RMSD Research Articles

Which one is more accurate, BILOG or R program? (a comparison for score test equating)

Evaluation may be carried out using different tests that are not necessarily parallel. Students with lower abilities may get higher scores while those with higher abilities get lower scores. Measurement errors caused by this condition require test equating. Several computer programs, including Bilog and the R program, can be used for test equating. Each program has a different level of accuracy, and the accuracy of the equating results will affect the standard errors of equating. This study aimed to find out the most accurate equating test method and the accuracy of the estimated BILOG and R program. This research used two sets of tests with equivalent group designs. The determination of the most accurate equating method was based on the root mean square deviation (RMSD) value. Equating test packages, A to package B with BILOG program estimation on the mean and Sigma method resulted in RMSD value of 0.320. In the mean and mean method, RMSD value is 0.250. Meanwhile, equating package A to package B using R program on the mean and sigma resulted in RMSD value of 0.300, and the mean and mean method with the RMSD value is 0.272. The mean and mean yield RMSD values smaller than the mean and sigma methods. Therefore, the mean and mean method is more accurate and applicable. Moreover, the estimation results of the BILOG program are more accurate and can be used in test equating.

Investigating emodin derivatives against SARS-CoV-2 found in medicinal herbs

SARS-CoV-2 continues to mutate and circulate at alarming levels around the world and is exemplified by the emergence of the new variant JN.1. The emergence of novel SARS-CoV variants underscores the urgency for the development of new drugs. Phytochemicals, known for their safety and efficacy, have been widely used to address various ailments. This study aims at identifying the anti-SARS-CoV potential of emodin, a bioactive anthraquinone, and its derivatives. Key proteins, including hemagglutinin-esterase (HE), papain-like protease (PLpro), major protease (3CLpro), non-structural protein (nsp3) and spike protein(S) of SARS-CoV, were used as protein targets for the virtual screening of 110 emodin derivatives (ED) and remdesivir a proven antiviral drug. Among the 110 derivatives, ED21, ED25, ED5 inhibited HE, 3CLpro and S protein, respectively. ED29 inhibited both PLpro and nsp3 with high binding affinity. Similar receptor binding sites were occupied by remdesivir and emodin derivatives. These emodin derivatives are bound to similar amino acids in receptors as compared to remdesivir. Further dynamic simulations studies with ED21-HE, ED25-3CLpro, ED5-S, ED29-PLpro and ED29-nsp3 complexes showed all of them are stable with minimum root mean square deviation (RMSD), root mean square fluctuation (RMSF), solvent-accessible surface area (SASA) and radius of gyration (Rg) and are comparable to APO protein. All the ligands accepted Lipinski's rule of five. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis revealed only ED21 and ED5 as promising druglike candidates that can have high therapeutic value and no side effects. These in-silico findings contribute to the development of potent SARS-CoV-2 inhibitors, potentially advancing the quest for effective antiviral drugs.

A molecular modeling study to identify novel anticancer phytocompounds against the Tankyrase 1 protein

Tankyrase 1 is considered a promising target for various cancer treatments. The inhibition of Tankyrase 1 has long been considered as a substantial challenge for cancer therapy due to its on-target intestinal toxicity. Therefore, an effort was taken to identify novel and potent inhibitors of Tankyrase 1 target by employing various computational approaches from the natural products library. Hence, in our study, we employed integrated pharmacophore strategies, docking and binding energy of the 1574 compounds from the NPACT database against the Tankyrase 1 target. Two anti-cancerous moieties from this database have yielded better docking scores alongside their superior binding free energies than the XAV939 (reference). The root mean square deviation (RMSD) and H-bond etc. were also evaluated for both the hit molecules (Taxiresinol and 5-O-caffeoylshikimic acid) through dynamics simulation studies for 50 ns. Both the compounds depict a constant deviation in comparison with the reference compound. Altogether, our study uncovers two best hits that could be promising drug candidates against cancer.

Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Studies on Potential Phytochemicals as Sphingosine Kinase 1 Inhibitors for Cancer Therapy

Sphingosine kinases (SphKs) as lipid kinases catalyze the phosphorylation of sphingosine (Sph) to sphingosine-1-phosphate (S1P). Targeting the S1P signaling pathway is a significant strategy for many human diseases. Herein, we evaluated main prenylated bioactive components of a medicinal plant and performed a virtual screening study with flavonoid compounds and then, molecular docking and molecular dynamics (MD) simulation for the targeted cancer therapy. In silico ADMET and drug-likeness results were determined by BIOVIA Discovery Studio (DS). Molecular docking and molecular dynamics (MD) simulations were carried out by using Glide/SP and Desmond of Maestro with the filtered ligands. Glide/SP docking results showed higher binding affinity with xanthohumol (XN), 8-prenylnaringenin (8-PN), and neobavaisoflavone against SphK1. Three hits displayed strong hydrogen binding between the specific amino acid residues of targeting SphK1. There were no significant structural changes between SphK1-XN and SphK1-neobavaisoflavone complexes during 200 ns MD simulation analysis performed by GROMACS. Root-mean square deviation (RMSD) average values of XN- and neobavaisoflavone-protein complexes were compared to free SphK1 and were found as 0.2626 nm, 0.2589 nm, and 0.2508 nm, respectively. As a result, XN and 8-PN, and neobavaisoflavone have been determined as potential inhibitor candidates of SphK1 to examine for further in vitro and in vivo studies.

Molecular Docking and Dynamics of Xylocarpus granatum as A Potential Parkinson’s Drug Targeting Multiple Enzymes

Parkinson's disease is a global health challenge affecting over 10 million individuals worldwide, leading to increased disability-adjusted life years (DALYs) and a rise in mortality rates. This study explores the potential anti-Parkinson's properties of Xylocarpus granatum, focusing on its interaction with key enzymes associated with the disease: catechol-O-methyltransferase (COMT), adenosine A2A receptor (A2AR), and monoamine oxidase-B (MAO-B). Using molecular docking and molecular dynamics approaches with YASARA Structure, the ethanol extract of X. granatum was investigated for its mechanism of action. Among 30 compounds, five demonstrated promising binding affinities. Structural flexibility analysis revealed minimal fluctuations in active-site residues, highlighting the stability of key complexes involving kaempferol, epicatechin, epigallocatechin, and native ligands. Molecular Mechanics Poisson–Boltzmann Surface Area (MM-PBSA) simulations provided insights into the binding energy of these complexes. Notably, kaempferol exhibited higher binding energy than the natural ligand, suggesting superior binding affinity. Analysis of the average radius of gyration (Rg) showcased control drug-MAO-B exhibited higher Rg values, indicating a more flexible protein conformation. Confirming mode stability with root mean square deviation (RMSD) analysis shows overall stability, except in the A2AR-bound complex. The study's collective findings underscore the structural stabilization of ligand-protein complexes, contributing valuable insights into the potential anti-Parkinson's properties of X. granatum. These discoveries hold promise for developing more effective therapies for Parkinson's disease and significantly contribute to the neurology field.

The study of interaction between human serum albumin and alternaria toxins using multi-spectroscopy, molecular docking and molecular dynamic

Alternaria Toxins (ATs) is a kind of mycotoxin widely existed in fruits, vegetables and processed foods. Four ATs including alternariol monomethyl ether (AME), 3′-hydroxyalternariol monomethyl ether (3HME), altenuisol (ALI) and altenuene (ALT) isolated from Alternaria interacting with human serum albumin (HSA) were studied. The fluorescence quenching method proved that the four ATs and HSA were all statically quenched and formed stable complexes. The binding constant of each AT was calculated after experiment, which were AME: 1.26 × 1013 M−1s−1; 3HME: 2.00 × 1013 M−1s−1; ALI: 4.43 × 1012 M−1s−1 and ALT: 3.64 × 1012 M−1s−1 in 298 K, respectively. The interaction force of each AT and HSA was determined by thermodynamic calculation, which shown that the four systems all had van der Waals forces and hydrogen bonds involved in their interaction, but in AME and ALI, electrostatic action was also involved and in 3HME and ALT, hydrophobic action was also involved. It was proved that combination processes were spontaneous heat release process. 3HME and ALT were confirmed to be located at binding site I, wheras the other two were at site II. Synchronous fluorescence, three-dimensional (3D) fluorescence, UV absorption and CD spectra were used to investigate the effect of ATs interaction with HSA on the structure and function of HSA. Molecular docking provided a visual understanding and validation of the conclusions, while explaining the preliminary conclusions of the experiment. The root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg) were calculated by molecular dynamics simulation.

Validation of upper extremity kinematics using Markerless motion capture

Movement research has typically been performed using three-dimensional (3D) marker-based motion capture, which is considered the “gold-standard” for biomechanical assessment. However, limitations exist due to the lack of portability, extensive preparation for data collection, marker placement training, error due to marker movement, and possible skin irritation due to marker adhesives. There is inherent error due to motion artifact stemming from skin movement and differences in marker placement between testers. Markerless motion capture systems are emerging as a new method of kinematic assessment. These methods require little preparation and there is no need to alter participant clothing. Markerless motion capture has also been validated for the lower extremity in healthy older adults during gait. However, it has not been validated for other populations or for the assessment of upper extremity (UE) motion. Therefore, the purpose of this study was to examine differences in calculated UE kinematics between marker-based and a markerless motion capture system. Participants attended two data collection sessions. Marker-based and markerless motion capture data was collected simultaneously while participants completed the Box and Blocks test (BBT). Kinematic and spatiotemporal data from both systems was exported using identical time series to ensure the same conditions for comparisons. Intraclass Correlation Coefficients (ICCs) were calculated to determine between session reliability for both systems on range of motion and peak joint angular data to ensure movement variability was not affecting measurement consistency. ICCs and Bland Altman statistics were also calculated between the systems. Root mean square deviation (RMSD) values were determined between demeaned UE joint angles for the two systems to examine movement pattern differences. The resulting between-session ICCs for each system showed that the markerless system shared similar reliability during this task as the marker-based system, further supporting the effect of variability on between-session reliability. Between-system ICCs resulted in good (0.7<ICC<0.9) to excellent (ICC>0.9) agreement. Bland Altman results confirmed the existence of measurement bias between the systems. RMSD values for all UE joint angles were found to be less than 6°. Overall, the results from this study support the use of markerless motion capture in clinical settings to examine upper extremity biomechanics in children.

MicronuclAI: Automated quantification of micronuclei for assessment of chromosomal instability.

Chromosomal instability (CIN) is a hallmark of cancer that drives metastasis, immune evasion and treatment resistance. CIN results from chromosome mis-segregation events during anaphase, as excessive chromatin is packaged in micronuclei (MN), that can be enumerated to quantify CIN. Despite recent advancements in automation through computer vision and machine learning, the assessment of CIN remains a predominantly manual and time-consuming task, thus hampering important work in the field. Here, we present micronuclAI , a novel pipeline for automated and reliable quantification of MN of varying size, morphology and location from DNA-only stained images. In micronucleAI , single-cell crops are extracted from high-resolution microscopy images with the help of segmentation masks, which are then used to train a convolutional neural network (CNN) to output the number of MN associated with each cell. The pipeline was evaluated against manual single-cell level counts by experts and against routinely used MN ratio within the complete image. The classifier was able to achieve a weighted F1 score of 0.937 on the test dataset and the complete pipeline can achieve close to human-level performance on various datasets derived from multiple human and murine cancer cell lines. The pipeline achieved a root-mean-square deviation (RMSE) value of 0.0041, an R 2 of 0.87 and a Pearson's correlation of 0.938 on images obtained at 10X magnification. We tested the approach in otherwise isogenic cell lines in which we genetically dialed up or down CIN rates, and also on a publicly available image data set (obtained at 100X) and achieved an RMSE value of 0.0159, an R 2 of 0.90, and a Pearson's correlation of 0.951. Given the increasing interest in developing therapies for CIN-driven cancers, this method provides an important, scalable, and rapid approach to quantifying CIN on routinely obtained images. We release a GUI-implementation for easy access and utilization of the pipeline.

Network pharmacology, molecular docking, and dynamics analyses to predict the antiviral activity of ginger constituents against coronavirus infection.

COVID-19 is a global pandemic that caused a dramatic loss of human life worldwide, leading to accelerated research for antiviral drug discovery. Herbal medicine is one of the most commonly used alternative medicine for the prevention and treatment of many conditions including respiratory system diseases. In this study, a computational pipeline was employed, including network pharmacology, molecular docking simulations, and molecular dynamics simulations, to analyze the common phytochemicals of ginger rhizomes and identify candidate constituents as viral inhibitors. Furthermore, experimental assays were performed to analyze the volatile and non-volatile compounds of ginger and to assess the antiviral activity of ginger oil and hydroalcoholic extract. Network pharmacology analysis showed that ginger compounds target human genes that are involved in related cellular processes to the viral infection. Docking analysis highlighted five pungent compounds and zingiberenol as potential inhibitors for the main protease (Mpro), spike receptor-binding domain (RBD), and human angiotensin-converting enzyme 2 (ACE2). Then, (6)-gingerdiacetate was selected for molecular dynamics (MD) simulations as it exhibited the best binding interactions and free energies over the three target proteins. Trajectories analysis of the three complexes showed that RBD and ACE2 complexes with the ligand preserved similar patterns of root mean square deviation (RMSD) and radius of gyration (Rg) values to their respective native structures. Finally, experimental validation of the ginger hydroalcoholic extract confirmed the existence of (6)-gingerdiacetate and revealed the strong antiviral activity of the hydroalcoholic extract with IC of 2.727 . Our study provides insights into the potential antiviral activity of (6)-gingerdiacetate that may enhance the host immune response and block RBD binding to ACE2, thereby, inhibiting SARS-CoV-2 infection.

Theoretical simulation of TADF character of 3,9'-bicarbazole-modified 2,4,6-triphenyl-1,3,5-triazine.

Three donor (D)-acceptor (A)-type temperature-activated delayed fluorescent (TADF) molecules of 9-(2-(4,6-diphenyl-1,3,5-triazin-2-yl)phenyl)-9H-3,9'-bicarbazole (o-TrzDCz), 9-(3-(4,6-diphenyl-1,3,5-triazin-2-yl)phenyl)-9H-3,9'-bicarbazole (m-TrzDCz), and 9-(4-(4,6-diphenyl-1,3,5-triazin-2-yl)phenyl)-9H-3,9'-bicarbazole (p-TrzDCz) were designed in this paper, and the photophysical properties, including the intersystem crossing rate, the reorganization energies (λ), and the intersystem crossing/reverse intersystem crossing (ISC/RISC) rate, were simulated to explore the effect of substitution sites on their TADF character. The values of the twist angle between the D and A moieties in ground state and the molecular root-mean-square deviation (RMSD) of the S1 and T1 states referenced to the S0 state indicate that o-TrzDCz possess bigger steric hindrance and stabler molecular configuration. The λ values of the ISC/RISC process should be 0.06/0.04eV for o-TrzDCz, which are much smaller than those of m-TrzDCz (0.51/0.41eV) and p-TrzDCz (1.93/1.06eV). At the same time, o-TrzDCz possess the biggest kRISC (7.28 × 106s-1) and kr (3.12 × 106s-1) values and the smallest kp (0.10s-1) value among the three titled molecules. These data indicate that o-TrzDCz should have more excellent TADF character than m-TrzDCz and p-TrzDCz. In a word, this research presents that adjusting the molecular linking manner should be a charming way to explore novel high-efficient TADF molecules. Quantum chemical calculations were performed at PBE0/6-31G* level by Gaussian 09 and ORCA 4.1.0 software packages, and reorganization energies and Huang-Rhys were performed by the DUSHIN program and MOMAP 2019B software package based on the Gaussian 09 output files, while the phosphorescence rates were performed at B3LYP/6-31G* level by Dalton 2021.

Measurement and correlation of solubility data for sodium picosulphate in selected pure solvents and mixed-solvent systems from 298.15 K to 328.15 K

An investigation was carried out to determine the solubility of the stimulant laxative drug Sodium Picosulphate (SP). A wide range of pure solvents were studied, including methanol, ethanol, 1-propanol, 1-butanol, dimethyl formamide, dimethyl sulfoxide, acetonitrile, 1,4-dioxane, acetic acid, and water. More to the point, the solubility of the compound was determined using mixed solvent systems; methanol + acetonitrile and water + acetonitrile. Experimental mole fraction solubility of SP was determined by the gravimetric method over a range of temperatures (298.15 K to 328.15 K) under atmospheric pressure (p=0.1MPa). According to experimental results, a temperature-dependent relationship exists between solubility and temperature. Further, we correlated the experimental mole fraction solubility data with theoretical models including Apelblat, Yaws, Van't Hoff, Modified Jouyban-Acree, CNIBS/R-K models. It appears that the results are well in agreement with the experimental results due to the small values of relative average deviation (RAD) and root mean square deviation (RMSD).The solubility data might be useful in the various areas such as modification, production, crystallization, and separation of SP.

Evaluation of DFT methods for predicting geometries and NMR spectra of Bi(III) dithiocarbamate complexes with antitumor properties.

Bismuth complexes with dithiocarbamate ligands have attracted attention because of their biological applications, such as antimicrobial, antileishmanial, and anticancer properties. These complexes have high cytotoxic activity against cancer cells, being more active than the standard drugs cisplatin, doxorubicin, and tamoxifen. In the present study, we investigated the ability of some DFT methods to reproduce the geometries and NMR spectra of the Bi(III) dithiocarbamate complexes, selected based on their proven antitumor activity. Our investigation revealed that the M06-L/def2-TZVP/ECP/CPCM method presented good accuracy in predicting geometries, while the TPSSh/def2-SVP/ECP/CPCM method proved effective in analyzing the 13C NMR spectra of these molecules. In general, all examined methods exhibited comparable performance in predicting 1H NMR signals. Calculations were performed with the Gaussian 09 program using the def2-SVP and def2-TZVP basis sets, employing relativistic effective core potential (ECP) for Bi and using the CPCM solvent model. The exchange-correlation functionals BP86, PBE, OLYP, M06-L, B3LYP, B3LYP-D3, M06-2X, TPSSh, CAM-B3LYP, and ωB97XD were used in the study. Geometry optimizations were started from crystallographic structures available at the Cambridge Structural Database. The theoretical results were compared with experimental data using the mean root-mean-square deviation (RMSD), mean absolute deviations (MAD), and linear correlation coefficient (R2).

Identification of Selisistat Derivatives as SIRT1-3 Inhibitors by in Silico Virtual Screening

Sirtuins family are a Nicotinamide Adenine Dinucleotide (NAD+) dependent histone deacetylase enzyme. Sirtuins have been implicated in the pathogenesis of various diseases including cancer, neurological disorders and metabolic syndromes, hence sirtuins appointed as a promising therapeutic target for diseases, by regulating of its activity by small molecules modulators. The indole containing selisistat (EX-527) and its derivatives set as the most potent and selective SIRT1 inhibitors. Selisistat showed an effective sirtuin inhibition on various cancer cell line, and has reached the clinical trials for endometriosis and Huntington’s disease. In this study a set of selisistat derivatives were designed and virtually studied by means of molecular docking, ADMET, and molecular dynamics (MD) simulations. Two molecules were showed promising virtual binding affinity on the SIRT1-3 proteins. Compound 1 exhibits stronger in silico SIRT1 and SIRT2 affinities than EX-527, whereas compound 8 prefers SIRT3 binding. The ADMET analysis of the virtually active molecules demonstrated an acceptable drug-like profile and desirable pharmacokinetics properties. The MD simulation analysis revealed that compound 1 had significantly better alignment with SIRT1 and SIRT2 proteins than EX-527 according to Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) data, while compound 8 had a perfect alignment and fitting with SIRT3 protein than EX-527.

Time-Domain Transfer Learning for Accurate Heavy Metal Concentration Retrieval Using Remote Sensing and TrAdaBoost Algorithm: A Case Study of Daxigou, China

Traditionally, the assessment of heavy metal concentrations using remote sensing technology is sample-intensive, with expensive model development. Using a mining area case study of Daxigou, China, we propose a cross-time-domain transfer learning model to monitor heavy metal pollution using samples collected from different time domains. Specifically, spectral indices derived from Landsat 8 multispectral images, terrain, and other auxiliary data correlative to soil heavy metals were prepared. A cross time-domain sample transfer learning model proposed in the paper based on the TrAdaBoost algorithm was used for the Cu content mapping in the topsoil by selective use of soil samples acquired in 2017 and 2019. We found that the proposed model accurately estimated the concentration of Cu in the topsoil of the mining area in 2019 and performed better than the traditional TrAdaBoost algorithms. The goodness of fit (R2) of the test set increased from 0.55 to 0.66; the relative prediction deviation (RPD) increased from 1.37 to 1.76; and finally, the root-mean-square deviation (RMSE), decreased from 8.33 to 7.24 mg·kg−1. The proposed model is potentially applicable to more accurate and inexpensive monitoring of heavy metals, facilitating remediation-related efforts.

Heterologous expression and characterization of mutant cellulase from indigenous strain of Aspergillus niger.

The purpose of current research work was to investigate the effect of mutagenesis on endoglucanase B activity of indigenous strain of Aspergillus niger and its heterologous expression studies in the pET28a+ vector. The physical and chemical mutagens were employed to incorporate mutations in A. niger. For determination of mutations, mRNA was isolated followed by cDNA synthesis and cellulase gene was amplified, purified and sequenced both from native and mutant A. niger. On comparison of gene sequences, it was observed that 5 nucleotide base pairs have been replaced in the mutant cellulase. The mutant recombinant enzyme showed 4.5 times higher activity (428.5 µmol/mL/min) as compared to activity of native enzyme (94 µmol/mL/min). The mutant gene was further investigated using Phyre2 and I-Tesser tools which exhibited 71% structural homology with Endoglucanase B of Thermoascus aurantiacus. The root mean square deviation (RMSD), root mean square fluctuation (RMSF), solvent accessible surface area (SASA), radius of gyration (Rg) and hydrogen bonds analysis were carried at 35°C and 50°C to explore the integrity of structure of recombinant mutant endoglucanase B which corresponded to its optimal temperature. Hydrogen bonds analysis showed more stability of recombinant mutant endoglucanase B as compared to native enzyme. Both native and mutant endoglucanase B genes were expressed in pET 28a+ and purified with nickel affinity chromatography. Theoretical masses determined through ExPaSy Protparam were found 38.7 and 38.5 kDa for native and mutant enzymes, respectively. The optimal pH and temperature values for the mutant were 5.0 and 50°C while for native these were found 4.0 and 35°C, respectively. On reacting with carboxy methyl cellulose (CMC) as substrate, the mutant enzyme exhibited less Km (0.452 mg/mL) and more Vmax (50.25 µmol/ml/min) as compared to native having 0.534 mg/mL as Km and 38.76 µmol/ml/min as Vmax. Among metal ions, Mg2+ showed maximum inducing effect (200%) on cellulase activity at 50 mM concentration followed by Ca2+ (140%) at 100 mM concentration. Hence, expression of a recombinant mutant cellulase from A. niger significantly enhanced its cellulytic potential which could be employed for further industrial applications at pilot scale.

Direct Interaction of Minocycline to p47phox Contributes to its Attenuation of TNF-α-Mediated Neuronal PC12 Cell Death: Experimental and Simulation Validation.

Minocycline, a repurposed approved medication, shows promise in treating neurodegeneration. However, the specific pathways targeted by minocycline remain unclear despite the identification of molecular targets. This study explores minocycline's potential protective effects against TNF-α-mediated neuronal death in PC12 cells, with a focus on unraveling its interactions with key molecular targets. The study begins by exploring minocycline's protective role against TNF-α-mediated neuronal death in PC12 cells, showcasing a substantial reduction in cleaved caspase-3 expression, DNA fragmentation, and intracellular ROS levels following minocycline pretreatment. Subsequently, a comprehensive analysis utilizing pull-down assays, computational docking, mutation analysis, molecular dynamics simulations, and free energy calculations is conducted to elucidate the direct interaction between minocycline and p47phox-the organizer subunit of NADPH oxidase-2 (NOX2) complex. Computational insights, including a literature survey and analysis of key amino acid residues, reveal a potential binding site for minocycline around Trp193 and Cys196. In silico substitutions of Trp193 and Cys196 further confirm their importance in binding with minocycline. These integrated findings underscore minocycline's protective mechanisms, linking its direct interaction with p47phox to the modulation of NOX2 activity and attenuation of NOX-derived ROS generation. Minocycline demonstrates protective effects against TNF-α-induced PC12 cell death, potentially linked to its direct interaction with p47phox. This interaction leads to a reduction in NOX2 complex assembly, ultimately attenuating NOX-derived ROS generation. These findings hold significance for researchers exploring neuroprotection and the development of p47phox inhibitors.

Systemic Anti-inflammatory Activity of American Cockroach (Periplaneta americana) Extract: A Molecular Docking Study

Surgery can trigger systemic inflammatory response syndrome. This study aims to determine the effectiveness of Periplaneta americana cockroach extract as an oral systemic anti-inflammatory agent using molecular docking. The molecular docking method consisted of five steps. The first step was preparing the TNF-α converting enzyme (TACE) receptor as a native ligand, dexamethasone as a control ligand, and three test ligands of Periplaneta americana cockroach extract. The second step was docking preparation. The third step was analyzing Gibbs free energy (∆G) and root mean square deviation (RMSD). The fourth step was docking the test and control ligands with TACE. The fifth step was analyzing ∆G, inhibition constant (Ki), visualization of two- and three-dimensional interactions, percentage of binding site similarity (%BSS), and the rule of five (Ro5) on test ligands. The ∆G results for the native, control, and test ligands 1, 2, and 3 were -12.8, -7.1, -7.7, -6.9, and -9.0 kcal/mol, respectively. The Ki values for the native, control, and test ligands 1, 2, and 3 were 4.091, 6.205, 2.253, 9.521, and 2.507 µM, respectively. The results of the Ro5 analysis suggested that the three test ligands satisfied Lipinski’s rule of five. This study concluded that Periplaneta americana cockroach extract is an effective oral systemic anti-inflammatory agent.

Structural insight into the binding mode of cefotaxime and meropenem to TEM-1, SHV-1, KPC-2, and Amp-C type beta-lactamases.

Antimicrobial resistance is an emerging threat to public health around the world. The study employs computational and biophysical methods to investigate the properties of cefotaxime and meropenem's binding to various beta-lactamases like TEM-1, SHV-1, KPC-2, and Amp-C. The enzyme kinetics of purified proteins revealed an increase in Michaelis constant (Km) value in the presence of meropenem and cefotaxime, indicating a decrease in enzyme affinity for nitrocefin. Proteins interact with meropenem/cefotaxime, causing quenching through complex formation. All proteins have one binding site, and binding constant (Kb) values are 104, indicating strong interaction. The study found that meropenem and cefotaxime had high fitness scores for Amp-C, KPC-2,TEM-1 and SHV-1, with binding energy ranging from -7.4 to -7.8, and hydrogen bonds between them. Molecular Dynamic simulation of protein-ligand complexes revealed cefotaxime-binding proteins have slightly lower Root Mean Square Deviation(RMSD) than meropenem-binding proteins, indicating stable association antibiotics with these proteins.

Confluence Effect of Debris-Filled Damage and Temperature Variations on Guided-Wave Ultrasonic Testing (GWUT)

Continuous monitoring of structural health is essential for the timely detection of damage and avoidance of structural failure. Guided-wave ultrasonic testing (GWUT) assesses structural damages by correlating its sensitive features with the damage parameter of interest. However, few or no studies have been performed on the detection and influence of debris-filled damage on GWUT under environmental conditions. This paper used the pitch–catch technique of GWUT, signal cross-correlation, statistical root mean square (RMS) and root mean square deviation (RMSD) to study the combined influence of varying debris-filled damage percentages and temperatures on damage detection. Through experimental result analysis, a predictive model with an R2 of about 78% and RMSE values of about 7.5×10−5 was established. When validated, the model proved effective, with a comparable relative error of less than 10%.

UNIFAC PREDICTION OF VAPOR LIQUID EQUILIBRIA INVOLVING GAMMA-VALEROLACTONE DERIVATIVE SYSTEMS

Researchers have studied the hydrogenation of Gamma-Valerolactone (GVL) over Ru/C to produce 2-methyltetrahydrofuran (2-MTHF), a biomass-based platform chemical with potential as a biofuel and green solvent. Other byproducts of this reaction include 2-butanol (2-BuOH), 2-pentanol (2-PeOH), and 1,4-pentanediol (1,4-PDO). In this study, UNIFAC activity coefficient models were used to predict the vapor-liquid equilibrium of several systems included in the process to explain the phase behavior which is important in purification process. The accuracy of the UNIFAC model is tested by comparing the experimental boiling points for the binary system of 2-propanol + 1-butanol and the vapor-liquid equi-librium of the GVL + 2-MTHF system. From this comparison, the Root Mean Square Deviation (RMSD) values for the boiling point measurements are obtained to be 3.153%, and for the liquid and vapor phases in the vapor-liquid equilibrium measurements, the RMSD values are 1.934% and 0.298% respectively. These RMSD values indicate the level of accuracy of the UNIFAC model in representing the experimental data for both boiling point measurements and vapor-liquid equilibrium phase behavior. The prediction results of vapor-liquid equilibrium data for GVL derivative systems showed that the 2-BuOH + 2-MTHF system does form an azeotrope when the mol fraction of 2-BuOH is 0.0031 at 79.780C. The calculation was performed using ChemCAD commercial software for chemical process modeling and simulation