Chelation of iron(II) ions by ellagitannins-Effects of hexahydroxydiphenoyl and nonahydroxytriphenoyl groups

Tannins represent secondary plant metabolites that are used to control bacterial populations by chelation of essential metal ions. Their presence in food also affects the bioavailability of iron. This study investigates the influence of ellagitannins (vescalin, castalin, vescalagin, castalagin) structure and pH on the stoichiometry and formation constants of ellagitannin-Fe(II) coordination compounds. We demonstrated that ellagitannins are stable for at least one hour at pH values lower than 7.25. The spectra of neutral compounds were measured and explained with the help of TDDFT calculations. Furthermore, the pH-dependence of the ellagitannins UV-Vis spectra was examined to obtain insight into their protolytic equilibrium. Using Job's method in the pH range 3.50-5.51, the stoichiometry of the formed ellagitannin-Fe(II) ions complexes was determined. A model explaining interactions between ellagitannins and Fe(II) ions, that took into account the protolytic equilibrium of ellagitannins, was fitted globally to all four Job plots, whereby the corresponding formation constants were obtained.

Osmolality and Tonicity of Isotonic Beverages

This study aimed to measure and compare the osmolality and tonicity of isotonic beverages that can be bought on the Slovenian market. The main goal was to examine how good is the agreement between the measured osmolalities of the beverages and the requirements for isotonic beverages set up by EFSA. Osmolalities were measured with an osmometer using the freezing point depression method. Afterwards, two complementary methods for the observation of tonicity were developed. Erythrocytes were exposed to standard NaCl solutions of different osmolalities to observe their influence on the volume and shape of cells following the turbidity of the solution and the morphology of erythrocytes. These two methods enabled us to determine whether standard solutions were hypo-, iso-, or hypertonic. In this way, we found that the osmolality of 12 out of the 18 investigated isotonic beverages was in the range of 270-330 mOsm/kg, as required by EFSA. However, six samples did not meet this criterion and should therefore not have the label "isotonic" or be described as such. The measurements of turbidity of solutions indicated that most isotonic beverages exhibit a lower tonicity than standard NaCl solutions of identical osmolality. However, examination of the erythrocytes in isotonic beverages showed that the measurements were additionally complicated by the low pH values of these beverages. Finally, by demonstrating how different components of isotonic beverages pass through the erythrocyte membranes, we found that even isoosmolal beverages are often not isotonic, as the concentration of actively transported sugars in these beverages is relatively high.

The Effect of Microwaves on Protein Structure: Molecular Dynamics Approach

The impact of microwave (MW) irradiation on protein folding, potentially inciting misfolding, was investigated by employing molecular dynamics (MD) simulations. Twenty-nine proteins were subjected to MD simulations under equilibrium (300 K) and MW conditions, where the rotational temperature was elevated to 700 K. The utilized replacement model captures the microwave effects of δ- and γ-relaxation processes (frequency range of ∼300 MHz to ∼20 GHz). The results disclosed that MW heating incited a shift toward more compact protein conformations, as indicated by decreased root-mean-square deviations, root-mean-square fluctuations, head-to-tail distances, and radii of gyration. This compaction was attributed to the intensification of intramolecular electrostatic interactions and hydrogen bonds within the protein caused by MW-destabilized hydrogen bonds between the protein and solvent. The solvent-accessible surface area (SASA), particularly that of polar amino-acid residues, shrank under MW conditions, corresponding to a reduced polarity of the water solvent. However, MW irradiation produced no significant alterations in protein secondary structures; hence, MW heating was observed to primarily affect the protein tertiary structures.

Identification of Triazolopyrimidinyl Scaffold SARS-CoV-2 Papain-Like Protease (PLpro) Inhibitor

The global impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its companion disease, COVID-19, has reminded us of the importance of basic coronaviral research. In this study, a comprehensive approach using molecular docking, in vitro assays, and molecular dynamics simulations was applied to identify potential inhibitors for SARS-CoV-2 papain-like protease (PLpro), a key and underexplored viral enzyme target. A focused protease inhibitor library was initially created and molecular docking was performed using CmDock software (v0.2.0), resulting in the selection of hit compounds for in vitro testing on the isolated enzyme. Among them, compound 372 exhibited promising inhibitory properties against PLpro, with an IC50 value of 82 ± 34 μM. The compound also displayed a new triazolopyrimidinyl scaffold not yet represented within protease inhibitors. Molecular dynamics simulations demonstrated the favorable binding properties of compound 372. Structural analysis highlighted its key interactions with PLpro, and we stress its potential for further optimization. Moreover, besides compound 372 as a candidate for PLpro inhibitor development, this study elaborates on the PLpro binding site dynamics and provides a valuable contribution for further efforts in pan-coronaviral PLpro inhibitor development.

Naive Prediction of Protein Backbone Phi and Psi Dihedral Angles Using Deep Learning

Protein structure prediction represents a significant challenge in the field of bioinformatics, with the prediction of protein structures using backbone dihedral angles recently achieving significant progress due to the rise of deep neural network research. However, there is a trend in protein structure prediction research to employ increasingly complex neural networks and contributions from multiple models. This study, on the other hand, explores how a single model transparently behaves using sequence data only and what can be expected from the predicted angles. To this end, the current paper presents data acquisition, deep learning model definition, and training toward the final protein backbone angle prediction. The method applies a simple fully connected neural network (FCNN) model that takes only the primary structure of the protein with a sliding window of size 21 as input to predict protein backbone ϕ and ψ dihedral angles. Despite its simplicity, the model shows surprising accuracy for the ϕ angle prediction and somewhat lower accuracy for the ψ angle prediction. Moreover, this study demonstrates that protein secondary structure prediction is also possible with simple neural networks that take in only the protein amino-acid residue sequence, but more complex models are required for higher accuracies.

Antioxidant Activity of Different Hop (Humulus lupulus L.) Genotypes

The antioxidant activity (AA) of hop extracts obtained from different hop genotypes (n = 14) was studied. For comparison, the purified β-acids-rich fraction and α-acids-with-β-acids-rich fraction were also used to test the antioxidative potential. The AA of purified hydroacetonic hop extracts was investigated using the Ferric Reducing Ability of Plasma (FRAP), Oxygen Radical Absorption Capacity (ORAC) and Intracellular Antioxidant (IA) methods. The FRAP values in different hop genotypes ranged between 63.5 and 101.6 μmol Trolox equivalent (TE)/g dry weight (DW), the ORAC values ranged between 1069 and 1910 μmol TE/g DW and IA potential values ranged between 52.7 and 118.0 mmol TE/g DW. Significant differences in AA between hop genotypes were observed with all three methods. AAs were determined using three different methods, which did not highly correlate with each other. We also did not find significant correlations between AA and different chemical components, which applies both to AA determined using individual methods as well as the total AA. Based on this fact, we assume that the synergistic or antagonistic effects between hop compounds have a more pronounced effect on AA than the presence and quantity of individual hop compounds.

Nanomaterials and Their Recent Applications in Impedimetric Biosensing

Impedimetric biosensors measure changes in the electrical impedance due to a biochemical process, typically the binding of a biomolecule to a bioreceptor on the sensor surface. Nanomaterials can be employed to modify the biosensor's surface to increase the surface area available for biorecognition events, thereby improving the sensitivity and detection limits of the biosensor. Various nanomaterials, such as carbon nanotubes, carbon nanofibers, quantum dots, metal nanoparticles, and graphene oxide nanoparticles, have been investigated for impedimetric biosensors. These nanomaterials have yielded promising results in improving sensitivity, selectivity, and overall biosensor performance. Hence, they offer a wide range of possibilities for developing advanced biosensing platforms that can be employed in various fields, including healthcare, environmental monitoring, and food safety. This review focuses on the recent developments in nanoparticle-functionalized electrochemical-impedimetric biosensors.

Identifying Metal Binding Sites in Proteins Using Homologous Structures, the MADE Approach

In order to identify the locations of metal ions in the binding sites of proteins, we have developed a method named the MADE (MAcromolecular DEnsity and Structure Analysis) approach. The MADE approach represents an evolution of our previous toolset, the ProBiS H2O (MD) methodology, for the identification of conserved water molecules. Our method uses experimental structures of proteins homologous to a query, which are subsequently superimposed upon it. Areas with a particular species present in a similar location among many homologous protein structures are identified using a clustering algorithm. Dense clusters likely represent positions containing species important to the query protein structure or function. We analyze well-characterized apo protein structures and show that the MADE approach can identify clusters corresponding to the expected positions of metal ions in their binding sites. The greatest advantage of our method lies in its generality. It can in principle be applied to any species found in protein records; it is not only limited to metal ions. We additionally demonstrate that the MADE approach can be successfully applied to predict the location of cofactors in computer-modeled structures, e.g., via AlphaFold. We also conduct a careful protein superposition method comparison and find our methodology robust and the results largely independent of the selected protein superposition algorithm. We postulate that with increasing structural data availability, additional applications of the MADE approach will be possible such as non-protein systems, water network identification, protein binding site elaboration, and analysis of binding events, all in a dynamic manner. We have implemented the MADE approach as a plugin for the PyMOL molecular visualization tool. The MADE plugin is available free of charge at https://gitlab.com/Jukic/made_software.

Design of Tetra-Peptide Ligands of Antibody Fc Regions Using In Silico Combinatorial Library Screening

Peptides, or short chains of amino-acid residues, are becoming increasingly important as active ingredients of drugs and as crucial probes and/or tools in medical, biotechnological, and pharmaceutical research. Situated at the interface between small molecules and larger macromolecular systems, they pose a difficult challenge for computational methods. We report an in silico peptide library generation and prioritization workflow using CmDock for identifying tetrapeptide ligands that bind to Fc regions of antibodies that is analogous to known in vitro recombinant peptide libraries' display and expression systems. The results of our in silico study are in accordance with existing scientific literature on in vitro peptides that bind to antibody Fc regions. In addition, we postulate an evolving in silico library design workflow that will help circumvent the combinatorial problem of in vitro comprehensive peptide libraries by focusing on peptide subunits that exhibit favorable interaction profiles in initial in silico peptide generation and testing.

Fentanyl and the Fluorinated Fentanyl Derivative NFEPP Elicit Distinct Hydrogen-Bond Dynamics of the Opioid Receptor

The development of safe therapeutics to manage pain is of central interest for biomedical applications. The fluorinated fentanyl derivative N-(3-fluoro-1-phenethylpiperidin-4-yl)-N-phenylpropionamide (NFEPP) is potentially a safer alternative to fentanyl because unlike fentanyl─which binds to the μ-opioid receptor (MOR) at both physiological and acidic pH─NFEPP might bind to the MOR only at acidic pH typical of inflamed tissue. Knowledge of the protonation-coupled dynamics of the receptor-drug interactions is thus required to understand the molecular mechanism by which receptor activation initiates cell signaling to silence pain. To this end, here we have carried out extensive atomistic simulations of the MOR in different protonation states, in the absence of opioid drugs, and in the presence of fentanyl vs NFEPP. We used graph-based analyses to characterize internal hydrogen-bond networks that could contribute to the activation of the MOR. We find that fentanyl and NFEPP prefer distinct binding poses and that, in their binding poses, fentanyl and NFEPP partake in distinct internal hydrogen-bond networks, leading to the cytoplasmic G-protein-binding region. Moreover, the protonation state of functionally important aspartic and histidine side chains impacts hydrogen-bond networks that extend throughout the receptor, such that the ligand-bound MOR presents at its cytoplasmic G-protein-binding side, a hydrogen-bonding environment where dynamics depend on whether fentanyl or NFEPP is bound, and on the protonation state of specific MOR groups. The exquisite sensitivity of the internal protein-water hydrogen-bond network to the protonation state and to details of the drug binding could enable the MOR to elicit distinct pH- and opioid-dependent responses at its cytoplasmic G-protein-binding site.

The Influence of Chestnut Extract and Its Components on Antibacterial Activity against Staphylococcus aureus

Increasing antimicrobial resistance has caused a great interest in natural products as alternatives or potentiators of antibiotics. The objective of this study was to isolate individual tannins from crude chestnut extract as well as to determine the influence of both crude extracts (tannic acid extract, chestnut extract) and individual pure tannins (gallic acid, vescalin, vescalagin, castalin, castalagin) on the growth of Gram-positive Staphylococcus aureus bacteria. Their antibacterial activity was monitored by measuring the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) as well as the duration of the lag phase, growth rate and generation time. The effect of growth medium strength on the MIC of different tannins was also investigated. Bacterial growth was followed spectrophotometrically, and MIC values were determined by the microdilution method. The MIC values of various isolated compounds allowed us to determine the bioactive compounds and their contribution to antimicrobial activity. It was found that MIC values increase with increasing growth medium strength and that the lag phase lengthens with increasing tannin concentrations, while the growth rates decrease. Comparing the results of the two studies, the antimicrobial activity of tannins against S. aureus was not as pronounced as in the case of E. coli, which may indicate that a different mechanism of action is responsible for the antimicrobial effects of tannins on Gram-positive than on Gram-negative bacteria, or that a different mechanism is more pronounced.

Helichrysum italicum: From Extraction, Distillation, and Encapsulation Techniques to Beneficial Health Effects

Helichrysum italicum (family Asteraceae), due to its various beneficial health effects, represents an important plant in the traditional medicine of Mediterranean countries. Currently, there is a renewed interest in this medicinal plant, especially in investigations involving the isolation and identification of its bioactive compounds from extracts and essential oils, as well as in experimental validation of their pharmacological activities. In this paper, we review the current knowledge on the beneficial health effects of Helichrysum italicum extracts, essential oils, and their major bioactive polyphenolic compounds, ranging from antioxidative, anti-inflammatory, and anticarcinogenic activities to their antiviral, antimicrobial, insecticidal, and antiparasitic effects. This review also provides an overview of the most promising extraction and distillation techniques for obtaining high-quality extracts and essential oils from Helichrysum italicum, as well as methods for determining their antioxidative, antimicrobial, anti-inflammatory, and anticarcinogenic activities. Finally, new ideas for in silico studies of molecular mechanisms of bioactive polyphenols from Helichrysum italicum, together with novel suggestions for their improved bioavailability through diverse encapsulation techniques, are introduced.

Monocarbonyl Curcumin Analogues as Potent Inhibitors against Human Glutathione Transferase P1-1

The isoenzyme of human glutathione transferase P1-1 (hGSTP1-1) is involved in multi-drug resistance (MDR) mechanisms in numerous cancer cell lines. In the present study, the inhibition potency of two curcuminoids and eleven monocarbonyl curcumin analogues against hGSTP1-1 was investigated. Demethoxycurcumin (Curcumin II) and three of the monocarbonyl curcumin analogues exhibited the highest inhibitory activity towards hGSTP1-1 with IC₅₀ values ranging between 5.45 ± 1.08 and 37.72 ± 1.02 μM. Kinetic inhibition studies of the most potent inhibitors demonstrated that they function as non-competitive/mixed-type inhibitors. These compounds were also evaluated for their toxicity against the prostate cancer cells DU-145. Interestingly, the strongest hGSTP1-1 inhibitor, (DM96), exhibited the highest cytotoxicity with an IC₅₀ of 8.60 ± 1.07 μΜ, while the IC₅₀ values of the rest of the compounds ranged between 44.59-48.52 μΜ. Structural analysis employing molecular docking, molecular dynamics (MD) simulations, and binding-free-energy calculations was performed to study the four most potent curcumin analogues as hGSTP1-1 inhibitors. According to the obtained computational results, DM96 exhibited the lowest binding free energy, which is in agreement with the experimental data. All studied curcumin analogues were found to form hydrophobic interactions with the residue Gln52, as well as hydrogen bonds with the nearby residues Gln65 and Asn67. Additional hydrophobic interactions with the residues Phe9 and Val36 as well as π-π stacking interaction with Phe9 contributed to the superior inhibitory activity of DM96. The van der Waals component through shape complementarity was found to play the most important role in DM96-inhibitory activity. Overall, our results revealed that the monocarbonyl curcumin derivative DM96 acts as a strong hGSTP1-1 inhibitor, exerts high prostate cancer cell cytotoxicity, and may, therefore, be exploited for the suppression and chemosensitization of cancer cells. This study provides new insights into the development of safe and effective GST-targeted cancer chemosensitizers.

Antimicrobial Properties of Different Hop (Humulus lupulus) Genotypes

The antimicrobial activity of hop extracts obtained from different hop genotypes were investigated against Staphylococcus aureus and Lactobacillus acidophilus. In this study the pure xanthohumol, purified β-acids rich fraction, as well as α-acids with β-acids rich fraction were used to test antimicrobial activity against Staphylococcus aureus and Lactobacillus acidophilus; whereby, the antimicrobial activity of different hop extracts against Lactobacillus acidophilus was studied for the first time. Microbial susceptibility to purified hydroacetonic extracts from different hop varieties was investigated by the broth microdilution assay to determine the minimum inhibitory concentration (MIC) and the minimum bactericidal concentration (MBC). The hop hydroacetonic extracts were more effective against Staphylococcus aureus than against Lactobacillus acidophilus. Strong inverse correlations of MIC and MBC values were obtained with xanthohumol, cohumulone, n+adhumulone, colupulone and n+adlupulone contents, suggesting that the identified chemical hop compounds are directly responsible for antimicrobial effects. Moreover, the effect of the growth medium strength on the MIC values of hop extracts against Staphylococcus aureus was systematically investigated for the first time. The current study also reveals the effect of different hop extracts on Staphylococcus aureus, which responds to their presence by lag phase extension and generation time prolongation.

Recent Developments in Electrochemical-Impedimetric Biosensors for Virus Detection

Viruses, including influenza viruses, MERS-CoV (Middle East respiratory syndrome coronavirus), SARS-CoV (severe acute respiratory syndrome coronavirus), HAV (Hepatitis A virus), HBV (Hepatitis B virus), HCV (Hepatitis C virus), HIV (human immunodeficiency virus), EBOV (Ebola virus), ZIKV (Zika virus), and most recently SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), are responsible for many diseases that result in hundreds of thousands of deaths yearly. The ongoing outbreak of the COVID-19 disease has raised a global concern and intensified research on the detection of viruses and virus-related diseases. Novel methods for the sensitive, rapid, and on-site detection of pathogens, such as the recent SARS-CoV-2, are critical for diagnosing and treating infectious diseases before they spread and affect human health worldwide. In this sense, electrochemical impedimetric biosensors could be applied for virus detection on a large scale. This review focuses on the recent developments in electrochemical-impedimetric biosensors for the detection of viruses.

Conserved Water Networks Identification for Drug Design Using Density Clustering Approaches on Positional and Orientational Data

This work describes the development and testing of a method for the identification and classification of conserved water molecules and their networks from molecular dynamics (MD) simulations. The conserved waters in the active sites of proteins influence protein-ligand binding. Recently, several groups have argued that a water network formed from conserved waters can be used to interpret the thermodynamic signature of the binding site. We implemented a novel methodology in which we apply the complex approach to categorize water molecules extracted from the MD simulation trajectories using clustering approaches. The main advantage of our methodology as compared to current state of the art approaches is the inclusion of the information on the orientation of hydrogen atoms to further inform the clustering algorithm and to classify the conserved waters into different subtypes depending on how strongly certain orientations are preferred. This information is vital for assessing the stability of water networks. The newly developed approach is described in detail as well as validated against known results from the scientific literature including comparisons with the experimental data on thermolysin, thrombin, and Haemophilus influenzae virulence protein SiaP as well as with the previous computational results on thermolysin. We observed excellent agreement with the literature and were also able to provide additional insights into the orientations of the conserved water molecules, highlighting the key interactions which stabilize them. The source code of our approach, as well as the utility tools used for visualization, are freely available on GitHub.

The Effect of the Ala16Val Mutation on the Secondary Structure of the Manganese Superoxide Dismutase Mitochondrial Targeting Sequence

Manganese Superoxide Dismutase (MnSOD) represents a mitochondrial protein that scavenges reactive oxygen species (ROS) responsible for oxidative stress. A known single nucleotide polymorphism (SNP) rs4880 on the SOD2 gene, causing a mutation from alanine to valine (Ala16Val) in the primary structure of immature MnSOD, has been associated with several types of cancer and other autoimmune diseases. However, no conclusive correlation has been established yet. This study aims to determine the effect of the alanine to valine mutation on the secondary structure of the MnSOD mitochondrial targeting sequence (MTS). A model for each variant of the MTS was prepared and extensively simulated with molecular dynamics simulations using the CHARMM36m force field. The results indicate that the alanine variant of the MTS preserves a uniform α-helical secondary structure favorable for the protein transport into mitochondria, whereas the valine variant quickly breaks down its α-helix. Thus, the alanine MTS represents the more active MnSOD variant, the benefits of which have yet to be determined experimentally.

Electrochromic Device Demonstrator from Household Materials

Electrochromism encompasses reversible changes of material's optical properties (color, opacity) under the influence of an external electric current or applied voltage. The effect has been known for decades, but its importance continues to grow due to the rapid development of smart systems and the accompanying demand to build devices that consume less power. Most commercial electrochromic devices (ECDs) require sophisticated chemicals and advanced material preparation techniques. Also, the demonstration of electrochromism in chemistry classes mainly uses expensive WO₃ films, intrinsically conductive polymers, and/or optically transparent electrodes (OTEs). The aim of this article is to present a simple and fast educational method to build ECDs from household materials without the need for OTEs: unsharpened kitchen knives are used as electrodes, curcumin from turmeric is used as the electrochromic dye, and baking soda is used as the electrolyte. The laboratory experiments presented will help students gain a deeper understanding of the fundamentals of electrochemistry (electrolysis, pH change) and electrochromism (in our case, color changes due to pH-induced keto-enol tautomerism of curcumin).

Perspective Chapter: Bioinformatics Study of the Evolution of SARS-CoV-2 Spike Protein

SARS-CoV-2 belongs to the family of coronaviruses, which are characterized by spikes that sit densely on the surface of the virus. The spike protein (Spro) is responsible for the attachment of the virus to the host cell via the ACE2 receptor on the surface of the host cell. The strength of the interaction between the receptor-binding domain (RBD) of the highly glycosylated spike protein of the virus and the host cell ACE2 receptor represents the key determinant of the infectivity of the virus. The SARS-CoV-2 virus has mutated since the beginning of the outbreak, and the vast majority of mutations has been detected in the spike protein or its RBD. Since specific mutations significantly affect the ability of the virus to transmit and to evade immune response, studies of these mutations are critical. We investigate GISAID data to show how viral spike protein mutations evolved during the pandemic. We further present the interactions of the viral Spro RBD with the host ACE2 receptor. We have performed a large-scale mutagenesis study of the Spro RBD-ACE2 interface by performing point mutations in silico and identifying the ambiguous interface stabilization by the most common point mutations in the viral variants of interest (beta, gamma, delta, omicron).

The Use of Yeast Saccharomyces Cerevisiae as a Biorecognition element in the Development of a Model Impedimetric Biosensor for Caffeine Detection

In the present study, an electrochemical-impedimetric biosensor using Saccharomyces cerevisiae as an effective biorecognition element was designed to detect caffeine. The presented biosensor consists of a previously developed stainless steel electrochemical cell constructed as a three-electrode system in the RCW side-by-side configuration. The electrochemical stability of the sensing electrode was evaluated by measuring the open circuit potential (OCP), and electrochemical impedance spectroscopy (EIS) was applied to determine the impedimetric response of the biosensor with Saccharomyces cerevisiae cells attached to the working electrode (WE) in the absence (0.9% NaCl) and presence (10 mg/mL in 0.9% NaCl) of caffeine. Moreover, the limit of detection (LOD) was determined. In this way, a new approach in biosensor development has been established, which involves assembling a low-cost and disposable electrochemical system to detect alkaloids such as caffeine. The developed biosensor represents a good candidate for detecting caffeine in beverages, foods, and drugs with the merits of time-saving, robustness, low cost, and low detection limit.

Machine Learning in Antibacterial Drug Design

Advances in computer hardware and the availability of high-performance supercomputing platforms and parallel computing, along with artificial intelligence methods are successfully complementing traditional approaches in medicinal chemistry. In particular, machine learning is gaining importance with the growth of the available data collections. One of the critical areas where this methodology can be successfully applied is in the development of new antibacterial agents. The latter is essential because of the high attrition rates in new drug discovery, both in industry and in academic research programs. Scientific involvement in this area is even more urgent as antibacterial drug resistance becomes a public health concern worldwide and pushes us increasingly into the post-antibiotic era. In this review, we focus on the latest machine learning approaches used in the discovery of new antibacterial agents and targets, covering both small molecules and antibacterial peptides. For the benefit of the reader, we summarize all applied machine learning approaches and available databases useful for the design of new antibacterial agents and address the current shortcomings.

Inverse Molecular Docking Elucidating the Anticarcinogenic Potential of the Hop Natural Product Xanthohumol and Its Metabolites

Natural products from plants exert a promising potential to act as antioxidants, antimicrobials, anti-inflammatory, and anticarcinogenic agents. Xanthohumol, a natural compound from hops, is indeed known for its anticarcinogenic properties. Xanthohumol is converted into three metabolites: isoxanthohumol (non-enzymatically) as well as 8- and 6-prenylnaringenin (enzymatically). An inverse molecular docking approach was applied to xanthohumol and its three metabolites to discern their potential protein targets. The aim of our study was to disclose the potential protein targets of xanthohumol and its metabolites in order to expound on the potential anticarcinogenic mechanisms of xanthohumol based on the found target proteins. The investigated compounds were docked into the predicted binding sites of all human protein structures from the Protein Data Bank, and the best docking poses were examined. Top scoring human protein targets with successfully docked compounds were identified, and their experimental connection with the anticarcinogenic function or cancer was investigated. The obtained results were carefully checked against the existing experimental findings from the scientific literature as well as further validated using retrospective metrics. More than half of the human protein targets of xanthohumol with the highest docking scores have already been connected with the anticarcinogenic function, and four of them (including two important representatives of the matrix metalloproteinase family, MMP-2 and MMP-9) also have a known experimental correlation with xanthohumol. Another important protein target is acyl-protein thioesterase 2, to which xanthohumol, isoxanthohumol, and 6-prenylnaringenin were successfully docked with the lowest docking scores. Moreover, the results for the metabolites show that their most promising protein targets are connected with the anticarcinogenic function as well. We firmly believe that our study can help to elucidate the anticarcinogenic mechanisms of xanthohumol and its metabolites as after consumption, all four compounds can be simultaneously present in the organism.

A HepG2 Cell-Based Biosensor That Uses Stainless Steel Electrodes for Hepatotoxin Detection

Humans are frequently exposed to environmental hepatotoxins, which can lead to liver failure. Biosensors may be the best candidate for the detection of hepatotoxins because of their high sensitivity and specificity, convenience, time-saving, low cost, and extremely low detection limit. To investigate suitability of HepG2 cells for biosensor use, different methods of adhesion on stainless steel surfaces were investigated, with three groups of experiments performed in vitro. Cytotoxicity assays, which include the resazurin assay, the neutral red assay (NR), and the Coomassie Brilliant Blue (CBB) assay, were used to determine the viability of HepG2 cells exposed to various concentrations of aflatoxin B1 (AFB1) and isoniazid (INH) in parallel. The viability of the HepG2 cells on the stainless steel surface was quantitatively and qualitatively examined with different microscopy techniques. A simple cell-based electrochemical biosensor was developed by evaluating the viability of the HepG2 cells on the stainless steel surface when exposed to various concentrations of AFB1 and INH by using electrochemical impedance spectroscopy (EIS). The results showed that HepG2 cells can adhere to the metal surface and could be used as part of the biosensor to determine simple hepatotoxic samples.

The influence of pH on UV/Vis spectra of gallic and ellagic acid: A combined experimental and computational study

The pH dependence of the UV/Vis spectrum of gallic and ellagic acid was measured in a buffer-free solution to obtain reliable data at wavelengths bellow 230 nm. UV/Vis absorption spectra were also calculated for all possible ionised species of gallic and ellagic acid using time dependent density functional theory (TD-DFT). From pK_a values of gallic and ellagic acid the molar fraction of different ionised species was calculated for each pH value. Finally, the simulated spectra at different pH values were obtained as a weighted average of spectra of neutral, once, twice, three-times, and four-times deprotonated species. The calculated spectra were then compared to the experimental spectra, and the peaks in the experimental spectrum were explained in the terms of main electronic transitions that results in the observed absorption bands. At low pH values the agreement between the experimental and calculated spectra was excellent. At near-neutral pH values the majority of the experimental spectra features were well reproduced in the calculated spectra. A satisfactory agreement between experimental and calculated spectrum at high pH values was also achieved by incorporating the calculated spectra of the oxidised species of gallic acid as well as ellagic acid spectra with one lactone ring open.

Commercial SARS-CoV-2 Targeted, Protease Inhibitor Focused and Protein-Protein Interaction Inhibitor Focused Molecular Libraries for Virtual Screening and Drug Design

Since December 2019, the new SARS-CoV-2-related COVID-19 disease has caused a global pandemic and shut down the public life worldwide. Several proteins have emerged as potential therapeutic targets for drug development, and we sought out to review the commercially available and marketed SARS-CoV-2-targeted libraries ready for high-throughput virtual screening (HTVS). We evaluated the SARS-CoV-2-targeted, protease-inhibitor-focused and protein-protein-interaction-inhibitor-focused libraries to gain a better understanding of how these libraries were designed. The most common were ligand- and structure-based approaches, along with various filtering steps, using molecular descriptors. Often, these methods were combined to obtain the final library. We recognized the abundance of targeted libraries offered and complimented by the inclusion of analytical data; however, serious concerns had to be raised. Namely, vendors lack the information on the library design and the references to the primary literature. Few references to active compounds were also provided when using the ligand-based design and usually only protein classes or a general panel of targets were listed, along with a general reference to the methods, such as molecular docking for the structure-based design. No receptor data, docking protocols or even references to the applied molecular docking software (or other HTVS software), and no pharmacophore or filter design details were given. No detailed functional group or chemical space analyses were reported, and no specific orientation of the libraries toward the design of covalent or noncovalent inhibitors could be observed. All libraries contained pan-assay interference compounds (PAINS), rapid elimination of swill compounds (REOS) and aggregators, as well as focused on the drug-like model, with the majority of compounds possessing their molecular mass around 500 g/mol. These facts do not bode well for the use of the reviewed libraries in drug design and lend themselves to commercial drug companies to focus on and improve.

Repurposing of Drugs for SARS-CoV-2 Using Inverse Docking Fingerprints

Severe acute respiratory syndrome coronavirus 2 or SARS-CoV-2 is a virus that belongs to the Coronaviridae family. This group of viruses commonly causes colds but possesses a tremendous pathogenic potential. In humans, an outbreak of SARS caused by the SARS-CoV virus was first reported in 2003, followed by 2012 when the Middle East respiratory syndrome coronavirus (MERS-CoV) led to an outbreak of Middle East respiratory syndrome (MERS). Moreover, COVID-19 represents a serious socioeconomic and global health problem that has already claimed more than four million lives. To date, there are only a handful of therapeutic options to combat this disease, and only a single direct-acting antiviral, the conditionally approved remdesivir. Since there is an urgent need for active drugs against SARS-CoV-2, the strategy of drug repurposing represents one of the fastest ways to achieve this goal. An in silico drug repurposing study using two methods was conducted. A structure-based virtual screening of the FDA-approved drug database on SARS-CoV-2 main protease was performed, and the 11 highest-scoring compounds with known 3CLpro activity were identified while the methodology was used to report further 11 potential and completely novel 3CLpro inhibitors. Then, inverse molecular docking was performed on the entire viral protein database as well as on the Coronaviridae family protein subset to examine the hit compounds in detail. Instead of target fishing, inverse docking fingerprints were generated for each hit compound as well as for the five most frequently reported and direct-acting repurposed drugs that served as controls. In this way, the target-hitting space was examined and compared and we can support the further biological evaluation of all 11 newly reported hits on SARS-CoV-2 3CLpro as well as recommend further in-depth studies on antihelminthic class member compounds. The authors acknowledge the general usefulness of this approach for a full-fledged inverse docking fingerprint screening in the future.

Mechanistic Insights into Biological Activities of Polyphenolic Compounds from Rosemary Obtained by Inverse Molecular Docking

Rosemary (Rosmarinus officinalis L.) represents a medicinal plant known for its various health-promoting properties. Its extracts and essential oils exhibit antioxidative, anti-inflammatory, anticarcinogenic, and antimicrobial activities. The main compounds responsible for these effects are the diterpenes carnosic acid, carnosol, and rosmanol, as well as the phenolic acid ester rosmarinic acid. However, surprisingly little is known about the molecular mechanisms responsible for the pharmacological activities of rosemary and its compounds. To discern these mechanisms, we performed a large-scale inverse molecular docking study to identify their potential protein targets. Listed compounds were separately docked into predicted binding sites of all non-redundant holo proteins from the Protein Data Bank and those with the top scores were further examined. We focused on proteins directly related to human health, including human and mammalian proteins as well as proteins from pathogenic bacteria, viruses, and parasites. The observed interactions of rosemary compounds indeed confirm the beforementioned activities, whereas we also identified their potential for anticoagulant and antiparasitic actions. The obtained results were carefully checked against the existing experimental findings from the scientific literature as well as further validated using both redocking procedures and retrospective metrics.

Model Electrochemical Biosensor for the Detection of Methanol in Aqueous Solutions with Yeast Cells

An electrochemical device that serves as a model biosensor and contains yeast Saccharomyces cerevisiae as the active biological element was developed. Different configurations of the electrochemical cells were assembled and tested. Stainless steel was used in the electrochemical cell composition process and the surface of this metal electrode was modified with a thin layer of WO3 if necessary. The yeast Saccharomyces cerevisiae was adhered to the working electrode. The resulting model biosensor was then used to monitor the response to a 10% CH3OH. For detection of biological activity, the electrochemical impedance spectroscopy (EIS) method was applied with a portable potentiostat/galvanostat, where the Bode and the Nyquist plots were interpreted. The stability of the device was beforehand determined by measuring the open circuit potential (OCP). The topography of the electrodes was inspected using the techniques of scanning electron microscopy and optical microscopy. The investigated model biosensor serves as a case study for the development of more complex biosensors that utilize living cells as the active layer.

Dependence of the Fe(II)-Gallic Acid Coordination Compound Formation Constant on the pH

One important property of tannins involves their ability to form coordination compounds with metal ions, which is vital for the bioavailability of these ions, as well as for the antibacterial and antioxidative activities of tannins. In this study, the pH dependence of interactions between gallic acid, one of the basic building blocks of tannins, and Fe(II) ions, was investigated using UV/Vis spectroscopy, in conjunction with density functional theory (DFT) calculations. Moreover, two models were developed to explain the processes taking place in the solution. The first model treated the reaction as a simple bimolecular process while the second also considered the protolytic equilibrium, which was proven very successful in discerning the pH dependence of formation constants, and whose assumptions were well supported by DFT calculations. We showed that the two-time deprotonated gallic acid species forms the coordination compound with Fe(II) ions in a 1:1 molar ratio. To gain better insight into the process, the coordination compound formation was also studied using various DFT functionals, which further supported the model results. Furthermore, due to the relatively low sample amounts needed, the methodology developed here will be useful to study compounds that are more difficult to isolate.

Potential Novel Thioether-Amide or Guanidine-Linker Class of SARS-CoV-2 Virus RNA-Dependent RNA Polymerase Inhibitors Identified by High-Throughput Virtual Screening Coupled to Free-Energy Calculations

SARS-CoV-2, or severe acute respiratory syndrome coronavirus 2, represents a new pathogen from the family of Coronaviridae that caused a global pandemic of COVID-19 disease. In the absence of effective antiviral drugs, research of novel therapeutic targets such as SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) becomes essential. This viral protein is without a human counterpart and thus represents a unique prospective drug target. However, in vitro biological evaluation testing on RdRp remains difficult and is not widely available. Therefore, we prepared a database of commercial small-molecule compounds and performed an in silico high-throughput virtual screening on the active site of the SARS-CoV-2 RdRp using ensemble docking. We identified a novel thioether-amide or guanidine-linker class of potential RdRp inhibitors and calculated favorable binding free energies of representative hits by molecular dynamics simulations coupled with Linear Interaction Energy calculations. This innovative procedure maximized the respective phase-space sampling and yielded non-covalent inhibitors representing small optimizable molecules that are synthetically readily accessible, commercially available as well as suitable for further biological evaluation and mode of action studies.

CHARMM Force-Field Parameters for Morphine, Heroin, and Oliceridine, and Conformational Dynamics of Opioid Drugs

Opioid drug binding to specialized G protein-coupled receptors (GPCRs) can lead to analgesia upon activation via downstream G_i protein signaling and to severe side effects via activation of the β-arrestin signaling pathway. Knowledge of how different opioid drugs interact with receptors is essential, as it can inform and guide the design of safer therapeutics. We performed quantum and classical mechanical computations to explore the potential energy landscape of four opioid drugs: morphine and its derivatives heroin and fentanyl and for the unrelated oliceridine. From potential energy profiles for bond twists and from interactions between opioids and water, we derived a set of force-field parameters that allow a good description of structural properties and intermolecular interactions of the opioids. Potential of mean force profiles computed from molecular dynamics simulations indicate that fentanyl and oliceridine have complex energy landscapes with relatively small energy penalties, suggesting that interactions with the receptor could select different binding poses of the drugs.

Molecular Dynamics Simulations Reveal Interactions of an IgG1 Antibody With Selected Fc Receptors

In a survey of novel interactions between an IgG1 antibody and different Fcγ receptors (FcγR), molecular dynamics simulations were performed of interactions of monoclonal antibody involved complexes with FcγRs. Free energy simulations were also performed of isolated wild-type and substituted Fc regions bound to FcγRs with the aim of assessing their relative binding affinities. Two different free energy calculation methods, Molecular Mechanical/Generalized Born Molecular Volume (MM/GBMV) and Bennett Acceptance Ratio (BAR), were used to evaluate the known effector substitution G236A that is known to selectively increase antibody dependent cellular phagocytosis. The obtained results for the MM/GBMV binding affinity between different FcγRs are in good agreement with previous experiments, and those obtained using the BAR method for the complete antibody and the Fc-FcγR simulations show increased affinity across all FcγRs when binding to the substituted antibody. The FcγRIIa, a key determinant of antibody agonistic efficacy, shows a 10-fold increase in binding affinity, which is also consistent with the published experimental results. Novel interactions between the Fab region of the antibody and the FcγRs were discovered with this in silico approach, and provide insights into the antibody-FcγR binding mechanism and show promise for future improvements of therapeutic antibodies for preclinical studies of biological drugs.

Prioritisation of Compounds for 3CLpro Inhibitor Development on SARS-CoV-2 Variants

COVID-19 represents a new potentially life-threatening illness caused by severe acute respiratory syndrome coronavirus 2 or SARS-CoV-2 pathogen. In 2021, new variants of the virus with multiple key mutations have emerged, such as B.1.1.7, B.1.351, P.1 and B.1.617, and are threatening to render available vaccines or potential drugs ineffective. In this regard, we highlight 3CL^pro, the main viral protease, as a valuable therapeutic target that possesses no mutations in the described pandemically relevant variants. 3CL^pro could therefore provide trans-variant effectiveness that is supported by structural studies and possesses readily available biological evaluation experiments. With this in mind, we performed a high throughput virtual screening experiment using CmDock and the "In-Stock" chemical library to prepare prioritisation lists of compounds for further studies. We coupled the virtual screening experiment to a machine learning-supported classification and activity regression study to bring maximal enrichment and available structural data on known 3CL^pro inhibitors to the prepared focused libraries. All virtual screening hits are classified according to 3CL^pro inhibitor, viral cysteine protease or remaining chemical space based on the calculated set of 208 chemical descriptors. Last but not least, we analysed if the current set of 3CL^pro inhibitors could be used in activity prediction and observed that the field of 3CL^pro inhibitors is drastically under-represented compared to the chemical space of viral cysteine protease inhibitors. We postulate that this methodology of 3CL^pro inhibitor library preparation and compound prioritisation far surpass the selection of compounds from available commercial "corona focused libraries".

Insight into Inhibitory Mechanism of PDE4D by Dietary Polyphenols Using Molecular Dynamics Simulations and Free Energy Calculations

Phosphodiesterase 4 (PDE4), mainly present in immune, epithelial, and brain cells, represents a family of key enzymes for the degradation of cyclic adenosine monophosphate (cAMP), which modulates inflammatory response. In recent years, the inhibition of PDE4 has been proven to be an effective therapeutic strategy for the treatment of neurological disorders. PDE4D constitutes a high-interest therapeutic target primarily for the treatment of Alzheimer’s disease, as it is highly involved in neuroinflammation, learning ability, and memory dysfunctions. In the present study, a thorough computational investigation consisting of molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations based on the linear response approximation (LRA) method was performed to study dietary polyphenols as potential PDE4D inhibitors. The obtained results revealed that curcumin, 6-gingerol, capsaicin, and resveratrol represent potential PDE4D inhibitors; however, the predicted binding free energies of 6-gingerol, capsaicin, and resveratrol were less negative than in the case of curcumin, which exhibited the highest inhibitory potency in comparison with a positive control rolipram. Our results also revealed that the electrostatic component through hydrogen bonding represents the main driving force for the binding and inhibitory activity of curcumin, 6-gingerol, and resveratrol, while the van der Waals component through shape complementarity plays the most important role in capsaicin’s inhibitory activity. All investigated compounds form hydrophobic interactions with residues Gln376 and Asn602 as well as hydrogen bonds with nearby residues Asp438, Met439, and Ser440. The binding mode of the studied natural compounds is consequently very similar; however, it significantly differs from the binding of known PDE4 inhibitors. The uncovered molecular inhibitory mechanisms of four investigated natural polyphenols, curcumin, 6-gingerol, capsaicin, and resveratrol, form the basis for the design of novel PDE4D inhibitors for the treatment of Alzheimer’s disease with a potentially wider therapeutic window and fewer adverse side effects.

Molecular Dynamics Simulations Predict That rSNP Located in the HNF‑1α Gene Promotor Region Linked with MODY3 and Hepatocellular Carcinoma Promotes Stronger Binding of the HNF‑4α Transcription Factor

Our study aims to investigate the impact of the Maturity-onset diabetes of the young 3 disease-linked rSNP rs35126805 located in the HNF-1α gene promotor on the binding of the transcription factor HNF-4α and consequently on the regulation of HNF-1α gene expression. Our focus is to calculate the change in the binding affinity of the transcription factor HNF-4α to the DNA, caused by the regulatory single nucleotide polymorphism (rSNP) through molecular dynamics simulations and thermodynamic analysis of acquired results. Both root-mean-square difference (RMSD) and the relative binding free energy ΔΔG_bind reveal that the HNF-4α binds slightly more strongly to the DNA containing the mutation (rSNP) making the complex more stable/rigid, and thereby influencing the expression of the HNF-1α gene. The resulting disruption of the HNF-4α/HNF-1α pathway is also linked to hepatocellular carcinoma metastasis and enhanced apoptosis in pancreatic cancer cells. To the best of our knowledge, this represents the first study where thermodynamic analysis of the results obtained from molecular dynamics simulations is performed to uncover the influence of rSNP on the protein binding to DNA. Therefore, our approach can be generally applied for studying the impact of regulatory single nucleotide polymorphisms on the binding of transcription factors to the DNA.

Determination of Camelina Oil Sterol Composition and Its Application for Authenticity Studies

Camelina oil has a high sterol concentration and is rather expensive compared to other vegetable oils. Because of its higher price, it is often adulterated by the addition of other, cheaper oils. This study was performed to validate a method for sterol determination in camelina oil, enabling the detection of camelina oil adulteration. Sterol levels in camelina oil samples were determined by gas chromatography after saponification and solid phase extraction. The method was validated, and the results proved that the chosen method is specific and selective, repeatable and accurate. The quantitatively assessed average contents of sterols in camelina oil samples of Slovenian origin were 21.4 mg 100 g–1 for brassicasterol, 153.6 mg 100 g–1 for campesterol, 3.9 mg 100 g–1 for stigmasterol, and 447.0 mg 100 g–1 for β-sitosterol. Results of camelina oil authenticity studies regarding botanical origin, performed by Principal Component Analysis (PCA) and Regularized Discriminant Analysis (RDA) enabled us to differentiate 100 % camelina oils from camelina oils adulterated with 10%–40% added sunflower, rapeseed or soya oil.

Determination of Camelina Oil Sterol Composition and Its Application for Authenticity Studies

Camelina oil has a high sterol concentration and is rather expensive compared to other vegetable oils. Because of its higher price, it is often adulterated by the addition of other, cheaper oils. This study was performed to validate a method for sterol determination in camelina oil, enabling the detection of camelina oil adulteration. Sterol levels in camelina oil samples were determined by gas chromatography after saponification and solid phase extraction. The method was validated, and the results proved that the chosen method is specific and selective, repeatable and accurate. The quantitatively assessed average contents of sterols in camelina oil samples of Slovenian origin were 21.4 mg 100 g-1 for brassicasterol, 153.6 mg 100 g-1 for campesterol, 3.9 mg 100 g-1 for stigmasterol, and 447.0 mg 100 g-1 for b-sitosterol. Results of camelina oil authenticity studies regarding botanical origin, performed by Principal Component Analysis (PCA) and Regularized Discriminant Analysis (RDA) enabled us to differentiate 100 % camelina oils from camelina oils adulterated with 10 %-40 % added sunflower, rapeseed or soya oil.

Generation Times of E. coli Prolong with Increasing Tannin Concentration while the Lag Phase Extends Exponentially

The current study examines the effect of tannins and tannin extracts on the lag phase duration, growth rate, and generation time of Escherichia coli. Effects of castalagin, vescalagin, gallic acid, Colistizer, tannic acid as well as chestnut, mimosa, and quebracho extracts were determined on E. coli's growth phases using the broth microdilution method and obtained by turbidimetric measurements. E. coli responds to the stress caused by the investigated antimicrobial agents with reduced growth rates, longer generation times, and extended lag phases. Prolongation of the lag phase was relatively small at low tannin concentrations, while it became more pronounced at concentrations above half the MIC. Moreover, for the first time, it was observed that lag time extensions follow a strict exponential relationship with increasing tannin concentrations. This feature is very likely a direct consequence of the tannin complexation of certain essential ions from the growth medium, making them unavailable to E. coli for its growth.

ProBiS H2O MD Approach for Identification of Conserved Water Sites in Protein Structures for Drug Design

The ProBiS H2O MD approach for identification of conserved waters and water sites of interest in macromolecular systems, which is becoming a typical step in a structure-based drug design or macromolecular study in general, is described. This work explores an extension of the ProBiS H2O approach introduced by Jukič et al. Indeed, water molecules are key players in the interaction mechanisms of macromolecules and small molecules and play structural roles. Our earlier developed approach, ProBiS H2O, is a simple and transparent workflow for conserved water detection. Here we have considered generalizing the idea by supplementing the experimental data with data derived from molecular dynamics to facilitate work on less known systems. Newly developed ProBiS H2O MD workflow uses trajectory data, extracts and identifies interesting water sites, and visualizes the results. ProBiS H2O MD can thus robustly process molecular dynamic trajectory snapshots, perform local superpositions, collect water location data, and perform density-based clustering to identify discrete sites with high conservation of water molecules. This is a new approach that uses experimental data in silico to identify interesting water sites. Methodology is fast and water-model or molecular dynamics software independent. Trends in the conservation of water molecules can be followed over a variety of trajectories, and our approach has been successfully validated using reported protein systems with experimentally observed conserved water molecules. ProBiS H2O MD is freely available as PyMOL plugin at http://insilab.org.

Computational design of probes to detect bacterial genomes by multivalent binding

Rapid methods for diagnosis of bacterial infections are urgently needed to reduce inappropriate use of antibiotics, which contributes to antimicrobial resistance. In many rapid diagnostic methods, DNA oligonucleotide probes, attached to a surface, bind to specific nucleotide sequences in the DNA of a target pathogen. Typically, each probe binds to a single target sequence; i.e., target-probe binding is monovalent. Here we show using computer simulations that the detection sensitivity and specificity can be improved by designing probes that bind multivalently to the entire length of the pathogen genomic DNA, such that a given probe binds to multiple sites along the target DNA. Our results suggest that multivalent targeting of long pieces of genomic DNA can allow highly sensitive and selective binding of the target DNA, even if competing DNA in the sample also contains binding sites for the same probe sequences. Our results are robust to mild fragmentation of the bacterial genome. Our conclusions may also be relevant for DNA detection in other fields, such as disease diagnostics more broadly, environmental management, and food safety.

Could Microwave Irradiation Cause Misfolding of Peptides?

Microwaves have been experimentally shown to affect the folding dynamics of peptides and proteins. Using molecular dynamics, we performed all-atom simulations of a model β-peptide in aqueous solution where individual degrees of freedom of solvent molecules were decoupled to allow for investigation at non-equilibrium microwave-irradiated conditions. An elevated rotational temperature of the water medium was found to significantly affect the conformation of the peptide due to the weakened hydrogen-bonding interactions with the surrounding solvent molecules. Cluster analysis revealed that microwave irradiation can indeed act as a promoter in the formation of new misfolded peptide structures of the hairpin type, which are generally associated with the onset of several neurodegenerative disorders such as Alzheimer’s, Parkinson’s, Huntington’s, and Creutzfeldt–Jakob diseases as well as certain cancer types such as amyloidosis.

Carcinogenesis of β-Propiolactone: A Computational Study

The discovery that β-propiolactone (BPL), once a commercially important chemical, causes various tumors in experimental animals has led to a significant decrease in its use. However, owing to its efficacy this possible human carcinogen remains to be utilized in vaccines for inactivation of viruses. The focus of the current study was to uncover the mechanisms of β-propiolactone reactions with both nucleobases and glutathione (GSH) through computer simulations based on quantum chemical methods. Our results, in accordance with in vitro studies, show that among all nucleobases guanine most readily forms adducts with BPL through S_N2 reaction mechanism. Acquired activation energies with incorporated solvent effects reveal that alkylation represents an energetically more favorable reaction than acylation for all nucleobases. Comparison of activation free energies of glutathione and guanine reactions with BPL suggest that glutathione may represent an efficient natural scavenger of BPL. Therefore, glutathione present in the organism may provide protection to the DNA and thus prevent BPL’s genotoxicity, mutagenicity, and possibly even carcinogenicity.

Protective Effects of [6]-Gingerol Against Chemical Carcinogens: Mechanistic Insights

[6]-Gingerol from ginger has received considerable attention as a potential cancer therapeutic agent because of its chemopreventive and chemotherapeutic effects, as well as its safety. In the current study, we examined [6]-gingerol as a natural scavenger of nine ultimate chemical carcinogens to which we are frequently exposed: glycidamide, styrene oxide, aflatoxin B1 exo-8,9-epoxide, β-propiolactone, ethylene oxide, propylene oxide, 2-cyanoethylene oxide, chloroethylene oxide, and vinyl carbamate epoxide. To evaluate [6]-gingerol efficacy, we expanded our research with the examination of glutathione-the strongest natural scavenger in human cells. The corresponding activation free energies were calculated using Hartree-Fock method with three flexible basis sets and two implicit solvation models. According to our results, [6]-gingerol proves to be an extremely effective scavenger of chemical carcinogens of the epoxy type. On the other hand, with the exception of aflatoxin B1 exo-8,9-epoxide, glutathione represents a relatively poor scavenger, whose efficacy could be augmented by [6]-gingerol. Moreover, our quantum mechanical study of the alkylation reactions of chemical carcinogens with [6]-gingerol and glutathione provide valuable insights in the reaction mechanisms and the geometries of the corresponding transition states. Therefore, we strongly believe that our research forms a solid basis for further computational, experimental and clinical studies of anticarcinogenic properties of [6]-gingerol as well as for the development of novel chemoprophylactic dietary supplements. Finally, the obtained results also point to the applicability of quantum chemical methods to studies of alkylation reactions related to chemical carcinogenesis.

Tannin Basic Building Blocks as Potential Scavengers of Chemical Carcinogens: A Computational Study

Tannins are natural compounds that have historically been used in the tanning of leather. In the scientific literature, one finds many reports of their possible beneficial health effects, although these are not always unequivocally confirmed. In order to gain a better insight into their proposed anticancer potential, we studied the scavenging capacity of the basic tannin building blocks against various chemical carcinogens of the epoxy type. The reactivity of gallic acid, ellagic acid, and epicathechin was examined using quantum mechanical calculations at the Hartree-Fock level of theory in conjunction with flexible basis sets and implicit solvation models. The monomeric tannin building blocks exhibited significant scavenging potential, with epicatechin presenting the best scavenger, thus encouraging and guiding future experimental studies of their anticarcinogenic properties.

Functionalization of Polyethylene (PE) and Polypropylene (PP) Material Using Chitosan Nanoparticles with Incorporated Resveratrol as Potential Active Packaging

The present paper reports a novel method to improve the properties of polyethylene (PE) and polypropylene (PP) polymer foils suitable for applications in food packaging. It relates to the adsorption of chitosan-colloidal systems onto untreated and oxygen plasma-treated foil surfaces. It is hypothesized that the first coated layer of chitosan macromolecular solution enables excellent antibacterial properties, while the second (uppermost) layer contains a network of polyphenol resveratrol, embedded into chitosan nanoparticles, which enables antioxidant and antimicrobial properties simultaneously. X-ray photon spectroscopy (XPS) and infrared spectroscopy (FTIR) showed successful binding of both coatings onto foils as confirmed by gravimetric method. In addition, both attached layers (chitosan macromolecular solution and dispersion of chitosan nanoparticles with incorporated resveratrol) onto foils reduced oxygen permeability and wetting contact angle of foils; the latter indicates good anti-fog foil properties. Reduction of both oxygen permeability and wetting contact angle is more pronounced when foils are previously activated by O2 plasma. Moreover, oxygen plasma treatment improves stability and adhesion of chitosan structured adsorbates onto PP and PE foils. Foils also exhibit over 90% reduction of Staphylococcus aureus and over 77% reduction of Escherichia coli as compared to untreated foils and increase antioxidant activity for over a factor of 10. The present method may be useful in different packaging applications such as food (meat, vegetables, dairy, and bakery products) and pharmaceutical packaging, where such properties of foils are desired.

Discovery of Novel Potential Human Targets of Resveratrol by Inverse Molecular Docking

Resveratrol is a polyphenol known for its antioxidant and anti-inflammatory properties, which support its use as a treatment for variety of diseases. There are already known connections of resveratrol to chemoprevention of cancer because of its ability to prevent tumor initiation and inhibit tumor promotion and progression. Resveratrol is also believed to be important in cardiovascular diseases and neurological disorders, such as Alzheimer's disease. Using an inverse molecular docking approach, we sought to find new potential targets of resveratrol. Docking of resveratrol into each ProBiS predicted binding site of >38 000 protein structures from the Protein Data Bank was examined, and a number of novel potential targets into which resveratrol was docked successfully were found. These explain known actions or predict new effects of resveratrol. The results included three human proteins that are already known to bind resveratrol. A majority of proteins discovered however have no already described connections with resveratrol. We report new potential target human proteins and proteins connected with different organisms into which resveratrol can dock. Our results reveal previously unknown potential target human proteins, whose connection with cardiovascular and neurological disorders could lead to new potential treatments for variety of diseases. We believe that our research could help in future experimental studies on revestratol bioactivity in humans.

Hop Compounds: Extraction Techniques, Chemical Analyses, Antioxidative, Antimicrobial, and Anticarcinogenic Effects

Hop plants comprise a variety of natural compounds greatly differing in their structure and properties. A wide range of methods have been developed for their isolation and chemical analysis, as well as for determining their antioxidative, antimicrobial, and antigenotoxic potentials. This contribution provides an overview of extraction and fractionation techniques of the most important hop compounds known for their health-promoting features. Although hops remain the principal ingredient for providing the taste, stability, and antimicrobial protection of beer, they have found applications in the pharmaceutical and other food industries as well. This review focuses on numerous health-promoting effects of hops raging from antioxidative, sedative, and anti-inflammatory potentials, over anticarcinogenic features to estrogenic activity. Therefore, hops should be exploited for the prevention and even healing of several prevalent diseases like cardiovascular disorders and various cancer types. New ideas for future studies on hops are finally presented: computational investigations of chemical reactivities of hop compounds, nanoencapsulation, and synergistic effects leading to a higher bioavailability of biologically active substances as well as the application of waste hop biomass from breweries for the production of high-added-value products in accordance with the biorefinery concept.