Molecular Dynamics Simulation Approach Research Articles

COMPUTATIONAL ANALYSIS OF PHOSPHORYLATED GSTP1: INSIGHTS INTO ALTERED ACTIVITY UPON BINDING WITH GLUTATHIONE AND ETHACRYNIC ACID

Glutathione S-transferase pi 1 (GSTP1) is an essential detoxifying enzyme that plays a critical role in protecting cells from oxidative stress and carcinogenesis. Employing a molecular dynamics simulations approach, we delineate the specific phosphorylation sites on GSTP1 except the WT. Our study unveils critical residues and structural motifs susceptible to phosphorylation-induced destabilization, offering novel insights into the regulatory mechanisms underlying GSTP1 function and potential avenues for therapeutic intervention in diseases associated with dysregulated GSTP1 activity.

Structure-based drug-development study against fibroblast growth factor receptor 2: molecular docking and Molecular dynamics simulation approaches

Developing new therapeutic strategies to target specific molecular pathways has become a primary focus in modern drug discovery science. Fibroblast growth factor receptor 2 (FGFR2) is a critical signaling protein involved in various cellular processes and implicated in numerous diseases, including cancer. Existing FGFR2 inhibitors face limitations like drug resistance and specificity issues. In this study, we present an integrated structure-based bioinformatics analysis to explore the potential of FGFR2 inhibitors-like compounds from the PubChem database with the Tanimoto threshold of 80%. We conducted a structure-based virtual screening approach on a dataset comprising 2336 compounds sourced from the PubChem database. Primarily, the selection of promising compounds was based on several criteria, such as drug-likeness, binding affinities, docking scores, and selectivity. Further, we conducted all-atom molecular dynamics (MD) simulations for 200 ns, followed by an essential dynamics analysis. Finally, a promising FGFR2 inhibitor with PubChem CID:507883 (1-[7-(1H-benzimidazol-2-yl)-4-fluoro-1H-indol-3-yl]-2-(4-benzoylpiperazin-1-yl)ethane-1,2-dione) was screened out from the study. This compound indicates a higher potential for inhibiting FGFR2 than the control inhibitor, Zoligratinib. The identified compound, CID:507883 shows >80% structural similarity with Zoligratinib. ADMET analysis showed promising pharmacokinetic potential of the screened compound. Overall, the findings indicate that the compound CID:507883 may have promising potential to serve as a lead candidate against FGFR2 and could be further exploited in therapeutic development.

A computational approach to identifying peptide inhibitors againstWhite Spot Syndrome Virus: Targeting the virus envelope protein

The white spot syndrome virus (WSSV), a rapidly replicating and highly lethal pathogen that targets Penaeid shrimp, has emerged as one of the most widespread viruses globally due to its high virulence. With effective chemotherapeutics still unavailable, the pursuit of novel and viable strategies against WSSV remains a crucial focus in the field of shrimp farming. The envelope proteins of WSSV are essential for virus entry, serving as excellent targets for the development of antiviral therapeutics. Novel strategies in the design of inhibitory peptides, especially those targeting envelope protein (VP28) located on the surface of the virus particle, play a critical role as a significant virulence factor during the early stages of inherent WSSV infection in shrimp. In this direction, the current computational study focused on identifying self-inhibitory peptides from the hydrophobic membrane regions of the VP28 protein, employing peptide docking and molecular dynamics simulation (MDS) approaches. Such inhibitory peptides could be useful building blocks for the rational engineering of inhibitory therapeutics since they imitate the mechanism of binding to homologous partners used by their origin domain to interact with other molecules. The N-terminal sequence of VP28 has been reported as the potential site for membrane interactions during the virus entry. Moreover, drug delivery systems mediated by chitosan and gold nanoparticles are being developed to enhance the therapeutic efficacy of anti-viral peptides. These systems can increase the solubility, stability, and selectivity of peptides, possessing better qualities than conventional delivery methods. This computational study on self-inhibitory peptides could be a valuable resource for further in vitro and in vivo studies on anti-viral therapeutics in the aquaculture industry.

Evaluation of Potential Furin Protease Inhibitory Properties of Pioglitazone, Rosiglitazone, and Pirfenidone: An In Silico Docking and Molecular Dynamics Simulation Approach.

Furin (Fur) is a member of the protease convertase family; its expression is crucial for cleaving and maturing many proteins. Fur also represents a therapeutic target in cancer, autoimmune diseases, and viral infections. Pioglitazone (PGZ) and rosiglitazone (RGZ) are thiazolidinediones prescribed to type 2 diabetes patients and are structurally similar to the known Fur inhibitors naphthofluorescein (NPF) and pirfenidone (PFD). Thus, this study used molecular docking and molecular dynamics to assess and compare the affinities and the molecular interactions of these four ligands with the Fur active site (FurAct) and the recently described Fur allosteric site (FurAll). The 7QXZ Fur structure was used for molecular dockings, and for the best pose complexes, molecular dynamics were run for 100 ns. The best affinities of the ligand/FurAct and ligand/FurAll complexes were with NPF, PGZ, and RGZ, while PFD presented the lowest affinity. Asp154 was the central residue involved in FurAct complex formation, while Glu488 and Asn310 were the central residues involved in FurAll complex formation. This study shows the potential of RGZ, PGZ, and PFD as Fur competitive (FurAct) and non-competitive (FurAll) inhibitors. Therefore, they are candidates for repurposing in response to future emerging diseases through the modulation of Fur activity.

Insilico assessment of hesperidin on SARS-CoV-2 main protease and RNA polymerase: Molecular docking and dynamics simulation approach

The present study uses molecular docking and dynamic simulations to evaluate the inhibitory effect of flavonoid glycosides-based compounds on coronavirus Main protease (Mpro) and RNA polymerase. The Molegro Virtual Docker (MVD) software is utilized to simulate and calculate the binding parameters of compounds with coronavirus. The docking results show that the selected herbal compounds are more effective than those of chemical compounds. It is also revealed that five herbal ligands and two chemical ligands have the best docking scores. Furthermore, a Molecular Dynamics (MD) simulation was conducted for Hesperidin, confirming docking results. Analysis based on different parameters such as Root-mean-square deviation (RMSD), Root mean square fluctuation (RMSF), Radius of gyration (Rg), Solvent accessibility surface area (SASA), and the total number of hydrogen bonds suggests that Hesperidin formed a stable complex with Mpro. Absorption, Distribution, Metabolism, Excretion, And Toxicity (ADMET) analysis was performed to compare Hesperidin and Grazoprevir as potential antiviral medicines, evaluating both herbal and chemical ligand results. According to the study, herbal compounds could be effective on coronavirus and are admissible candidates for developing potential operative anti-viral medicines. Hesperidin was found to be the most acceptable interaction. Grazoprevir is an encouraging candidate for drug development and clinical trials, with the potential to become a highly effective Mpro inhibitor. Compared to RNA polymerase, Mpro showed a greater affinity for bonding with Hesperidin. van der Waals and electrostatic energies dominated, creating a stable Hesperidin-Mpro and Hesperidin-RNA polymerase complex.

Theoretical and Molecular Dynamics Simulation Approaches to Praseodymium Content Effect on Radiation Shielding and Time Dependent Volume‐Collapse for a Newly Produced Borate Glass

AbstractGamma‐ray, fast neutron and charged particle shielding characteristics of Praseodymium (Pr3+) activated glasses with composition 10ZnF2‐(10‐x)SrO‐15Li2O‐65H3BO3‐xPr2O3(where x = 0.1, 0.5, 1.0, 1.5, and 2.0) are investigated. For this, the radiation shielding parameters are estimated by using Photon Shielding and Dosimetry (Phy‐X/PSD), Interaction of Proton, Alpha, Gamma rays, Electrons, and X‐rays with matter (PAGEX), Stopping Powers and Ranges for Electrons (ESTAR), and The Stopping and Range of Ions in Matter (SRIM) codes. Furthermore, the results are compared comprehensively and comparatively. The glasses with increasing Pr3+ content exhibited higher shielding potential. It can be said that the ZFLHBPr2.0 sample could be used as a shielding material in various applied fields. Additionally, the effect of Pr composition on structural transitions and time‐dependent volume‐collapse of this new family of borate glass doped with Pr is analyzed by molecular dynamics study (MD) based density functional tight binding method. The simulation results show that the addition of Pr led to the cubic‐orthorhombic transformation of simulation cell at determined temperature and 1 atm pressure. Also, a sudden decrease in volume are observed within a short time at 8% Pr composition (x = 2.0) atmospheric pressure. This result provides a strong connection between Pr composition and volume change with time and at constant low pressure.

Structure-based Virtual Screening and Molecular Dynamic Simulation Approach for the Identification of Terpenoids as Potential DPP-4 Inhibitors.

Diabetes mellitus is a metabolic disorder where insulin secretion is compromised, leading to hyperglycemia. DPP-4 is a viable and safer target for type 2 diabetes mellitus. Computational tools have proven to be an asset in the process of drug discovery. In the present study, tools like structure-based virtual screening, MM/GBSA, and pharmacokinetic parameters were used to identify natural terpenoids as potential DPP-4 inhibitors for treating diabetes mellitus. Structure-based virtual screening, a cumulative mode of elimination technique, was adopted, identifying the top five potent hit compounds depending on the docking score and nonbonding interactions. According to the docking data, the most important contributors to complex stability are hydrogen bonding, hydrophobic interactions, and Pi-Pi stacking interactions. The dock scores ranged from -6.492 to -5.484 kcal/mol, indicating robust ligand-protein interactions. The pharmacokinetic characteristics of top-scoring hits (CNP0309455, CNP0196061, CNP0122006, CNP0 221869, CNP0297378) were also computed in this study, confirming their safe administration in the human body. Also, based on the synthetic accessibility score, all top-scored hits are easily synthesizable. Compound CNP0309455 was quite stable during molecular dynamic simulation studies. Virtual database screening yielded new leads for developing DPP-4 inhibitors. As a result, the findings of this study can be used to design and develop natural terpenoids as DPP-4 inhibitors for the medication of diabetes mellitus.

Electrochemical aptasensor based on RGO/PPy/Au*NPs for diagnostic biosensing of SARS-CoV-2 in clinical samples: Experimental and molecular dynamics simulations approaches

A highly sensitive and selective E-DNA biosensor was fabricated on a gold substrate using a reduced graphene oxide/polypyrrole/gold nanoparticle/oligonucleotide (RGO/PPy/Au*NPs/Apt) nanocomposite electrode to detect the nucleocapsid protein of SARS-CoV-2 in the patient blood plasma. The modified electrode was characterized by physicochemical techniques such as Fourier transform-infra red (FT-IR), Raman spectroscopy, X-ray diffraction (XRD), energy-dispersive X-ray (EDX) spectroscopy, X-ray photoelectron spectroscopy (XPS) analyses, Brunauer-Emmett-Teller (BET), and Barrett-Joyner-Halenda (BJH) analyses. Moreover, electrochemical analyses were employed to study the electrochemical performance of the electrodes including cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and square wave voltammetry (SWV). Computational investigations of N protein bindings such as hydrogen bonding, Van der Waals binding, and Gibbs binding energies of the N-protein, and aptamer were studied by Molecular Dynamics Simulations (MDS). The unique synergistic effect of RGO, PPy, and the well-known effect of Au nanoparticles makes the DNA probe immobilized on the gold electrode surface. After optimizing the systems, the E-DNA biosensor exhibited a fast SWV response, higher sensitivity (33.77 μA.nM−1.cm−2) and selectivity, high efficiency, good storage stability, and acceptable repeatability for monitoring DNA. The results of real samples based on SWV indicated the correct functioning of the aptasensor in the presence of the SARS-CoV-2 virus. The limit of detection was 3.16×10−17 M and the limit of quantitation was 1.42×10−16 M. The MDS results indicated the stable dynamic folding of the aptamer for beneficial binding. The results indicated that the RGO/PPy/Au*NPs/Apt biosensor is promising for detecting of SARS-CoV-2 virus.

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.

Integrating molecular docking and molecular dynamics simulation approaches for investigation of the affinity and interactions of the Curcumin with phosphatase and tensin homolog (PTEN) and mutated PTEN

Cancer is a complex disease that imposes a significant economic burden on populations globally. Curcumin, the active ingredient in turmeric, has anti-cancer properties that hold promise for preventing cancer. By affecting key intracellular signalling pathways and proteins like NF-κB and STAT3, Curcumin shows potential for thwarting cancer growth.Our research utilizes molecular docking and dynamics simulations to investigate how Curcumin interacts with Phosphatase and tensin homolog (PTEN) and mutated PTEN. PTEN, a tumor suppressor protein containing 403 amino acids, plays a vital role in various cancers due to its enzymatic activities. Our results suggest that Curcumin binds more strongly to mutated PTEN, indicating its potential to target cancer cells with mutated PTEN.Additionally, molecular dynamics simulations demonstrate that Curcumin effectively interacts with mutated PTEN, forming stable hydrogen bonds and van der Waals interactions. These findings suggest that Curcumin could serve as a safe and efficient natural compound for exploring as a therapeutic agent to reactivate mutated PTEN in cancer treatment.

Unveiling the impact of self-assembly on ultrafiltration: Insights from salvianolic acid B

This study explored the influence of self-assembly on the ultrafiltration (UF) rejection of salvianolic acid B (SaB), a model polyphenolic compound. Employing a combined approach of experimental analysis and molecular dynamics simulations (MDS), we demonstrated pH-dependent self-assembly of SaB at both macroscopic and microscopic levels. At lower pH, larger self-assemblies formed, exhibiting enhanced adsorption onto the membrane surface due to electrostatic attraction. This pH-dependent behavior significantly impacted rejection rates through size exclusion and adsorption mechanisms, leading to a decrease in SaB rejection from 100 % to 31 % as the solution pH increased from 2.4 to 5.6. These findings transcend the specific case of SaB, offering valuable insights into the broader role of self-assembly in UF processes. This knowledge holds potential applications in optimizing separation processes across diverse fields such as food, pharmaceuticals, and environmental science.

Identification of new inhibitors for the avian H1N1 virus through molecular docking and dynamic simulation approaches

The new variant of influenza A virus is known as avian H1N1 subtype which particularly affects birds, and poultry. However, recently it is affecting in human, and creating global health problem. So, this research has studied the myricetin derivatives as novel therapeutic agents that target the Hemagglutinin Protein in Avian H1N1 Virus. The study is focused on addressing the critical need for effective antiviral agents through computational drug design approaches. The research assesses the binding affinities, quantum calculation, molecular dynamic simulation, binding free energy calculation, electronic characteristics, DCCM, PCA and stability of myricetin derivatives with the hemagglutinin protein. This extensive investigation has documented that all the compounds showed outstanding binding affinities, more precisely compounds like 03 and 47, which show better binding energies than the conventional antiviral Tamiflu. Furthermore, the reactivity, pharmacokinetics, and stability, molecular dynamics simulations, ADMET characteristics, and quantum chemical descriptors are investigated, and they all are satisfied by favorable drug like properties. Besides that, this research highlights the significance of electrical characteristics, dipole moment, and hydrogen bonding in developing efficient antiviral medications. In addition, the myricetin derivatives show promise for oral delivery based on ADMET (absorption, distribution, metabolism, excretion, and toxicity) characteristics. Finally, the molecular dynamics simulations show that the ligand-protein complexes are stable and flexible over the MD simulation of 100 ns. Although, the discovered compounds show potential interactions with the avian H1N1 influenza A virus, with outstanding binding affinity, however, it is still crucial needed to perform experimental validation in near future.

Antibacterial potential of Propolis: molecular docking, simulation and toxicity analysis

The issue of antibiotic resistance in pathogenic microbes is a global concern. This study was aimed to explore in silico and in vitro analysis of the antibacterial efficacy of different natural ligands against bacterial activity. The ligands included in the study were Propolis Neoflavanoide 1, Carvacrol, Cinnamaldehyde, Thymol, p-benzoquinone, and Ciprofloxacin (standard drug S*). The outcomes of molecular docking revealed that Propolis Neoflavaniode-1 showed a highly significant binding energy of − 7.1 and − 7.2 kcal/mol for the two gram-positive bacteria, as compared to the gram-negative bacteria. All ligands demonstrated acute toxicity (oral, dermal), except for Propolis Neoflavanoide 1 and S* drugs, with a confidence score range of 50–60%. Using a molecular dynamic simulation approach, we investigated Propolis Neoflavaniode-1’s potential for therapeutic use in more detail. An MD simulation lasting 100 ns was performed using the Desmond Simulation software to examine the conformational stability and steady state of Propolis Neoflavaniode-1 in protein molecule complexes. Additionally, in vitro studies confirmed the antimicrobial activity of Propolis Neoflavaniode 1 by increasing the zone of inhibition against Gram-positive bacteria, p < 0.005 as compared to gram-negative bacteria. This study revealed the promising antibacterial efficacy of Propolis Neoflavaniode 1, demonstrated through robust in silico analyses, minimal toxicity, and confirmed in vitro antimicrobial activity, suggesting its potential as a viable alternative to combat antibiotic resistance.

Size-Dependent Fullerenes for Enhanced Interaction of l-Leucine: A Combined DFT and MD Simulations Approach.

Fullerene-based biosensors have received great attention due to their unique electronic properties that allow them to transduce electrical signals by accepting electrons from amino acids. Babies with MSUD (maple syrup urine disease) are unable to break down amino acids such as l-leucine, and excess levels of the l-leucine are harmful. Therefore, sensing of l-leucine is foremost required. We aim to investigate the interaction tendencies of size-variable fullerenes (CX; X = 24, 36, 50, and 70) toward l-leucine (LEU) using density functional theory (DFT-D3) and classical molecular dynamics (MD) simulation. The C24 fullerene shows the highest affinity of the LEU biomolecule in the gas phase. Smaller fullerenes (C24 and C36) show stronger interactions with leucine due to their higher curvature in water environments. Moreover, recovery times in the ranges of 1010 and 104 s make it a viable candidate for the isolation application of LEU from the biological system. Further, the interaction between LEU and fullerenes is in line with the natural bond order (NBO) analysis, Mulliken charge analysis, quantum theory atom in molecule (QTAIM) analysis, and reduced density gradient (RDG) analysis. At 310 K, employing the explicit water model in classical MD simulations, fullerenes C24 and C36 demonstrate notably elevated binding free energies (-24.946 kJ/mol) in relation to LEU, showcasing their potential as sensors for l-leucine. Here, we demonstrate that the smaller fullerene exhibits a higher potential for l-leucine sensors than the larger fullerene.

Effective removal of heavy metals from aqueous solutions using activated biomass: Analytical interpretation via molecular dynamic simulation, mathematical and statistical approaches

Activated carbons basis on low-cost natural materials, Diplotaxis harra (DH) and Glebionis coronaria L. (GCL) were prepared by chemical activation. The optimization of the manufacture conditions is performed by the full factorial design with four variables. Indeed, four activated carbons are prepared, DHACH3PO4, GCLACH3PO4, DHAC-KOH et GCLAC-KOH. The approach used has been evaluated regarding Cd(II) and Co(II) sorption capacities. The optimal conditions for activated carbons preparation are investigated. Therefore, the equilibrium study is assumed using Langmuir and Freundlich isotherm models. Under the optimum conditions, the highest adsorption of Cd(II) is acquired at 118.75 mg/g onto GCLACH3PO4. However, the greater efficiency of Co(II) sorption is obtained onto DHAC- H3PO4 and it was 82.55 mg/g. The current optimization overviews the Cd(II) and Co(II) removal involving various activated carbons. In the theoretical approach, the adsorption affinity of the heavy metal is computed using molecular dynamics (MD) simulation and compared with the adsorption affinity obtained from the experiment. The adsorption energy values were fitted to an empirical interaction energy model to predict the binding energy of arbitrary pollutants. This study used MD simulation to investigate the adsorption mechanism of Cd(II) on the AC (002) surface. The adsorption and interaction energies indicated a feasible, exothermic, and spontaneous adsorption process. MD simulations demonstrate that the adsorption process of Cd(II) on activated carbon is chemical in nature. This result is confirmed by the radial distribution function (RDF) analysis. This research adds new theoretical and experimental findings about heavy metal adsorption using activated carbon.

Wettability behavior of DTMS modified SiO2: Experimental and molecular dynamics study

In this research, the wetting behavior of SiO2 modified with dodecyltrimethoxysilane (DTMS) was explored using both experimental and molecular dynamics (MD) simulation approaches. The experimental results reveal that DTMS can chemically bond to the SiO2 surface, and the contact angle (CA) reaches the maximum value of 157.7° when the mass of DTMS is twice that of SiO2. The different wetting behaviors caused by DTMS grafting were analyzed by CA fitting, ionic pairs, concentration distribution, molecule orientation, and interfacial interaction energy. The results demonstrate that a 25% DTMS grafting rate resulted in a maximum CA of 158.2°, which is ascribed to the disruption of interfacial hydrogen bonding and changes in the hydration structure caused by DTMS grafting. Moreover, the above hydrophobic SiO2 model shows a slight decrease in CA as the water temperature increases, which is consistent with the experimental findings. In contrast, an opposite change was observed for the pristine SiO2 model. Although the higher water temperature enhances the diffusion capacity of water molecules in both models, the difference in interfacial interactions is responsible for the change in CA. We hope this finding will contribute to a deeper understanding of the wetting adjustment of SiO2.

Integrating molecular docking and molecular dynamics simulation approaches for investigation of the affinity and interactions of quercetin with Class D beta-lactamase, OXA-10

Introduction: The misuse of β-lactam antibiotics has led to the development of β-lactamase-producing organisms, which inhibit β-lactam activity by hydrolyzing the peptide bond. This study aims to investigate the inhibitory effect of quercetin, a natural composite and isoquinoline alkaloid, on β-lactamase enzyme action, potentially increasing antibiotic effectiveness. Materials and Methods: This study utilized computational techniques like molecular docking and MD simulation to predict the binding mode and possible conformation poses of quercetin with the OXA-10 β-lactamase enzyme. Autodock software was used for docking, while Gromacs 2019.6 package was used for MD simulations to study molecular complex behavior over time. Results: The outcomes of the molecular docking analysis revealed a favorable interaction between quercetin and the OXA-10 β-lactamase enzyme, as evidenced by a binding energy of -5.95 kcal/mol and a suitable binding mode. MD simulations confirmed the docking results, showing stable hydrogen bonds between Quercetin and OXA-10, as well as comparable RMSD, RMSF, SASA values, and other parameters. Discussion: This research shows the potential of quercetin, a natural compound with multiple medicinal effects, as a possible inhibitor of the class D type β-lactamase OXA-10. Therefore, this study maintains valuable intuition for designing new inhibitors of antimicrobial resistance to combat β-lactamase activity.

The active components of Erzhi wan and their anti-Alzheimer's disease mechanisms determined by an integrative approach of network pharmacology, bioinformatics, molecular docking, and molecular dynamics simulation

Erzhi Wan (EZW), a classic Traditional Chinese Medicine formula, has shown promise as a potential therapeutic option for Alzheimer's disease (AD), yet its mechanism remains elusive. Herein, we employed an integrative in-silico approach to investigate the active components and their mechanisms against AD. We screened four active components with blood-brain barrier permeabilities from TCMSP, along with 307 corresponding targets predicted by SwissTargetPrediction, PharmMapper, and TCMbank websites. Then, we retrieved 2260 AD-related targets from Genecards, OMIM, and NCBI databases. Furthermore, we constructed the protein-protein interaction (PPI) network of the intersected targets via the STRING database and performed the GO and KEGG enrichment analyses using the “clusterProfiler” R package. The results showed that the intersected targets were intimately related to the p53/PI3K/Akt signaling pathway, serotonergic synapse, and response to oxygen level. Subsequently, 25 core targets were found differentially expressed in brain regions by bioinformatics analyses of GEO datasets of clinical samples from the Alzdata database. The binding sites and stabilities between the active components and the core targets were investigated by the molecular docking approach using Autodock 4.2.6 software, followed by pocket detection and druggability assessment via the DoGSiteScorer server. The results showed that acacetin, β-sitosterol, and 3-O-acetyldammarenediol-II strongly interacted with the druggable pockets of AR, CASP8, POLB, and PREP. Eventually, the docking results were further cross-referenced with the literature research and validated by 100 ns of molecular dynamics simulations using GROMACS software. Binding free energies were calculated via MM/PBSA strategy combined with interaction entropy. The simulation results indicated stable bindings between four docking pairs including acacetin-AR, acacetin-CASP8, β-sitosterol-POLB, and 3-O-acetyldammarenediol–II–PREP. Overall, our study demonstrated a theoretical basis for how three active components of EZW confer efficacy against AD. It provides a promising reference for subsequent research regarding drug discoveries and clinical applications.

Synthesis and investigation of acrylamide and 2-acrylamido-2-methylpropanesulfonic acid copolymer-modified graphene oxide nanomaterials with intensive viscosification capacity: An experimental and molecular dynamics study

The polymer-modified nanomaterials with spontaneously generated cross-linked network greatly improve the dispersion viscosity, which is crucial for extending the sweep range and enhancing oil recovery. Recently, graphene oxide (GO) nanosheets have attracted extensive attention due to their high chemical reactivity and specific surface. In this paper, the AA molecule, synthesized by acrylamide (AM) and 2-acrylamido-2-methypropanesulfonic acid (AMPS) copolymerization, modified GO nanosheets (GAA) material is firstly synthesized and characterized. With the same content of AMPS segments, GAAn systems consistently exhibit better dispersion stability than AAn systems, along with higher absolute zeta potential values. The comprehensive investigation on the rheological property of GAA system reveals that GAA15 with the highest AMPS content exhibits the largest zero-shear viscosity (409.27 mPa·s) and the longest relaxation time. Based on the molecular dynamic simulation approaches, the aggregation morphology and stability of AA and GAA molecules are evaluated via the configuration analysis and the statistics of hydrogen bond numbers. The abundant binding sites from GO segments of GAA promote additional hydrogen bonds between GAA molecules and water, resulting in a more stable configuration. Molecular surface potential analysis and the independent gradient model based on Hirshfeld partition (IGMH) methods are further used to visualize the non-bonded interaction existed in cross-linked networks, which also predict and validate non-bonding interaction sites among molecular segments. The simulation results indicate higher viscosity in the GAA system should be ascribed to the formation of dispersion-strengthened cross-linked structures (AM-GO plane and GO-GO stacking segments). In summary, the microscopic viscosity-increasing mechanism of novel GAA system is proposed from the perspective of intermolecular interactions, which lays a preliminary theoretical foundation for the application of GAA material in the oil industry.

In silico degradation of fluoroquinolones by a microalgae-based constructed wetland system

Fluoroquinolone antibiotics (FQs) have been used worldwide due to their extended antimicrobial spectrum. However, the overuse of FQs leads to frequent detection in the environment and cannot be efficiently removed. Microalgae-based constructed wetland systems have been proven to be a relatively proper method to treat FQs, mainly by microalgae, plants, microorganisms, and sediments. To improve the removal efficiency of microalgae-constructed wetland, a systematic molecular design, screening, functional, and risk evaluation method was developed using three-dimensional quantitative structure–activity relationship models, molecular dynamics simulation, molecular docking, and TOPKAT approaches. Five designed ciprofloxacin alternatives with improved bactericidal effects and lower human health risks were found to be more easily degraded by microalgae (16.11–167.88 %), plants (6.72–58.86 %), microorganisms (9.10–15.02 %), and sediments (435.83 %–1763.51 %) compared with ciprofloxacin. According to the mechanism analysis, the removal effect of the FQs can be affected via changes in the number, bond energy, and molecular descriptors of favorable and unfavorable amino acids. To the best of our knowledge, this is the first comprehensive study of improving the microalgae, plants, microorganisms, and sediment removal efficiency of FQs in constructed wetlands, which provides theoretical support for the treatment of FQ pollution.