Deciphering the complexity of the chemicals in food packaging materials using molecular networks.

Chemicals from packaging materials might be transferred into food resulting in consumer exposure. Identifying these migrated chemicals is highly challenging and crucial to perform their safety assessment, usually starting by the understanding of the chemical composition of the packaging material itself. This study explores the use of the Molecular Networking (MN) approach to support identification of the extracted chemicals. Two formulations of bioplastics were analyzed using Liquid Chromatography hyphenated to High-Resolution Mass Spectrometry. Data processing and interpretation using a conventional manual method was performed as a point of comparison to understand the power of MN. Interestingly, only the MN approach facilitated the identification of unknown chemicals belonging to a novel oligomer series containing the azelaic acid monomer. The MN approach provided a faster visualization of chemical families in addition to the highlight of unrelated chemicals enabling to prioritize chemicals for further investigation improving the safety assessment of packaging materials.

Protective effects and molecular mechanisms of Litopenaeus vannamei treated with l-arginine/l-lysine against myofibrillar proteins oxidation and quality degradation during freeze-thaw cycles.

The storage and processing of Litopenaeus vannamei are often challenged by the freeze-thaw (F-T) cycle phenomenon. This study delved into the influence of pretreatment with l-arginine (Arg) and l-lysine (Lys) on the myofibrillar proteins oxidation and quality of shrimp subjected to F-T cycles. Arg and Lys pretreatment notably improved water-holding capacity (WHC), textural integrity as well as the myofibrillar structure of the shrimps. A lesser reduction in the amounts of immobile and bound water was found in the amino acid-treated groups, and the oxidation of lipids and proteins were both decelerated. Molecular simulation results indicated that Arg and Lys could form hydrogen and salt-bridge bonds with myosin, enhancing the stability of Litopenaeus vannamei. The study concludes that Arg and Lys are effective in alleviating the adverse effects of F-T cycles on the quality of Litopenaeus vannamei, and provides a new solution for the quality maintenance during storage and processing.

Molecularly imprinted polymers-coated magnetic covalent organic frameworks for efficient solid-phase extraction of sulfonamides in fish.

In this study, covalent organic frameworks (COFs) were grown in situ on magnetic nitrogen-doped graphene foam (MNGF), and the resulting composite of COFs-modified MNGF (MNC) was wrapped by molecularly imprinted polymers (MNC@MIPs) for specifically capturing SAs. A magnetic solid phase extraction (MSPE) method for SAs was established using MNC@MIPs with good magnetic responsiveness. The adsorption performance of MNC@MIPs was superior to that of non-molecularly imprinted polymers (MNC@NIPs), with shorter adsorption/desorption time and higher imprinting factors. A high-efficiency SAs analytical method was developed by fusing HPLC and MNC@MIPs-based MSPE. This approach provides excellent precision, a low detection limit, and wide linearity. By analyzing fish samples, the feasibility of the approach was confirmed, with SAs recoveries and relative standard deviations in spiked samples in the ranges of 77.2-112.7 % and 2.0-7.2 %, respectively. This study demonstrated the potential use of MNC@MIPs-based MSPE for efficient extraction and quantitation of trace hazards in food.

Exploring the conformational landscape through rotational spectroscopy and computational modelling: The tunneling dynamics in 2,6-diethylphenol.

Phenol and some of its derivatives exhibit interesting tunneling motions consisting of two groups of transitions separated by a few hundred MHz. Recently, one of its derivatives, 2,6-di-tert-butylphenol, has shown additional hyperfine tunneling components, the origin of which remains unclear. In this work, another member of the family, 2,6-diethylphenol, has been investigated through its rotational spectrum. The jet-cooled broadband chirped-pulse Fourier transform microwave spectra in the 2-8 GHz frequency region revealed the presence of two conformers. The comparison with the equilibrium structure obtained by computational calculations at the B3LYP-D3(BJ)/Def2-TZVP level validates the structural determination and the orientation of the lateral ethyl groups. Additional observation of all the singly-substituted 13C isotopologues for the most stable ones allowed the determination of the substitution structure by means of the Kraitchman equations. Both conformers exhibited tunneling that was reproduced using an advanced 1D model, which provides an estimate of the barrier height for both conformers.

Exploring antithrombotic mechanisms and effective constituents of Lagopsis supina using an integrated strategy based on network pharmacology, molecular docking, metabolomics, and experimental verification in rats.

ETHNOPHARMACOLOGICAL RELEVANCE: Thrombosis is a common cause of morbidity and mortality worldwide. Lagopsis supina (Stephan ex Willd.) Ikonn.-Gal. ex Knorring is an ancient Chinese herbal medicine used for treating thrombotic diseases. Nevertheless, the antithrombotic mechanisms and effective constituents of this plant have not been clarified. AIM OF THE STUDY: This work aimed to elucidate the pharmacodynamics and mechanism of L. supina against thrombosis. MATERIALS AND METHODS: Systematic network pharmacology was used to explore candidate effective constituents and hub targets of L. supina against thrombosis. Subsequently, the binding affinities of major constituents with core targets were verified by molecular docking analysis. Afterward, the therapeutic effect and mechanism were evaluated in an arteriovenous bypass thrombosis rat model. In addition, the serum metabolomics analysis was conducted using ultra-high performance liquid chromatography coupled with Q-Exactive mass spectrometry. RESULTS: A total of 124 intersected targets of L. supina against thrombosis were predicted. Among them, 24 hub targets were obtained and their mainly associated with inflammation, angiogenesis, and thrombosis approaches. Furthermore, 9 candidate effective constituents, including (22E,24R)-5α,8α-epidioxyergosta-6,22-dien-3ß-ol, aurantiamide, (22E,24R)-5α,8α-epidioxyergosta-6,9 (11),22-trien-3ß-ol, lagopsinA, lagopsin C, 15-epi-lagopsin C, lagopsin D, 15-epi-lagopsin D, and lagopsin G in L. supina and 6 potential core targets (TLR-4, TNF-α, HIF-1α, VEGF-A, VEGFR-2, and CLEC1B) were acquired. Then, these 9 constituents demonstrated strong binding affinities with the 6 targets, with their lowest binding energies were all less than -5.0 kcal/mol. The antithrombotic effect and potential mechanisms of L. supina were verified, showing a positively associated with the inhibition of inflammation (TNF-α, IL-1ß, IL-6, IL-8, and IL-10) and coagulation cascade (TT, APTT, PT, FIB, AT-III), promotion of angiogenesis (VEGF), suppression of platelet activation (TXB2, 6-keto-PGF1α, and TXB2/6-keto-PGF1α), and prevention of fibrinolysis (t-PA, u-PA, PAI-1, PAI-1/t-PA, PAI-1/u-PA, and PLG). Finally, 14 endogenous differential metabolites from serum samples of rats were intervened by L. supina based on untargeted metabolomics analysis, which were closely related to amino acid metabolism, inflammatory and angiogenic pathways. CONCLUSION: Our integrated strategy based on network pharmacology, molecular docking, metabolomics, and in vivo experiments revealed for the first time that L. supina exerts a significant antithrombotic effect through the inhibition of inflammation and coagulation cascade, promotion of angiogenesis, and suppression of platelet activation. This paper provides novel insight into the potential of L. supina as a candidate agent to treat thrombosis.

Uncovering the pharmacological mechanisms of Patchouli essential oil for treating ulcerative colitis.

ETHNOPHARMACOLOGICAL RELEVANCE: Pogostemonis Herba has long been used in traditional Chinese medicine to treat inflammatory disorders. Patchouli essential oil (PEO) is the primary component of Pogostemonis Herba, and it has been suggested to offer curative potential when applied to treat ulcerative colitis (UC). However, the pharmacological mechanisms of PEO for treating UC remain to be clarified. AIM OF THE STUDY: To elucidate the pharmacological mechanisms of PEO for treating UC. METHODS AND RESULTS: In the present study, transcriptomic and network pharmacology approaches were combined to clarify the mechanisms of PEO for treating UC. Our results reveal that rectal PEO administration in UC model mice significantly alleviated symptoms of UC. In addition, PEO effectively suppressed colonic inflammation and oxidative stress. Mechanistically, PEO can ameliorate UC mice by modulating gut microbiota, inhibiting inflammatory targets (OPTC, PTN, IFIT3, EGFR, and TLR4), and inhibiting the PI3K-AKT pathway. Next, the 11 potential bioactive components that play a role in PEO's anti-UC mechanism were identified, and the therapeutic efficacy of the pogostone (a bioactive component) in UC mice was partially validated. CONCLUSION: This study highlights the mechanisms through which PEO can treat UC, providing a rigorous scientific foundation for future efforts to develop and apply PEO for treating UC.

The Potential of Molecular Docking for Predictive Toxicology.

Molecular modeling techniques are widely used in medicinal chemistry for the study of biological targets, the rational design of new drugs, or the investigation of their mechanism of action.They are also applied in toxicology to identify chemical potential harmful effects.Molecular docking is a computational technique to predict the ligand binding mode and evaluate the interaction energy with a biological target.This chapter describes a computational workflow to predict possible endocrine disruptors on peroxisome proliferator-activated receptor alpha (PPARα), a nuclear receptor involved in glucose and lipid metabolism. The analyzed compounds are food contact chemicals, natural or synthetic substances intentionally added to food or released from the package or during production or technological processes.

Approaching Pharmacological Space: Events and Components.

The pharmacological space comprises all the dynamic events that determine the bioactivity (and/or the metabolism and toxicity) of a given ligand. The pharmacological space accounts for the structural flexibility and property variability of the two interacting molecules as well as for the mutual adaptability characterizing their molecular recognition process. The dynamic behavior of all these events can be described by a set of possible states (e.g., conformations, binding modes, isomeric forms) that the simulated systems can assume. For each monitored state, a set of state-dependent ligand- and structure-based descriptors can be calculated. Instead of considering only the most probable state (as routinely done), the pharmacological space proposes to consider all the monitored states. For each state-dependent descriptor, the corresponding space can be evaluated by calculating various dynamic parameters such as mean and range values.The reviewed examples emphasize that the pharmacological space can find fruitful applications in structure-based virtual screening as well as in toxicity prediction. In detail, in all reported examples, the inclusion of the pharmacological space parameters enhances the resulting performances. Beneficial effects are obtained by combining both different binding modes to account for ligand mobility and different target structures to account for protein flexibility/adaptability.The proposed computational workflow that combines docking simulations and rescoring analyses to enrich the arsenal of docking-based descriptors revealed a general applicability regardless of the considered target and utilized docking engine. Finally, the EFO approach that generates consensus models by linearly combining various descriptors yielded highly performing models in all discussed virtual screening campaigns.

Hypotensive effect of potent angiotensin-I-converting enzyme inhibitory peptides from corn gluten meal hydrolysate: Gastrointestinal digestion and transepithelial transportation modifications.

The study examined the antihypertensive effect of peptides derived from pepsin-hydrolyzed corn gluten meal, namely KQLLGY and PPYPW, and their in silico gastrointestinal tract digested fragments, KQL and PPY, respectively. KQLLGY and PPYPW showed higher angiotensin I-converting enzyme (ACE)-inhibitory activity and lower ACE inhibition constant (Ki) values when compared to KQL and PPY. Only KQL showed a mild antihypertensive effect in spontaneously hypertensive rats with -7.83 and - 5.71 mmHg systolic and diastolic blood pressure values, respectively, after 8 h oral administration. During passage through Caco-2 cells, KQL was further degraded to QL, which had reduced ACE inhibitory activity. In addition, molecular dynamics revealed that the QL-ACE complex was less stable compared to the KQL-ACE. This study reveals that structural transformation during peptide permeation plays a vital role in attenuating antihypertensive effect of the ACE inhibitor peptide.

Improving paste stabilities of cassava starch through molecular density after maltogenic amylase and transglucosidase.

To improve paste stability of cassava starch, including acid resistance, high-temperature shear resistance and freeze-thaw stability, cassava starch was modified by sequential maltogenic amylase and transglucosidase to form an optimally denser structure, or branched density (12.76 %), molecular density (15.17 g/mol/nm3), and the proportions of short-branched chains (41.41 % of A chains and 44.01 % of B1 chains). Viscosity stability (88.52 %) of modified starch was higher than that (64.92 %) of native starch. After acidic treatment for 1 h, the viscosity of modified starch and native starch decreased by 56.53 % and 65.70 %, respectively. Compared to native starch, modified starch had lower water loss in freeze-thaw cycles and less viscosity reduction during high-temperature and high-shear processing. So, the appropriate molecular density and denser molecule structure enhanced paste stabilities of modified starch. The outcome expands the food and non-food applications of cassava starch.

The Evolution of Nucleic Acid-Based Diagnosis Methods from the (pre-)CRISPR to CRISPR era and the Associated Machine/Deep Learning Approaches in Relevant RNA Design.

Nucleic acid tests (NATs) are considered as gold standard in molecular diagnosis. To meet the demand for onsite, point-of-care, specific and sensitive, trace and genotype detection of pathogens and pathogenic variants, various types of NATs have been developed since the discovery of PCR. As alternatives to traditional NATs (e.g., PCR), isothermal nucleic acid amplification techniques (INAATs) such as LAMP, RPA, SDA, HDR, NASBA, and HCA were invented gradually. PCR and most of these techniques highly depend on efficient and optimal primer and probe design to deliver accurate and specific results. This chapter starts with a discussion of traditional NATs and INAATs in concert with the description of computational tools available to aid the process of primer/probe design for NATs and INAATs. Besides briefly covering nanoparticles-assisted NATs, a more comprehensive presentation is given on the role CRISPR-based technologies have played in molecular diagnosis. Here we provide examples of a few groundbreaking CRISPR assays that have been developed to counter epidemics and pandemics and outline CRISPR biology, highlighting the role of CRISPR guide RNA and its design in any successful CRISPR-based application. In this respect, we tabularize computational tools that are available to aid the design of guide RNAs in CRISPR-based applications. In the second part of our chapter, we discuss machine learning (ML)- and deep learning (DL)-based computational approaches that facilitate the design of efficient primer and probe for NATs/INAATs and guide RNAs for CRISPR-based applications. Given the role of microRNA (miRNAs) as potential future biomarkers of disease diagnosis, we have also discussed ML/DL-based computational approaches for miRNA-target predictions. Our chapter presents the evolution of nucleic acid-based diagnosis techniques from PCR and INAATs to more advanced CRISPR/Cas-based methodologies in concert with the evolution of deep learning (DL)- and machine learning (ml)-based computational tools in the most relevant application domains.

Molecular Similarity in Predictive Toxicology with a Focus on the q-RASAR Technique.

The concept of similarity is an important aspect in various in silico-based prediction approaches. Most of these approaches follow the basic similarity property principle that states that two or more compounds having a high level of similarity are expected to exert similar biological activity or physicochemical property. Although in some cases this principle fails to predict the biological activity or property efficiently for certain compounds, it is applicable to most of the compounds in a given dataset. With the emerging need to efficiently fill data gaps in the regulatory context, Read-Across (RA), a similarity-based approach, has gained popularity, since this is not a statistical approach like QSAR, which requires a sizeable amount of data points to train a meaningful model. The basic idea behind Read-Across is the identification of the close source neighbors, and based on the similarity considerations, predictions are made for the query compound. Although RA is originally an unsupervised prediction method, recent efforts for quantitative Read-Across (qRA) have introduced supervised similarity-based weightage for quantitative predictions. RA is a useful tool in predictive toxicology, but one of its important drawbacks is the lack of interpretability of the features (especially for q-RA) used to generate the Read-Across-based predictions. To bridge this gap, a novel quantitative Read-Across Structure-Activity Relationship (q-RASAR) approach has recently been proposed, which combines the concepts of QSAR and Read-Across, generating statistically reliable and predictive models using similarity and error-based descriptors. The q-RASAR models are simple and interpretable and can be efficiently used to identify not only the essential features but also the nature of the source and query compounds. In this chapter, we have discussed the concepts and various studies on RA, q-RA, and q-RASAR along with some of the tools available from different research groups.

Computational Toxicology Methods in Chemical Library Design and High-Throughput Screening Hit Validation.

The discovery of molecular toxicity in a clinical drug candidate can have a significant impact on both the cost and timeline of the drug discovery process. Early identification of potentially toxic compounds during screening library preparation or, alternatively, during the hit validation process is critical to ensure that valuable time and resources are not spent pursuing compounds that may possess a high propensity for human toxicity. This report focuses on the application of computational molecular filters, applied either pre- or post-screening, to identify and remove known reactive and/or potentially toxic compounds from consideration in drug discovery campaigns.

PFAS-Biomolecule Interactions: Case Study Using Asclepios Nodes and Automated Workflows in KNIME for Drug Discovery and Toxicology.

The Asclepios suite of KNIME nodes represents an innovative solution for conducting cheminformatics and computational chemistry tasks, specifically tailored for applications in drug discovery and computational toxicology. This suite has been developed using open-source and publicly accessible software. In this chapter, we introduce and explore the Asclepios suite through the lens of a case study. This case study revolves around investigating the interactions between per- and polyfluorinated alkyl substances (PFAS) and biomolecules, such as nuclear receptors. The objective is to characterize the potential toxicity of PFAS and gain insights into their chemical mode of action at the molecular level. The Asclepios KNIME nodes have been designed as versatile tools capable of addressing a wide range of computational toxicology challenges. Furthermore, they can be adapted and customized to accomodate the specific needs of individual users, spanning various domains such as nanoinformatics, biomedical research, and other related applications. This chapter provides an in-depth examination of the technical underpinnings and foundations of these tools. It is accompanied by a practical case study that demonstrates the utilization of Asclepios nodes in a computational toxicology investigation. This showcases the extendable functionalities that can be applied in diverse computational chemistry contexts. By the end of this chapter, we aim for readers to have a comprehensive understanding of the effectiveness of the Asclepios node functions. These functions hold significant potential for enhancing a wide spectrum of cheminformatics applications.

Role of urea in the retention of DON in soil by clay minerals: Analysis based upon molecular weight.

As a widely used fertilizer, urea significantly promotes the leaching of dissolved organic nitrogen (DON) in soils and aggravates nitrogen contamination in groundwater. Clay minerals are considered the most important factor in retaining DON. However, the effect of urea on the retention of DON with different molecular weights by clay minerals is unknown. In this study, the retention of both low-molecular weight DON (LMWD) and high-molecular weight DON (HMWD) by clay minerals in the presence of urea was investigated. For this purpose, batch adsorption and soil column leaching experiments, characterization analysis (Fourier transform infrared spectroscopy X-ray diffraction, and X-ray photoelectron spectroscopy), and molecular dynamics simulations were carried out. Urea had a positive effect on the adsorption of LMWD, whereas a competitive effect existed for the adsorption of HMWD. The dominant interactions among DON, urea, and clay minerals included H-bonding, ligand exchange, and cation exchange. The urea was preferentially adsorbed on clay minerals and formed a complex, which provided more adsorption sites to LMWD and only a few to HMWD. The presence of urea increased the retention of LMWD and decreased the retention of HMWD in clay minerals. The retention capacity of LMWD increased by 6.9%-12.8%, while that of HMWD decreased by 6.7%-53.1%. These findings suggest that LMWD tended to be trapped in soils, while HMWD was prone to be leached into groundwater, which can be used to evaluate the leaching of DON from soil to groundwater.

Construction of Small Genes with Repetitive Elements Using Oligo Extension and Golden Gate Assembly.

Gene synthesis efficiency has greatly improved in recent years but is limited when it comes to repetitive sequences and results in synthesis failure or delays by DNA synthesis vendors. Here, we describe a method for the assembly of small synthetic genes with repetitive elements: First, a gene of interest is split in silico into small synthons of up to 80 base pairs flanked by Golden Gate-compatible overhangs. Then synthons are made by oligo extension and finally assembled into a synthetic gene by Golden Gate assembly.

Mechanism of overscreening breakdown by molecular-scale electrode surface morphology in asymmetric ionic liquids.

The interfacial nature of the electric double layer (EDL) assumes that electrode surface morphology significantly impacts the EDL properties. Since molecular-scale roughness modifies the structure of EDL, it is expected to disturb the overscreening effect and alter differential capacitance (DC). In this paper, we present a model that describes EDL near atomically rough electrodes with account for short-range electrostatic correlations. We provide numerical and analytical solutions for the analysis of conditions for the overscreening breakdown and DC shift estimation. Our findings reveal that electrode surface structure leads to DC decrease and can both break or enhance overscreening depending on the relation of surface roughness to electrostatic correlation length and ion size asymmetry.

Time-resolved small-angle neutron scattering for characterization of molecular exchange in lipid nanoparticle therapeutics.

HYPOTHESIS: Nano-scale dynamics of self-assembled therapeutics play a large role in their biological function. However, assessment of such dynamics remains absent from conventional pharmaceutical characterization. We hypothesize that time-resolved small-angle neutron scattering (TR-SANS) can reveal their kinetic properties. For lipid nanoparticles (LNP), limited molecular motion is important for avoiding degradation prior to entering cells while, intracellularly, enhanced molecular motion is then vital for effective endosomal escape. We propose TR-SANS for quantifying molecular exchange in LNPs and, therefore, enabling optimization of opposing molecular behaviors of a pharmaceutical in two distinct environments. EXPERIMENTS: We use TR-SANS in combination with traditional SANS and small-angle x-ray scattering (SAXS) to experimentally quantify nano-scale dynamics and provided unprecedented insight to molecular behavior of LNPs. FINDINGS: LNPs have molecular exchange dynamics relevant to storage and delivery which can be captured using TR-SANS. Cholesterol exchanges on the time-scale of hours even at neutral pH. As pH drops below the effective pKa of the ionizable lipid, molecular exchange occurs faster. The results give insight into behavior enabling delivery and provide a quantifiable metric by which to compare formulations. Successful analysis of this multi-component system also expands the opportunities for using TR-SANS to characterize complex therapeutics.

Impact of fermentation by Saccharomyces Cerevisiae on the macronutrient and in vitro digestion characteristics of Chinese noodles.

This study examined the impact of live bread yeast (Saccharomyces cerevisiae) on the nutritional characteristics of Asian dried noodles. Micronutrient analysis of fermented noodles revealed a 6.9% increase in the overall amino acid content, a 37.1% increase in the vitamin B content and a 63.0% decrease in the phytic acid level. Molecular weight analysis of starch and protein contents revealed moderate decrease in the fermented noodles. The in vitro digestion of fermented noodles showed a slightly faster initial acidification, four-fold decrease in the initial shear viscosity (from 8.85 to 1.94 Pa·s). The initial large food particle count (>2 mm diameter) was 19.5% lower in the fermented noodles. The fermented noodles contained slightly higher free sugar content (73.5 mg g-1 noodle) during the gastric digestion phase. The overall nutrition and digestion results indicate nutritional improvement and digestion-easing attributes in the fermented noodles.

Engineering S-scheme mCN@mPDIP molecular heterojunction with highly efficient interface charge transfer for photocatalytic aerobic oxidation synthesis.

The construction of S-scheme heterojunctions, which offers a promising approach for spatially separating photogenerated charge carriers with high redox potentials and multimolecular activation, represents a viable modification strategy in photocatalytic applications. However, the prevalent insufficient contact areas between two components result in low interface charge transfer efficiency, thereby impeding the photocatalytic performance of such heterostructures. Herein, we address this limitation by introducing a unique mCN@mPDIP molecular heterojunction through a pH-triggered molecule self-assembly eutectoid technique, enabling intimate interface contact and promoting highly efficient interfacial charge transfer following an S-scheme mechanism. Consequently, the mCN@mPDIP molecular heterojunction achieves significantly improved charge separation efficiency and higher concentration of active carriers compared to typical bCN-bPDIP bulk heterojunction and nCN/nPDIP nano heterojunction. Combined with the effective sulfide activation on mPDIP sites and O2 activation on mCN sites, the resulting mCN@mPDIP demonstrates outstanding activity in the photocatalytic aerobic oxidation of sulfides into sulfoxides without any redox mediators.