to that of other DAs. With the aim of optimally informing risk assessment with a continuous point of departure (PoD), a weighted sum of the SkinSens-BN probabilities for four potency classes (non-, weak, moderate, and strong/extreme sensitizer) was calculated, using fixed weights based on associated LLNA EC3-values. The approach was promising, e.g., the derived PoDs for substances classified as non-sensitizers did not overlap with any others and 77% of PoDs were similar or more conservative than LLNA EC3. In addition, the predictions were assigned a level of confidence based on the probabilities to inform the evaluation of uncertainty in an NGRA context. In conclusion, the PoD derivation approach can substantially contribute to reliable skin sensitization NGRAs.

Discovery and prospects of new heterocyclic Isatin-hydrazide derivative with a novel role as estrogen receptor α degrader in breast cancer cells

Introduction: Isatin, a heterocycle scaffold, is the backbone of many anticancer drugs and has previously been reported to engage multiple cellular targets and mechanisms, including angiogenesis, cell cycle, checkpoint pathways and multiple kinases. Here, we report that a novel isatin derivative, 5i, degrades estrogen receptor alpha (ERα) in estrogen-dependent breast cancer cells. This effect of the isatin nucleus has not been previously reported. Tamoxifen and fulvestrant represent standard therapy options in estrogen-mediated disease but have their own limitations. Isatin-based triple angiokinase inhibitor BIBF1120 (Nintedanib) and multikinase inhibitor Sunitinib (Sutent) have been approved by the FDA. Methods: Keeping this in view, we synthesized a series of N'-(1-benzyl-2-oxo-1, 2-dihydro-3H-indol-3-ylidene) hydrazide derivatives and evaluated them in vitro for antiproliferative activities in MCF-7 (ER+) cell line. We further investigated the effect of the most potent compound (5i) on the Erα through Western Blot Analysis. We used in silico pharmacokinetics prediction tools, particularly pkCSM tool, to assess the activity profiles of the compounds. Results and discussion: Compound 5i showed the best antiproliferative activity (IC50 value; 9.29 ± 0.97 µM) in these cells. Furthermore, 5i downregulated ERα protein levels in a dose-dependent manner in MCF-7. A multifaceted analysis of physicochemical properties through Data Warrior software revealed some prominent drug-like features of the synthesized compounds. The docking studies predicted the binding of ligands (compounds) with the target protein (ERα). Finally, molecular dynamics (MD) simulations indicated stable behavior of the protein-ligand complex between ERα and its ligand 5i. Overall, these results suggest that the new isatin derivative 5i holds promise as a new ERα degrader.

The evaluation of skin sensitization potential of the UVCB substance diisopentyl phthalate by in silico and in vitro methods

Diisopentyl phthalate (DiPeP) is primarily used as a plasticizer or additive within the production of polyvinyl chloride (PVC), and has many additional industrial applications. Its metabolites were recently found in urinary samples of pregnant women; thus, this substance is of concern as relates to human exposure. Depending upon the nature of the alcohol used in its synthesis, DiPeP may exist either as a mixture consisting of several branched positional isomers, or as a single defined structure. This article investigates the skin sensitization potential and immunomodulatory effects of DiPeP CAS No. 84777-06-0, which is currently marketed and classified as a UVCB substance, by in silico and in vitro methods. Our findings showed an immunomodulatory effect for DiPeP in LPS-induced THP-1 activation assay (increased CD54 expression). In silico predictions using QSAR TOOLBOX 4.5, ToxTree, and VEGA did not identify DiPeP, in the form of a discrete compound, as a skin sensitizer. The keratinocyte activation (Key Event 2 (KE2) of the adverse outcome pathway (AOP) for skin sensitization) was evaluated by two different test methods (HaCaT assay and RHE assay), and results were discordant. While the HaCaT assay showed that DiPeP can activate keratinocytes (increased levels of IL-6, IL-8, IL-1α, and ILA gene expression), in the RHE assay, DiPeP slightly increased IL-6 release. Although inconclusive for KE2, the role of DiPeP in KE3 (dendritic cell activation) was demonstrated by the increased levels of CD54 and IL-8 and TNF-α in THP-1 cells (THP-1 activation assay). Altogether, findings were inconclusive regarding the skin sensitization potential of the UVCB DiPeP-disagreeing with the results of DiPeP in the form of discrete compound (skin sensitizer by the LLNA assay). Additional studies are needed to elucidate the differences between DiPeP isomer forms, and to better understand the applicability domains of non-animal methods in identifying skin sensitization hazards of UVCB substances.

Identification of pseudobaptigenin as a novel polyphenol-based multi-target antagonist of different hormone receptors for breast cancer therapeutics

Breast cancer (BC) is one of the most prevalent cancers in the world and is one of the major reasons for the death of women worldwide. BC is majorly categorized based on the presence or absence of three cell receptors ER, PR and HER2. The latest treatment for BC involves interfering with the production and action of hormones such as estrogen and progesterone. These hormones bind with receptors such as ER and PR and enhance the growth and proliferation of the BC cells. Although the available are effective, the increasing resistance and side effects related to hormonal imbalance are significant and hence there is a need for designing. On the other hand, plant-derivative products have gained a lot of popularity for their promising anti-cancerous activities. Polyphenols are one such group of plant derivatives that have proven to be useful against cancer. In the present study, an in-silico approach was used to search for a polyphenol that can inhibit ER. In this work, a total of 750 polyphenols were taken into consideration. This number was narrowed down to 55, based on their ADMET properties. These 55 polyphenols were then docked to the receptors, ER, PR and HER2. The molecular docking was followed by Molecular Dynamics (MD) simulations. Based on molecular docking and MD simulation results it was concluded that Pseudobaptigenin has the potential to be an inhibitor of ER, PR and HER2.Communicated by Ramaswamy H. Sarma.

Pharmaceutical and Trace Metal Interaction within the Water-Soil-Plant Continuum: Implications for Human and Soil Health

Unplanned water reuse for crop irrigation may pose a global health risk due to the entry of contaminants into the food chain, undesirable effects on crop quality, and impact on soil health. In this study, we evaluate the impact derived from the co-occurrence of pharmaceuticals (Phs), trace metals (TMs), and one metalloid within the water-soil-plant continuum through bioassay experiments with Lactuca sativa L. Results indicate that the co-occurrence of Phs and TMs has synergistic or antagonistic effects, depending on target contaminants and environmental compartments. Complex formations between drugs and TMs may be responsible for enhanced sorption onto the soil of several Phs and TMs. Concerning plant uptake, the co-occurrence of Phs and TMs exerts antagonistic and synergistic effects on carbamazepine and diazepam, respectively. With the exception of Cd, drugs exert an antagonistic effect on TMs, negatively affecting their uptake and translocation. Drug contents in lettuce edible parts do not pose any threat to human health, but Cd levels exceed the maximum limits set for leafy vegetable foodstuffs. Under Ph-TM conditions, lettuce biomass decreases, and a nutrient imbalance is observed. Soil enzyme activity is stimulated under Ph-TM conditions (β-galactosidase) and Ph and Ph-TM conditions (urease and arylsulfatase), or it is not affected (phosphatase).

Toxicological evaluation of microbial secondary metabolites in the context of European active substance approval for plant protection products

Risk assessment (RA) of microbial secondary metabolites (SM) is part of the EU approval process for microbial active substances (AS) used in plant protection products (PPP). As the number of potentially produced microbial SM may be high for a certain microbial strain and existing information on the metabolites often are low, data gaps are frequently identified during the RA. Often, RA cannot conclusively clarify the toxicological relevance of the individual substances. This work presents data and RA conclusions on four metabolites, Beauvericin, 2,3-deepoxy-2,3-didehydro-rhizoxin (DDR), Leucinostatin A and Swainsonin in detail as examples for the challenging process of RA. To overcome the problem of incomplete assessment reports, RA of microbial AS for PPP is in need of new approaches. In view of the Next Generation Risk Assessment (NGRA), the combination of literature data, omic-methods, in vitro and in silico methods combined in adverse outcome pathways (AOPs) can be used for an efficient and targeted identification and assessment of metabolites of concern (MoC).

Analysis of non-mutagenic substances in the context of drug impurity assessment - Few are potent toxicants

ICH Q3A/B guidelines provide qualification thresholds for impurities or degradation products in new drug substances and products. However, the guidelines note that certain impurities/degradation products may warrant further safety evaluation for being unusually potent or toxic. The purpose of this study was to confirm that especially toxic non-mutagenic compounds are rare and to identify classes of compounds that could warrant lower qualification thresholds. A total of 2815 compounds were evaluated, of which 2213 were assessed as non-mutagenic. For the purpose of this analysis, compounds were considered potent when the point of departure was ≤0.2 mg/kg/day based on the qualification threshold (1 mg/day or 0.02 mg/kg/day for a 50 kg human) in a new drug substance, with an additional 10-fold margin. Only 54 of the entire set (2.4%) would be considered potent based on this conservative potency analysis, confirming that the existing ICH Q3A/B qualification thresholds are appropriate for the majority of impurities. If the Q3A/B threshold, without the additional 10-fold margin is used, 14 compounds (0.6%) are considered "highly potent". Very few non-mutagenic structural classes were identified, including organothiophosphates and derivatives, polychlorinated benzenes and polychlorinated polycyclic aliphatics, that correlate with potential high potency, consistent with prior publications.

Prioritizing of potential environmental exposure carcinogens beyond IARC group 1-2B based on weight of evidence (WoE) approach

Environmental exposures are the main cause of cancer, and their carcinogenicity has not been fully evaluated, identifying potential carcinogens that have not been evaluated is critical for safety. This study is the first to propose a weight of evidence (WoE) approach based on computational methods to prioritize potential carcinogens. Computational methods such as read across, structural alert, (Quantitative) structure-activity relationship and chemical-disease association were evaluated and integrated. Four different WoE approach was evaluated, compared to the best single method, the WoE-1 approach gained 0.21 and 0.39 improvement in the area under the receiver operating characteristic curve (AUC) and Matthew's correlation coefficient (MCC) value, respectively. The evaluation of 681 environmental exposures beyond IARC list 1-2B prioritized 52 chemicals of high carcinogenic concern, of which 21 compounds were known carcinogens or suspected carcinogens, and eight compounds were identified as potential carcinogens for the first time. This study illustrated that the WoE approach can effectively complement different computational methods, and can be used to prioritize chemicals of carcinogenic concern.

Computational study on the endocrine-disrupting metabolic activation of Benzophenone-3 catalyzed by cytochrome P450 1A1: A QM/MM approach

Predicting the metabolic activation mechanism and potential hazardous metabolites of environmental endocrine-disruptors is a challenging and significant task in risk assessment. Here the metabolic activation mechanism of benzophenone-3 catalyzed by P450 1A1 was investigated by using Molecular Dynamics, Quantum Mechanics/Molecular Mechanics and Density Functional Theory approaches. Two elementary reactions involved in the metabolic activation of BP-3 with P450 1A1: electrophilic addition and hydrogen abstraction reactions were both discussed. Further conversion reactions of epoxidation products, ketone products and the formaldehyde formation reaction were investigated in the non-enzymatic environment based on previous experimental reports. Binding affinities analysis of benzophenone-3 and its metabolites to sex hormone binding globulin indirectly demonstrates that they all exhibit endocrine-disrupting property. Toxic analysis shows that the eco-toxicity and bioaccumulation values of the benzophenone-3 metabolites are much lower than those of benzophenone-3. However, the metabolites are found to have skin-sensitization effects. The present study provides a deep insight into the biotransformation process of benzophenone-3 catalyzed by P450 1A1 and alerts us to pay attention to the adverse effects of benzophenone-3 and its metabolites in human livers.

MetSim: Integrated Programmatic Access and Pathway Management for Xenobiotic Metabolism Simulators

Xenobiotic metabolism is a key consideration in evaluating the hazards and risks posed by environmental chemicals. A number of software tools exist that are capable of simulating metabolites, but each reports its predictions in a different format and with varying levels of detail. This makes comparing the performance and coverage of the tools a practical challenge. To address this shortcoming, we developed a metabolic simulation framework called MetSim, which comprises three main components. A graph-based schema was developed to allow metabolism information to be harmonized. The schema was implemented in MongoDB to store and retrieve metabolic graphs for subsequent analysis. MetSim currently includes an application programming interface for four metabolic simulators: BioTransformer, the OECD Toolbox, EPA's chemical transformation simulator (CTS), and tissue metabolism simulator (TIMES). Lastly, MetSim provides functions to help evaluate simulator performance for specific data sets. In this study, a set of 112 drugs with 432 reported metabolites were compiled, and predictions were made using the 4 simulators. Fifty-nine of the 112 drugs were taken from the Small Molecule Pathway Database, with the remainder sourced from the literature. The human models within BioTransformer and CTS (Phase I only) and the rat models within TIMES and the OECD Toolbox (Phase I only) were used to make predictions for the chemicals in the data set. The recall and precision (recall, precision) ranked in order of highest recall for each individual tool were CTS (0.54, 0.017), BioTransformer (0.50, 0.008), Toolbox in vitro (0.40, 0.144), TIMES in vivo (0.40, 0.133), Toolbox in vivo (0.40, 0.118), and TIMES in vitro (0.39, 0.128). Combining all of the model predictions together increased the overall recall (0.73, 0.008). MetSim enabled insights into the performance and coverage of in silico metabolic simulators to be more efficiently derived, which in turn should aid future efforts to evaluate other data sets.

A Potential Multitarget Insect Growth Regulator Candidate: Design, Synthesis, and Biological Activity of Novel Acetamido Derivatives Containing Hexacyclic Pyrazole Carboxamides

Insect growth regulators (IGRs) are important green insecticides that disrupt normal growth and development in insects to reduce the harm caused by pests to crops. The ecdysone receptor (EcR) and three chitinases OfChtI, OfChtII, and OfChi-h are closely associated with the molting stage of insects. Thus, they are considered promising targets for the development of novel insecticides such as IGRs. Our previous work identified a dual-target compound 6j, which could act simultaneously on both EcR and OfChtI. In the present study, 6j was first found to have inhibitory activities against OfChtII and OfChi-h, too. Subsequently, taking 6j as a lead compound, 19 novel acetamido derivatives were rationally designed and synthesized by introducing an acetamido moiety into the amide bridge based on the flexibility of the binding cavities of 6j with EcR and three chitinases. Then, their insecticidal activities against Plutella xylostella (P. xylostella), Ostrinia furnacalis (O. furnacalis), and Spodoptera frugiperda (S. frugiperda) were carried out. The bioassay results revealed that most of these acetamido derivatives possessed moderate to good larvicidal activities against three lepidopteran pests. Especially, compound I-17 displayed excellent insecticidal activities against P. xylostella (LC50, 93.32 mg/L), O. furnacalis (LC50, 114.79 mg/L), and S. frugiperda (86.1% mortality at 500 mg/L), significantly better than that of 6j. In addition, further protein validation and molecular docking demonstrated that I-17 could act simultaneously on EcR (17.7% binding activity at 8 mg/L), OfChtI (69.2% inhibitory rate at 50 μM), OfChtII (71.5% inhibitory rate at 50 μM), and OfChi-h (73.9% inhibitory rate at 50 μM), indicating that I-17 is a potential lead candidate for novel multitarget IGRs. This work provides a promising starting point for the development of novel types of IGRs as pest management agents.

Br - nanoconjugate enhances the antibacterial efficacy of nimboloide against Flavobacterium columnare infection in Labeo rohita: A nanoinformatics approach

BACKGROUND

The bacterial pathogen, Flavobacterium columnare causes columnaris disease in Labeo rohita globally. Major effects of this bacterial infection include skin rashes and gill necrosis. Nimbolide, the key ingredient of the leaf extract of Azadirachta indica possesses anti-bacterial properties effective against many microorganisms. Nano-informatics plays a promising role in drug development and its delivery against infections caused by multi-drug-resistant bacteria. Currently, studies in the disciplines of dentistry, food safety, bacteriology, mycology, virology, and parasitology are being conducted to learn more about the wide anti-virulence activity of nimbolide.

METHODS

The toxicity of nimbolide was predicted to determine its dosage for treating bacterial infection in Labeo rohita. Further, comparative 3-D structure prediction and docking studies are done for nimbolide conjugated nanoparticles with several key target receptors to determine better natural ligands against columnaris disease. The nanoparticle conjugates are being designed using in-silico approaches to study molecular docking interactions with the target receptor.

RESULTS

Bromine conjugated nimbolide shows the best molecular interaction with the target receptors of selected species ie L rohita. Nimbolide comes under the class III level of toxic compound so, attempts are made to reduce the dosage of the compound without compromising its efficiency. Further, bromine is also used as a common surfactant and can eliminate heavy metals from wastewater.

CONCLUSION

The dosage of bromine-conjugated nimbolide can be reduced to a non-toxic level and thus the efficiency of the Nimbolide can be increased. Moreover, it can be used to synthesize nanoparticle composites which have potent antibacterial activity towards both gram-positive and gram-negative bacteria. This material also forms a good coating on the surface and kills both airborne and waterborne bacteria.

The comprehensive prediction of carcinogenic potency and tumorigenic dose (TD50) for two problematic N-nitrosamines in food: NMAMPA and NMAMBA using toxicology in silico methods

The identification and toxicological assessment of potential carcinogens is of paramount importance for public health and safety. This study aimed to predict the carcinogenic potency and tumorigenic dose (TD50) for two problematic N-nitrosamines (N-NAs) commonly found in food: N-2-methylpropyl-N-1-methylacetonylnitrosamine (NMAMPA, CAS: 93755-83-0) and N-3-Methylbutyl-N-1-methylacetonylnitrosamine (NMAMBA, CAS: 71016-15-4). To achieve this goal, in silico toxicology methods were employed due to their practical applications and potential in risk assessment. The justification for conducting these studies was incoherent results published by the European Food Safety Authority (EFSA). For this purpose, we applied various in silico tools, including qualitative methods (ToxTree, ProTox II and CarcinoPred-EL) and quantitative methods (QSAR Toolbox and LAZAR) were applied to predict the carcinogenic potency. These tools leverage computational approaches to analyze chemical structures for finding toxicophores and generating predictions, making them efficient alternatives to traditional in vivo experiments. The results obtained indicated that N-NAs are carcinogenic compounds, and quantitative data was obtained in the form of estimated doses of TD50 for the compounds tested.

Understanding intentionally and non-intentionally added substances and associated threshold of toxicological concern in post-consumer polyolefin for use as food packaging materials

The use of post-consumer recycled (PCR) polymers in food contact materials (FCMs) can facilitate achieving a circular economy by reducing environmental waste and landfill accumulation. This study aimed to identify potentially harmful substances, including non-intentionally added substances (NIAS) and unapproved intentionally added substances (IAS), in polyolefin samples from material recovery facilities using gas-chromatography mass-spectrometry. Selected phthalates and bisphenols were quantified by targeted gas-chromatography tandem mass-spectrometry. The analysis detected 9 compounds in virgin polymers and 52 different compounds including alcohols, hydrocarbons, phenols in virgin and hydrocarbons, aromatic, phthalates, organic acids, per- and polyfluoroalkyl substances (PFAS) in PCR polymers. The Cramer classification system was used to assesses the Threshold of Toxicological Concern associated with the detected compounds. The PCR sample showed a slightly higher proportion of Cramer Class III compounds (48.08 %) than the virgin sample (44.44 %), indicating higher toxicity potential. Quantification detected bisphenols only in PCR material including BPA (2.88 ± 0.53 μg/g), BPS (5.12 ± 0.003 μg/g), BPF (3.42 ± 0.01 μg/g), and BADGE (4.638 μg/g). Phthalate concentrations were higher in PCR than virgin samples, with the highest levels detected as DIDP, at 6.18 ± 0.31 μg/g for PCR and 6.04 ± 0.02 for virgin. This study provides critical understanding of the safety and potential risks associated with using PCR polyolefins from different sources in food contact applications.

Effect of pH on UV/H2O2-mediated removal of single, mixed and halogenated parabens from water

Adjusting pH values in aqueous environments can significantly improve the efficiency by which parabens and halo-parabens are removed. In this study, 20 neutral and deprotonated species were selected as models to investigate their pH-dependent removal mechanisms and kinetics by a UV/H2O2 process using density functional theory (DFT). Compared to neutral species, deprotonated species exhibit higher reactivity to HO• due to their high electron cloud density. H atom abstraction (HAA) reactions on the substitution groups are the most favorable pathways for neutral species, while radical adduct formation (RAF) reactions are the most favorable for deprotonated species. Single electron transfer (SET) reactions can be neglected for neutral species, while these reactions become a viable route for deprotonated molecules. The total reaction rate constants range from 1.63 × 109 to 3.74 × 1010 M- 1 s- 1 at pH 7.0, confirming the experimental results. Neutral and weakly alkaline conditions are favorable for the degradation of MeP and halo-parabens in the UV/H2O2 process. The order of removal efficiency at optimum pH is dihalo-parabens > mono-halo-parabens ≈ F, F-MeP > MeP. Furthermore, the transformation products must undergo oxidative degradation due to their high toxicity. Our findings provide new insights into the removal of parabens and their halogenated derivatives from wastewater.

Synthetic azo-dye, Tartrazine induces neurodevelopmental toxicity via mitochondria-mediated apoptosis in zebrafish embryos

Tartrazine (TZ), or E 102 or C Yellow, is a commonly used azo dye in the food and dyeing industries. Its excessive usage beyond permissible levels threatens human health and the aquatic environment. While previous studies have reported adverse effects such as mutagenicity, carcinogenicity, and reproductive toxicity. Our study aimed to comprehensively evaluate the developmental neurotoxicity of TZ exposure via biochemical and behavioral examinations and explored the underlying mechanism via gene expression analyses. TZ at an environmentally relevant concentration (50 mg/L) significantly induces oxidative stress, altered antioxidant (SOD, CAT and GSH) response, triggered cellular damage (MDA and LDH), and induced neuro-biochemical changes (AChE and NO). Gene expression analyses revealed broad disruptions in genes associated with antioxidant defense (sod1, cat, and gstp1), mitochondrial dysfunction (mfn2, opa1, and fis1),evoked inflammatory response (nfkb, tnfa, and il1b), apoptosis activation (bcl2, bax, and p53), and neural development (bdnf, mbp, and syn2a). Behavioral analysis indicated altered thigmotaxis, touch response, and locomotion depending on the concentration of TZ exposure. Remarkably, the observed effective concentrations were consistent with the permitted levels in food products, highlighting the neurodevelopmental effects of TZ at environmentally relevant concentrations. These findings provide valuable insights into the underlying molecular mechanisms, particularly the role of mitochondria-mediated apoptosis, contributing to TZ-induced neurodevelopmental disorders in vivo.

In-silico prediction of anti-breast cancer activity of ginger (Zingiber officinale) using machine learning techniques

INTRODUCTION

Indonesian civilization extensively uses traditional medicine to cure illnesses and preserve health. The lack of knowledge on the security and efficacy of medicinal plants is still a significant concern. Although the precise chemicals responsible for this impact are unknown, ginger is a common medicinal plant in Southeast Asia that may have anticancer qualities.

METHOD

Using data from Dudedocking, a machine-learning model was created to predict possible breast anticancer chemicals from ginger. The model was used to forecast substances that block KIT and MAPK2 proteins, essential elements in breast cancer.

RESULT

Beta-carotene, 5-Hydroxy-74'-dimethoxyflavone, [12]-Shogaol, Isogingerenone B, curcumin, Trans-[10]-Shogaol, Gingerenone A, Dihydrocurcumin, and demethoxycurcumin were all superior to the reference ligand for MAPK2, according to molecular docking studies. Lycopene, [8]-Shogaol, [6]-Shogaol, and [1]-Paradol exhibited low toxicity and no Lipinski violations, but beta carotene had toxic predictions and Lipinski violations. It was anticipated that all three substances would have anticarcinogenic qualities.

CONCLUSION

Overall, this study shows the value of machine learning in drug development and offers insightful information on possible anticancer chemicals from ginger.

Application of the threshold of toxicological concern (TTC) in the evaluation of drinking water contact chemicals

The Threshold of Toxicological Concern (TTC) is an approach for assessing the safety of chemicals with low levels of exposure for which limited toxicology data are available. The original TTC criteria were derived for oral exposures from a distributional analysis of a dataset of 613 chemicals that identified 5th percentile no observed effect level (NOEL) values grouped within three tiers of compounds having specific structural functional groups and/or toxic potencies known as Cramer I, II and III classifications. Subsequent assessments of the TTC approach have established current thresholds to be scientifically robust. While the TTC has gained acknowledgment and acceptance by many regulatory agencies and organizations, use of the TTC approach in evaluating drinking water chemicals has been limited. To apply the TTC concept to drinking water chemicals, an exposure-based approach that incorporates the current weight of evidence for the target chemical is presented. Such an approach provides a comparative point of departure to the 5th percentile TTC NOEL using existing data, while conserving the allocation of toxicological resources for quantitative risk assessment to chemicals with greater exposure or toxicity. This approach will be considered for incorporation into NSF/ANSI/CAN 600, a health effects standard used in the safety evaluation of chemicals present in drinking water from drinking water contact additives and materials certified to NSF/ANSI/CAN 60 and 61, respectively.

In-silico and in-vitro screening of Asiatic acid and Asiaticoside A against Cathepsin S enzyme

BACKGROUND

Atherosclerosis is a form of cardiovascular disease that affects the endothelium of the blood vessel. Series of events are involved in the pathophysiology of this disease which includes the breaking down of the connective tissue elastin and collagen responsible for the tensile strength of the arterial wall by proteolytic enzyme. One of these enzymes called Cathepsin S (CatS) is upregulated in the progression of the disease and its inhibition has been proposed to be a promising pharmacological target to improve the prognosis of the disease condition. Asiatic acid and asiaticoside A are both pentacyclic triterpenoids isolated from Centella asiatica. Their use in treating various cardiovascular diseases has been reported.

METHODS

In this study through in silico and in vitro methods, the pharmacokinetic properties, residue interaction, and inhibitory activities of these compounds were checked against the CatS enzyme. The SwissADME online package and the ToxTree 3.01 version of the offline software were used to determine the physicochemical properties of the compounds.

RESULT

Asiatic acid reported no violation of the Lipinski rule while asiaticoside A violated the rule with regards to its molecular structure and size. The molecular docking was done using Molecular Operating Environment (MOE) and the S-score of - 7.25988, - 7.08466, and - 4.147913 Kcal/mol were recorded for LY300328, asiaticoside A, and asiatic acid respectively. Asiaticoside A has a docking score value (- 7.08466Kcal/mol) close to the co-crystallize compound. Apart from the close docking score, the amino acid residue glycine69 and asparagine163 both interact with the co-crystallized compound and asiaticoside A. The in vitro result clearly shows the inhibitory effect of asiaticoside and asiatic acid. Asiaticoside A has an inhibitory value of about 40% and asiatic acid has an inhibitory value of about 20%.

CONCLUSION

This clearly shows that asiaticoside will be a better drug candidate than asiatic acid in inhibiting the CatS enzyme for the purpose of improving the outcome of atherosclerosis. However, certain modifications need to be made to the structural make-up of asiaticoside A to improve its pharmacokinetics properties.

Quantitative and qualitative approaches for CEC prioritization when reusing reclaimed water for irrigation needs - A critical review

The use of reclaimed water for irrigation is an option that is becoming increasingly widespread to alleviate water scarcity and to cope with drought. However, reclaimed water, if used for irrigation, may introduce Contaminants of Emerging Concern (CECs) into the agroecosystems, which may be taken up by the crops and subsequently enter the food chain. The number of CECs is steadily increasing due to their continuous introduction on the market for different uses. There is an urgent need to draw up a short list of potential high priority CECs, which are substances that could be taken up by plants and accumulated in food produce, and/or that could have negative effects on human health and the environment. This review presents and discusses the approaches developed to prioritize CECs when reclaimed water is (re-)used for irrigation. They are divided into quantitative methodologies, which estimate the risk for environmental compartments (soil and water), predators and humans through equations, and qualitative methodologies, which are instead conceptual frameworks or procedures based on the simultaneous combination of data/information/practices with the judgment of experts. Three antibiotics (erythromycin, sulfamethoxazole and ciprofloxacin), one estrogen (17-α ethinylestradiol) and one analgesic (ibuprofen) were found on at least two priority lists, although comparison among studies is still difficult. The review remarks that it is advisable to harmonize the different methodologies in order to identify the priority CECs to include in monitoring programs in reclaimed water reuse projects and to ensure a high level of protection for humans and the environment.

New insights into the degradation mechanism of ibuprofen in the UV/H2O2 process: role of natural dissolved matter in hydrogen transfer reactions

Ibuprofen (IBU), a widely used antipyretic and analgesic, has been frequently detected in various natural water systems. Advanced oxidation processes (AOPs) are effective ways to remove pollutants from water. The degradation of IBU under UV/H2O2 conditions in the presence of various kinds of natural dissolved matter was investigated using density functional theory (DFT). The eco-toxicological properties were predicted based on a quantitative structure-activity relationship (QSAR) model. The calculated results showed that two H-abstraction reactions occurring at the side chain are predominant pathways in the initial reaction. H2O, NH3, CH3OH, C2H5OH, HCOOH and CH3COOH can catalyze the H transfer in the degradation process through decreasing the energy barriers and the catalysis effects follow the order of NH3 > alcohols > acids > H2O. The catalysis effects differ under acid or alkaline conditions. The overall rate coefficient of the reaction of IBU with ˙OH is calculated to be 5.04 × 109 M-1 s-1 at 298 K. IBU has harmful effects on aquatic organisms and human beings and the degradation process cannot significantly reduce its toxicity. Among all products, 2-(4-formylphenyl)propanoic acid, which is more toxic than IBU, is the most toxic with acute and chronic toxicity, developmental toxicity, mutagenicity, genotoxic carcinogenicity and irritation/corrosivity to skin. The findings in this work provide new insights into the degradation of IBU and can help to assess its environmental risks.

Non-target screening and human risk assessment for adult and child populations of semi-volatile organic compounds in residential indoor dust in Spain

In this work, an analytical strategy based on non-target screening of semi-volatile organic compounds and subsequent risk assessment for adult and child populations has been conducted for the first time in household indoor dust samples in Spain. The methodology was based on a microwave-assisted extraction followed by gas chromatography coupled to high resolution mass spectrometry determination, using a hybrid quadrupole-orbitrap analyzer. The procedure was applied to 19 residential indoor dust samples, collected in different Spanish regions (namely Galicia, La Rioja, Catalunya, the Balearic Islands, and the Valencian Region). From the generated data, 4067 features were obtained, of which 474 compounds were tentatively identified with a high level of identification confidence (probable structure by library spectrum match or confirmed by reference standard), using a restrictive set of identification criteria. Most of the identified chemicals were natural products, metabolites, additives, and substances with industrial applications in the field of foods, cosmetics, pharmaceuticals, pesticides, and plastics. Finally, risk assessment was carried out by applying the threshold of toxicological concern approach, showing that risk to adult and child populations associated with the presence of the identified substances in the indoor dust was not expected, although the existence of indoor environments with conditions of potential risk cannot be discarded under a worst-case scenario approach.

Sclerostin small-molecule inhibitors promote osteogenesis by activating canonical Wnt and BMP pathways

Background

The clinical healing environment after a posterior spinal arthrodesis surgery is one of the most clinically challenging bone-healing environments across all orthopedic interventions due to the absence of a contained space and the need to form de novo bone. Our group has previously reported that sclerostin in expressed locally at high levels throughout a developing spinal fusion. However, the role of sclerostin in controlling bone fusion remains to be established.

Methods

We computationally identified two FDA-approved drugs, as well as a single novel small-molecule drug, for their ability to disrupt the interaction between sclerostin and its receptor, LRP5/6. The drugs were tested in several in vitro biochemical assays using murine MC3T3 and MSCs, assessing their ability to (1) enhance canonical Wnt signaling, (2) promote the accumulation of the active (non-phosphorylated) form of β-catenin, and (3) enhance the intensity and signaling duration of BMP signaling. These drugs were then tested subcutaneously in rats as standalone osteoinductive agents on plain collagen sponges. Finally, the top drug candidates (called VA1 and C07) were tested in a rabbit posterolateral spine fusion model for their ability to achieve a successful fusion at 6 wk.

Results

We show that by controlling GSK3b phosphorylation our three small-molecule inhibitors (SMIs) simultaneously enhance canonical Wnt signaling and potentiate canonical BMP signaling intensity and duration. We also demonstrate that the SMIs produce dose-dependent ectopic mineralization in vivo in rats as well as significantly increase posterolateral spine fusion rates in rabbits in vivo, both as standalone osteogenic drugs and in combination with autologous iliac crest bone graft.

Conclusions

Few if any osteogenic small molecules possess the osteoinductive potency of BMP itself - that is, the ability to form de novo ectopic bone as a standalone agent. Herein, we describe two such SMIs that have this unique ability and were shown to induce de novo bone in a stringent in vivo environment. These SMIs may have the potential to be used in novel, cost-effective bone graft substitutes for either achieving spinal fusion or in the healing of critical-sized fracture defects.

Funding

This work was supported by a Veteran Affairs Career Development Award (IK2-BX003845).

Migration of oligomers from Tritan™ copolyester: application of hydrolysis for overall oligomer determination

Tritan™ (a kind of glycol-modified polycyclohexylene dimethylene terephthalate) is a novel copolyester mainly in use for the production of sports bottles and food storage containers. Oligomers in three food-grade Tritan™ samples were identified after dissolution-precipitation by high performance liquid chromatography with diode array detection and mass spectrometry and quantified after alkaline hydrolysis to the monomers. The obtained overall oligomer content <1000 Da determined by hydrolysis ranged from 7.2 to 10.6 mg/g material. Three consecutive migration experiments were performed according to the Commission Regulation (EU) No 10/2011. Oligomer migration values decreased from first to third migration during all simulations. Less than 25 µg/kg (third migrate) were detected in bottle migrates when tested under room temperature storage conditions (40 °C, 24 h) with simulants 3% acetic acid, 20 and 50% ethanol and during hot-fill testing (70 °C, 2 h) with simulants 3% acetic acid and 20% ethanol, respectively, while 170 µg/kg were determined in 50% ethanol after migration at 70 °C for 2 h. Food storage containers that were labelled as microwave-suitable by the supplier were tested according to the Joint Research Centre recommendations for microwave dishware. A strong deformation of the containers as well as a loss of transparency were observed during the tests (100 °C, 2 h with 10% ethanol and 3% acetic acid in an autoclave, 121 °C, 30 min with sunflower oil), questioning the suitability of the material for microwave applications. Maximum oligomer migration was 379 µg/kg during the third migration (sunflower oil at 121 °C for 30 min). Based on the migration data and an in silico oligomer evaluation according to the threshold of toxicological concern concept, no exceedances of daily thresholds for oligomers are expected from a proper use of Tritan™ drinking bottles, even with hot drinks.

Simultaneous Determination and Exposure Assessment of Antioxidants in Food Contact Plastic Materials by HPLC-MS/MS

Antioxidants are widely used to prevent oxidative degradation of food-contact plastics materials. However, when plastic products come into contact with food, antioxidants may contaminate food. Herein, twenty-three kinds of possible antioxidants were monitored in 257 products of seven polymers. The migration of antioxidants into the food simulants at different temperatures and times was detected by using HPLC-MS/MS. Risk assessment was performed based on the EU, U.S. FDA methods and Monte Carlo simulation. The antioxidants migrated mainly to fatty food simulant, with the highest concentration and occurrence frequency of Irgafos 168, followed byIrganox 1010, Irganox 1076, and Antioxidant LTDP in polyethylene terephthalate, polyvinyl chloride, polypropylene, polyethylene. No antioxidants were detected in polystyrene, polycarbonate, and polyvinylidene chloride. Additionally, antioxidants exhibited the highest detection rate of 0.81 in polyethylene. Risk assessment demonstrated that the antioxidants have no obvious health risk to the exposed population. However, the risk of polypropylene was relatively high compared to other polymers.

Identification of Some Glutamic Acid Derivatives with Biological Potential by Computational Methods

Glutamic acid is a non-essential amino acid involved in multiple metabolic pathways. Of high importance is its relationship with glutamine, an essential fuel for cancer cell development. Compounds that can modify glutamine or glutamic acid behaviour in cancer cells have resulted in attractive anticancer therapeutic alternatives. Based on this idea, we theoretically formulated 123 glutamic acid derivatives using Biovia Draw. Suitable candidates for our research were selected among them. For this, online platforms and programs were used to describe specific properties and their behaviour in the human organism. Nine compounds proved to have suitable or easy to optimise properties. The selected compounds showed cytotoxicity against breast adenocarcinoma, lung cancer cell lines, colon carcinoma, and T cells from acute leukaemia. Compound 2Ba5 exhibited the lowest toxicity, and derivative 4Db6 exhibited the most intense bioactivity. Molecular docking studies were also performed. The binding site of the 4Db6 compound in the glutamine synthetase structure was determined, with the D subunit and cluster 1 being the most promising. In conclusion, glutamic acid is an amino acid that can be manipulated very easily. Therefore, molecules derived from its structure have great potential to become innovative drugs, and further research on these will be conducted.

Structural analysis of hERG channel blockers and the implications for drug design

The repolarizing current (I_kr) produced by the hERG potassium channel forms a major component of the cardiac action potential and blocking this current by small molecule drugs can lead to life-threatening cardiotoxicity. Understanding the mechanisms of drug-mediated hERG inhibition is essential to develop a second generation of safe drugs, with minimal cardiotoxic effects. Although various computational tools and drug design guidelines have been developed to avoid binding of drugs to the hERG pore domain, there are many other aspects that are still open for investigation. This includes the use computational modelling to study the implications of hERG mutations on hERG structure and trafficking, the interactions of hERG with hERG chaperone proteins and with membrane-soluble molecules, the mechanisms of drugs that inhibit hERG trafficking and drugs that rescue hERG mutations. The plethora of available experimental data regarding all these aspects can guide the construction of much needed robust computational structural models to study these mechanisms for the rational design of safe drugs.

Occurrence of volatile contaminants in recycled poly(ethylene terephthalate) by HS-SPME-GC×GC-QTOF-MS combined with chemometrics for authenticity assessment of geographical recycling regions

A comparison was performed on various methods detecting the volatile contaminants (VCs) in recycled poly(ethylene terephthalate) (rPET) flakes, the results demonstrated that head-space solid phase micro-extraction combined with comprehensive two-dimensional gas chromatograph-tandem quadrupole-time-of-flight mass spectrometry (HS-SPME-GC×GC-QTOF-MS) was a sensitive, effective, accurate method, and successfully applied to analyze 57 rPET flakes collected from different recycling plants in China. A total of 212 VCs were tentatively identified, and the possible source were associated with plastic, food, and cosmetics. 45 VCs are classified as high-priority compounds with toxicity level IV or V and may pose a risk to human health. Combined chemometrics for further analysis revealed that significant differences among these three geographical recycling regions. 6, 7, and 6 volatile markers were chosen based on VIP values and S-plot among plant1 plant 2 and plant 3, respectively. The markers differed significantly between recycled rPET samples in three geographical recycling regions based on chemometrics analysis. The initial classification rate and cross-validation accuracy were 100% on the identified VCs. These significant differences demonstrate that a systematic study is needed to obtain a comprehensive data on the contamination of rPET for food contact applications in China.

C-glycosides analogues of the okadaic acid central fragment exert neuroprotection via restoration of PP2A-phosphatase activity: A rational design of potential drugs for Alzheimer's disease targeting tauopathies

Protein phosphatase 2A (PP2A) is an important Ser/Thr phosphatase that participates in the regulation of multiple cellular processes. This implies that any deficient activity of PP2A is the responsible of severe pathologies. For instance, one of the main histopathological features of Alzheimer's disease is neurofibrillary tangles, which are mainly comprised by hyperphosphorylated forms of tau protein. This altered rate of tau phosphorylation has been correlated with PP2A depression AD patients. With the goal of preventing PP2A inactivation in neurodegeneration scenarios, we have aimed to design, synthesize and evaluate new ligands of PP2A capable of preventing its inhibition. To achieve this goal, the new PP2A ligands present structural similarities with the central fragment C19-C27 of the well-established PP2A inhibitor okadaic acid (OA). Indeed, this central moiety of OA does not exert inhibitory actions. Hence, these compounds lack PP2A-inhibiting structural motifs but, in contrast, compete with PP2A inhibitors, thus recovering phosphatase activity. Proving this hypothesis, most compounds showed a good neuroprotective profile in neurodegeneration models related to PP2A impairment, highlighting derivative 10, named ITH12711, as the most promising one. This compound (1) restored in vitro and cellular PP2A catalytic activity, measured on a phospho-peptide substrate and by western-blot analyses, (2) proved good brain penetration measured by PAMPA, and (3) prevented LPS-induced memory impairment of mice in the object recognition test. Thus, the promising outcomes of the compound 10 validate our rational approach to design new PP2A-activating drugs based on OA central fragment.

Poly(ethylene terephthalate), Poly(butylene terephthalate), and Polystyrene Oligomers: Occurrence and Analysis in Food Contact Materials and Food

Polyesters (PES) and polystyrene (PS) are among the most used plastics in the production of food contact materials (FCM). The existence of compounds that could migrate from these materials into food requires a constant analytical control to ensure the safety of consumers due to consumption. It also implies a significant research challenge for their identification and quantification. One of the most important groups of known FCM migrants are the substances known as oligomers. PES and PS oligomers have long been suspected to possess some toxicological effects. The International Agency for Research on Cancer and the European Food Safety Authority alerted recently to the potential carcinogenicity of styrene, with its oligomers consequently being also in the spotlight. At the same time, PES cyclic oligomers are categorized as having Cramer III toxicity. Many recent works on the occurrence of poly(ethylene terephthalate) (PET), poly(butylene terephthalate) (PBT), and PS oligomers in FCM and food have been published. The oligomeric chemical analysis requires the use of demanding analytical strategies to address their different physicochemical characteristics (melting points, octanol/water partition coefficients, and solubility properties). Chromatographic methods are normally preferred due to the intrinsic complexity of the target matrices, but the reduced amount of reliable analytical standards still hinders the widespread screening analysis of oligomers in food. This work presents the most relevant recent studies and analytical methodologies used in the analysis of PET, PBT, and PS oligomers in food and FCM, as well as current and future challenges.

Elucidation of Non-Intentionally Added Substances from Plant Fiber/Plastic Composites by UPLC-QTOF/MS

Plant fiber/plastic composites (PPCs) have been widely used in food contact materials (FCMs) for many benefits, such as their claimed better environmental footprint compared to conventional plastics. However, their safety is still not fully understood and must be comprehensively evaluated. Non-volatiles extracted from six PPCs with different plant fibers and polymer matrices were characterized by employing ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry in combination with various spectral libraries and manual elucidation, taking into account spectral similarity and characteristic product ions. A total of 115 compounds were tentatively identified, 50 of which were oligomers or their derivatives from the sample with polylactic acid (PLA) and polybutylene adipate terephthalate (PBAT) as the polymer matrix, and some of them were Cramer rules class III substances based on the threshold of toxicological concern (TTC). Seven reaction products between PLA and PBAT monomers, as well as four derivatives of melamine, were elucidated and well detailed for the first time. In addition, bisphenol S was detected in all samples even though its origin remains to be further explored. Isoprothiolane, as an insecticide and fungicide used to control a range of rice pests, was identified in the sample with rice husk as fillers, experimentally confirming the presence of agrochemicals in samples containing plant fibers.

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.

Oligomers in polybutylene terephthalate for food contact-strategies on identification, quantification, and risk assessment

Oligomers are a significant group of migrating substances from food contact materials made of polyesters like polybutylene terephthalate (PBT). Twenty-three cyclic and linear oligomers with different end groups including olefin-terminated oligomers, which are associated with thermal stress of the material, were tentatively identified in PBT extracts by high-performance liquid chromatography with mass spectrometry and diode array detection. Quantification approaches based on chromophore concentration, relative response factors, and overall oligomer determination after hydrolysis to the monomer terephthalic acid were employed. An exhaustive extraction of thirteen PBT samples yielded an overall oligomer content of 1.87-6.10 mg/g material (sum of individual oligomers < 1,000 Da) with a predominant content of cyclic over linear oligomers. Migration experiments were performed according to Regulation (EU) No. 10/2011 using the official food simulants as well as cows' milk. A total of 218 µg cyclic oligomers/L milk were detected in the third migrate relevant for risk assessment of repeated-use articles under hot-fill conditions (70 °C, 2 h). The official food simulant for milk, 50% ethanol, was found to overestimate the actual migration into milk by a factor of four. Frying conditions using sunflower oil as the food simulant (200 °C, 10 min) resulted in a migration of 7.5 mg cyclic oligomers/kg oil. The exposure to migrating oligomers is critical in some scenarios when evaluated by the threshold of toxicological concern concept; however, the toxicological evaluation poses a challenge due to the possible hydrolysis of cyclic oligomers in the human gastrointestinal tract. Our experiments display the need for a toxicological evaluation of PBT oligomers because the migration of cyclic oligomers is expected to exceed the current in silico-based thresholds under foreseeable conditions of use.

Evaluating the utility of the Threshold of Toxicological Concern (TTC) and its exclusions in the biocompatibility assessment of extractable chemical substances from medical devices

The Threshold of Toxicological Concern (TTC) is a pragmatic approach used to establish safe thresholds below which there can be no appreciable risk to human health. Here, a large inventory of ~45,000 substances (referred to as the LRI dataset) was profiled through the Kroes TTC decision module within Toxtree v3.1 to assign substances into their respective TTC categories. Four thousand and two substances were found to be not applicable for the TTC approach. However, closer examination of these substances uncovered several implementation issues: substances represented in their salt forms were automatically assigned as not appropriate for TTC when many of these contained essential metals as counter ions which would render them TTC applicable. High Potency Carcinogens and dioxin-like substances were not fully captured based on the rules currently implemented in the software. Phosphorus containing substances were considered exclusions when many of them would be appropriate for TTC. Refinements were proposed to address the limitations in the current software implementation. A second component of the study explored a set of substances representative of those released from medical devices and compared them to the LRI dataset as well as other toxicity datasets to investigate their structural similarity. A third component of the study sought to extend the exclusion rules to address application to substances released from medical devices that lack toxicity data. The refined rules were then applied to this dataset and the TTC assignments were compared. This case study demonstrated the importance of evaluating the software implementation of an established TTC workflow, identified certain limitations and explored potential refinements when applying these concepts to medical devices.

Estimating provisional margins of exposure for data-poor chemicals using high-throughput computational methods

Current computational technologies hold promise for prioritizing the testing of the thousands of chemicals in commerce. Here, a case study is presented demonstrating comparative risk-prioritization approaches based on the ratio of surrogate hazard and exposure data, called margins of exposure (MoEs). Exposures were estimated using a U.S. EPA’s ExpoCast predictive model (SEEM3) results and estimates of bioactivity were predicted using: 1) Oral equivalent doses (OEDs) derived from U.S. EPA’s ToxCast high-throughput screening program, together with in vitro to in vivo extrapolation and 2) thresholds of toxicological concern (TTCs) determined using a structure-based decision-tree using the Toxtree open source software. To ground-truth these computational approaches, we compared the MoEs based on predicted noncancer TTC and OED values to those derived using the traditional method of deriving points of departure from no-observed adverse effect levels (NOAELs) from in vivo oral exposures in rodents. TTC-based MoEs were lower than NOAEL-based MoEs for 520 out of 522 (99.6%) compounds in this smaller overlapping dataset, but were relatively well correlated with the same (r² = 0.59). TTC-based MoEs were also lower than OED-based MoEs for 590 (83.2%) of the 709 evaluated chemicals, indicating that TTCs may serve as a conservative surrogate in the absence of chemical-specific experimental data. The TTC-based MoE prioritization process was then applied to over 45,000 curated environmental chemical structures as a proof-of-concept for high-throughput prioritization using TTC-based MoEs. This study demonstrates the utility of exploiting existing computational methods at the pre-assessment phase of a tiered risk-based approach to quickly, and conservatively, prioritize thousands of untested chemicals for further study.

Identification of CB1 Ligands among Drugs, Phytochemicals and Natural-Like Compounds: Virtual Screening and In Vitro Verification

Cannabinoid receptor type 1 (CB1) is an important modulator of many key physiological functions and thus a compelling molecular target. However, safe CB1 targeting is a non-trivial task. In recent years, there has been a surge of data indicating that drugs successfully used in the clinic for years (e.g. paracetamol) show CB1 activity. Moreover, there is a lot of promise in finding CB1 ligands in plants other than Cannabis sativa. In this study, we searched for possible CB1 activity among already existing drugs, their metabolites, phytochemicals, and natural-like molecules. We conducted two iterations of virtual screening, verifying the results with in vitro binding and functional assays. The in silico procedure consisted of a wide range of structure- and ligand-based methods, including docking, molecular dynamics, and quantitative structure-activity relationship (QSAR). As a result, we identified travoprost and ginkgetin as CB1 ligands, which provides a starting point for future research on the impact of their metabolites or preparations on the endocannabinoid system. Moreover, we found five natural-like compounds with submicromolar or low micromolar affinity to CB1, including one mixed partial agonist/antagonist viable for hit-to-lead phase. Finally, the computational procedure established in this work will be of use for future screening campaigns for novel CB1 ligands.