RMSD Research Articles

Numerical Analysis of Steel Frame Using Electro-Mechanical Impedance Technique

Nowadays, piezoelectric materials are most widely used in structural health monitoring (SHM) system for nondestructive evaluation. In this paper the damage study using electro-mechanical impedance (EMI) technique, which is nondestructive method of SHM. This paper presents a numerical analysis of four-story steel frame and multiple damages were induced in the steel frame by utilizing smart material like Lead Zirconate Titanate (PZT). A PZT-4 piezoelectric material was embedded in the beam of the frame. The type of damping used in steel frame model was Rayleigh damping. The numerical analysis was done in COMSOL MULTIPHYSICS 6.2 and frequency domain analysis was done, from that admittance values were find out for 30-300KHz frequency range. The real part of the admittance gives conductance values. Then, conductance verses frequency graph was created that will indicate the structural health and performance. Moreover, root mean square deviation (RMSD) index was found out for each case that provides a quantitative measure of deviation.

Computational Assessment of Clinical Drugs against SARS-CoV-2: Foreseeing Molecular Mechanisms and Potent Mpro Inhibitors.

The emergence of new SARS-CoV-2 variants of concern (VOC) is a propulsion for accelerated potential therapeutic discovery. SARS-CoV-2's main protease (Mpro), essential for host cell viral replication, is a pre-eminent druggable protein target. Here, we perform extensive drug re-profiling of the comprehensive Excelra database, which compiles various under-trial drug candidates for COVID-19 treatment. For mechanistic understanding, the most promising screened-out molecules with targets are subjected to molecular dynamics (MD) simulations. Post-MD analyses demonstrate Darunavir, Ponatinib, and Tomivosertib forming a stable complex with Mpro, characterized by less fluctuation of Cα atoms, smooth and stable root-mean-square deviation (RMSD), and robust contact with the active site residues. Likewise, they all have lower binding free energy with Mpro, demonstrating strong affinity. In free energy landscape profiles, the distances from His41 and Cys145 exhibit a single energy minima basin, implying their preponderance in proximity to Mpro's catalytic dyad. Overall, the computational assessment earmarks promising candidates from the Excelra database, emphasizing on carrying out exhaustive biochemical experiments along with clinical trials. The work lays the foundation for potential therapeutic interventions in treating COVID-19.

Can satellite products monitor solar brightening in Europe?

Satellite products provide the best way to monitor the solar radiation reaching the Earth’s surface on a global scale. However, their capability to monitor solar radiation trends needs to be constantly evaluated. This depends on their temporal stability and the accurate representation of all processes driving solar radiation. This study evaluates these aspects by comparing and cross-comparing different solar radiation products (ERA5, CAMS-RAD 4.6, SARAH-3, CLARA-A3, CERES-EBAF 4.2) against in-situ measurements over Europe.All products show a moderate positive bias over Europe but strong differences in their root mean squared deviation (RMSD) related to their different cloud transmittance models. Geostationary-based products (SARAH-3, CAMS-RAD 4.6) provide the smallest RMSD closely followed by CLARA-A3, whereas ERA5 shows a large RMSD due to random errors in cloud transmittance.All products show an increase in surface solar radiation, or brightening, over the last 40 years over Europe, but the magnitude of the trends and their spatiotemporal variability differ between products. Despite finding temporal inhomogeneities in some products, the different trends are mostly due to different aerosol modeling approaches implemented by each product. Both SARAH-3 (+2.3 W/m2/decade, 2001–22) and CERES-EBAF 4.2 (+2.2 W/m2/decade, 2001–22) provide the most consistent trends compared to in-situ data, showing that after stabilizing in the late 2000s, brightening is particularly recovering in Western Europe. In-situ measurements show a reduction of aerosol optical depth from 2001 to 2022 that has been accentuated in the last 10 years, particularly in Western Europe. This would be consistent with the hypothesis that brightening recovery is driven by an aerosol reduction, though other analyses suggest that clouds also play a role in this recovery. More work is needed to understand the contribution of aerosols to solar radiation trends and the exact aerosol effects represented by each solar radiation product.

Modeling and economic analysis of block absorber (RadFrac) performance with stage variations for post-combustion CO2 capture

This study presents a comprehensive modeling and economic evaluation of a Monoethanolamine (MEA)-based post-combustion carbon capture (PCC) absorber unit. The simulation provides detailed insights into the absorber's internal profiles, including temperature gradients and the percentage of CO2 captured, with a particular focus on the effects of varying the number of stages and absorber diameters. Validation against experimental data demonstrated close alignment between simulated and observed values, with an average Root Mean Square Deviation (RMSD) of 0.018 and 4.0129, respectively, confirming the reliability of the simulation in capturing the complex dynamics of the absorber.The economic analysis, conducted using the Aspen Process Economic Analyzer (APEA), simplified the complex relationship between absorber segmentation, capital and operational costs, and absorber diameter. The study revealed that increasing the absorber diameter and the number of stages leads to a significant rise in Total Capital Cost (TCC), Total Operating Cost (TOC), Equipment Cost, and Total Installed Cost (TIC), with the highest costs observed at a stage number of 90 and a diameter of 1.0 m. However, the analysis identified an optimal configuration at an absorber diameter of 0.45 m with either 10 or 20 stages. This setup effectively balances cost and CO2 capture efficiency, offering a more economical solution compared to configurations with larger diameters and higher stage numbers, which substantially increase expenses. The findings highlight the critical trade-offs between operational efficiency and capital expenditure, stressing on the crucial role of absorber diameter in determining the economic feasibility of the absorber block in PCC systems.

Visualising the strength development of FICP-treated sand using impedance spectroscopy

Fungal Induced Calcium Carbonate Precipitation (FICP) is a novel method used in geotechnical engineering that enhances the engineering properties of sand by using the potential of fungal activity. This research is the first attempt to monitor the strength of FICP treated sand using embedded Piezoelectric (PZT) patch based Electromechanical Impedance (EMI) spectroscopy. In the past, the strength of such treated sand has been determined through the destructive methods like Unconfined Compressive Strength (UCS) test. In this study, the sand is mixed with the filamentous fungus Aspergillus Niger and the cementation solution (urea and \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:{\ ext{C}\ ext{a}\ ext{C}\ ext{l}}_{2}$$\\end{document} in the ratio of 1:1) is injected after every 24 h. Results recorded from the cost-effective EVAL AD5933 chip indicate that the shifting of frequency impedance signals in each phase is in good alignment with UCS and calcium carbonate content (CCC). Following the 28-day treatment period, the treated sand achieves a maximum UCS of 3.93 MPa, accompanied by a CCC of 15.19%. In order to correlate EMI signals with treatment cycles, UCS, and CCC, various multi linear regression (MLR) equations for statistical metrics like root mean square deviation (RMSD), mean absolute percentage deviation (MAPD), and correlation coefficient deviation (CCD) are developed. Additionally, Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray (EDX) analyses have been conducted to observe the success of the FICP process in the sand.

The Effects of Different Restoration Materials on the Trueness of Intraoral Scanners

Aim: This study aimed to assess how different restoration materials affect the trueness of intraoral scanners. Materials and Methods: Artificial teeth on a typodont model were prepared for crowns and fixed partial dentures (FPDs) using full metal, monolithic zirconia, and porcelain-fused-to-metal (PFM) materials. Each group underwent 10 scans with a Trios intraoral scanner, generating 60 STL files. A reference scanner created a master model using scanning spray to reduce reflection errors. The STL files were aligned with reverse engineering software for comparison and were analyzed in micrometers (μm) using Root Mean Square (RMS) and Mean Distance measurements. The Levene test and two-way ANOVA with Post Hoc analysis were used for statistical evaluation. Results: The RMS deviations for the FPDs were 77.9 ± 15.2 μm (full metal), 84.6 ± 6.9 μm (monolithic zirconia), and 130 ± 19.7 μm (PFM). For the crowns, the RMS values were 76.9 ± 6.5 μm (metal), 71 ± 8.2 μm (monolithic zirconia), and 153 ± 22.4 μm (PFM). The mean distance deviations for the FPDs were 11.4 ± 4.8 μm (metal), 11.2 ± 3.4 μm (monolithic zirconia), and 18.3 ± 2.6 μm (PFM). For the crowns, the mean distances were 8.6 ± 3.4 μm (metal), 10.2 ± 3 μm (monolithic zirconia), and 24.7 ± 3.3 μm (PFM). Significant differences were noted in the PFM groups. Conclusion: Restoration materials notably affected intraoral scanner trueness, especially PFM restorations. The restoration length did not significantly affect the accuracy.

Computational exploration of novel ketoprofen derivatives: Molecular dynamics simulations and MM-PBSA calculations for COX-2 inhibition as promising anti-inflammatory drugs

Computer-aided drug design is widely employed to identify novel compounds for therapeutic applications. Ketoprofen (KTP), a commonly used and marketed nonsteroidal anti-inflammatory drug (NSAID), is effective in treating pain, fever, inflammation, and some cancers. In this research, we explored the behavior of six analogues designed by structurally modifying the KTP molecule. Specifically, KTP-A and KTP-B contain a –CN group at the ortho position, KTP-C and KTP-D have a –CN group at the meta position, and KTP-E and KTP-F feature a –CF3 group at the meta position. To assess these analogues, we conducted molecular dynamics simulations (MD) to study their inhibitory effects on human cyclooxygenase 2 (COX-2), providing detailed insights into the structure and dynamics of the protein both with and without ligands. MD simulation, enhanced by technological advances, has proven to be a powerful tool for new drug discovery. We further quantified the binding affinity of these drug molecules toward COX-2 using molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) binding free energy calculations. The dynamic properties were evaluated through analyses of root mean square deviations (RMSD), root mean square fluctuations (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA), covariance matrix, principal component analysis (PCA), and Gibbs free energy landscapes (FEL). Ultimately, this study confirms that the six KTP derivatives are promising candidates for the treatment of inflammation, with KTP-B standing out as particularly effective.

Discovery of 5-(Substituted Phenyl)-2-aryl Benzimidazole Derivatives as SIRT1 Activators: Their Design, in silico Studies, Synthesis, and in vitro Evaluation.

Silent information regulator two homologue one (SIRT1) is an emerging target for managing metabolic disorders. This study aimed to synthesize novel 5-(- substituted phenyl)-2-aryl benzimidazole derivatives and evaluate them for SIRT1 activation. The compounds were designed according to the findings of the QSAR models framed in our previous studies. Molecular docking and dynamics studies were also performed to explore the interactions of designed compounds with the active site of the SIRT1 enzyme using AutoDock Vina and Schrödinger Maestro version 11.8.012, respectively. Compounds with good binding affinity were synthesized by Suzuki-Miyaura cross-coupling and spectrally characterized. The molecules were evaluated for their in vitro SIRT1 activation properties using a fluorescent screening kit. Based on the results of in vitro assay, a structure-activity relationship was established. SwissADME was employed to calculate the pharmacokinetics characteristics of the synthesized molecules. The molecular docking studies revealed that all the activators were effectively docked in the catalytic active site. All compounds demonstrated interactions with important amino acids like Glu230 and Arg446. In molecular dynamics simulations, the root mean square deviation (RMSD) of compound 5m and protein SIRT1 remained stable, i.e., below 3mm. Compound 5m, 4-(2-(3,4-dihydroxy-5-nitrophenyl)-1H-benzo[d]imidazol- 5-yl)benzaldehyde, was the most potent compound with an EC50 value of 0.006 mM (±0.001) and maximum activation of 240.5%. All the synthesized compounds had acceptable theoretical ADME profiles, and drug-likeness properties complied with Lipinski's rule. According to the findings, synthesized compounds may be viable leads for SIRT1 activators and may be used to advance preclinical in vivo research utilizing animal models.

Evaluation of tamoxifen analogues as potential estrogen receptor alpha inhibitors for breast cancer treatment: A computational approach

Estrogen receptors, particularly ERα, play a key role in breast cancer progression, making them prime targets for therapeutic intervention. Tamoxifen (TAM), a selective estrogen receptor modulator (SERM), has been widely used for the treatment of ER+ breast cancer; however, its clinical application is limited by side effects and the emergence of resistance. This study aims to identify and evaluate TAM analogues with improved efficacy and reduced side effects by employing molecular docking and molecular dynamics (MD) simulations. Droloxifene, endoxifen, and afimoxifene emerged as promising candidates, exhibiting strong binding affinities with ERα, as indicated by highly negative binding energy (BE) values in docking simulations. MD simulations further validated the stability of the complexes formed between these analogues and ERα, with low root mean square deviation (RMSD) values and stable radius of gyration (Rg) profiles. Root mean square fluctuation (RMSF) analysis revealed balanced flexibility, with droloxifene and afimoxifene showing optimized flexibility for stable binding. Hydrogen bond analysis indicated more stable interactions between these analogues and ERα compared to TAM, suggesting enhanced binding affinity. MM/GBSA binding free energy analysis confirmed the high affinity of these analogues, with droloxifene displaying the most effective binding free energy (ΔGtotal) value. ADMET profiling suggests that droloxifene and endoxifen have superior pharmacokinetic properties relative to TAM. Overall, droloxifene, endoxifen, and afimoxifene represent promising alternatives to TAM, with the potential for further clinical development in breast cancer treatment. Experimental validation in cell-based and in vivo models will be crucial in future studies to confirm their efficacy and safety profiles.

Solvent screening for the purification of monoterpenoids by countercurrent and centrifugal partition chromatography

AbstractBACKGROUNDCountercurrent chromatography (CCC) and centrifugal partition chromatography (CPC) are efficient techniques to purify terpenoids from essential oils. These methods require suitable solvent systems for the partition between the two immiscible liquid phases. In this study, using the analytical shake‐flask method, we measured the partition coefficients of three model monoterpenoids, namely carvone, eucalyptol and thymol, in 11 biphasic solvent systems, at 298.2 K. Moreover, the predictive COSMO‐RS model was applied to represent the partition coefficients of data measured in this work and retrieved from the literature, the liquid–liquid equilibrium (LLE) data of three solvent families suitable for CCC/CPC separations (i.e., Arizona, Modified Arizona and Green Arizona) and the solute's partition coefficients in the three solvent families.RESULTSThe partition coefficients obtained for thymol and eucalyptol are the first partition data available in the literature. The obtained root mean square deviations (RMSDs) between the experimental and predicted partition coefficients (log basis) varied between 0.28 and 0.49. For LLE, RMSDs of 0.040 and 0.048 were achieved for the Arizona and Green Arizona families, respectively.CONCLUSIONThe predictive COSMO‐RS model describes the monoterpenoid partition coefficients and the LLE data of the solvent families well. The most favorable solvent systems to perform the separations were identified, showing that systems with low and intermediate‐to‐low polarities are the most promising options for separating the selected monoterpenoids from their natural matrices by CCC/CPC techniques. © 2024 Society of Chemical Industry (SCI).

Evaluation of the impact of cardiac implantable electronic devices on cine MRI for real-time adaptive cardiac radioablation on a 1.5 T MR-linac.

Stereotactic arrhythmia radioablation (STAR) is a novel treatment approach for refractory ventricular tachycardia (VT). The risk of treatment-induced toxicity and geographic miss can be reduced with online MRI-guidance on an MR-linac. However, most VT patients carry cardiac implantable electronic devices (CIED), which compromise MRimages. Robust MR-linac imaging sequences are required for cardiac visualization and accurate motion monitoring in presence of a CIED during MRI-guided STAR. We optimized two clinically available cine sequences for cardiorespiratory motion estimation in presence of a CIED on a 1.5 T MR-linac. The image quality, motion estimation accuracy, and geometric fidelity using these cine sequences wereevaluated. Clinically available 2D balanced steady-state free precession (bSSFP, voxel size = 3.0 3.0 10 mm3, Tscan = 96 ms, bandwidth (BW) = 1884 Hz/px) and -spoiled gradient echo ( -GRE, voxel size = 4.0 4.0 10 mm3, Tscan = 97 ms, BW = 500 Hz/px) sequences were adjusted for real-time cardiac visualization and cardiorespiratory motion estimation on a 1.5 T Unity MR-linac (Elekta AB, Stockholm, Sweden), while complying with safety guidelines for MRI in presence of CIEDs (specific absorption rate 2 W/kg and 80 mT/s). Cine acquisitions were performed in five healthy volunteers, with and without an implantable cardioverter- defibrillator (ICD) placed on the clavicle, and a VT patient. Generalized divergence-curl (GDC) deformable image registration (DIR) was used for automated landmark motion estimation in the left ventricle (LV). Gaussian processes (GP), a machine-learning technique, was trained using GDC landmarks and deployed for real-time cardiorespiratory motion prediction. -mapping was performed to assess geometric image fidelity in the presence ofCIEDs. CIEDs introduced banding artifacts partially obscuring cardiac structures in bSSFP acquisitions. In contrast, the -GRE was more robust to CIED-induced artifacts at the expense of a lower signal-to-noise ratio. In presence of an ICD, image-based cardiorespiratory motion estimation was possible for 85% (100%) of the volunteers using the bSSFP ( -GRE) sequence. The in-plane 2D root-mean-squared deviation (RMSD) range between GDC-derived landmarks and manual annotations using the bSSFP (T1-GRE) sequence was 3.1-3.3 (3.3-4.1) mm without ICD and 4.6-4.6 (3.2-3.3) mm with ICD. Without ICD, the RMSD between the GP-predictions and GDC-derived landmarks ranged between 0.9 and 2.2 mm (1.3-3.0 mm) for the bSSFP (T1-GRE) sequence. With ICD, the RMSD between the GP-predictions and GDC-derived landmarks ranged between 1.3 and 2.2 mm (1.2-3.2 mm) using the bSSFP (T1-GRE) sequence resulting in an RMSD-increase of 42%-143% (bSSFP) and -61%-142% (T1-GRE). Lead-induced spatial distortions ranged between -0.2 and 0.2 mm (-0.7-1.2 mm) using the bSSFP ( -GRE) sequence. The 98th percentile range of the spatial distortions in the gross target volume of the patient was between 0.0 and 0.4 mm (0.0-1.8 mm) when using bSSFP ( -GRE). Tailored bSSFP and -GRE sequences can facilitate real-time cardiorespiratory estimation using GP trained with GDC-derived landmarks in the majority of landmark locations in the LV despite the presence of CIEDs. The need for high temporal resolution noticeably reduced achievable spatial resolution of the cine MRIs. However, the effect of the CIED-induced artifacts is device, patient and sequence dependent and requires specific assessment percase.

Screening of FDA-approved Drugs against Protein Thymidine Kinase 2 Using Machine Learning Method Validated Applying Molecular Dynamics and Free Energy Landscape Calculation

Background: Thymidine kinase 2 (TK2) is a crucial enzyme in the mitochondrial pyrimidine salvage pathway, strongly associated with several mitochondrial diseases. Current treatments frequently damage mitochondria, leading to a decrease in cellular energy output. Objective: This study aimed to use computational approaches to identify inhibitors of TK2 that could prevent these harmful consequences. Method: The initial screening process entailed the application of machine learning algorithms, more particularly a Random Forest model, which was trained on 189 FDA-approved drugs and decoy datasets obtained from the DUD-E database. Its purpose was to identify potential inhibitors. The molecular docking technique was employed to evaluate the affinity of the chosen medicines towards TK2. Molecular dynamics (MD) simulations lasting 100 nanoseconds were employed to conduct additional validation by examining the dynamic interactions between the top-found compounds and TK2. Results: Three hit compounds (3168, 5209502, and 135402009) were identified through the screening process for their high affinity for TK2. Compound 5209502 had the most stable interaction with the lowest root-mean-square deviation (RMSD) in the molecular dynamics (MD) simulations and maintained 12 hydrogen bonds consistently. MM/GBSA computations verified that 5209502 exhibited the strongest binding affinity with a binding free energy of -62.14 kcal/mol, which was notably lower than that of the control ligand. Conclusion: Compound 5209502 is a promising candidate for additional experimental evaluation because of its notable stability and great affinity for TK2. This chemical may provide a focused and less harmful treatment for mitochondrial illnesses linked to TK2 malfunction.

Continuous Process Verification 4.0 application in upstream: adaptiveness implementation managed by AI in the hypoxic bioprocess of the Pichia pastoris cell factory.

The experimental approach developed in this research demonstrated how the cloud, the Internet of Things (IoT), edge computing, and Artificial Intelligence (AI), considered key technologies in Industry 4.0, provide the expected horizon for adaptive vision in Continued Process Verification (CPV), the final stage of Process Validation (PV). Pichia pastoris producing Candida rugosa lipase 1 under the regulation of the constitutive GAP promoter was selected as an experimental bioprocess. The bioprocess worked under hypoxic conditions in carbon-limited fed-batch cultures through a physiological control based on the respiratory quotient (RQ). In this novel bioprocess, a digital twin (DT) was built and successfully tested. The implementation of online sensors worked as a bridge between the microorganism and AI models, to provide predictions from the edge and the cloud. AI models emulated the metabolism of Pichia based on critical process parameters and actionable factors to achieve the expected quality attributes. This innovative AI-aided Adaptive-Proportional Control strategy (AI-APC) improved the reproducibility comparing to a Manual-Heuristic Control strategy (MHC), showing better performance than the Boolean-Logic-Controller (BLC) tested. The accuracy, indicated by the Mean Relative Error (MRE), was for the AI-APC lower than 4%, better than the obtained for MHC (10%) and BLC (5%). Moreover, in terms of precision, the same trend was observed when comparing the Root Mean Square Deviation (RMSD) values, becoming lower as the complexity of the controller increases. The successful automatic real time control of the bioprocess orchestrated by AI models proved the 4.0 capabilities brought by the adaptive concept and its validity in biopharmaceutical upstream operations.

Exploring novel antitubercular agents: Innovative design of 2,3-diaryl-quinoxalines targeting DprE1 for effective tuberculosis treatment

Abstract The rising instances of drug resistance in Mycobacterium tuberculosis strains pose a significant global health challenge. Conventional tuberculosis (TB) treatments, which typically involve multiple antibiotics, face hurdles like drug resistance, reduced effectiveness, and heightened toxicity. Consequently, there is a pressing need for innovative anti-TB agents with new modes of action. Decaprenyl-phosphoryl-β-d-ribose 2′-epimerase 1(DprE1), a crucial enzyme in Mycobacterium tuberculosis, plays a vital role in cell wall biosynthesis – a critical aspect for the bacterium’s survival. Building on the success of diarylquinolines like bedaquiline, targeting DprE1 presents a promising avenue for developing anti-TB drugs, especially against drug-resistant strains. Our research focused on discovering novel DprE1 inhibitors using a ligand-based drug design strategy, starting with the established non-covalent inhibitor Ty38c. We assembled a library of 16 molecules, modifying them based on factors like drug-like properties, chemical accessibility, and synthetic feasibility. Molecular docking analyses of this library identified three molecules with binding affinities comparable to Ty38c. Among these, KS_QD_05 and KS_QD_04 are promising candidates, which were further validated through molecular dynamics simulation studies where root-mean-square deviation (RMSD) values of all three complexes reached a plateau, measuring around 0.3 nm, indicating that the apoprotein and all complexes stabilized during the simulation. The ligands KS_QD_04 and KS_QD_05 displayed significantly stable deviation. KS_QD_05 reached about 0.1 nm equilibrium value. However, the ligand KS_QD_04 reached an RMSD value of 0.17 nm and showed distress at 70 nm. KS_QD_04 and KS_QD_05 showed an average value of 1-3 H-bond interaction and regarding the RMSF values, both the compounds showed fluctuations less than 0.5 nm in the case of Mtb. DprE1 enzyme. This indicates the potential of both compounds to become lead compounds in the pursuit of DprE1 inhibitors for TB treatment.

Phytobioinformatics screening of ayurvedic plants for potential α-glucosidase inhibitors in diabetes management

The enzyme α-glucosidase in the small intestine regulates blood glucose levels and stimulates the hydrolysis of oligosaccharides and polysaccharides, increasing glucose levels in the body. Inhibiting this enzyme slows glucose digestion and absorption and as a result post-prandial blood glucose levels remain low, causing decreased insulin demand. Here, we investigated the ayurvedic antidiabetic plants and virtually screened an in-house library of 478 phytochemicals of these plants against the human α-glucosidase. We identified 11 secondary metabolites, including palmitic acid α-monoglyceride, (+)-(2 R)-6-propionyloxyethyl-4′,5,7-trihydroxyisoflavanone, Abruquinone E, and Aurantiamide Acetate, among others, showed stronger interactions with the receptor than the native ligand N-acetyl cysteine. Surprisingly, except one, all of these metabolites were from Abrus precatorius L. [Fabaceae] affirming its ethnopharmacological use against diabetes. The stability of the interactions between the ligands and receptor protein was evaluated through Molecular Dynamic (MD) simulation trajectories including root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), H bonds, β-factor analysis, and binding energy calculation through MM/GBSA method. The efficacy of top metabolites in inhibiting α-glucosidase is depicted in pharmacophore analysis. A comprehensive pharmacokinetics analysis confirmed the druggability, safety, and efficiency of top drug candidates. Additionally, we predicted the interactions of these top metabolites within the biological system. The medicinal properties described in this study will help develop active drug candidates for therapeutic purposes. Further experiments are recommended to prove the effectiveness of these metabolites in inhibiting the α-glucosidase enzyme for exploring their potential in the treatment of diabetes.

Structural insights into conformational stability of both wild-type and mutant Insulin Receptor Gene

Type 2 diabetes (T2D) poses a health challenge. It can lead to complications such as heart disease, hypertension, heart failure, and stroke. Factors like obesity and lack of activity can contribute to insulin resistance. The insulin receptor gene (INSR) is responsible for producing insulin receptors. When this gene malfunctions, it can contribute to the development of T2D.In this study, we investigated the stability of the structure of variants of INSR using an extended molecular dynamics simulation and the perturbation effect of compound CheBI_88339 on the protein structure. During the analysis, we observed that all three systems—the wild-type INSR, the R1191Q variant, and the R1191Q variant bound to compound CheBI_88339 (R1191Q-D) reached equilibrium in 30ns without any instability. Throughout the simulation process, it was generally observed that the wild-type INSR exhibited higher stability than the R1191Q variant and R1191Q-D. The Root Mean Square Deviation (RMSD) and root-mean-square fluctuation (RMSF) of INSR, R1191Q and the variant bound to compound CheBI_88339 (R1191Q-D) are 9.28Å, 10.35Å, 8.65Å, 2.59Å, 2.98Å, and 2.89Å respectively.These values indicate that the mutated INSR introduced levels of deviations and flexibility in the protein structure. However, considering the variant bound to compound CheBI_88339 suggests that this drug may contribute to stabilizing the dynamics of the mutant protein. Overall, our findings shed light on the effect of genetic variants and their impact on protein stability. This research provides further insight into the dynamics of INSR and the potential of CheBI_88339 in targeting INSR. However, this study is computational, and further experimental studies are required.

Comprehensive analysis of peripheral dose in electron beam therapy with a Varian TrueBeam Linac

ObjectiveTo investigate the characteristics of peripheral doses outside electron-beam applicators in Varian TrueBeam linacs. MethodPeripheral doses outside the electron applicator were measured for 6-, 9- and 12-MeV beams at the maximum dose depth (Dmax) for each energy source and at a source-to-surface distance of 100 cm. Measurements were performed using EBT3 films in solid water phantoms. The impact of field size on the penumbra width and peripheral doses was studied using various cutouts, including 3 cm × 3 cm, 6 cm × 6 cm, and 10 cm × 10 cm in a 10 cm × 10 cm applicator with the gantry and collimator at 0°. The influence of the applicator size was investigated using a circular cutout of 5 cm in diameter for various applicator sizes, including 6 cm × 6 cm, 10 cm × 10 cm, 15 cm × 15 cm, 20 × 20 cm, and 25 cm × 25 cm, at Dmax for each energy, while keeping the gantry and collimator angle at 0°. The measured dose profiles were compared with the Eclipse treatment planning system (TPS) predicted dose profiles. The effect of varying gantry angles (0°, 90°, and 270°) for a 3 cm × 3 cm cutout in a 10 cm × 10 cm applicator for each energy source and varying collimator angles (0°, 90°, and 270°) for a 10 cm × 10 cm field were investigated to determine their effects on the penumbra widths and peripheral doses. ResultsBoth the penumbra width and peripheral dose values increased with energy across different field sizes, gantry angles, collimator angles, and applicator sizes. Root Mean Square Deviation (RMSD) analysis indicated minimal differences between the measured profiles and TPS data. Peripheral doses remained below 5% of the maximum dose approximately 10–15 mm away from the field edges, suggesting the potential for implementing additional shielding where required. ConclusionsThis study highlights the importance of considering peripheral doses in electron radiotherapy. It is important to note the impact on healthy tissues beyond the treatment area to ensure patient safety and prevent the long-term side effects of treatment. These findings emphasize the necessity of implementing appropriate measures to minimize peripheral doses.

Molecular Dynamics Simulation Insights into Hydrogen Bonding‐Mediated Conformational Changes Topoisomerase‐IB

AbstractTopoisomerase‐IB changes the topological state of DNA during central dogma by the formation of intermediate bond in between active amino acid and DNA strand. How the hydrogen bonding provides hooks restriction during the topological change and gives the conformational change. This study employs a 200 ns Molecular Dynamics (MD) simulation to analyze the conformational changes of Topo‐IB resulting from artificially created intermediate bonds. Specifically, the study focuses on hydrogen bonding interactions between Tyrosine at position Y509 in the protein and Thymine at DT561 in the DNA. The investigation reveals that these artificial intermediate bonds act as temporary hooks, stabilizing the complex's structure, and driving significant conformational changes. The analysis of Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) values underscores the dynamic nature of the complex, with artificial intermediate bonds playing a pivotal role.

Molecular docking, dynamic simulation, and ADME/T analysis of Natural Compounds as potential therapeutic candidate against Hepatitis E virus

Hepatitis E virus (HEV) is a single-stranded RNA virus, capable of infecting both humans and animals. This investigation targets ORF2 of the HEV, as it plays an essential role in forming the viral capsid. Inhibiting the capsid protein could prevent the virus from completing its life cycle and infecting new cells, making ORF2 an ideal target for new drug development, and the primary objective of this investigation is to identify the potential therapeutic candidate against HEV.The molecular docking analysis was conducted against the Hepatitis E virus ORF2 and out of the initially chosen 25 chemicals, eight demonstrated better binding affinities, particularly with Quercetin and Pinostrobin, which exhibited the most favorable binding energies. After that, theoretical ADMET analysis was analyzed to ensure the pharmacokinetics and safety profile of these therapeutic candidate. The stability of the maximum binding affinity containing compounds with the target protein was confirmed through molecular dynamics simulations over 100 ns timeframe including analyzed Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), Dynamic Cross-Correlation Matrix (DCCM), and Principal Component Analysis (PCA).The finding of this investigation is highlighted as strong antiviral properties against the HEV, supported by in silico analysis, suggesting the urgent need for cost-effective and time-efficient strategies to discover potential therapeutic candidate against HEV. Further, laboratory experiments together with pre-clinical and clinical research are suggested to be carried out.

Identification of steroidal cardenolides from Calotropis procera as novel HIV-1 PR inhibitors: A molecular docking & molecular dynamics simulation study.

Background & objectives Despite advancements in antiretroviral therapy, drug-resistant strains of HIV (human immunodeficiency virus) remain a global health concern. Natural compounds from medicinal plants offer a promising avenue for developing new HIV-1 PR (protease) inhibitors. This study aimed to explore the potential of compounds derived from Calotropis procera, a medicinal plant, as inhibitors of HIV-1 PR. Methods This in silico study utilized natural compound information and the crystal structure of HIV-1 PR. Molecular docking of 17 steroidal cardenolides from Calotropis procera against HIV-1 PR was performed using AutoDock 4.2 to identify compounds with higher antiviral potential. A dynamic simulation study was performed to provide insights into the stability, binding dynamics, and potential efficacy of the top potential antiviral compound as an HIV-1 therapeutic. Results We found that all tested cardenolides had higher binding affinities than Amprenavir, indicating their potential as potent HIV-1 PR inhibitors. Voruscharin and uscharidin displayed the strongest interactions, forming hydrogen bonds and hydrophobic interactions with HIV-1 PR. Voruscharin showed improved stability with lower RMSD (Root Mean Square Deviation) values and reduced fluctuations in binding site residues but increased flexibility in certain regions. The radius of gyration analysis confirmed a stable binding pose between HIV-1 PR and Voruscharin. Interpretation & conclusions These findings suggest that Calotropis procera could potentially be a source of compounds for developing novel HIV-1 PR inhibitors, contributing to the efforts to combat HIV. Further studies and clinical trials are needed to evaluate the safety and efficacy of these compounds as potential drug candidates for the treatment of HIV-1 infection.