Four-dimensional imaging for cryo-electron microscopy experiments using molecular simulations and manifold learning

Elucidating protein conformational changes is essential because conformational changes are closely related to the functions of proteins. Cryo-electron microscopy (cryo-EM) experiment can be used to reconstruct protein conformational changes via a method that involves using the experimental data (two-dimensional protein images). In this study, a reconstruction method, referred to as the "four-dimensional imaging," was proposed. In our four-dimensional imaging technique, the protein conformational change was obtained using the two-dimensional protein images (the three-dimensional electron density maps used in previously proposed techniques were not used). The protein conformation for each two-dimensional protein image was obtained using our original protocol with molecular dynamics simulations. Using a manifold-learning technique and two-dimensional protein images, the protein conformations were arranged according to the conformational change of the protein. By arranging the protein conformations according to the arrangement of the protein images, four-dimensional imaging is constructed. A simulation for a cryo-EM experiment demonstrated the validity of our four-dimensional imaging technique.

Rapid and Accurate Screening of the COF Space for Natural Gas Purification: COFInformatics

In this work, we introduced COFInformatics, a computational approach merging molecular simulations and machine learning (ML) algorithms, to evaluate all synthesized and hypothetical covalent organic frameworks (COFs) for the CO2/CH4 mixture separation under four different adsorption-based processes: pressure swing adsorption (PSA), vacuum swing adsorption (VSA), temperature swing adsorption (TSA), and pressure-temperature swing adsorption (PTSA). We first extracted structural, chemical, energy-based, and graph-based molecular fingerprint features of every single COF structure in the very large COF space, consisting of nearly 70,000 materials, and then performed grand canonical Monte Carlo simulations to calculate the CO2/CH4 mixture adsorption properties of 7540 COFs. These features and simulation results were used to develop ML models that accurately and rapidly predict CO2/CH4 mixture adsorption and separation properties of all 68,614 COFs. The most efficient separation process and the best adsorbent candidates among the entire COF spectrum were identified and analyzed in detail to reveal the most important molecular features that lead to high-performance adsorbents. Our results showed that (i) many hypoCOFs outperform synthesized COFs by achieving higher CO2/CH4 selectivities; (ii) the top COF adsorbents consist of narrow pores and linkers comprising aromatic, triazine, and halogen groups; and (iii) PTSA is the most efficient process to use COF adsorbents for natural gas purification. We believe that COFInformatics promises to expedite the evaluation of COF adsorbents for CO2/CH4 separation, thereby circumventing the extensive, time- and resource-intensive molecular simulations.

Molecular Modeling of Shockwave-Mediated Blood-Brain Barrier Opening for Targeted Drug Delivery

Bubble-enhanced shock waves induce the transient opening of the blood-brain barrier (BBB) providing unique advantages for targeted drug delivery of brain tumor therapy, but little is known about the molecular details of this process. Based on our BBB model including 28 000 lipids and 280 tight junction proteins and coarse-grained dynamics simulations, we provided the molecular-level delivery mechanism of three typical drugs for the first time, including the lipophilic paclitaxel, hydrophilic gemcitabine, and siRNA encapsulated in liposome, across the BBB. The results show that the BBB is more difficult to be perforated by shock-induced jets than the human brain plasma membrane (PM), requiring higher shock wave speeds. For the pores formed, the BBB exhibits a greater ability to self-heal than PM. Hydrophobic paclitaxel can cross the BBB and be successfully absorbed, but the amount is only one-third of that of PM; however, the absorption of hydrophilic gemcitabine was almost negligible. Liposome-loaded siRNAs only stayed in the first layer of the BBB. The mechanism analysis shows that increasing the bubble size can promote drug absorption while reducing the risk of higher shock wave overpressure. An exponential function was proposed to describe the relation between bubble and overpressure, which can be extended to the experimental microbubble scale. The calculated overpressure is consistent with the experimental result. These molecular-scale details on shock-assisted BBB opening for targeted drug delivery would guide and assist experimental attempts to promote the application of this strategy in the clinical treatment of brain tumors.

Rational Design of a Robust G-Quadruplex Aptamer as an Inhibitor to Alleviate Listeria monocytogenes Infection

Listeria monocytogenes (LM) is one of the most invasive foodborne pathogens that cause listeriosis, making it imperative to explore novel inhibiting strategies for alleviating its infection. The adhesion and invasion of LM within host cells are partly orchestrated by an invasin protein internalin A (InlA), which facilitates bacterial passage by interacting with the host cell E-cadherin (E-Cad). Hence, in this work, we proposed an aptamer blocking strategy by binding to the region on InlA that directly mediated E-Cad receptor engagement, thereby alleviating LM infection. An aptamer GA8 with a robust G-quadruplex (G4) structural feature was designed through truncation and base mutation from the original aptamer A8. The molecular docking and dynamics analysis showed that the InlA/aptamer GA8 binding interface was highly overlapping with the natural InlA/E-Cad binding interface, which confirmed that GA8 can tightly and stably bind InlA and block more distinct epitopes on InlA that involved the interaction with E-Cad. On the cellular level, it was confirmed that GA8 effectively blocked LM adhesion with an inhibition rate of 78%. Overall, the robust G4 aptamer-mediated design provides a new direction for the development of inhibitors against other wide-ranging and emerging pathogens.

Trypsin is inhibited by phytocompounds liquiritin and terpinen-4-ol from the herb Glycyrrhiza glabra: in vitro and in silico studies

Serine proteases are a class of hydrolytic enzymes involved in various physiological functions like digestion, coagulation, fibrinolysis and immunity. The present study evaluates the serine protease inhibitory potential of phytochemicals liquiritin and terpinen-4-ol present in the herb Glycyrrhiza glabra L. using trypsin as the model enzyme. In silico studies showed that both the compounds have a significant binding affinity towards trypsin with a binding energy of -26.66 kcal/mol and -19.79 kcal/mol for liquiritin and terpinen-4-ol, respectively. Their binding affinity was confirmed through in vitro enzyme inhibition assays. The mode of inhibition was found to be uncompetitive. In order to explain the mode of inhibition, docking of the ligands to the enzyme-substrate complex was also done and binding energy was calculated after MD simulation. The energy values showed that the binding affinities of these compounds towards the enzyme substrate complex are more than that towards the enzyme alone. This explains the uncompetitive mode of inhibition.Communicated by Ramaswamy H. Sarma.

Design, synthesis and characterization of ethyl 3-benzoyl-7-morpholinoindolizine-1-carboxylate as anti-tubercular agents: In silico screening for possible target identification

A thorough search for the development of innovative drugs to treat tuberculosis, especially considering the urgent need to address developing drug resistance, we report here a synthetic series of ethyl 3-benzoyl-7-morpholinoindolizine-1-carboxylate analogues (5a-o) as potent anti-tubercular agents. These morpholino-indolizines were synthesized by reacting 4-morpholino pyridinium salts, with various electron-deficient acetylenes to afford the ethyl 3-benzoyl-7-morpholinoindolizine-1-carboxylate analogues (5a-o). All synthesized intermediate and final compounds are characterized by spectroscopic methods such as 1H NMR, 13C NMR and HRMS and further examined for their anti-tubercular activity against the M. tuberculosis H37Rv strain (ATCC 27294-American type cell culture). All the compounds screened for anti-tubercular activity in the range of 6.25-50 μM against the H37Rv strain of Mycobacterium tuberculosis. Compound 5g showed prominent activity with MIC99 2.55 μg/mL whereas compounds 5d and 5j showed activity with MIC99 18.91 μg/mL and 25.07 μg/mL, respectively. In silico analysis of these compounds revealed drug-likeness. Additionally, the molecular target identification for Malate synthase (PDB 5CBB) is attained by computational approach. The compound 5g with a MIC99 value of 2.55 μg/mL against M. tuberculosis H37Rv emerged as the most promising anti-TB drug and in silico investigations suggest Malate synthase (5CBB) might be the compound's possible target.

Molecular Simulation Study on the Hydrogen Permeation Behavior and Mechanism of Common Polymers

This research aimed to provide an understanding of the selection and safe application of pipeline liner materials for hydrogen transport by examining the permeation properties and mechanisms of hydrogen within polymers commonly used for this purpose, such as high-density polyethylene (HDPE) and ethylene-vinyl alcohol copolymer (EVOH), through molecular simulation. The study was carried out within defined operational parameters of temperature (ranging from room temperature to 80 °C) and pressure (from 2.5 to 10 MPa) that are pertinent to hydrogen pipeline infrastructures. The results reveal that with an increase in temperature from 30 °C to 80 °C, the solubility, diffusion, and permeability coefficients of hydrogen in HDPE increase by 18.7%, 92.9%, and 129.0%, respectively. Similarly, in EVOH, these coefficients experience increments of 15.9%, 81.6%, and 112.7%. Conversely, pressure variations have a negligible effect on permeability in both polymers. HDPE exhibits significantly higher hydrogen permeability compared to EVOH. The unique chain segment configuration of EVOH leads to the formation of robust hydrogen bonds among the hydroxyl groups, thereby impeding the permeation of hydrogen. The process by which hydrogen is adsorbed in polymers involves aggregation at low potential energy levels. During diffusion, the hydrogen molecule primarily vibrates within a limited range, with intermittent occurrences of significant hole-to-hole transitions over larger distances. Hydrogen exhibits a stronger interaction with HDPE compared to EVOH, leading to a higher number of adsorption sites and increased hydrogen adsorption capacity in HDPE. Hydrogen molecules move more actively in HDPE than in EVOH, exhibiting greater hole amplitude and more holes in transition during the diffusion process.

Potential Mechanisms of Casein Hexapeptide YPVEPF on Stress-Induced Anxiety and Insomnia Mice and Its Molecular Effects and Key Active Structure

The hexapeptide YPVEPF with strong sleep-enhancing effects could be detected in rat brain after a single oral administration as we previously proved. In this study, the mechanism and molecular effects of YPVEPF in the targeted stress-induced anxiety mice were first investigated, and its key active structure was further explored. The results showed that YPVEPF could significantly prolong sleep duration and improve the anxiety indexes, including prolonging the time spent in the open arms and in the center. Meanwhile, YPVEPF showed strong sleep-enhancing effects by significantly increasing the level of the GABA/Glu ratio, 5-HT, and dopamine in brain and serum and regulating the anabolism of multiple targets, but the effects could be blocked by bicuculline and WAY100135. Moreover, the molecular simulation results showed that YPVEPF could stably bind to the vital GABAA and 5-HT1A receptors due to the vital structure of Tyr-Pro-Xaa-Xaa-Pro-, and the electrostatic and van der Waals energy played dominant roles in stabilizing the conformation. Therefore, YPVEPF displayed sleep-enhancing and anxiolytic effects by regulating the GABA-Glu metabolic pathway and serotoninergic system depending on distinctive self-folding structures with Tyr and two Pro repeats.

Experimental and Simulation Studies of Imidazolium Chloride Ionic Liquids with Different Alkyl Chain Lengths for Viscosity Reductions in Heavy Crude Oil: The Effect on Asphaltene Dispersion

Heavy crude oil poses challenges in terms of extraction and transportation due to its high viscosity. In the pursuit of effective methods to reduce viscosity in heavy crude oil, this study investigates the potential of imidazolium chloride ionic liquids with varying alkyl chain lengths as viscosity reducers. The experimental results demonstrate that the addition of 1-dodecyl-3-methylimidazole chloride ([C12-MIM]Cl) leads to a maximum viscosity reduction of 49.87%. Solubility parameters were calculated based on characterization of the average molecular structure of the asphaltenes. The viscosity reduction effect is enhanced when the solubility parameter of the ionic liquid closely matches that of the asphaltene. The initial asphaltene deposition point of heavy crude oil is increased from 63% to 68% with the addition of 150 mg/L [C12-MIM]Cl. Furthermore, the average particle size of asphaltene deposits decreases from 79.35 μm to 48.54 μm. The viscosity of heavy crude oil is influenced by the aggregation of asphaltenes. The ability of ionic liquids, especially those with longer alkyl chains, to disperse asphaltene molecules and reduce viscosity has been confirmed through molecular dynamics and quantum mechanical simulations.

Repurposing FDA-approved drugs to target malaria through inhibition of dihydrofolate reductase in the folate biosynthesis pathway: A prospective approach

Dihydrofolate reductase (DHFR) is a ubiquitous enzyme that regulates the biosynthesis of tetrahydrofolate among various species of Plasmodium parasite. It is a validated target of the antifolate drug pyrimethamine (Pyr) in Plasmodium falciparum (Pf), but its clinical efficacy has been hampered due to the emergence of drug resistance. This has made the attempt to screen Food & Drug Administration-approved drugs against wild- and mutant PfDHFR by employing an in-silico pipeline to identify potent candidates. The current study has followed a virtual screening approach for identifying potential DHFR inhibitors from DrugBank database, based on a structure similarity search of candidates, followed by absorption, distribution, metabolism, and excretion estimation. The screened drugs were subjected to various parameters like docking, molecular mechanics with generalized born and surface area solvation calculations, and molecular simulations. We have thus identified two potential drug candidates, duloxetine and guanethidine, which can be repurposed to be tested for their efficacy against wild type and drug resistant falciparum malaria.

Computational Design of Peptides for Biomaterials Applications

Computer-aided molecular design and protein engineering emerge as promising and active subjects in bioengineering and biotechnological applications. On one hand, due to the advancing computing power in the past decade, modeling toolkits and force fields have been put to use for accurate multiscale modeling of biomolecules including lipid, protein, carbohydrate, and nucleic acids. On the other hand, machine learning emerges as a revolutionary data analysis tool that promises to leverage physicochemical properties and structural information obtained from modeling in order to build quantitative protein structure-function relationships. We review recent computational works that utilize state-of-the-art computational methods to engineer peptides and proteins for various emerging biomedical, antimicrobial, and antifreeze applications. We also discuss challenges and possible future directions toward developing a roadmap for efficient biomolecular design and engineering.

Network pharmacology, molecular simulation, and binding free energy calculation-based investigation of Neosetophomone B revealed key targets for the treatment of cancer

In the current study, Neosetophomone B (NSP-B) was investigated for its anti-cancerous potential using network pharmacology, quantum polarized ligand docking, molecular simulation, and binding free energy calculation. Using SwissTarget prediction, and Superpred, the molecular targets for NSP-B were predicted while cancer-associated genes were obtained from DisGeNet. Among the total predicted proteins, only 25 were reported to overlap with the disease-associated genes. A protein-protein interaction network was constructed by using Cytoscape and STRING databases. MCODE was used to detect the densely connected subnetworks which revealed three sub-clusters. Cytohubba predicted four targets, i.e., fibroblast growth factor , FGF20, FGF22, and FGF23 as hub genes. Molecular docking of NSP-B based on a quantum-polarized docking approach with FGF6, FGF20, FGF22, and FGF23 revealed stronger interactions with the key hotspot residues. Moreover, molecular simulation revealed a stable dynamic behavior, good structural packing, and residues' flexibility of each complex. Hydrogen bonding in each complex was also observed to be above the minimum. In addition, the binding free energy was calculated using the MM/GBSA (Molecular Mechanics/Generalized Born Surface Area) and MM/PBSA (Molecular Mechanics/Poisson-Boltzmann Surface Area) approaches. The total binding free energy calculated using the MM/GBSA approach revealed values of -36.85 kcal/mol for the FGF6-NSP-B complex, -43.87 kcal/mol for the FGF20-NSP-B complex, and -37.42 kcal/mol for the FGF22-NSP-B complex, and -41.91 kcal/mol for the FGF23-NSP-B complex. The total binding free energy calculated using the MM/PBSA approach showed values of -30.05 kcal/mol for the FGF6-NSP-B complex, -39.62 kcal/mol for the FGF20-NSP-B complex, -34.89 kcal/mol for the FGF22-NSP-B complex, and -37.18 kcal/mol for the FGF23-NSP-B complex. These findings underscore the promising potential of NSP-B against FGF6, FGF20, FGF22, and FGF23, which are reported to be essential for cancer signaling. These results significantly bolster the potential of NSP-B as a promising candidate for cancer therapy.

Accelerating In Silico Discovery of Metal-Organic Frameworks for Ethane/Ethylene and Propane/Propylene Separation: A Synergistic Approach Integrating Molecular Simulation, Machine Learning, and Active Learning

Cryogenic distillation, a currently employed method for C2H4/C2H6 and C3H6/C3H8 mixture separation, is energy-intensive, prompting the research toward alternative technologies, including adsorbent-based separation. In this work, we combine machine learning (ML) technique with high-throughput screening to screen ∼23,000 hypothetical metal-organic frameworks (MOFs) for paraffin (C2H6 and C3H8) selective adsorbent separation. First, structure-based prescreening was employed to remove MOFs with undesired geometric properties. Further, a random forest model built upon the multicomponent grand canonical Monte Carlo (m-GCMC) simulation data of training set MOFs was found to be the most successful in learning the relationship between MOF features and olefin/paraffin mixture separation. Using this technique, the separation performance of the remaining (test set) MOFs was predicted, and the top-performing MOFs were identified. We also employed active learning (AL) to evaluate its effectiveness in improving the prediction of olefin/paraffin selectivity. AL was discovered to be ∼29 times more efficient than the best-supervised ML model, as it was able to identify the top materials in limited training data and at a fraction of computational cost and time as compared to ML techniques. Among the top selected materials, framework chemistry was found to be the most important parameter. Nickel and copper (as a metal node) in a tfzd and hms topological arrangement respectively, were discovered to be a prevalent attribute in high-performing MOFs, further demonstrating the prominent significance of framework chemistry. Additionally, the top MOFs discovered were studied in detail and further compared to the previously reported MOFs. These MOFs show the highest selectivity for C2H4/C2H6 and C3H6/C3H8 mixture separation, as reported until date. The hierarchical strategy devised in this study will facilitate the quick screening of MOFs across multiple databases toward industrially significant separation processes by leveraging molecular simulations and AL.

Cloning and Characterization of Chitin Deacetylase from Euphausia superba

Chitin deacetylase (CDA) can catalyze the deacetylation of chitin to produce chitosan. In this study, we identified and characterized a chitin deacetylase gene from Euphausia superba (EsCDA-9k), and a soluble recombinant protein chitin deacetylase from Euphausia superba of molecular weight 45 kDa was cloned, expressed, and purified. The full-length cDNA sequence of EsCDA-9k was 1068 bp long and encoded 355 amino acid residues that contained the typical domain structure of carbohydrate esterase family 4. The predicted three-dimensional structure of EsCDA-9k showed a 67.32% homology with Penaeus monodon. Recombinant chitin deacetylase had the highest activity at 40 °C and pH 8.0 in Tris-HCl buffer. The enzyme activity was enhanced by metal ions Co2+, Fe3+, Ca2+, and Na+, while it was inhibited by Zn2+, Ba2+, Mg2+, and EDTA. Molecular simulation of EsCDA-9k was conducted based on sequence alignment and homology modeling. The EsCDA-9k F18G mutant showed a 1.6-fold higher activity than the wild-type enzyme. In summary, this is the first report of the cloning and heterologous expression of the chitin deacetylase gene in Euphausia superba. The characterization and function study of EsCDA-9k will serve as an important reference point for future application.

Effect of the Side-Chain Length in Polycarboxylic Superplasticizer on the Competition Adsorption in the Presence of Montmorillonite: A Density Functional Theory Study

Polycarboxylic superplasticizers (PCEs) exhibit numerous advantages as concrete additives, effectively improving the stability and strength of concrete. However, competitive adsorption of PCEs occurs in the presence of clay, which may affect the cement dispersion and water-reducing performance. Extensive research has been conducted on the physical and mechanical properties of PCEs; however, the effect of the diverse structures of PCEs on the competitive adsorption on clay and cement hydration products has been rarely studied. This study employs Ca-montmorillonite (CaMMT) as a clay representative, by constructing adsorption models of PCEs on CaMMT and cement hydration products. A comparison of the adsorption energies considering different side-chain lengths of PCEs is included. Typically, the adsorption energy on CaMMT is lower than that on hydration products, leading PCEs to preferentially adsorb on the clay, thereby reducing its effective dosage in the cement particles. The challenge of PCE adsorption on CaMMT increases with the polymerization degree, and methylallyl polyoxyethylene ether (HPEG) exhibits lower adsorption energies on CaMMT. The density of states (DOS) analysis indicated the highest peak values of allyl polyethylene ether (APEG) as well as the peak area at n (polymerization degree) = 1. The total number of transferred electrons for APEG was 0.648, surpassing those of other PCEs. The interaction mechanism of PCEs with clay and hydration products is further elucidated through electronic gain/loss analysis, also providing a basis for the theoretical analysis on how to reduce the adsorption of PCEs on clay and the structural design of mud-resistant PCEs.

Aquatic Functional Liquid Crystals: Design, Functionalization, and Molecular Simulation

Aquatic functional liquid crystals, which are ordered molecular assemblies that work in water environment, are described in this review. Aquatic functional liquid crystals are liquid-crystalline (LC) materials interacting water molecules or aquatic environment. They include aquatic lyotropic liquid crystals and LC based materials that have aquatic interfaces, for example, nanoporous water treatment membranes that are solids preserving LC order. They can remove ions and viruses with nano- and subnano-porous structures. Columnar, smectic, bicontinuous LC structures are used for fabrication of these 1D, 2D, 3D materials. Design and functionalization of aquatic LC sensors based on aqueous/LC interfaces are also described. The ordering transitions of liquid crystals induced by molecular recognition at the aqueous interfaces provide distinct optical responses. Molecular orientation and dynamic behavior of these aquatic functional LC materials are studied by molecular dynamics simulations. The molecular interactions of LC materials and water are key of these investigations. New insights into aquatic functional LC materials contribute to the fields of environment, healthcare, and biotechnology.

Cross-reaction mediated by distinct key amino acid combinations in the complementary-determining region (CDR) of a monoclonal antibody

In immunology, cross-reaction between antigens and antibodies are commonly observed. Prior research has shown that various monoclonal antibodies (mAbs) can recognize a broad spectrum of epitopes related to influenza viruses. However, existing theories on cross-reactions fall short in explaining the phenomena observed. This study explored the interaction characteristics of H1-74 mAb with three peptides: two natural peptides, LVLWGIHHP and LPFQNI, derived from the hemagglutinin (HA) antigen of the H1N1 influenza virus, and one synthetic peptide, WPFQNY. Our findings indicate that the complementarity-determining region (CDR) of H1-74 mAb comprised five antigen-binding sites, containing eight key amino acid residues from the light chain variable region and 16 from the heavy chain variable region. These critical residues formed distinct hydrophobic or hydrophilic clusters and functional groups within the binding sites, facilitating interaction with antigen epitopes through hydrogen bonding, salt bridge formation, and π-π stacking. The study revealed that the formation of the antibody molecule led to the creation of binding groups and small units in the CDR, allowing the antibody to attach to a variety of antigen epitopes through diverse combinations of these small units and functional groups. This unique ability of the antibody to bind with antigen epitopes provides a new molecular basis for explaining the phenomenon of antibody cross-reaction.

Sulfadiazine Exerts Potential Anticancer Effect in HepG2 and MCF7 Cells by Inhibiting TNFα, IL1b, COX-1, COX-2, 5-LOX Gene Expression: Evidence from In Vitro and Computational Studies

Drug repurposing is a promising approach that has the potential to revolutionize the drug discovery and development process. By leveraging existing drugs, we can bring new treatments to patients more quickly and affordably. Anti-inflammatory drugs have been shown to target multiple pathways involved in cancer development and progression. This suggests that they may be more effective in treating cancer than drugs that target a single pathway. Cell viability was measured using the MTT assay. The expression of genes related to inflammation (TNFa, IL1b, COX-1, COX-2, and 5-LOX) was measured in HepG2, MCF7, and THLE-2 cells using qPCR. The levels of TNFα, IL1b, COX-1, COX-2, and 5-LOX were also measured in these cells using an ELISA kit. An enzyme binding assay revealed that sulfadiazine expressed weaker inhibitory activity against COX-2 (IC50 = 5.27 μM) in comparison with the COX-2 selective reference inhibitor celecoxib (COX-2 IC50 = 1.94 μM). However, a more balanced inhibitory effect was revealed for sulfadiazine against the COX/LOX pathway with greater affinity towards 5-LOX (IC50 = 19.1 μM) versus COX-1 (IC50 = 18.4 μM) as compared to celecoxib (5-LOX IC50 = 16.7 μM, and COX-1 IC50 = 5.9 μM). MTT assays revealed the IC50 values of 245.69 ± 4.1 µM and 215.68 ± 3.8 µM on HepG2 and MCF7 cell lines, respectively, compared to the standard drug cisplatin (66.92 ± 1.8 µM and 46.83 ± 1.3 µM, respectively). The anti-inflammatory effect of sulfadiazine was also depicted through its effect on the levels of inflammatory markers and inflammation-related genes (TNFα, IL1b, COX-1, COX-2, 5-LOX). Molecular simulation studies revealed key binding interactions that explain the difference in the activity profiles of sulfadiazine compared to celecoxib. The results suggest that sulfadiazine exhibited balanced inhibitory activity against the 5-LOX/COX-1 enzymes compared to the selective COX-2 inhibitor, celecoxib. These findings highlight the potential of sulfadiazine as a potential anticancer agent through balanced inhibitory activity against the COX/LOX pathway and reduction in the expression of inflammatory genes.

Screening of novel bovine-elastin-derived peptides with elastase inhibition and photoprotective potential: a combined in silico and in vitro study

BACKGROUND

The demand for food-based anti-photoaging products is surging because of the rising recognition of health and beauty, as well as enhanced comprehension of the detrimental impact of ultraviolet (UV) radiation. This study aimed to investigate the potential of bioactive peptides derived from bovine elastin, specifically focusing on identifying novel elastase inhibitory peptides and assessing their photoprotective properties using bioinformatics techniques.

RESULTS

A total of 48 bioactive peptides were screened in bovine elastin hydrolysate (EH) utilizing Peptide Ranker analysis. Three novel elastase inhibitory peptides, GAGQPFPI, FFPGAG and FPGIG (in descending order of activity), exhibited potent inhibitory effects on elastase in vitro, surpassing the inhibitory effect of EH by a factor of 1-2 and reaching significantly lower concentrations (8-15 times lower) than EH. The cumulative inhibitory effect of GAGQPFPI, FFPGAG, and FPGIG reached 91.5%. Further analysis revealed that FFPGAG and FPGIG exhibited mixed inhibition, whereas GAGQPFPI displayed non-competitive inhibition. Molecular simulations showed that these peptides interacted effectively with the elastase active site through hydrogen bonding and hydrophobic interactions. Furthermore, GAGQPFPI, FFPGAG, and FPGIG demonstrated high stability in gastrointestinal digestion, demonstrated transcellular permeability across Caco-2 cell monolayers, and exhibited remarkable photoprotective properties against UVB-irradiated HaCaT cells.

CONCLUSION

GAGQPFPI showed the most promising potential as a functional food with photoprotective effects against UVB damage and inhibitory properties against elastase. © 2023 Society of Chemical Industry.

Encapsulation of Benzaldehyde Produced by the Eco-Friendly Degradation of Amygdalin in the Apricot Kernel Debitterizing Wastewater

In order to fully utilize the by-products of apricot kernel-debitterizing and address the chemical instability of benzaldehyde in the food industry, benzaldehyde was first prepared by adding the apricot kernel powder to degrade the amygdalin present in the apricot kernel-debitterizing water. Subsequently, β-cyclodextrin was employed to encapsulate the benzaldehyde, and its encapsulation efficacy was evaluated through various techniques including Fourier transform infrared spectroscopy, thermogravimetric analysis, release kinetics fitting inhibitory effect and the effect on Botrytis cinerea. Finally, the encapsulation was explored via molecular docking and molecular dynamics simulations. The results indicate that the optimal preparation conditions for the benzaldehyde were 1.8 h, 53 °C and pH 5.8, and the encapsulation of benzaldehyde with β-cyclodextrin (wall-core ratio of 5:1, mL/g) has been verified by the deceleration in the release rate, the enhanced thermal stability and the prolonged inhibition effect against Botrytis cinerea. The encapsulation proceeded spontaneously without steric hindrance in the simulation, which led to a reduction in the hydrophobic cavity of β-cyclodextrin. In conclusion, the amygdalin in the debitterizing wastewater can be degraded in an eco-friendly way to produce benzaldehyde by adding apricot kernel powder, which contains β-glucosidase; the encapsulation of benzaldehyde is stable, thus enhancing the utilization of amygdalin in the debitterizing wastewater of apricot kernels.

Screening of Organic Small Molecule Excipients on Ternary Solid Dispersions Based on Miscibility and Hydrogen Bonding Analysis: Experiments and Molecular Simulation

The preparation of solid dispersions by mixing insoluble drugs with polymers is the main way to improve the aqueous solubility of drugs. The introduction of organic small molecule excipients into binary solid dispersions is expected to further enhance drug solubility by regulating intermolecular hydrogen bonding within the system at the microscopic level. In this study, we used carbamazepine (CBZ) as the target drug and polyvinylpyrrolidone as the solid dispersion matrix and screened the third component from 13 organic small molecules with good miscibility in the solid dispersion based on the principle of similarity of solubility parameters. The hydrogen bonding parameters and dissociation Gibbs free energy of the 13 organic small molecule-CBZ dimer were calculated by quantum mechanical simulation, and the tryptophan (Try) was identified as the optimal third component of organic small molecule. The migration of CBZ in binary and ternary systems was also analyzed by molecular dynamics simulation. On this theoretical basis, the corresponding solid dispersions were prepared, characterized, and tested for solubility analysis, which verified that the drug solubility was stronger for the system with the addition of polar fractions and the Try was indeed the best third component of organic small molecule compound, which was consistent with the simulation predictions. This screening method may provide theoretical guidance for drug modification design and clinical studies.

Application of Polymeric CO2 Thickener Polymer-Viscosity-Enhance in Extraction of Low-Permeability Tight Sandstone

The conventional production technique employed for low-permeability tight reservoirs exhibits limited productivity. To solve the problem, an acetate-type supercritical carbon dioxide (scCO2) thickener, PVE, which contains a large number of microporous structures, was prepared using the atom transfer radical polymerization (ATRP) method. The product exhibited an ability to decrease the minimum miscibility pressure of scCO2 during a solubility test and demonstrated a favorable extraction efficiency in a low-permeability tight core displacement test. At 15 MPa and 70 °C, PVE-scCO2 at a concentration of 0.2% exhibits effective oil recovery rates of 5.61% for the 0.25 mD core and 2.65% for the 5 mD core. The result demonstrates that the incorporation of the thickener PVE can effectively mitigate gas channeling, further improve oil displacement efficiency, and inflict minimal damage to crude oil. The mechanism of thickening was analyzed through molecular simulation. The calculated trend of thickening exhibited excellent agreement with the experimental measurement rule. The simulation results demonstrate that the contact area between the polymer and CO2 increases in direct proportion to both the number of thickener molecules and the viscosity of the system. The study presents an effective strategy for mitigating gas channeling during scCO2 flooding and has a wide application prospect.

Molecular Dynamics Simulation and Experimental Study of Mechanical Properties of Graphene-Cement Composites

To investigate the mechanical properties of graphene (G) and calcium silicate hydrate (C-S-H) composites in different directions, molecular dynamics (MD) simulations and experiments were used, and the effects of temperature, loading rate, and graphene defects were also investigated. The experimental results show that the addition of graphene can improve the flexural, compressive, and tensile strength of the composite. The results of molecular dynamics simulation show that the addition of graphene in x and z directions can enhance the tensile strength of G/C-S-H in three directions, while the addition of graphene in y direction can reduce the tensile strength of G/C-S-H. At the same time, the tensile strength of G/C-S-H decreases with the increase in temperature and increases with the increase in loading rate. Meanwhile, the mechanical properties of G/C-S-H can be improved using a certain concentration of monatomic vacancy defects, diatomic vacancy defects, and S-W defects.

Chrysin Directing an Enhanced Solubility through the Formation of a Supramolecular Cyclodextrin-Calixarene Drug Delivery System: A Potential Strategy in Antifibrotic Diabetes Therapeutics

Calixarene 0118 (OTX008) and chrysin (CHR) are promising molecules for the treatment of fibrosis and diabetes complications but require an effective delivery system to overcome their low solubility and bioavailability. Sulfobutylated β-cyclodextrin (SBECD) was evaluated for its ability to increase the solubility of CHR by forming a ternary complex with OTX008. The resulting increase in solubility and the mechanisms of complex formation were identified through phase-solubility studies, while dynamic light-scattering assessed the molecular associations within the CHR-OTX008-SBECD system. Nuclear magnetic resonance, differential scanning calorimetry, and computational studies elucidated the interactions at the molecular level, and cellular assays confirmed the system's biocompatibility. Combining SBECD with OTX008 enhances CHR solubility more than using SBECD alone by forming water-soluble molecular associates in a ternary complex. This aids in the solubilization and delivery of CHR and OTX008. Structural investigations revealed non-covalent interactions essential to complex formation, which showed no cytotoxicity in hyperglycemic in vitro conditions. A new ternary complex has been formulated to deliver promising antifibrotic agents for diabetic complications, featuring OTX008 as a key structural and pharmacological component.

Screening and unveiling antibacterial mechanism of dandelion phenolic extracts against Staphylococcus aureus by inhibiting intracellular Na+-K+ ATPase based on molecular docking and molecular dynamics simulation

Staphylococcus aureus is one of the most frequently food-contaminated incidence of healthcare-associated Gram-positive bacteria. The antibacterial function and mechanism of phenolic compounds from dandelion are still unclear. Herein, this work aims to screen one of dandelion phenolic extracts with the strongest antibacterial function from its organ such as flower, stem, leaf and root, and to reveal its antibacterial mechanism. The results indicated dandelion flower phenolic extract (DFPE) containing the highest content of caffeic acid, followed by luteolin and luteolin-7-O-glucoside. They, especially caffeic acid and luteolin-7-O-glucoside, played a key role in making the bacterial cellular-membrane ruptured against the bacteria. The leakage of the intracellular substances (adenosine triphosphate and Na+-K+ ATPase) was further confirmed. Conventional hydrogen bond, pi-anion, pi-alkyl were involved in the interaction between caffeic acid or luteolin-7-O-glucoside and Na+-K+ ATPase. Additionally, the dynamic equilibrium of the liganded ATPase complex were achieved after 105 ns, and the lower values from the radius of gyration and solvent accessible surface area in the complex demonstrated the highly tight and compact structure of the liganded protein. The highest free binding energy (ΔGbind = -47.80 kJ/mol) between Na+-K+ ATPase and luteolin-7-O-glycloside was observed. Overall, DFPE can be used as an effective anti-bacterial agent due to the contribution of its bioactive ingredients such as caffeic acid and luteolin-7-O-glucoside for membrane-breaking.Communicated by Ramaswamy H. Sarma.

Structural and molecular investigation of the impact of S30L and D88N substitutions in G9R protein on coupling with E4R from Monkeypox virus (MPXV)

Understanding the pathogenesis mechanism of the Monkeypox virus (MPXV) is essential to guide therapeutic development against the Monkeypox virus. In the current study, we investigated the impact of the only two reported substitutions, S30L, D88N, and S30L-D88N on the G9R of the replication complex in 2022 with E4R using structural modeling, simulation, and free energy calculation methods. From the molecular docking and dissociation constant (KD) results, it was observed that the binding affinity did not increase in the mutants, but the interaction paradigm was altered by these substitutions. Molecular simulation data revealed that these mutations are responsible for destabilization, changes in protein packing, and internal residue fluctuations, which can cause functional variance. Additionally, hydrogen bonding analysis revealed that the estimated number of hydrogen bonds are almost equal among the wild-type G9R and each mutant. The total binding free energy for the wild-type G9R with E4R was -85.00 kcal/mol while for the mutants the TBE was -42.75 kcal/mol, -43.68 kcal/mol, and -48.65 kcal/mol respectively. This shows that there is no direct impact of these two reported mutations on the binding with E4R, or it may affect the whole replication complex or any other mechanism involved in pathogenesis. To explore these variations further, we conducted PCA and FEL analyses. Based on our findings, we speculate that within the context of interaction with E4R, the mutations in the G9R protein might be benign, potentially leading to functional diversity associated with other proteins.Communicated by Ramaswamy H. Sarma.

Efficient Assessment of 'Instantaneous pK' Values from Molecular Dynamics Simulations

We present a molecular simulation approach to studying the role of local and momentary molecular environment for potential acid-base reactions. For this, we combine thermodynamic considerations on the pK of ionic species with rapid sampling of energy changes related to (de)protonation. Using dispersed carbonate ions in water as a reference, our approach aims at the fast assessment of the momentary protonation energy, and thus the 'instantaneous pK', of calcium-carbonate ion aggregates. The latter include transient complexes that are elusive to long sampling runs. This motivated the elaboration of approximate, yet particularly fast assessable sampling strategies. Along this line, we were able to characterize instantaneous pK values at a statistical accuracy of 0.4 pK units within sampling runs of only 10 ps duration, whereas statistical errors reduce to 0.1 pK units in 75 ps sampling runs, respectively. This readily enabled the required time resolution for the characterization of [Cax (CO3 )y ]2(x-y) aggregates with x=1,2 and y=1,2,3, respectively. In turn, the analysis of the pH-dependent nature of calcite-water interfaces and dynamically ordered liquid-like oxyanion polymers (dollop) domains is outlined at 10 ps resolution.

MOF-GRU: A MOFid-Aided Deep Learning Model for Predicting the Gas Separation Performance of Metal-Organic Frameworks

The remarkable versatility of metal-organic frameworks (MOFs) stems from their rich chemical information, leading to numerous successful applications. However, identifying optimal MOFs for specific tasks necessitates a thorough assessment of their chemical attributes. Conventional machine learning approaches for MOF prediction have relied on intricate chemical and structural details, hampering rapid evaluations. Drawing inspiration from recent advancements exemplified by Snurr et al., wherein a text string was used to represent a MOF (MOFid), we introduce a MOFid-aided deep learning model, named the MOF-GRU model. This model, founded on natural language processing principles and utilizing the gated recurrent unit architecture, leverages the serialized text string representation of metal-organic frameworks (MOFs) to forecast gas separation performance. Through a focused study on CH4/N2 separation, we substantiate the efficacy of this approach. Comparative assessments against traditional machine learning techniques underscore our model's superior predictive accuracy and its capacity to handle extensive data sets adeptly. The MOF-GRU model remarkably uncovers latent structure-performance relationships with only MOF sequences, obviating the necessity for intricate three-dimensional (3D) structural information. Overall, this model's judicious design empowers efficient data utilization, thereby hastening the discovery of high-performance materials tailored for gas separation applications.

HIV-1 Transcription Inhibition Using Small RNA-Binding Molecules

The HIV-1 transactivator protein Tat interacts with the transactivation response element (TAR) at the three-nucleotide UCU bulge to facilitate the recruitment of transcription elongation factor-b (P-TEFb) and induce the transcription of the integrated proviral genome. Therefore, the Tat-TAR interaction, unique to the virus, is a promising target for developing antiviral therapeutics. Currently, there are no FDA-approved drugs against HIV-1 transcription, suggesting the need to develop novel inhibitors that specifically target HIV-1 transcription. We have identified potential candidates that effectively inhibit viral transcription in myeloid and T cells without apparent toxicity. Among these candidates, two molecules showed inhibition of viral protein expression. A molecular docking and simulation approach was used to determine the binding dynamics of these small molecules on TAR RNA in the presence of the P-TEFb complex, which was further validated by a biotinylated RNA pulldown assay. Furthermore, we examined the effect of these molecules on transcription factors, including the SWI/SNF complex (BAF or PBAF), which plays an important role in chromatin remodeling near the transcription start site and hence regulates virus transcription. The top candidates showed significant viral transcription inhibition in primary cells infected with HIV-1 (98.6). Collectively, our study identified potential transcription inhibitors that can potentially complement existing cART drugs to address the current therapeutic gap in current regimens. Additionally, shifting of the TAR RNA loop towards Cyclin T1 upon molecule binding during molecular simulation studies suggested that targeting the TAR loop and Tat-binding UCU bulge together should be an essential feature of TAR-binding molecules/inhibitors to achieve complete viral transcription inhibition.

Evaluation of Myocilin Variant Protein Structures Modeled by AlphaFold2

Deep neural network-based programs can be applied to protein structure modeling by inputting amino acid sequences. Here, we aimed to evaluate the AlphaFold2-modeled myocilin wild-type and variant protein structures and compare to the experimentally determined protein structures. Molecular dynamic and ligand binding properties of the experimentally determined and AlphaFold2-modeled protein structures were also analyzed. AlphaFold2-modeled myocilin variant protein structures showed high similarities in overall structure to the experimentally determined mutant protein structures, but the orientations and geometries of amino acid side chains were slightly different. The olfactomedin-like domain of the modeled missense variant protein structures showed fewer folding changes than the nonsense variant when compared to the predicted wild-type protein structure. Differences were also observed in molecular dynamics and ligand binding sites between the AlphaFold2-modeled and experimentally determined structures as well as between the wild-type and variant structures. In summary, the folding of the AlphaFold2-modeled MYOC variant protein structures could be similar to that determined by the experiments but with differences in amino acid side chain orientations and geometries. Careful comparisons with experimentally determined structures are needed before the applications of the in silico modeled variant protein structures.

Hierarchical Computational Screening of Quantum Metal-Organic Framework Database to Identify Metal-Organic Frameworks for Volatile Organic-Compound Capture from Air

The design and discovery of novel porous materials that can efficiently capture volatile organic compounds (VOCs) from air are critical to address one of the most important challenges of our world, air pollution. In this work, we studied a recently introduced metal-organic framework (MOF) database, namely, quantum MOF (QMOF) database, to unlock the potential of both experimentally synthesized and hypothetically generated structures for adsorption-based n-butane (C4H10) capture from air. Configurational Bias Monte Carlo (CBMC) simulations were used to study the adsorption of a quaternary gas mixture of N2, O2, Ar, and C4H10 in QMOFs for two different processes, pressure swing adsorption (PSA) and vacuum-swing adsorption (VSA). Several adsorbent performance evaluation metrics, such as C4H10 selectivity, working capacity, the adsorbent performance score, and percent regenerability, were used to identify the best adsorbent candidates, which were then further studied by molecular simulations for C4H10 capture from a more realistic seven-component air mixture consisting of N2, O2, Ar, C4H10, C3H8, C3H6, and C2H6. Results showed that the top five QMOFs have C4H10 selectivities between 6.3 × 103 and 9 × 103 (3.8 × 103 and 5 × 103) at 1 bar (10 bar). Detailed analysis of the structure-performance relations showed that low/mediocre porosity (0.4-0.6) and narrow pore sizes (6-9 Å) of QMOFs lead to high C4H10 selectivities. Radial distribution function analyses of the top materials revealed that C4H10 molecules tend to confine close to the organic parts of MOFs. Our results provided the first information in the literature about the VOC capture potential of a large variety and number of MOFs, which will be useful to direct the experimental efforts to the most promising adsorbent materials for C4H10 capture from air.

Discussion on the mechanism of Lingguizhugan Decoction in treating hypertension based on network pharmacology and molecular simulation technology

To explore the mechanism of Lingguizhugan Decoction in treating hypertension based on network pharmacology and molecular simulation. The active ingredients and potential targets were screened by the Systematic Pharmacological Analysis Platform of Traditional Chinese Medicine (TCMSP). Hypertension-related targets were obtained from OMIM and GeneCards databases. Common targets between drug and hypertension were screened in the Venny platform. A protein-protein interaction (PPI) network was constructed in the STRING database using intersection targets. Key targets in PPI network were analyzed by Cytoscape. R language program was used for Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Finally, the binding abilities of the main active ingredients to critical targets were verified by molecular simulation. Naringenin, quercetin, kaempferol, and β-sitosterol in Lingguizhugan Decoction, and potential targets such as STAT3, AKT1, TNF, IL6, JUN, PTGS2, MMP9, CASP3, TP53, and MAPK3, were screened out. KEGG Enrichment analysis revealed that the common targets of Lingguizhugan Decoction and hypertension are mainly involved in the lipid and atherosclerosis signaling pathway, AGE-RAGE signaling pathway in diabetic complications, fluid shear stress and atherosclerosis, and IL17 signaling pathway. The molecular simulation results showed that naringenin-MAPK3, quercetin-MMP9, quercetin-PTGS2, and quercetin-TP53 were the top four in the docking scores. Naringenin-MAPK3 and quercetin-MMP9 were stable, with binding free energies of -27.97 ± 1.41 kcal/mol and -21.15 ± 3.17 kcal/mol, respectively. The possible mechanism of Lingguizhugan Decoction in treating hypertension is characterized of multi-component, multi-target, and multi-pathway.Communicated by Ramaswamy H. Sarma.

Molecular Dynamics Simulation of the Cu3Sn/Cu Interfacial Diffusion Mechanism under Electrothermal Coupling

With the increasing power density of electronic devices, solder joints are prone to electromigration under high currents, which results in a significant threat to reliability. In this study, the molecular dynamics method is used to study the diffusion mechanism of the Cu3Sn/Cu interface under the action of electrothermal coupling. The results show that the diffusion activation energy decreases with an increase in electric field intensity, accelerating the diffusion of the Cu3Sn/Cu interface. Furthermore, it is noted that the abrupt change in the vacancy-time curve lags behind that of the mean square displacement curve, which depicts that the responses of the vacancies are driven by the electric field. The vacancy-responsive diffusion mechanism of the Cu3Sn/Cu interface is proposed. The atoms around the interface in the electric field get rid of the shackles of the neighboring atoms easily. The vacancy concentration increases as the atoms leave the equilibrium position, which accelerates the movement of vacancies and enhances the diffusion of the Cu3Sn/Cu interface.

Repurposing rabeprazole sodium as an anti-Clostridium perfringens drug by inhibiting perfringolysin O

AIMS

Clostridium perfringens infections affect food safety, human health, and the development of the poultry feed industry. Anti-virulence is an alternative strategy to develop new drug. Perfringolysin O (PFO) is an exotoxin of C. perfringens that has been demonstrated to play critical roles in the pathogenesis of this organism, promising it an attractive target to explore drugs to combat C. perfringens infection.

METHODS AND RESULTS

Based on an activity-based screening, we identified six PFO inhibitors from the Food and Drug Administration (FDA)-approved drug library, among which rabeprazole sodium (RS) showed an optimal inhibitory effect with an IC50 of 1.82 ± 0.746 µg ml-1. The GLY57, ASP58, SER190, SER193-194, ASN199, GLU204, ASN377, THR379, and ALA200 in PFO interacted with RS during binding based on an energy analysis and H-bond analysis. This interaction blocked the oligomer formation of PFO, thereby inhibiting its cytotoxicity. RS treatment significantly increased the survival rate and alleviated pathological damage in C. perfringens or PFO-treated Galleria mellonella.

CONCLUSIONS

RS could potentially be used as a candidate drug for treating C. perfringens infection.

Inhibition by components of Glycyrrhiza uralensis of 3CLpro and HCoV-OC43 proliferation

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). 3CLpro is a key enzyme in coronavirus proliferation and a treatment target for COVID-19. In vitro and in silico, compounds 1-3 from Glycyrrhiza uralensis had inhibitory activity and binding affinity for 3CLpro. These compounds decreased HCoV-OC43 cytotoxicity in RD cells. Moreover, they inhibited viral growth by reducing the amounts of the necessary proteins (M, N, and RDRP). Therefore, compounds 1-3 are inhibitors of 3CLpro and HCoV-OC43 proliferation.

Toxicity of chemical-based hand sanitizers on children and the development of natural alternatives: a computational approach

The unintended exposure of children to hand sanitizers poses a high risk of potentially fatal complications. Skin irritation, dryness, cracking, peeling, hypoglycemia, apnea, and acidosis are examples of unintended consequences of hand sanitizer. The sanitizer reportedly kills normal microbial flora on hands, which usually promotes innate immunity among children under 12. Children are more susceptible to the toxicity associated with the chemical constituents of marketed chemical-based hand sanitizers; however, the studies to develop sanitizer formulations for children are rudimentary. The adverse events limit the use of hand sanitizers specifically in children because of their sensitive and delicate skin. Additionally, it is reported that many chemical-based hand sanitizer formulations, especially alcohol-based ones may also contain contaminants like methanol, acetaldehyde, benzene, isopropanol, and ethyl-acetate. These contaminants are found to be hazardous to human health exhibiting toxicity on ingestion, inhalation, or dermal exposure, especially in children. Therefore, it is important to design novel, innovative, safer sanitizer formulations for children. The study aims to discuss the toxic contaminants in chemical-based sanitizer formulations and propose a design for novel herbal formulations with minimal toxicity and adverse effects, especially for children. The review focuses on ADMET analysis of the common contaminants in hand sanitizers, molecular docking, Lipinski's rule of five analysis, and molecular simulation studies to analyze the efficacy of interaction with the receptor leading to anti-microbial activity and drug-likeness of the compound. The in silico methods can effectively validate the potential efficacy of novel formulations of hand sanitizers designed for children as an efficient alternative to chemical-based sanitizers with greater efficacy and the absence of toxic contaminants.

Computer simulation of carbonization and graphitization of coal

This study describes computer simulations of carbonization and graphite formation, including the effects of hydrogen, nitrogen, oxygen, and sulfur. We introduce a novel technique to simulate carbonization, ``Simulation of Thermal Emission of Atoms and Molecules (STEAM)," designed to elucidate volatile outgassing and density variations in the intermediate material during carbonization. The investigation analyzes the functional groups that endure through high-temperature carbonization and examines the graphitization processes in carbon-rich materials containing non-carbon "impurity elements". The physical, vibrational, and electronic attributes of impure amorphous graphite are analyzed, and the impact of nitrogen on electronic conduction is investigated.

In silico analysis, isolation, and cytotoxicity evaluation of the coumestans from Cullen corylifolium (L.) Medik

Cullen corylifolium is well known for diverse phytoconstituents that possess multifaceted pharmacology, and one such less explored class is coumestans, which have not been well explored for their anticancer activities. One of the popular cancer targets is the Epidermal Growth Factor Receptor, a tyrosine kinase involved in various cancers, especially breast and lung cancer hence, a crucial cancer target. This work is focussed on molecular docking and molecular simulation studies on coumestans against EGFR. The rigorous docking studies resulted in two coumestans (1 and 5) with binding energy less than Gefitinib and Erlotinib. Compounds 1 and 5 were subjected to molecular simulation, binding free energy calculation, per-residue energy decomposition, and in silico ADMET prediction. The best hit, compound 1 was evaluated for its cytotoxicity against MDA-MB-231 and A549 cells via in vitro assay. The ligand-protein complex exhibited good stability, binding free energies, better in silico pharmacokinetics, low toxicity, and good cytotoxicity.

Modern Alchemical Free Energy Methods for Drug Discovery Explained

This Perspective provides a contextual explanation of the current state-of-the-art alchemical free energy methods and their role in drug discovery as well as highlights select emerging technologies. The narrative attempts to answer basic questions about what goes on "under the hood" in free energy simulations and provide general guidelines for how to run simulations and analyze the results. It is the hope that this work will provide a valuable introduction to students and scientists in the field.

Insights into Molecular Diversity within the FET Family: Unraveling Phase Separation of the N-Terminal Low Complexity Domain from RNA-Binding Protein EWS

The FET family proteins, which includes FUS, EWS, and TAF15, are RNA chaperones instrumental in processes such as mRNA maturation, transcriptional regulation, and the DNA damage response. These proteins have clinical significance: chromosomal rearrangements in FET proteins are implicated in Ewing family tumors and related sarcomas. Furthermore, point mutations in FUS and TAF15 are associated with neurodegenerative conditions like amyotrophic lateral sclerosis and frontotemporal lobar dementia. The fusion protein EWS::FLI1, the causative mutation of Ewing sarcoma, arises from a genomic translocation that fuses the low-complexity domain (LCD) of EWS (EWSLCD) with the DNA binding domain of the ETS transcription factor FLI1. This fusion not only alters transcriptional programs but also hinders native EWS functions like splicing. However, the precise function of the intrinsically disordered EWSLCD is still a topic of active investigation. Due to its flexible nature, EWSLCD can form transient interactions with itself and other biomolecules, leading to the formation of biomolecular condensates through phase separation - a mechanism thought to be central to the oncogenicity of EWS::FLI1. In our study, we used paramagnetic relaxation enhancement NMR, analytical ultracentrifugation, light microscopy, and all-atom molecular dynamics (MD) simulations to better understand the self-association and phase separation tendencies of EWSLCD. Our aim was to elucidate the molecular events that underpin EWSLCD-mediated biomolecular condensation. Our NMR data suggest tyrosine residues primarily drive the interactions vital for EWSLCD phase separation. Moreover, a higher density and proximity of tyrosine residues amplify the likelihood of condensate formation. Atomistic MD simulations and hydrodynamic experiments revealed that the tyrosine-rich N and C-termini tend to populate compact conformations, establishing unique contact networks, that are connected by a predominantly extended, tyrosine-depleted, linker region. MD simulations provide critical input on the relationship between contacts formed within a single molecule (intramolecular) and inside the condensed phase (intermolecular), and changes in protein conformations upon condensation. These results offer deeper insights into the condensate-forming abilities of the FET proteins and highlights unique structural and functional nuances between EWS and its counterparts, FUS and TAF15.

Molecular dynamics simulation of the interaction between palmitic acid and high pressure CO2

In this study, molecular dynamics simulation was used to explore the interaction characteristics of palmitic acid and CO2, and the effects of temperature and pressure on the solubility of palmitic acid in CO2 were investigated. In the range of 293-353 K and 5-30 MPa, the snapshot of palmitic acid distribution in CO2 shows that the molecular chain of palmitic acid in high-density CO2 system is more straight and more dispersed than that in low-density CO2 system. The radial distribution function further clearly shows that the solubility of palmitic acid in CO2 decreases with the increase of temperature and increases with the increase of pressure, which is consistent with the fatty acid solubility data reported in the literature and the setting rules of supercritical CO2 extraction process conditions. As the temperature decreases and the pressure increases, the interaction energy between palmitic acid and CO2 increases, which is conducive to overcoming the intermolecular force of palmitic acid and promoting dissolution. The solubility parameters of palmitic acid and CO2 can better reflect the trend of palmitic acid solubility changing with temperature and pressure, which can play a guiding role in the determination of process conditions and even the development of new processes.

Drug cross-linking electrospun fiber for effective infected wound healing

The management of infected wounds is still an intractable challenge in clinic. Development of antibacterial wound dressing is of great practical significance for wound management. Herein, a natural-derived antibacterial drug, tannic acid (TA), was incorporated into the electrospun polyvinyl alcohol (PVA) fiber (TA/PVA fiber, 952 ± 40 nm in diameter). TA worked as a cross-linker via hydrogen bonding with PVA to improve the physicochemical properties of the fiber and to reach a sustained drug release (88% release of drug at 48 h). Improved mechanical property (0.8-1.2 MPa) and computational simulation validated the formation of the hydrogen bonds between TA and PVA. Moreover, the antibacterial and anti-inflammatory characteristics of TA laid the foundation for the application of TA/PVA fiber in repairing infected wounds. Meanwhile, in vitro studies proved the high hemocompatibility and cytocompatibility of TA/PVA fiber. Further in vivo animal investigation showed that the TA/PVA fiber promoted the repair of infected wound by inhibiting the bacterial growth, promoting granulation formation, and collagen matrix deposition, accelerating angiogenesis, and inducing M2 macrophage polarization within 14 days. All the data demonstrated that the TA cross-linked fiber would be a potent dressing for bacteria-infected wound healing.

Screening for a Fenpropidin Enantiomer with High Activity and Low Toxicity

Fenpropidin has been extensively used for managing fungal diseases in different crops. There is a lack of literature on the enantioselective bioactivity and toxicity of fenpropidin. This study aims to explore the enantioselective bioactivity and toxicity of fenpropidin. R-Fenpropidin exhibited more potent bioactivity against seven plant pathogens than S-fenpropidin. R-Fenpropidin was more effective than S-fenpropidin in inhibiting sclerotial production, affecting mycelial growth and morphology, increasing cell membrane permeability, and decreasing the ergosterol content of Rhizoctonia solani. R-Fenpropidin exhibited a tighter binding affinity and formed hydrogen bonds with two target proteins. Fenpropidin also has enantioselective toxicity to Selenastrum capricornutum, with the toxicity of S-fenpropidin being seven times that of R-fenpropidin. S-Fenpropidin significantly reduced the content of the photosynthetic pigments. The results showed that R-fenpropidin was a highly active enantiomer with low toxicity. This study can provide a basis for the development of enantiomers with high activity and low toxicity.

Mechanisms of Shock Dissipation in Semicrystalline Polyethylene

Semicrystalline polymers are lightweight, multiphase materials that exhibit attractive shock dissipation characteristics and have potential applications as protective armor for people and equipment. For shocks of 10 GPa or less, we analyzed various mechanisms for the storage and dissipation of shock wave energy in a realistic, united atom (UA) model of semicrystalline polyethylene. Systems characterized by different levels of crystallinity were simulated using equilibrium molecular dynamics with a Hugoniostat to ensure that the resulting states conform to the Rankine-Hugoniot conditions. To determine the role of structural rearrangements, order parameters and configuration time series were collected during the course of the shock simulations. We conclude that the major mechanisms responsible for the storage and dissipation of shock energy in semicrystalline polyethylene are those associated with plastic deformation and melting of the crystalline domain. For this UA model, plastic deformation occurs primarily through fine crystallographic slip and the formation of kink bands, whose long period decreases with increasing shock pressure.

Graph Transformer with Convolution Parallel Networks for Predicting Single and Binary Component Adsorption Performance of Metal-Organic Frameworks

Metal-organic frameworks (MOFs) are considered one of the most important materials for carbon capture and storage (CCS) due to the advantages of porosity, multifunction, diverse structure, and controllable chemical composition. With the continuous development of artificial intelligence (AI) technology, more and more machine learning models are used to identify MOFs with high performance within a massive search space. However, current works have yet to form a model that uses graph-structured data only, which can predict the adsorption properties of single and binary components. In this work, we proposed and developed a graph transformer, combined with convolution parallel networks, called GC-Trans. The model can accurately and efficiently predict the adsorption performance of MOFs under the single- and binary-component adsorption conditions using only the features of the crystal diagram as inputs. By extracting and fusing local and global feature information, the model has stronger expression and generalization abilities. Thus, we used it to screen the ARC-MOF database and analyze the MOF structures that meet the target requirements. Additionally, to demonstrate the transferability of the model, we applied transfer learning methods to predict the CO2/CH4 separations and CH4 uptake, both of which showed good predictive performance.

Inhibitory Activity of Natural cis-Khellactone on Soluble Epoxide Hydrolase and Proinflammatory Cytokine Production in Lipopolysaccharides-Stimulated RAW264.7 Cells

The pursuit of anti-inflammatory agents has led to intensive research on the inhibition of soluble epoxide hydrolase (sEH) and cytokine production using medicinal plants. In this study, we evaluated the efficacy of cis-khellactone, a compound isolated for the first time from the roots of Peucedanum japonicum. The compound was found to be a competitive inhibitor of sEH, exhibiting an IC50 value of 3.1 ± 2.5 µM and ki value of 3.5 µM. Molecular docking and dynamics simulations illustrated the binding pose of (-)cis-khellactone within the active site of sEH. The results suggest that binding of the inhibitor to the enzyme is largely dependent on the Trp336-Gln384 loop within the active site. Further, cis-khellactone was found to inhibit pro-inflammatory cytokines, including NO, iNOS, IL-1β, and IL-4. These findings affirm that cis-khellactone could serve as a natural therapeutic candidate for the treatment of inflammation.

Itraconazole Loaded Biosurfactin Micelles with Enhanced Antifungal Activity: Fabrication, Evaluation and Molecular Simulation

Itraconazole (ITZ) is a broad-spectrum antifungal for superficial subcutaneous and systemic fungal infections. This study aimed to enhance the antifungal activity of ITZ using surfactin A (SA), a cyclic lipopeptide produced by the SA-producing Bacillus strain NH-100, possessing strong antifungal activity. SA was extracted, and ITZ-loaded SA micelles formulations were prepared via a single-pot rinsing method and characterized by particle size, zeta potential, and infrared spectroscopy. In vitro dissolution at pH 1.2, as well as hemolysis studies, was also carried out. The fabricated formulations were stable and non-spherical in shape, with an average size of about 179 nm, and FTIR spectra depicted no chemical interaction among formulation components. ITZ-loaded micelles showed decreased hemolysis activity in comparison to pure ITZ. The drug released followed the Korsmeyer-Peppas model, having R2 0.98 with the diffusion release mechanism. In an acidic buffer, drug release of all prepared formulations was in the range of 73-89% in 2 h. The molecular simulation showed the outstanding binding and stability profile of the ITZ-SA complex. The aromatic ring of the ITZ mediates a π-alkyl contact with a side chain in the SA. It can be concluded that ITZ-loaded micelles, owing to significant enhanced antifungal activity up to 6-fold due to the synergistic effect of SA, can be a promising drug delivery platform for delivery of poorly soluble ITZ.

Regulation Mechanism of Special Functional Groups Contained in Polymer Molecular Chains on the Tribological Properties of Modified Ti6Al4V

Polymer coatings can effectively improve the surface tribological properties of human implant materials, thereby increasing their service life. In this study, poly(vinylsulfonic acid, sodium salt) (PVS), poly(acrylic acid) (PAA) and poly(vinylphosphonic acid) (PVPA) were used to modify Ti6Al4V surfaces. Experimental analyses were combined with molecular simulation to explore the regulation mechanism of special functional groups contained in polymer molecular chains on the tribological properties of modified surfaces. In addition, the bearing capacities and velocity dependence of different polymer modified surfaces during friction were also explored. The PVS coating, due to physical adsorption, can have an anti-friction effect under NaCl solution lubrication, but is not durable under long-term or repeated usage. Both PAA and PVPA molecular chains can form chemical bonds with Ti6Al4V. Phosphate acid groups can firmly bind to the substrate, and the adsorption of salt ions and water molecules can form a hydrated layer on the PVPA coating surface, achieving ultra-low friction and wear. The adsorption of salt ions would aggravate the surface wear of the PAA-modified Ti6Al4V due to the unfirm binding of carboxyl groups to the substrate, resulting in a high friction coefficient. This study can provide effective guidance for the design of modified polymer coatings on metals.

Kokumi-Enhancing Mechanism of N-l-lactoyl-l-Met Elucidated by Sensory Experiments and Molecular Simulations

Recent research indicates that N-lactoyl amino acid derivatives have the potential as kokumi substances, with their kokumi profile closely linked to that of amino acids. This study aimed to explore the unexplored effects resulting from the introduction of lactate groups into l-Methional (l-Met), a prevalent flavor compound found in foods, such as tomatoes, known for its ability to activate the monosodium glutamate response. N-l-Lac-l-Met was enzymatically synthesized using food grade, and its taste profile and underlying mechanisms were investigated. The structure of N-l-Lac-l-Met was determined by high-performance liquid chromatography (HPLC)-mass spectrometry (MS)/MS. Sensory evaluation revealed the presence of astringency, kokumi, and bitterness of N-l-Lac-l-Met. In a stimulated broth, N-l-Lac-l-Met exhibited enhanced umami and kokumi taste perception compared to l-Met while demonstrating good stability within pH 5 to 9. A molecular simulation and quantum mechanics analysis indicated that the formation of an amide bond played a crucial role in the kokumi-enhancing effect of N-l-Lac-l-Met, specifically by increasing its affinity with umami receptors T1R1-T1R3 and a kokumi receptor CaSR. These findings established the relationship between amide bond formation and the kokumi-enhancing effect of N-l-Lac-l-Met, presenting its potential application as the kokumi substance in the food industry.

Molecular Simulation of Coal Molecular Diffusion Properties in Chicheng Coal Mine

In order to study the importance of the diffusion mechanism of CH4 and CO2 in coal for the development of coalbed methane, the aim of this paper is to reveal the influence mechanism of pressure, temperature, water content and other factors on the molecular diffusion behavior of gas at the molecular level. In this paper, non-sticky coal in Chicheng Coal Mine is taken as the research object. Based on the molecular dynamics method (MD) and Monte Carlo (GCMC) method, the diffusion characteristics and microscopic mechanism of CH4 and CO2 in coal under different pressures (100 kPa-10 MPa), temperatures (293.15-313.15 K) and water contents (1-5%) were analyzed in order to lay a theoretical foundation for revealing the diffusion characteristics of CBM in coal, and provide technical support for further improving CBM extraction. The results show that high temperature is conducive to gas diffusion, while high pressure and water are not conducive to gas diffusion in the coal macromolecular model.