Dynamics Simulation Analysis Research Articles

Phytochemical Analysis and Anti‐inflammatory Potential of Floscopa Scandens Lour. and Exploring Ecdysterone as Promising Therapeutic Agent: An HR‐LCMS Screening and Molecular Docking Analysis

AbstractThis study delved into the exploration of bioactive constituent profiling of Floscopa scandens Lour. by using HRLC‐MS. The plant is well‐known as a folklore herb. It is extensively utilized in traditional medicine to address various ailments such as fractures, sore eyes, fevers, abscesses, pyoderma, and acute nephritis. This study aimed to explore the phytochemical composition of F. scandens and assess the anti‐inflammatory activity of the ecdysterone marker compound by molecular docking studies followed by MD simulations. Extracts were prepared using hexane, chloroform, and methanol solvents. Chromatographic techniques were applied to isolate compounds from the methanol extract, which underwent phytochemical screening via HR‐LCMS. Functional groups were assessed using NMR and Fourier transform infrared (FTIR), confirming the presence of bioactive compounds. HR‐LCMS analysis identified 21 phytoconstituents in the methanolic fraction, with ecdysterone being a prominent component characterized through spectroscopic techniques. Our findings confirm known molecules while unveiling new bioactive constituents, particularly highlighting the potential of ecdysterone as a novel chemical entity. Molecular docking and molecular dynamic simulation analysis further show the anti‐inflammatory properties of ecdysterone with various enzymes in the body.

Antioxidant Effect of Naringin Demonstrated Through a Bayes' Theorem Driven Multidisciplinary Approach Reveals its Prophylactic Potential as a Dietary Supplement for Ischemic Stroke.

Naringin (NAR), a flavanone glycoside, occurs widely in citrus fruits, vegetables, and alcoholic beverages. Despite evidence of the neuroprotective effects of NAR on animal models of ischemic stroke, brain cell-type-specific data about the antioxidant efficacy of NAR and possible protein targets of such beneficial effects are limited. Here, we demonstrate the brain cell type-specific prophylactic role of NAR, an FDA-listed food additive, in an in vitro oxygen-glucose deprivation (OGD) model of cerebral ischemia using MTT and DCFDA assays. Using Bayes' theorem-based predictive model, we first ranked the top-10 protein targets (ALDH2, ACAT1, CTSB, FASN, LDHA, PTGS1, CTSD, LGALS1, TARDBP, and CDK1) from a curated list of 289 NAR-interacting proteins in neurons that might be mediating its antioxidant effect in the OGD model. When preincubated with NAR for 2days, N2a and CTX-TNA2 cells could withstand up to 8h of OGD without a noticeable decrease in cell viability. This cerebroprotective effect is partly mediated by reducing intracellular ROS production in the above two brain cell types. The antioxidant effect of NAR was comparable with the equimolar (50µM) concentration of clinically used ROS-scavenger and neuroprotective edaravone. Molecular docking of NAR with the top-10 protein targets from Bayes' analysis showed the lowest binding energy for CDK1 (- 8.8kcal/M). Molecular dynamics simulation analysis showed that NAR acts by inhibiting CDK1 by stably occupying its ATP-binding cavity. Considering diet has been listed as a risk factor for stroke, NAR may be explored as a component of functional food for stroke or related neurological disorders.

Dynamic Simulation and Performance Analysis of Alkaline Water Electrolyzers for Renewable Energy-Powered Hydrogen Production

This paper presents a comprehensive study on the dynamic simulation modeling of alkaline water electrolyzers. Detailed experimental testing and characteristic analysis reveal that alkaline water electrolyzers have long startup times, rapid dynamic responses, and poor dynamic stability. These characteristics are critical for the development of accurate models and effective strategies. A dynamic simulation model was established in MATLAB R2022b and Simulink, enabling standalone simulation operation and module encapsulation. This model facilitates the construction of hydrogen production clusters and serves as a foundational tool for system strategy research. Simulations of rated current loading and unloading for four electrolyzers over 6 h showed significant differences in startup and operation. Key parameters such as cell voltage, maximum loadable power, hydrogen production efficiency, and energy consumption were analyzed. Temperature simulations indicated significant differences in thermal equilibrium points and cooling modes among the electrolyzers, as determined by structural design and cooling system efficiency. These findings highlight the need for efficiency improvements in high-current density electrolyzers. Overall, the model effectively represents commercial electrolyzer characteristics and offers a reliable tool for future research on control strategies for adapting hydrogen production systems to renewable energy power fluctuations, laying a solid foundation for the optimization of electrolyzer design and operation strategies.

Unsupervised Machine Learning in the Analysis of Nonadiabatic Molecular Dynamics Simulation.

The all-atomic full-dimensional-level simulations of nonadiabatic molecular dynamics (NAMD) in large realistic systems has received high research interest in recent years. However, such NAMD simulations normally generate an enormous amount of time-dependent high-dimensional data, leading to a significant challenge in result analyses. Based on unsupervised machine learning (ML) methods, considerable efforts were devoted to developing novel and easy-to-use analysis tools for the identification of photoinduced reaction channels and the comprehensive understanding of complicated molecular motions in NAMD simulations. Here, we tried to survey recent advances in this field, particularly to focus on how to use unsupervised ML methods to analyze the trajectory-based NAMD simulation results. Our purpose is to offer a comprehensive discussion on several essential components of this analysis protocol, including the selection of ML methods, the construction of molecular descriptors, the establishment of analytical frameworks, their advantages and limitations, and persistent challenges.

Comprehensive analysis of lignin dimer dissolution microscopic mechanism in different aromatic-based deep eutectic solvent

Aromatic-based deep eutectic solvent (DES) is a novel kind of DES that can dissolve lignin efficiently. Density functional (DFT) calculation, molecular dynamics (MD) simulation and multivariate analysis were used to investigate the interaction mechanism of five aromatic-based DES on two lignin dimer models. The effects of dissolution temperature and the type of aromatic hydrogen bond donor (HBD) on the breaking bonds between β-O-4 and 5–5 substructural units or interacting with different functional groups on lignin were investigated. With the introduction of DES, the electrostatic interaction between Cl- and lignin was obvious, while the van der Waals interaction between HBD, Ch+ and lignin was obvious. Among all the aromatic-based DES, choline chloride/p-hydroxybenzoic acid (ChCl/PB) is considered to have efficient dissolution effect. In the process of lignin dissolution, γ-OH was the preferred site for PB and Cl- acting on the lignin dimer (β-O-4), and the proportion of hydrogen bonding with γ-OH is 40 %. It was distributed around the lignin dimer (β-O-4) at 0.28–0.32 nm, and the total interaction energy was −4041.1452 kJ/mol. This study provided novel insights and theoretical basis for the preparation of renewable DES using aromatic components.

Application of Flores model considering variable recovery coefficient in dynamics analysis of ball bearings

PurposeThis paper aims to select an appropriate contact force model and apply it to the interaction model between the balls and the cage in the rolling bearings to describe the elastic–plastic collision phenomena between the two.Design/methodology/approachTaking the ball–disk collision mode as an example, several main contact force models were compared and analyzed through simulation and experiment. In addition, based on the consideration of yield strength of materials and initial collision velocity, a variable recovery coefficient model was proposed, and its validity and accuracy were verified by the ball–disk collision experiments. Then, respectively, the Flores model and the Hertz model were applied to the interaction between the balls and the cage, and the dynamics simulation results were compared.FindingsThe results indicate that the Flores model has good regression of recovery coefficient, indicating good applicability for both elastic and elastic–plastic contacts and can be applied to the contact collision situations of various materials. Under certain working conditions, there are significant differences in the dynamics results of rolling bearings simulated using the Flores model and Hertz model, respectively.Originality/valueThis paper applies the Flores model with variable recovery coefficients to the dynamics simulation analysis of ball bearings to solve the elastic–plastic collision problem between the rolling elements and the cage that cannot be reasonably handled by the Hertz model.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0138/

Novel benzothiazole/benzothiazole thiazolidine-2,4-dione derivatives as potential FOXM1 inhibitors: In silico, synthesis, and in vitro studies.

The oncogenic transcription factor FOXM1 overexpressed in breast and other solid cancers, is a key driver of tumor growth and progression through complex interactions, making it an attractive molecular target for the development of targeted therapies. Despite the availability of small-molecule inhibitors, their limited specificity, potency, and efficacy hinder clinical translation. To identify effective FOXM1 inhibitors, we synthesized novel benzothiazole derivatives (KC10-KC13) and benzothiazole hybrids with thiazolidine-2,4-dione (KC21-KC36). These compounds were evaluated for FOXM1 inhibition. Molecular docking and molecular dynamics simulation analysis revealed their binding patterns and affinities for the FOXM1-DNA binding domain. The interactions with key amino acids such as Asn283, His287, and Arg286, crucial for FOXM1 inhibition, have been determined with the synthesized compounds. Additionally, the molecular modeling study indicated that KC12, KC21, and KC30 aligned structurally and interacted similarly to the reference compound FDI-6. In vitro studies with the MDA-MB-231 breast cancer cell line demonstrated that KC12, KC21, and KC30 significantly inhibited FOXM1, showing greater potency than FDI-6, with IC50 values of 6.13, 10.77, and 12.86 µM, respectively, versus 20.79 µM for FDI-6. Our findings suggest that KC12, KC21, and KC30 exhibit strong activity as FOXM1 inhibitors and may be suitable for in vivo animal studies.

Network Pharmacology and Molecular Dynamics Simulations Reveal the Mechanism of Total Alkaloid Components in Anisodus tanguticus (Maxim.) Pascher in Treating Inflammation and Pain.

This study aimed to elucidate the mechanism that total alkaloids in Anisodus tanguticus (AT)(Maxim.) Pascher play anti-inflammatory and analgesic effects. In this paper, the anti-inflammatory effect in the total alkaloids of AT was confirmed via lipopolysaccharide (LPS)-induced inflammation model in RAW 264.7 cells and the main components of AT were immediately analyzed by UPLC/MS. Disease targets were obtained in GeneCards and DisGeNET. Targets of major compounds were searched in ETCM, TCMSP and other databases. The protein-protein interaction (PPI) network was constructed using STRING database, and Cytoscape was used for core targets screening. GO and KEGG enrichment analysis were performed using Daivid database. Sailvina was used for molecular docking. Molecular dynamics simulation analysis was performed using the Amber 20 program. The results showed that the main components in AT were anisodamine, atropine, fabiatrin, scopolamine, scopoletin and scopolin, possibly exerting anti-inflammatory and analgesic effects through pathways such as EGFR tyrosine kinase inhibitor resistance and IL-17 signaling pathway. Fabiatrin and scopolin could be potential drugs with good anti-inflammatory and analgesic effects.

Synthesis, Characterization and Assessment of Antioxidant and Melanogenic Inhibitory Properties of Edaravone Derivatives.

A series of edaravone derivatives and the corresponding Cu(II) complexes were synthesized and characterized using spectroscopic and analytical techniques such as IR, UV, NMR and elemental analysis. Antioxidant activities of all compounds were examined using free radical scavenging methods such as hydrogen peroxide scavenging activity (HPSA), 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 2-2'-azino-bis-(3-ethylbenzothiazoline-6-sulfonate) (ABTS) assays. All of the tested compounds exhibited good antioxidant activity. Further, the frontier orbital energy levels, as well as various chemical properties, were determined using the density functional theory (DFT) calculations. The MEP maps of all of the derivatives were plotted to identify the nucleophilic and electrophilic reactive sites. Further, binding energies of all of the organic compounds with the protein tyrosinase was investigated to determine their potential anti-melanogenic applications. The selected ligand, L6 was subjected to molecular dynamics simulation analysis to determine the stability of the ligand-protein complex. The MD simulation was performed (150 ns) to estimate the stability of the tyrosinase-L6 complex. Other key parameters, such as, RMSD, RMSF, Rg, hydrogen bonds, SASA and MMPBSA were also analyzed to understand the interaction of L6 with the tyrosinase protein.

Targeting Polyprotein to Design Potential Multiepitope Vaccine against Omsk Hemorrhagic Fever Virus (OHFV) by Evaluating Allergenicity, Antigenicity, and Toxicity Using Immunoinformatic Approaches.

Omsk Hemorrhagic Fever Virus (OHFV) is an RNA virus with a single-stranded, positive-sense genome. It is classified under the Flaviviridae family. The genome of this virus is 98% similar to the Alkhurma hemorrhagic fever virus (AHFV), which belongs to the same family. Cases of the virus have been reported in various regions of Saudi Arabia. Both OHFV and AHFV have similarities in pathogenic polyprotein targets. No effective and licensed vaccines are available to manage OHFV infections. Therefore, an effective and safe vaccine is required that can activate protective immunity against OHFV. The current study aimed to design a multiepitope subunit vaccine against the OHFV utilizing several immunoinformatic tools. The polyprotein of OHFV was selected and potent antigenic, non-allergenic, and nontoxic cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-lymphocyte (LBL) epitopes were chosen. After screening, eight (8) CTL, five (5) HTL, and six (6) B cell epitopes were joined with each other using different linkers. Adjuvant human beta defensin-2 was also linked to the epitopes to increase vaccine antigenic and immunogenic efficiency. The designed vaccine was docked with Toll-like receptor 4 (TLR4) as it activates and induces primary and secondary immune responses against OHFV. Codon optimization was carried out, which resulted in a CAI value of 0.99 and 53.4% GC contents. In addition, the construct was blindly docked to the TLR4 immune receptor and subjected to conformational dynamics simulation analysis to interpret the intricate affinity and comprehend the time-dependent behavior. Moreover, it was predicted that immune responses to the developed vaccine construct reported formation of strong humoral and cellular immune cells. Therefore, the proposed vaccine may be considered in experimental assays to combat OHFV infections. Laboratory experiments for the above predictions are essential in order to evaluate the effectiveness, safety, and protective properties of the subject in question.

Preparation of tenofovir amibufenamide fumarate spherical particles to improve tableting performance and sticking propensity by designing a spherical crystallization process

Tenofovir amibufenamide fumarate (TMF) is the first oral drug developed in Asia for the treatment of adult patients with chronic viral hepatitis B, however, further applications are limited by poor tableting performance and high sticking propensity. In this work, the spherulitic growth process of TMF has been designed and explored with the help of molecular dynamics simulation and process analysis technologies (ATR-FTIR, FBRM and EasyViewer). The spherical particles with high bulk density, good flowability and uniform particle size distribution are prepared by a simple quenching process. More importantly, experimental results show that spherical particles have higher average tensile strength (100.8% increase), higher plastic deformability and lower amount of punch sticking (87.4% decrease in 30 tablets) compared to the commercial powder products. These contributions not only shed light on the design principle of drug spherulitic growth processes, but also provide guidance for the manufacture of high-quality tablet products.

2D Computational Fluid Dynamics Simulation Analysis of the Assembly of Low‐Temperature Cofired Ceramics/Low‐Temperature Cofired Ceramics and Si/Si Sandwiches by Reactive Bonding

Numerical computational fluid dynamics simulations have been performed on 2D sandwich models to compare the performance of low‐temperature cofired ceramics (LTCC)/LTCC and Si/Si sandwiches used in reactive bonding. In the sandwich model layers of solder, silver and a reactive multilayer used to bond the substrates are modeled. Additional to this, the surrounding air environment is also modeled. For simulating the heat released by the multilayer system, a user‐defined function in the form of a square wave is written for the heat source with a defined width, corresponding to the reaction width, and this propagates at a fixed speed. Two sandwiches, one with LTCC/LTCC, and the other with Si/Si, are simulated and their response analyzed in terms of the solidification/melting of the solder and their respective time–temperature histories.

Hybrid Molecules Containing Methotrexate, Vitamin D, and Platinum Derivatives: Synthesis, Characterization, In VitroCytotoxicity, In Silico ADME Docking, Molecular Docking and Dynamics.

Designing hybrid-based drugs is one promising strategy for developing effective anticancer drugs that explore combination therapy to enhance treatment efficacy, overcome the development of drug resistance, and lower treatment duration. Bisphosphonates and Vitamin D are commonly administered drugs for the treatment of bone diseases and the prevention of bone metastases. Platinum-based and methotrexate are widely used anticancer drugs in clinics. However, their use is hampered by adverse side effects. Hybrid-based compounds containing either bisphosphonate, vitamin D, platinum-based or methotrexate were synthesized and characterized using FTIR, 1H-,31P, 13C-NMR, and UHPLC-HRMS which confirmed their successful synthesis. The hydroxyapatite bone binding assay revealed a promising percentage binding affinity of the bisphosphonate hybrid compounds. In vitro cytotoxicity assays on MCF-7 and HT-29 cell lines revealed a promising cytotoxic effect of hybrid 19 at 50 and 100 µg/mL on HT-29 and hybrid 15 on MCF-7 at 100 µg/mL. Molecular docking and dynamics simulation analysis revealed a binding affinity of -9.70 kcal/mol for hybrid 15 against Human 3 alpha-hydroxysteroid dehydrogenase type 3, showing its capability to inhibit Human 3 alpha-hydroxysteroid dehydrogenase type 3. The Swiss ADME, ProTox-II, GUSAR (General Unrestricted Structure-Activity Relationships), and molecular docking and dynamics studies revealed that these compounds are promising anticancer compounds.

Unveiling therapeutic biomarkers and druggable targets in ALS: An integrative microarray analysis, molecular docking, and structural dynamic studies

Amyotrophic lateral sclerosis (ALS), commonly known as Lou Gehrig's disease, is a debilitating neurodegenerative disorder characterized by the progressive degeneration of nerve cells in the brain and spinal cord. Despite extensive research, its precise etiology remains elusive, and early diagnosis is challenging due to the absence of specific tests. This study aimed to identify potential blood-based biomarkers for early ALS detection and monitoring using datasets from whole blood samples (GSE112680) and oligodendrocytes, astrocytes, and fibroblasts (GSE87385) obtained from the NCBI-GEO repository. Through bioinformatics analysis, including protein-protein interactions and molecular pathway analyses, we identified differentially expressed genes (DEGs) associated with ALS. Notably, ALS2, ADH7, ALDH8A1, ALDH3B1, ABHD2, ABHD17B, ABHD12, ABHD13, PGAM2, AURKB, ANAPC11, VAPA, UNC45B, and TNNT2 emerged as top-ranked DEGs, implicated in drug metabolism, protein depalmytilation, and the AKT/mTOR signaling pathways. Among these, AurKB established as a potential therapeutic biomarker with relevance to various neurological conditions. Consequently, AurKB was selected for identifying potential therapeutic molecules and utilized for in silico structural characterization studies. Exploration of the IMPATT database led to the discovery of a lead compound similar to Fostamatinib, currently used for AurKB. Initial molecular docking and MMGBSA-based binding energy analysis were followed by molecular dynamics simulation (MDS) and free energy landscape (FEL) analysis to validate the ligand's binding efficacy and understand dynamic processes within the biological system. The identified potential biomarkers and lead molecule provide novel insights into the correlation between blood cell transcripts and ALS pathology, paving the way for blood-based diagnostic tools for early ALS detection and ongoing disease monitoring.

Numerical simulation and theoretical analysis of pattern dynamics for the fractional-in-space Schnakenberg model

Numerical simulation and theoretical analysis of pattern dynamics for the fractional-in-space Schnakenberg model

An effective strategy to enhance phosphoric acid retention and proton conductivity stability: Construction of proton transfer channels with starch rather than H3PO4

To enhance the phosphoric acid (PA) retention as well as maintain high proton conductivity of phosphoric acid doped proton exchange membranes at high temperature, we successfully design a series of phosphoric acid doped biobased composite membranes by incorporation of starch and graphene oxide (GO) into poly arylene ether ketones (PAEK). Proton transfer channels should be mainly built through dense hydrogen bonds formed from massive oxygen-containing groups of starch mainchain, which is confirmed by Molecular dynamics (MD) simulation, FT-IR and XRD analysis. The dense hydrogen-bond structure could construct fast proton transfer channels with extreme low doping level (0.00484 molH3PO4). The excellent PA retention properties with almost unchanged proton conductivity at high temperature (200 °C) for 600 min indicates that PA molecules are firmly fixed into membranes. Thus, in this study, we suggest a novel strategy for stablizing proton conductivity at high temperature and improving PA retention properties of PA doped membranes, which is building dense hydrogen-bond structure with low PA doping level.Based on the results in this study and the Grotthuss proton transfer mechanism, dense hydrogen-bonds from oxygen-containing groups in polymer backbones should be more stable than hydrogen-bonds from massive H3PO4 molecules with high acid doping levels to promote proton conduction.

Novel chiral phthalimides: Antimicrobial evaluation and docking study against Acinetobacter baumannii's OmpA protein

Antibiotics have been a vital component in the fight against microbial diseases for over 75 years, saving countless lives. However, the global rise of multi-drug-resistance (MDR) bacterial infections is pushing us closer to a post-antibiotic era where common infections may once again become lethal. To combat MDR Acinetobacter baumannii, we investigated chiral phthalimides and used molecular docking to identify potential targets. Outer membrane protein A (OmpA) is crucial for A. baumannii resistant to antibiotics, making it a pathogen of great concern due to its high mortality rate and limited treatment options. In this study, we evaluated three distinct compounds against the OmpA protein: FIA (2-(1,3-dioxoindolin-2yl)-3-phenylpropanoic acid), FIC (2-(1,3-dioxoindolin-2yl)-4-(methylthio) butanoic acid), and FII (3-(1,3-dioxoindolin-2yl)-3-phenylpropanoic acid). Molecular docking results showed that these three compounds exhibited strong interactions with the OmpA protein. Molecular dynamics (MD) simulation analysis further confirmed the stability and binding efficacy of these compounds with OmpA. Their antimicrobial activities were assessed using the agar well diffusion method, revealing that FIA had an optimal zone of inhibition of 24 mm. Additionally, the minimum inhibitory concentrations (MIC) of these compounds were determined, demonstrating their bactericidal properties against A. baumannii, with MICs of 11 μg/μL for FIA, 46 μg/μL for FIC, and 375 μg/μL for FII. In vitro cytotoxicity data indicated that none of the three compounds were hemolytic when exposed to human red blood cells. This finding is particularly significant as it highlights the superior efficacy of FIA against A. baumannii compared to the other compounds. With thorough pharmacokinetic validations, these chiral phthalimides are promising alternative therapeutic options for treating infections caused by A. baumannii, offering new hope in the face of rising antibiotic resistance.

In-silico screening of Staphylococcus aureus antibacterial agents based on Isatin scaffold: QSAR, molecular docking, molecular dynamics simulation and DFT analysis

The design of novel antimicrobial drugs is necessary due to the increasing resistance to many existing antibiotics. Considering that the drug discovery process requires a lot of time and resources, computational chemistry and molecular docking as the basic components in the drug discovery process, can help the acceleration of this prolonged process and minimise the research costs. In this study, 64 molecules containing the Isatin scaffold were subjected to quantitative structure–activity relationship analysis to identify the necessary features for designing effective antimicrobial agents. Three chemometrics methods were employed to establish a connection between structural parameters and antibacterial effects. MLR was identified as the best model, demonstrating high accuracy compared to the other models. Based on the obtained model, ten novel lead compounds were designed, and their antibacterial potency of these compounds was assessed. The outputs of the molecular docking study revealed that compound S4 fits well in the ATP-binding site and blocks ATPase activity. Additionally, it was observed that compound S4 exhibited adequate binding affinity against the DNA gyrase target. An appropriate relationship was observed between QSAR, DFT and molecular modelling approaches. Therefore, compound S4 can be considered as a promising candidate for further development as an antibacterial agent.

Research on the aerodynamic characteristics of dragonfly leading edge.

Dragonflies are some of the most stable and maneuverable flying organisms. To explore the mechanism of how dragonfly leading edges enhance flight lift, this article conducts a detailed study on the leading edge veins and the microstructures on them of dragonfly wings. Observations have discovered the special leading edge vein and the regularly distributed microstructures on the leading edge vein. A biomimetic model has been established, and computational fluid dynamics (CFD) simulation analysis has been conducted on the biomimetic model. The analysis explores the effects of microstructure characteristics, distribution patterns, and positions on the aerodynamic characteristics of dragonfly gliding. The analysis shows that the leading edge structure influences the incoming flow, simultaneously promotes the formation of the leading edge vortex (LEV), and increases the lift-to-drag ratio by up to 4%. A wing prototype featuring biomimetic microstructures is subsequently fabricated and tested in wind tunnel experiments. Compared with a control group without leading edge structures, the airflow passing through the biomimetic structures is influenced by the shape and arrangement of these structures. The smoother transition of the leading edge vein's shape facilitates the flow of air. The microstructures primarily filter and accelerate the airflow. The spacing of the microstructures affects the stability of the airflow, thereby influencing aerodynamic performance. Additionally, the middle-row arrangement of microstructures is more beneficial for gliding conditions, while the upper-row arrangement is more advantageous for flapping conditions. These findings enhance our understanding of insect wings and advance micro aerial vehicle applications. RESEARCH HIGHLIGHTS: This study observed the leading-edge veins and microstructures of dragonfly wings in detail. Using a biomimetic model and computational fluid dynamics (CFD) simulations, it was found that these leading-edge structures promote the formation of leading-edge vortices (LEV), increasing the lift-to-drag ratio by up to 4%. Wind tunnel experiments demonstrated that wings with biomimetic microstructures significantly improved airflow smoothness and lift compared with control wings. Additionally, the arrangement of microstructures greatly affects airflow stability and aerodynamic performance, with middle-row arrangements being more beneficial for gliding and upper-row arrangements for flapping conditions. These findings enhance our understanding of insect wings and provide innovative guidance for designing efficient micro aerial vehicles.

In silico analysis reveals α-amylase inhibitory potential of Taraxerol (Coccinia indica) and Epoxywithanolide-1 (Withania coagulans): a possible way to control postprandial hyperglycemia-induced endothelial dysfunction and cardiovascular events.

Postprandial hyperglycemia (PPG) exacerbates endothelial dysfunction and impairs vascular function in diabetes as well in healthy people. Though synthetic drugs are available to regulate PPG, the severe gastrointestinal side effects of those medications have prompted the search for alternative treatments. Recently, some phytochemicals captured the attention because of their inhibitory effects on α-amylase to control diabetes. The aim of this study was to investigate and identify potential alpha-amylase inhibitors in C. indica and W. coagulans. This study also aims to understand one of the possible mechanisms of action of plants for their anti-diabetic activity. A total of 36 phytochemical ligands were subjected for protein-ligand docking analysis. Among the phytochemicals, Taraxerol and Epoxywithanolide-I demonstrated significant binding free energy of -10.2kcal/mol and -11.9kcal/mol respectively, which was higher than the reference acarbose with -8.6kcal/mol. These molecules were subjected for molecular dynamics simulation (MDS) analysis with alpha-amylase protein for a duration of 150ns. Among the three complexes, Taraxerol and Epoxywithanolide-I complexes demonstrates strong potential as inhibitors of the target protein. MDS results were analyzed via root mean square deviation (RMSD), fluctuation of residues, potential energy, radii of gyration and solvent access surface area analysis. Taraxerol demonstrated a significantly low potential energy of -1,924,605.25kJ/mol, and Epoxywithanolide-I demonstrated -1,964,113.3kJ/mol of potential energy. RMSD plot shows that Epoxywithanolide-I has much higher stability than the other MDS complexes. Drugability and toxicity studies show that the test ligands are demonstrating strong potential as drug like molecules. The results of the study conclude that, Taraxerol of C. indica and Epoxywithanolide-I of W. coagulans are strong inhibitors of alpha-amylase enzyme and that, this is one of the possible mechanisms of action of the plants for their reported anti-diabetic activities. Further in-vitro analysis is in demand to prove the observed results.