4D-QSAR, ADMET properties, and molecular dynamics simulations for designing N-substituted urea/thioureas as human glutaminyl cyclase inhibitors.

Human glutaminyl cyclase (hQC) inhibitors have great potential to be used as anti- Alzheimer's disease (AD) agents by reducing the toxic pyroform of ß-amyloid in the brains of AD patients. The four-dimensional quantitative structure activity relationship (4D-QSAR) model of N-substituted urea/thioureas was established with satisfying predictive ability and statistical reliability (Q2 = 0.521, R2 = 0.933, R2prep = 0.619). By utilizing the developed 4D-QSAR model, a set of new N-substituted urea/thioureas was designed and evaluated for their Absorption Distribution Metabolism Excretion and Toxicity (ADMET) properties. The results of molecular dynamics (MD) simulations, Principal component analysis (PCA), free energy landscape (FEL), dynamic cross-correlation matrix (DCCM) and molecular mechanics generalized Born Poisson-Boltzmann surface area (MM-PBSA) free energy calculations, revealed that the designed compounds were remained stable in protein binding pocket and compounds b ∼ f (-35.1 to -44.55 kcal/mol) showed higher binding free energy than that of compound 14 (-33.51 kcal/mol). The findings of this work will be a theoretical foundation for further research and experimental validation of urea/thiourea derivatives as hQC inhibitors.

Design, synthesis, biological evaluation, and molecular modeling simulations of new phthalazine-1,4-dione derivatives as anti-Alzheimer's agents.

The development of targeted phthalazine-1,4-dione acetylcholinesterase (AChE) inhibitors for treating Alzheimer's disease involved the synthesis of 32 compounds via a multistage process. Various analytical techniques confirmed the compounds' identities. Thirteen compounds were found to inhibit AChE by more than 50% without affecting butyrylcholinesterase (BChE). Among these, three compounds, 8m, 8n, and 8p, exhibited extraordinary activity similar to donepezil, a reference AChE inhibitor. During enzyme kinetic studies, compound 8n, displaying the highest AChE inhibitory activity, underwent evaluation at three concentrations (2 × IC50, IC50, and IC50/2). Lineweaver-Burk plots indicated mixed inhibition activity for compound 8n against AChE, suggesting a combination of competitive and noncompetitive characteristics. Additionally, effective derivatives 8m, 8n, and 8p exhibited high blood-brain barrier (BBB) permeability in in vitro parallel artificial membrane permeability assay tests. Molecular docking studies revealed that these compounds bind to the enzyme's active site residues in a position similar to donepezil. Molecular dynamic simulations confirmed the stability of the protein-ligand system, and the chemical reactivity characteristics of the compounds were investigated using density functional theory. The compounds' wide energy gaps suggest stability and therapeutic potential. This research represents a significant step toward finding a potential cure for Alzheimer's disease. However, further research and testing are required to determine the compounds' safety and efficacy. The unique structure of phthalazine derivatives makes them suitable for various biological activities, and these compounds show promise for developing effective drugs for treating Alzheimer's disease. Overall, the development of these targeted compounds is a crucial advancement in the search for an effective treatment for Alzheimer's disease.

Pseudomonas aeruginosa Recombinant L-asparaginase: PEGylation with Low Molecular Weight Polyethylene Glycol, Molecular Dynamics Simulation, In vitro and In vivo Serum half-life and Biochemical Characterization.

BACKGROUND: Microbial L-asparaginase (L-ASNase, EC 3.5.1.1) is a pivotal biopharmaceutical drug-protein that catalyzes the hydrolysis of the non-essential amino acid L-asparagine (L-Asn) into L-aspartic acid (L-Asp) and ammonia , resulting in deplenishing the cellular L-Asn pool, which leads to the ultimate death of the L-asparagine synthetase (L-ASNS) deficient cancerous cells. OBJECTIVE: This study aimed to investigate the impact of conjugating low molecular weight polyethylene glycol to recombinant P. aeruginosa L-ASNase by examining the pharmacokinetic properties, affinity towards the substrate, and enzyme stability prior to and following the reaction. METHODS: The recombinant P. aeruginosa L-ASNase was affinity purified and then PEGylated by attaching polyethylene glycol (MW= 330 Da) site-specifically to the protein's N-terminus end. After which, the PEGylated L-ASNase was examined by SDS-PAGE (15%), FTIR, and UV/Vis spectrophotometry and subsequently biochemically characterized. RESULTS: The Km and Vmax values of free P. aeruginosa rL-ASNase were determined to be 0.318 ±1.76 mM and 2915 µmol min-1and following the PEGylation, they were found to be 0.396 ±1.736 mM and 3193 µmol min-1, respectively. Polyethylene glycol (330 Da) has markedly enhanced LASNase thermostability at 37, 45, 50, and 55 °C, as opposed to the free enzyme, which retained 19.5% after 1 h of incubation at 37 °C. The PEGylated L-ASNase was found to be stable upon incubation with human serum for 28 h, in contrast to the sharp decline in the residual bioactivity of the free rL-ASNase after 4 h incubation. Accordingly, an in vivo study was used for validation, and it demonstrated that PEGylated rL-ASNase exhibited longer bioactivity for 24 h, while the free form's activity vanished entirely from the rats' blood sera after 8 h. Molecular dynamics simulation indicated that PEG (330 Da) has affected the hydrodynamic volume of L-ASNase and increased its structural stability. Docking analysis has explored the position of PEG with respect to binding sites and predicted a similar binding affinity to that of the free enzyme. CONCLUSION: For the first time, recombinant L-ASNase was modified by covalently attaching PEG (330 Da). The resultant novel proposed PEGylated rL-ASNase with remarkably increased stability and prolonged in vivo half-life duration, which could be considered an alternative to mitigate the high molecular weight of PEGylation's drawbacks.

[N2O Emission Factors from Wastewater Treatment Plants Based on Literature Statistics and Model Fitting].

The emission of nitrous oxide （N2O） during wastewater treatment cannot be ignored. The analysis of statistical data from literature based on 126 empirical studies revealed that the geographical factors of wastewater treatment plants （WWTPs） had a significant impact on N2O emission factors. However, the N2O emission factors of WWTPs in all regions of the world were generally lower than the Intergovernmental Panel on Climate Change （IPCC） recommended values. In China, the N2O emission factors （in N2O-N/Ninfluent） of WWTPs were approximately 0.000 35-0.065 20 kg·kg-1. Meanwhile, the N2O emission factors of different wastewater treatment processes were also significantly different, especially since the sequencing batch reactor （SBR） process had higher emissions. The use of uniform default emission factors for accounting was prone to overestimate N2O emissions, and it is recommended that countries conduct actual monitoring or modeling studies to develop categorical emission factors suitable for local conditions. In addition, the N2O emission factor based on total nitrogen （TN） removal was weakly negatively correlated with TN removal in 126 empirical data, which was more in line with bioprocessing stoichiometry and could provide an accurate accounting method for N2O. To this end, a digital twin model was developed to dynamically simulate a case anaerobic-anoxic-aerobic （AAO） WWTP to comprehensively quantify the dynamic emission behavior of N2O, which demonstrated that N2O emissions had significant seasonal and daily variability and were only equivalent to 11% of the calculated value of the emission factor based on the IPCC recommendation. Comparing the scatter linear fitting and categorical mean exponential fitting methods, it was found that the latter could more accurately reflect the negative correlation between the N2O emission factors and the TN removal rate, and an exponential regression equation between the average N2O emission factor based on the amount of TN removed and the TN removal rate was further developed to predict the N2O emission. The dynamic simulation and categorical index fitting methods provided in this study are important references for the accurate accounting of N2O emissions in similar WWTPs and provide help for understanding and responding to the N2O emission problems.

An intelligent spraying system for weeds in wheat fields based on a dynamic model of droplets impacting wheat leaves.

Introduction: Targeted herbicide application refers to precise application of herbicides in weed-infested areas according to the location and density of farmland weeds. At present, targeted herbicide application in wheat fields generally faces problems including the low herbicide adhesion rate, leading to omission and excessive loss of herbicides. Methods: To solve these problems, changes in the impact force of herbicide and the weed leaves in the operation process of a spraying system were studied from the interaction between weeds and herbicides applied. A dynamic model of weed leaves was established. On this basis, the research indicated that the herbicide adhesion rate is highest under spraying pressure of 0.4 MPa and flow rate of 0.011 kg/s when the spray height is 300 mm. To study the dynamic deformation of weed leaves and the distribution of liquid herbicides in the external flow field under weed-herbicide interaction, a dynamic simulation model of herbicide application was built using the finite element method. Results and Discussion: The results show that when the spray height is 300 mm, the maximum weed leaf deformation index (LDI) is 0.43 and the velocity in the external flow field is 0 m/s under spraying pressure of 0.4 MPa and flow rate of 0.011 kg/s. This finding indicates that the herbicide is not splashed elsewhere and the turbulence intensity in the weed area is 2%, implying steady flow of the herbicide, most of which can be retained on weed leaves. Field test results of application quality of the herbicide show that the maximum LDI is 0.41 and the coverage of the herbicide in the sheltered area below the leaves is 19.02% when the spraying pressure is 0.4 MPa, flow rate is 0.011 kg/s, and spray height is 300 mm. This solves the problem of a low rate of utilization of herbicides because the herbicide passes through weed plants, and achieves the precision herbicide application in wheat fields.

Quantitative evaluation of acid flow behavior in fractures and optimization of design parameters based on acid wormhole filtration losses.

The technique of matrix acidification or acid fracturing is commonly utilized to establish communication with natural fractures during reservoir reconstruction. However, this process often encounters limitations due to filtration, which restricts the expansion of the primary acid-etching fracture. To address this issue, a computational model has been developed to simulate the expansion of an acid-etching wormhole by considering various factors such as formation process, injection duration, pressure build-up, and time-varying acid percolation rate. By analyzing the pumping displacement of acid-etching wormholes, this model provides valuable insights into the time-dependent quantities of acid percolation. It has been revealed that the filtration rate of acid-etching wormholes is strongly influenced by pumping displacement, viscosity, and concentration of the acid fluid used in stimulation as well as physical properties of the reservoir itself. Notably, viscosity plays a significant role in determining the effectiveness of acid fracturing especially in low-viscosity conditions. Acid concentration within 15% to 20% exhibits maximum impact on successful acid fracturing while concentrations below 15% or above 20% show no obvious effect. Furthermore, it was found that pumping displacement has a major influence on effective fracturing. However, beyond a certain threshold (> 5.0 m3/min), increased pumping displacement leads to slower etching distance for acids used in construction purposes. The simulation also provides real-time distribution analysis for acidity levels within eroded fractures during matrix-acidification processes and quantifies extent of chemical reactions between acids and rocks within these fractures thereby facilitating optimization efforts for design parameters related to matrix-acidification.

Structure-Guided Identification of Novel Aromatase Inhibitors Targeting Breast Carcinoma.

Aromatase inhibitors play a critical therapeutic role in treating ER+ breast cancer, especially in postmenopausal women. However, their efficacy is often limited by resistance and severe side effects. Identifying new compounds that can disrupt aromatase enzyme function is essential. In this study, structural anomalies in the aromatase enzyme were corrected through energy minimization, and the structure was validated via Ramachandran plot. We screened 170,269 natural compounds from the ASINEX Biodesign library using high-throughput screening algorithms to target the aromatase enzyme. Molecular docking identified three compounds: BDD30170158, BDE33872639, and BDE30177677, all showing stable binding interactions with the aromatase enzyme. Molecular dynamics simulations over 100 ns confirmed the conformational stability of these compounds. Although all three compounds exhibited the desired pharmacokinetic and drug metabolism properties, only one compound (BDE33872639) was identified as a non-blocker, demonstrating a reduced risk of adverse cardiac effects. This compound exhibits significant potential as a novel aromatase inhibitor, warranting further experimental research to develop it as a therapeutic option for ER+ breast cancer.

Cumulative phylogenetic, sequence and structural analysis of Insulin superfamily proteins provide unique structure-function insights.

The insulin superfamily proteins (ISPs), in particular, insulin, IGFs and relaxin proteins are key modulators of animal physiology. They are known to have evolved from the same ancestral gene and have diverged into proteins with varied sequences and distinct functions, but maintain a similar structural architecture stabilized by highly conserved disulphide bridges. The recent surge of sequence data and the structures of these proteins prompted a need for a comprehensive analysis, which connects the evolution of these sequences (427 sequences) in the light of available functional and structural information including representative complex structures of ISPs with their cognate receptors. This study reveals (a) unusually high sequence conservation of IGFs (>90 % conservation in 184 sequences) and provides a possible structure-based rationale for such high sequence conservation; (b) provides an updated definition of the receptor-binding signature motif of the functionally diverse relaxin family members (c) provides a probable non-canonical C-peptide cleavage site in a few insulin sequences. The high conservation of IGFs appears to represent a classic case of resistance to sequence diversity exerted by physiologically important interactions with multiple partners. We also propose a probable mechanism for C-peptide cleavage in a few distinct insulin sequences and redefine the receptor-binding signature motif of the relaxin family. Lastly, we provide a basis for minimally modified insulin mutants with potential therapeutic application, inspired by concomitant changes observed in other insulin superfamily protein members supported by molecular dynamics simulation.

In-silico screening of missense nsSNPs in Delta-opioid receptor protein and their restoring tendency on MCRT interaction; focusing on dynamic nature.

Delta-opioid receptor protein (OPRD1) is one of the potential targets for treating pain. The presently available opioid agonists are known to cause unnecessary side effects. To discover a novel opioid agonist, our research group has synthesized a chimeric peptide MCRT and proved its potential activity through in vivo analysis. Non-synonymous SNPs (nsSNPs) missense mutations affect the functionality and stability of proteins leading to diseases. The current research was focused on understanding the role of MCRT in restoring the binding tendency of OPRD1 nsSNPs missense mutations on dynamic nature in comparison with Deltorphin-II and morphiceptin. The deleterious effects of nsSNPs were analyzed using various bioinformatics tools for predicting structural, functional, and oncogenic influence. The shortlisted nine nsSNPs were predicted for allergic reactions, domain changes, post-translation modification, multiple sequence alignment, secondary structure, molecular dynamic simulation (MDS), and peptide docking influence. Further, the docked complex of three shortlisted deleterious nsSNPs was analyzed using an MDS study, and the highly deleterious shortlisted nsSNP A149T was further analyzed for higher trajectory analysis. MCRT restored the binding tendency influence caused by nsSNPs on the dynamics of stability, functionality, binding affinity, secondary structure, residues connection, motion, and folding of OPRD1 protein.

In silico exploration of anti-prostate cancer compounds from differential expressed genes.

Prostate cancer (PCa) is a complex and biologically diverse disease with no curative treatment options at present. This study aims to utilize computational methods to explore potential anti-PCa compounds based on differentially expressed genes (DEGs), with the goal of identifying novel therapeutic indications or repurposing existing drugs. The methods employed in this study include DEGs-to-drug prediction, pharmacokinetics prediction, target prediction, network analysis, and molecular docking. The findings revealed a total of 79 upregulated DEGs and 110 downregulated DEGs in PCa, which were used to identify drug compounds capable of reversing the dysregulated conditions (dexverapamil, emetine, parthenolide, dobutamine, terfenadine, pimozide, mefloquine, ellipticine, and trifluoperazine) at a threshold probability of 20% on several molecular targets, such as serotonin receptors 2a/2b/2c, HERG protein, adrenergic receptors alpha-1a/2a, dopamine D3 receptor, inducible nitric oxide synthase (iNOS), epidermal growth factor receptor erbB1 (EGFR), tyrosine-protein kinases, and C-C chemokine receptor type 5 (CCR5). Molecular docking analysis revealed that terfenadine binding to inducible nitric oxide synthase (-7.833 kcal.mol-1) and pimozide binding to HERG (-7.636 kcal.mol-1). Overall, binding energy ΔGbind (Total) at 0 ns was lower than that of 100 ns for both the Terfenadine-iNOS complex (-101.707 to -103.302 kcal.mol-1) and Ellipticine-TOPIIα complex (-42.229 to -58.780 kcal.mol-1). In conclusion, this study provides insight on molecular targets that could possibly contribute to the molecular mechanisms underlying PCa. Further preclinical and clinical studies are required to validate the therapeutic effectiveness of these identified drugs in PCa disease.

Design of multi-epitope vaccine against porcine rotavirus using computational biology and molecular dynamics simulation approaches.

Porcine Rotavirus (PoRV) is a significant pathogen affecting swine-rearing regions globally, presenting a substantial threat to the economic development of the livestock sector. At present, no specific pharmaceuticals are available for this disease, and treatment options remain exceedingly limited. This study seeks to design a multi-epitope peptide vaccine for PoRV employing bioinformatics approaches to robustly activate T-cell and B-cell immune responses. Two antigenic proteins, VP7 and VP8*, were selected from PoRV, and potential immunogenic T-cell and B-cell epitopes were predicted using immunoinformatic tools. These epitopes were further screened according to non-toxicity, antigenicity, non-allergenicity, and immunogenicity criteria. The selected epitopes were linked with linkers to form a novel multi-epitope vaccine construct, with the PADRE sequence (AKFVAAWTLKAAA) and RS09 peptide attached at the N-terminus of the designed peptide chain to enhance the vaccine's antigenicity. Protein-protein docking of the vaccine constructs with toll-like receptors (TLR3 and TLR4) was conducted using computational methods, with the lowest energy docking results selected as the optimal predictive model. Subsequently, molecular dynamics (MD) simulation methods were employed to assess the stability of the protein vaccine constructs and TLR3 and TLR4 receptors. The results indicated that the vaccine-TLR3 and vaccine-TLR4 docking models remained stable throughout the simulation period. Additionally, the C-IMMSIM tool was utilized to determine the immunogenic triggering capability of the vaccine protein, demonstrating that the constructed vaccine protein could induce both cell-mediated and humoral immune responses, thereby playing a role in eliciting host immune responses. In conclusion, this study successfully constructed a multi-epitope vaccine against PoRV and validated the stability and efficacy of the vaccine through computational analysis. However, as the study is purely computational, experimental evaluation is required to validate the safety and immunogenicity of the newly constructed vaccine protein.

In silico bioprospecting of receptors associated with the mechanism of action of Rondonin, an antifungal peptide from spider Acanthoscurria rondoniae haemolymph.

Multiple drug-resistant fungal species are associated with the development of diseases. Thus, more efficient drugs for the treatment of these aetiological agents are needed. Rondonin is a peptide isolated from the haemolymph of the spider Acanthoscurria rondoniae. Previous studies have shown that this peptide has antifungal activity against Candida sp. and Trichosporon sp. strains, acting on their genetic material. However, the molecular targets involved in its biological activity have not yet been described. Bioinformatics tools were used to determine the possible targets involved in the biological activity of Rondonin. The PharmMapper server was used to search for microorganismal targets of Rondonin. The PatchDock server was used to perform the molecular docking. UCSF Chimera software was used to evaluate these intermolecular interactions. In addition, the I-TASSER server was used to predict the target ligand sites. Then, these predictions were contrasted with the sites previously described in the literature. Molecular dynamics simulations were conducted for two promising complexes identified from the docking analysis. Rondonin demonstrated consistency with the ligand sites of the following targets: outer membrane proteins F (id: 1MPF) and A (id: 1QJP), which are responsible for facilitating the passage of small molecules through the plasma membrane; the subunit of the flavoprotein fumarate reductase (id: 1D4E), which is involved in the metabolism of nitrogenous bases; and the ATP-dependent Holliday DNA helicase junction (id: 1IN4), which is associated with histone proteins that package genetic material. Additionally, the molecular dynamics results indicated the stability of the interaction of Rondonin with 1MPF and 1IN4 during a 10 ns simulation. These interactions corroborate with previous in vitro studies on Rondonin, which acts on fungal genetic material without causing plasma membrane rupture. Therefore, the bioprospecting methods used in this research were considered satisfactory since they were consistent with previous results obtained via in vitro experimentation. Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-024-00224-1.

Screening structure and predicting toxicity of pesticide adjuvants using molecular dynamics simulation and machine learning for minimizing environmental impacts.

Surfactants as synergistic agents are necessary to improve the stability and utilization of pesticides, while their use is often accompanied by unexpected release into the environment. However, there are no efficient strategies available for screening low-toxicity surfactants, and traditional toxicity studies rely on extensive experimentation which are not predictive. Herein, a commonly used agricultural adjuvant Triton X (TX) series was selected to study the function of amphipathic structure to their toxicity in zebrafish. Molecular dynamics (MD) simulations, transcriptomics, metabolomics and machine learning (ML) were used to study the toxic effects and predict the toxicity of various TX. The results showed that TX with a relatively short hydrophilic chain was highly toxic to zebrafish with LC50 of 1.526 mg/L. However, TX with a longer hydrophilic chain was more likely to damage the heart, liver and gonads of zebrafish through the arachidonic acid metabolic network, suggesting that the effect of surfactants on membrane permeability is the key to determine toxic results. Moreover, biomarkers were screened through machine learning, and other hydrophilic chain lengths were predicted to affect zebrafish heart health potentially. Our study provides an advanced adjuvants screening method to improve the bioavailability of pesticides while reducing environmental impacts.

Rational redesign of the loop dynamics of carbonyl reductase LfSDR1 to improve the stereoselectivity for asymmetric synthesis of bulky chiral alcohols.

Engineering biocatalysts with enhanced stereoselectivity is highly desirable, and active-site loop dynamics play an important role in its regulation. However, knowledge of their precise roles in catalysis and evolution is limited. Here, we used the strategy of Rosetta enzyme design combined molecular dynamic simulations (MDs) to reprogram the landscapes of the key active-site loop dynamics of the carbonyl reductase LfSDR1 to improve stereoselectivity. The key flexible loop in the active site showed the potential to regulate the catalytic properties. A library of virtual variants was produced using the Rosetta design and assessed dynamic effect of the loop with the aid of MDs. A potential candidate was obtained with significant stereoselectivity (ee > 99 %) compared to the wild-type (ee = 42 %) without loss of catalytic activity or thermostability. The molecular basis of the catalytic property enhancement was flanked by MDs, which revealed the role of the G92L mutation in regulating loop dynamics to stabilize the environment of the active site. Finally, a series of the challenge bulky substrate derivatives were assessed using the G92L variant, and all showed improved stereoselectivity ee > 99 %. This study provides novel insights for improving stereoselectivity through rational engineering of the loop dynamics of biocatalysts.

Calculating transmembrane voltage on the electric pulse-affected cancerous cell membrane: using molecular dynamics and finite element simulations.

CONTEXT: Electroporation is a technique that creates electrically generated pores in the cell membrane by modifying transmembrane potential. In this work, the finite element method (FEM) was used to examine the induced transmembrane voltage (ITV) of a spherical-shaped MCF-7 cell, allowing researchers to determine the stationary ITV. A greater ITV than the critical value causes permeabilization of the membrane. Furthermore, the present study shows how a specific surface conductivity can act as a stand-in for the thin layer that constitutes a cell membrane as the barrier between extracellular and intracellular environments. Additionally, the distribution of ITV on the cell membrane and its maximum value were experimentally evaluated for a range of applied electric fields. Consequently, the entire cell surface area was electroporated 66% and 68% for molecular dynamics (MD) simulations and FEM, respectively, when the external electric field of 1500 V/cm was applied to the cell suspension using the previously indicated numerical methods. Furthermore, the lipid bilayers' molecular structure was changed, which led to the development of hydrophilic holes with a radius of 1.33 nm. Applying MD and FEM yielded threshold values for transmembrane voltage of 700 and 739 mV, respectively. METHOD: Using MD simulations of palmitoyloleoyl-phosphatidylcholine (POPC), pores in cell membranes exposed to external electric fields were numerically investigated. The dependence on the electric field was estimated and developed, and the amount of the electroporated cell surface area matches the applied external electric field. To investigate more, a mathematical model based on an adaptive neuro-fuzzy inference system (ANFIS) is employed to predict the percent cell viability of cancerous cells after applying four pulses during electroporation. For MD simulations, ArgusLab, VMD, and GROMACS software packages were used. Moreover, for FEM analysis, COMSOL software package was used. Also, it is worth mentioning that for mathematical model, MATLAB software is used.

Exploring the role of γ-Oryzanol on stabilization mechanism of Pickering emulsion gels loaded by α-Lactalbumin or ß-Lactoglobulin via multiscale approaches.

The research explored the role of γ-oryzanol (γs) on stabilization behavior of Pickering emulsion gels (PEGs) loaded by α-lactalbumin (α-LA) or ß-lactoglobulin (ß-LG), being analyzed by experimental and computer methods (molecular dynamic simulation, MD). Primarily, the average particle size of ß-LG-γS was expressed 100.07% decrease over that of α-LA-γS. In addition, γs decreased the dynamic interfacial tension of two proteins with the order of ß-LG < α-LA. Meanwhile, quartz crystal microbalance with dissipation proved that ß-LG-γS exhibited higher adsorption mass and denser rigid interface layer than α-LA-γS. Moreover, the hydrophobic group of γS had electrostatic repulsion with polar water molecules in the aqueous phase, which spread to the oil phase. ß-LG-γS had lower RMSD/Rg value and narrower fluctuation compared with α-LA-γS. This work strength the exploration of interfacial stabilization mechanism of whey protein-based PEGs, which enriched its theoretical research for industrial-scale production as the replacement of trans fat and cholesterol.

Research into how carvacrol and metformin affect several human proteins in a hyperglycemic condition: A comparative study in silico and in vitro.

Carvacrol (CV) is an organic compound found in the essential oils of many aromatic herbs. It is nearly unfeasible to analyze all the current human proteins for a query ligand using in vitro and in vivo methods. This study aimed to clarify whether CV possesses an anti-diabetic feature via Docking-based inverse docking and molecular dynamic (MD) simulation and in vitro characterization against a set of novel human protein targets. Herein, the best poses of CV docking simulations according to binding energy ranged from -7.9 to -3.5 (kcal/mol). After pathway analysis of the protein list through GeneMANIA and WebGestalt, eight interacting proteins (DPP4, FBP1, GCK, HSD11ß1, INSR, PYGL, PPARA, and PPARG) with CV were determined, and these proteins exhibited stable structures during the MD process with CV. In vitro application, statistically significant results were achieved only in combined doses with CV or metformin. Considering all these findings, PPARG and INSR, among these target proteins of CV, are FDA-approved targets for treating diabetes. Therefore, CV may be on its way to becoming a promising therapeutic compound for treating Diabetes Mellitus (DM). Our outcomes expose formerly unexplored potential target human proteins, whose association with diabetic disorders might guide new potential treatments for DM.

Identification of Prospective Ebola Virus VP35 and VP40 Protein Inhibitors from Myxobacterial Natural Products.

The Ebola virus (EBOV) is a lethal pathogen causing hemorrhagic fever syndrome which remains a global health challenge. In the EBOV, two multifunctional proteins, VP35 and VP40, have significant roles in replication, virion assembly, and budding from the cell and have been identified as druggable targets. In this study, we employed in silico methods comprising molecular docking, molecular dynamic simulations, and pharmacological properties to identify prospective drugs for inhibiting VP35 and VP40 proteins from the myxobacterial bioactive natural product repertoire. Cystobactamid 934-2, Cystobactamid 919-1, and Cittilin A bound firmly to VP35. Meanwhile, 2-Hydroxysorangiadenosine, Enhypyrazinone B, and Sorangiadenosine showed strong binding to the matrix protein VP40. Molecular dynamic simulations revealed that, among these compounds, Cystobactamid 919-1 and 2-Hydroxysorangiadenosine had stable interactions with their respective targets. Similarly, molecular mechanics Poisson-Boltzmann surface area (MMPBSA) calculations indicated close-fitting receptor binding with VP35 or VP40. These two compounds also exhibited good pharmacological properties. In conclusion, we identified Cystobactamid 919-1 and 2-Hydroxysorangiadenosine as potential ligands for EBOV that target VP35 and VP40 proteins. These findings signify an essential step in vitro and in vivo to validate their potential for EBOV inhibition.

Study on the Application of Fluorinated Polyimide in the Acidic Corrosion Protection of 3-nitro-1,2,4-trizole-5-one (NTO)-Based Explosive Formulations.

3-nitro-1,2,4-triazol-5-one (NTO) has been widely used as a kind of insensitive single-compound explosive owing to its excellent balance between safety and explosive energy. To reduce its possible acid corrosion and extend its application to insensitive ammunition, acid protection research on NTO-based explosives is significant. Traditionally, the acid protection effect was evaluated by metal corrosion, which is time-consuming and qualitative. An efficient and quantitative method is desirable for evaluating the acid protection effect and exploring novel protection materials. Herein, a polyimide of 4,4'-(hexafluoroisopropene)diphthalic anhydride (6FDA)/2,2-bis(trifluoromethyl)-4,4-diaminobiphenyl (TFMB) was synthesized by replacing the 4,4'-diaminodiphenyl ether (ODA) monomer with a TFMB monomer to act as an acid-protective coating material for NTO-based explosives. Compared with three other coating materials, polyvinylidene fluoride (PVDF), polyetherimide (PEI), and copolyimide (P84), the fluorinated polyimide exhibits the best acid protection effect. Moreover, a new method was constructed to obtain the pH time-dependent curve in order to evaluate efficiently the acid protection effect of the polymer materials. By the virtue of molecular dynamic simulation (Materials Studio 2023), the interfacial effects of the coating materials with NTO-based explosives were obtained. The study provides an interpretation of the acid protection effect on the molecular level, suggesting that the higher content of fluorine atoms is beneficial for stabilizing the active hydrogen atom of the NTO by forming intermolecular hydrogen bonds.

Interfacial Interaction between Functionalization of Polysulfone Membrane Materials and Protein Adsorption.

This study that modified polysulfone membranes with different end-group chemical functionalities were prepared using chemical synthesis methods and experimentally characterized. The molecular dynamics (MD) method were used to discuss the adsorption mechanism of proteins on functionalized modified polysulfone membrane materials from a molecular perspective, revealing the interactions between different functionalized membrane surfaces and protein adsorption. Theoretical analysis combined with basic experiments and MD simulations were used to explore the orientation and spatial conformational changes of protein adsorption at the molecular level. The results show that BSA exhibits different variability and adsorption characteristics on membranes with different functional group modifications. On hydrophobic membrane surfaces, BSA shows the least stable configuration stability, making it prone to nonspecific structural changes. In addition, surface charge effects lead to electrostatic repulsion for BSA and reduce the protein adsorption sites. These MD simulation results are consistent with experimental findings, providing new design ideas and support for modifying blood-compatible membrane materials.