RMSD Research Articles

Investigating the Inhibitory Effects of Paliperidone on RAGEs: Docking, DFT, MD Simulations, MMPBSA, MTT, Apoptosis, and Immunoblotting Studies

Chronic diseases such as diabetes and cancer are the leading causes of mortality worldwide. Receptors for Advanced Glycation End products (RAGEs) are ubiquitous factors that catalyse Advanced Glycation End products (AGEs), proteins, and lipids that become glycated from sugar ingestion. RAGEs are cell surface receptor proteins and play a broad role in mediating the effects of AGEs on cells, contributing to modifying biological macromolecules like proteins and lipids, which can cause Reactive Oxygen Species (ROS) generation, inflammation, and cancer. We targeted RAGE inhibition analysis and screening of United States Food and Drug Administration (FDA) libraries through molecular docking studies that identified the four most suitable FDA compounds: Zytiga, Paliperidone, Targretin, and Irinotecan. We compared them with the control substrate, Carboxymethyllysine, which showed good binding interaction through hydrogen bonding, hydrophobic interactions, and π-stacking at active site residues of the target protein. Following a 100 ns simulation run, the docked complex revealed that the Root Mean Square Deviation (RMSD) values of two drugs, Irinotecan (1.3 ± 0.2 nm) and Paliperidone (1.2 ± 0.3 nm), were relatively stable. Subsequently, the Molecular Mechanics Poisson–Boltzmann Surface Area (MMPBSA) determined that the Paliperidone molecule had a high negative energy of −13.49 kcal/mol, and the Absorption, Distribution, Metabolism, and Excretion (ADME) properties were in control for use in the mentioned cases. We extended this with many in vitro studies, including an immunoblotting assay, which revealed that RAGEs with High Mobility Group Box 1 (HMGB1) showed higher expression, while RAGEs with Paliperidone showed lower expressions. Furthermore, cell proliferation assay and Apoptosis assay (Annexin-V/PI staining) results revealed that Paliperidone was an effective anti-glycation and anti-apoptotic drug—however, more extensive in vivo studies are needed before its use.

SIMECK-T: An Ultra-Lightweight Encryption Scheme for Resource-Constrained Devices

The Internet of Things produces vast amounts of data that require specialized algorithms in order to secure them. Lightweight cryptography requires ciphers designed to work on resource-constrained devices like sensors and smart things. A new encryption scheme is introduced based on a blend of the best-performing algorithms, SIMECK and TEA. A selection of software-oriented Addition–Rotation–XOR (ARX) block ciphers are augmented with a dynamic substitution security layer. The performance is compared against other lightweight approaches. The US National Institute of Standards and Technology (NIST) SP800-22 Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications and the German AIS.31 of the Federal Office for Information Security (BSI) are used to validate the output of the proposed encryption scheme. The law of iterated logarithm (LIL) for randomness is verified in all three forms. The total variance (TV), the Hellinger Distance (HD), and the root-mean-square deviation (RMSD) show values smaller than the required limit for 10.000 sequences of ciphertext. The performance evaluation is analyzed on a Raspberry PICO 2040. Several security metrics are compared against other ciphers, like χ2 and encryption quality (EQ). The results show that SIMECK-T is a powerful and fast, software-oriented, lightweight cryptography solution.

Network Pharmacology Reveals Cis-4-Benzyl-2,6-diphenyltetrahydropyran's Impact on Neurotransmitter Signaling, GPCR Modulation, and Cellular Pathways Associated with Diabetes Mellitus

Aims: To investigate the pharmacological implications of the ligand cis-4-Benzyl-2,6- diphenyltetrahydropyran, focusing on its pathways, potential disease associations, and therapeutic applications in Type 2 Diabetes Mellitus (T2DM). Background: Cis-4-Benzyl-2,6-diphenyltetrahydropyran has been previously identified for its heightened binding affinity to T2DM targets. Understanding its diverse pathways and interactions with neurotransmitter signaling, neuronal receptors, and enzymes/metabolism can provide insights into its potential roles in disease modulation and therapeutic applications. Objectives: The primary objective of this study was to investigate the pharmacological effects of cis-4- Benzyl-2,6-diphenyltetrahydropyran in the context of Type 2 Diabetes Mellitus (T2DM). The study sought to understand its influence on neurotransmitter signaling, focusing on its modulation of G Protein-Coupled Receptors (GPCRs) and their role in diabetes pathogenesis. Utilizing KEGG pathway and gene ontology analyses, the study aimed to explore the ligand's involvement in neuroactive ligand-receptor interactions and the calcium signaling pathway, examining its broader impact on biological functions like inflammation, immune response, reproductive processes, and cellular metabolism associated with diabetes. Method: The study employed KEGG pathway and gene ontology analyses to profile cis-4-Benzyl-2,6- diphenyltetrahydropyran. The ligand's influence on neurotransmitter signaling, neuronal receptors, enzymes, and metabolic pathways was examined. Enrichment analysis was conducted to identify associated genes and pathways, focusing on the ligand's role in Neuroactive ligand-receptor interaction and the Calcium signaling pathway. Molecular docking and molecular dynamic simulations were performed to assess the ligand's interaction with the OPRK1 receptor, a G protein-coupled receptor implicated in metabolic regulation. Binding stability was analyzed using Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), Radius of Gyration (Rg), and Solvent Accessible Surface Area (SASA). MMPBSA binding free energy analysis was conducted to validate the stability and strength of the ligand-receptor interaction. Result: The study revealed that cis-4-Benzyl-2,6-diphenyltetrahydropyran significantly impacts neurotransmitter signaling and cellular homeostasis by modulating GPCR pathways, including neuroactive ligand-receptor interaction and calcium signaling pathways. These pathways play critical roles in inflammation, immune response, reproductive processes, and cellular metabolism. Molecular docking and dynamic simulations demonstrated a strong and stable binding between the ligand and the OPRK1 receptor, a key GPCR implicated in metabolic regulation. The binding was supported by favorable binding free energy values (-255.58 kJ/mol) and consistent structural stability metrics, including minimal deviations in RMSD (0.2–0.4 nm) and stable radius of gyration (2.35–2.45 nm). Solvent Accessible Surface Area (SASA) analysis confirmed a compact ligand-receptor interaction, while hydrogen bonding reinforced binding specificity. These findings highlight the ligand's relevance in diabetes pathogenesis, particularly in regulating pathways involved in insulin sensitivity and glucose metabolism. Conclusion: This study advances our understanding of the cellular effects of cis-4-Benzyl-2,6- diphenyltetrahydropyran, highlighting its multifaceted potential in diabetes research. The strong interaction with OPRK1 suggests that the ligand could influence key pathways related to insulin sensitivity and metabolic regulation. However, the findings are derived from computational methodologies, and experimental validation through in vitro and in vivo studies is essential to confirm the ligand's biological activity and therapeutic relevance. The findings establish a foundation for targeted investigations and drug development, positioning this ligand as a promising candidate for therapeutic applications in diabetes mellitus.

Acetohydroxyacid Synthase (AHAS) inhibitors as Antitubercular agents: Insights from Molecular Docking and Dynamics Simulations.

Acetohydroxyacid synthase (AHAS) is a vital enzyme in Mycobacterium tuberculosis, the pathogen causing tuberculosis (TB), involved in branched-chain amino acid synthesis. Targeting AHAS for drug design against TB offers a promising strategy due to its essentiality in bacterial growth. In current investigation, we have designed 160 novel compounds by leveraging key scaffolds identified through structure-based drug design (SBDD) methodologies. Subsequently, these compounds underwent molecular docking analysis to elucidate their potential interactions with the AHAS protein. The top four compounds resulting from the docking studies were subjected to rigorous molecular dynamics simulations, spanning a runtime of 100 nanoseconds, to assess their stability across various parameters including Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), Secondary Structure Elements (SSE), Radius of Gyration (Rg), Solvent Accessible Surface Area (SASA), and MM-GBSA free energy values. Remarkably, compounds KG 98 and KG 131 exhibited superior stability profiles across all analyzed parameters. From the detailed interactions analysis, it was found that the nitrogen containg heterocyclic rings (1,3,5-triazine/imidizole) are essential to have the potential binding interactions with the AHAS enzyme. The findings suggest these lead molecules as promising candidates for AHAS inhibition, a potential avenue for tuberculosis treatment and management.

Ononin's Antagonistic Activity towards TRPV1: Insights from Molecular Dynamics and Capsaicin-Evoked Calcium Response in DRG Neurons.

The search for effective painkillers has led to intensive research, with a particular focus on the transient receptor potential vanilloid-1 (TRPV1) channel as a possible target. One promising candidate is ononin, which is investigated for its binding with TRPV1 through a 200-ns molecular dynamic simulation and analysed via root-meansquare deviation (RMSD), root-mean-square fluctuation (RMSF), hydrogen-bond interactions, radius of gyration (RadGyr), and MM-PBSA energy calculations. The results were further validated experimentally via calcium imaging studies. Molecular dynamics revealed that the ononin-TRPV1 complex achieved stable binding within a remarkably short time of approximately 38 ns while maintaining the degree of compactness of the receptor throughout a 200 ns simulation period. In contrast, the capsazepine-TRPV1 complex displayed more significant structural deviations during the whole simulation. Moreover, MM-PBSA energy calculations showed a relatively strong binding affinity between ononin and TRPV1, mainly attributed to favourable hydrophobic interactions. Pre-incubation of dorsal root ganglia (DRG) neurons with ononin (1 and 10 μM) or capsazepine (10 μM) for 4 min prior to stimulation with capsaicin significantly reduced capsaicin-evoked calcium responses. No significant difference between capsazepine and ononin was found at a concentration of 10 μM. Overall, this research demonstrates the potential of ononin as a potential antagonist for developing analgesics targeting TRPV1. Hence, and to our best knowledge, this study represents the first report of ononin's antagonistic activity towards TRPV1.

Boosting the catalytic efficiency of UGT51 for efficient production of rare ginsenoside Rh2.

Ginsenoside Rh2(S) is well-known for its therapeutic potential against diverse conditions, including some cancers, inflammation, and diabetes. The enzymatic activity of uridine diphosphate glycosyltransferase 51 (UGT51) from Saccharomyces cerevisiae plays a pivotal role in the glycosylation process between UDP-glucose (donor) and protopanaxadiol (acceptor), to form ginsenoside Rh2. However, the catalytic efficiency of the UGT51 has remained a challenging task. To this end, we employed site-directed mutagenesis on UGT51 to improve its catalytic efficiency for enhanced production of ginsenoside Rh2. The mutated structure, featuring four key mutations (E805A, S998A, R1031A, and L1032A), exhibited heightened stability, binding affinity, and active site accessibility for protopanaxadiol (PPD) compared to the wild type. Under in vitro conditions, three mutants (E805A, R1031A, and L1032A) demonstrated 10%, 58%, and 65% higher enzymatic activities compared to the wild strain. Notably, the double mutant R1031A/L1032A exhibited an 85% increase in activity. Employing a fed-batch technology with PPD as the substrate yielded a Rh2 production of 4.663g/L. The molecular dynamics (MD) simulations were employed to investigate the movements and dynamic dynamics of UGT51 mutations and PPD complexes. The root mean square deviation (RMSD) analysis revealed substantial alterations in structural conformation, particularly in the R1031A/L1032A mutations, correlating with boosted catalytic efficiency. Furthermore, the root mean square fluctuation (RMSF) simulation study aligned with both the RMSD and the solvent-accessible surface area (SASA) analyses. The computationally guided site-directed mutagenesis approach holds promise for extending its application to the development of commercially significant enzymes.

Forecasting Model for Danube River Water Temperature Using Artificial Neural Networks

The objective of this paper is to propose an artificial neural network (ANN) model to forecast the Danube River temperature at Chiciu–Călărași, Romania, bordered by Romanian and Bulgarian ecological sites, and situated upstream of the Cernavoda nuclear power plant. Given the temperature increase trend, the potential of thermal pollution is rising, impacting aquatic and terrestrial ecosystems. The available data covered a period of eight years, between 2008 and 2015. Using as input data actual air and water temperatures, and discharge, as well as air temperature data provided by weather forecasts, the ANN model predicts the Danube water temperature one week in advance with a root mean square deviation (RMSE) of 0.954 °C for training and 0.803 °C for testing. The ANN uses the Levenberg–Marquardt feedforward backpropagation algorithm. This feature is useful for the irrigation systems and for the power plants in the area that use river water for different purposes. The results are encouraging for developing similar studies in other locations and extending the ANN model to include more parameters that can have a significant influence on water temperature.

Near-Field Clutter Mitigation in Speckle Tracking Echocardiography.

Near-field (NF) clutter filters are critical for unveiling true myocardial structure and dynamics. Randomized singular value decomposition (rSVD) stands out for its proven computational efficiency and robustness. This study investigates the effect of rSVD-based NF clutter filtering on myocardial motion estimation. In silico, material points and their displacements in a homogeneous medium under uniaxial compressions (0.5% - 9% axial strains at 0.5% increments) were simulated in finite-element models. They were exported to the k-Wave toolbox for simulations of pre- and post-deformed ultrasound images with/ without a realistic phase aberrating layer in a high-contrast diverging wave compounding scheme. In vivo, echocardiograms of 20 normal human hearts were acquired using a coded diverging wave compounding imaging method at 3200 frames/second in the transthoracic apical four-chamber view. Morphological component analysis (MCA), which is also a sparse representation method but computationally intensive, was used for comparison with rSVD. Both rSVD- and MCA-based filters were applied to beamformed ultrasound radio-frequency (RF) data before cross-correlation-based speckle tracking. Contrast-to-noise ratios (CNRs) and root-mean-square deviations (RMSDs) were computed from regions of interest to evaluate NF clutter filtering performance of rSVD and MCA. In silico, 2-D displacements estimated from rSVD-based clutter-reduced image data showed strong agreement with ground truth (R2 of 0.95). In vivo, CNR improvements ranged from 1.02 dB to 17.68 dB, consistently enhancing image quality across all subjects. An improvement of ∼4.9 dB in the apical segments was observed in 80% of cases. Mean RMSDs were below 5.0% for all rSVD-based NF clutter-reduced data. While both rSVD and MCA effectively filtered NF clutter, rSVD was significantly more practical. Our findings confirm the reliability, accuracy, and efficiency of rSVD-based clutter filtering in speckle tracking echocardiography. This underscores the feasibility of matrix decomposition-based methods, exemplified by rSVD, in NF clutter filtering for myocardial motion estimation.

AlphaFold 3 sheds insights into chemical enhancer-induced structural changes in Cas12a RNPs

BackgroundThe CRISPR/Cas12a system has revolutionized nucleic acid detection through trigger-activated nonspecific trans-cleavage activity. Enhancing this activity is vital for improving the sensitivity of CRISPR/Cas biosensing systems. Although various chemical enhancers have been shown to affect Cas12a ribonucleoprotein (RNP), the underlying mechanisms remain poorly understood. Investigating how these enhancers alter the structure of Cas12a RNPs is essential for elucidating the enhancement mechanisms involved.ResultsThis study focuses on elucidating the structural changes in Cas12a RNPs induced by various chemical enhancers via AlphaFold 3, an emerging and powerful tool for analyzing structural changes in protein‒nucleic acid complexes. We validated the ability of AlphaFold 3 to simulate structural changes in Cas12a RNPs activated by triggers and subsequently analyzed the effects of specific enhancers, such as reducing agents (e.g., Dithiothreitol, namely DTT), divalent cations (e.g., Mg2+, Mn2+), and bovine serum albumin (BSA). Our findings revealed that DTT, simulated with a cysteine-to-serine Cas12a mutant, caused significant structural changes in Cas12a RNP, as evidenced by notable shifts in the distance between key residues (Val377 to Gln1136) and a high root mean square deviation (RMSD)(RMSD > 2). Conversely, divalent cations and BSA did not cause substantial structural changes, resulting in only minor shifts in residue distance and a low RMSD (RMSD < 2).ConclusionsThese results demonstrate that DTT enhances Cas12a activity by inducing significant structural rearrangements, whereas divalent cations and BSA-induced enhancements do not involve substantial structural modifications.Graphical Summary of structural changes from inactivated Cas12a RNP to activated Cas12a RNP and from activated Cas12a RNP to activated Cas12a RNP with an enhancer. The units of both the RMSD and distance are Å.

Development of a TSR-based method for understanding structural relationships of cofactors and local environments in photosystem I

BackgroundAll chemical forms of energy and oxygen on Earth are generated via photosynthesis where light energy is converted into redox energy by two photosystems (PS I and PS II). There is an increasing number of PS I 3D structures deposited in the Protein Data Bank (PDB). The Triangular Spatial Relationship (TSR)-based algorithm converts 3D structures into integers (TSR keys). A comprehensive study was conducted, by taking advantage of the PS I 3D structures and the TSR-based algorithm, to answer three questions: (i) Are electron cofactors including P700, A-1 and A0, which are chemically identical chlorophylls, structurally different? (ii) There are two electron transfer chains (A and B branches) in PS I. Are the cofactors on both branches structurally different? (iii) Are the amino acids in cofactor binding sites structurally different from those not in cofactor binding sites?ResultsThe key contributions and important findings include: (i) a novel TSR-based method for representing 3D structures of pigments as well as for quantifying pigment structures was developed; (ii) the results revealed that the redox cofactor, P700, are structurally conserved and different from other redox factors. Similar situations were also observed for both A-1 and A0; (iii) the results demonstrated structural differences between A and B branches for the redox cofactors P700, A-1, A0 and A1 as well as their cofactor binding sites; (iv) the tryptophan residues close to A0 and A1 are structurally conserved; (v) The TSR-based method outperforms the Root Mean Square Deviation (RMSD) and the Ultrafast Shape Recognition (USR) methods.ConclusionsThe structural analyses of redox cofactors and their binding sites provide a foundation for understanding the unique chemical and physical properties of each redox cofactor in PS I, which are essential for modulating the rate and direction of energy and electron transfers.

Cordycepin and Its Structural Derivatives Effectively Suppress the High Expression of Epidermal Growth Factor Receptor (EGFR) Tyrosine Kinase in Breast Carcinomas: A Computational Drug Development Approach.

Breast cancer is a frequently diagnosed malignant disease and the primary cause of mortality among women with cancer worldwide. The therapy options are influenced by the molecular subtype due to the intricate nature of the condition, which consists of various subtypes. By focusing on the activation of receptors, Epidermal Growth Factor Receptor (EGFR) tyrosine kinase can be utilized as an effective drug target for therapeutic purposes of breast cancer. The objective of this study is to compare the underlying pharmacological properties of several modified agents to the parental Cordycepin to target and inhibit the EGFR tyrosine kinase high expression, and to discover the inhibitor with the highest affinity for this drug target to treat the breast cancer patients. The Maestro Application of Schrödinger Suite Paid Software was initially employed for conducting extra precision (XP) structure-based virtual screening to evaluate the binding affinity of the Cordycepin and its 500 structural derivatives with the EGFR tyrosine kinase protein structure. In addition, the anti-breast cancer activity of the chosen compounds was assessed by looking at their drug-likeness and ADMET characteristics using Lipinski's rule of five along with Quantitative structure- activity relationship (QSAR) validation, the prediction of cell line anti-cancer, as well as anti- breast cancer activity of top docked scored compounds. Subsequently, the Desmond paid software- based molecular dynamics simulations (MDS) were conducted for a duration of 100 nanoseconds on the promising candidates followed by the binding free energy estimation was performed utilizing MM-GBSA analysis. To determine the stability of the protein-ligand complex, root-meansquare deviation (RMSD), root-mean-square fluctuation (RMSF), protein-ligand interactions, and other necessary parameters were evaluated from the 100 ns MDS Trajectory. Based on the overall analysis of our study, N (6)-octylamine adenosine (CID-194932) reported the optimum inhibitory potential against the EGFR tyrosine kinase protein, followed by Adenosine 5-monophosphate (CID-83862) and Cordycepin (CID-6303), which compared favorably to the control drug Vandetanib (CID-3081361). Consequently, these derivative compounds Cordycepin have the potential to be utilized as lead molecules in the development of highly effective and potent EGFR tyrosine kinase inhibitors for the treatment of breast cancer patients.

Integrating machine learning and structure-based approaches for repurposing potent tyrosine protein kinase Src inhibitors to treat inflammatory disorders

Tyrosine-protein kinase Src plays a key role in cell proliferation and growth under favorable conditions, but its overexpression and genetic mutations can lead to the progression of various inflammatory diseases. Due to the specificity and selectivity problems of previously discovered inhibitors like dasatinib and bosutinib, we employed an integrated machine learning and structure-based drug repurposing strategy to find novel, targeted, and non-toxic Src kinase inhibitors. Different machine learning models including random forest (RF), k-nearest neighbors (K-NN), decision tree, and support vector machine (SVM), were trained using already available bioactivity data of Src kinase targeting compounds. The performance evaluation of these models demonstrated SVM as the best model, which was further utilized to shortlist 51 highly potent compounds by screening an FDA-approved library of 1040 drugs. Molecular docking and molecular dynamic simulation were subsequently employed to evaluate the binding affinity and stability of the proposed compounds. Orlistat, acarbose and afatinib were identified as the potent leads, demonstrating stable conformations and stronger interactions, validated by root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (RoG), and hydrogen bond analyses. Molecular Mechanics/Generalized Born Surface Area (MMGBSA) analysis validated their binding affinities by providing comparably lower binding free energies for orlistat (− 33.4743 ± 3.8908), acarbose (− 19.5455 ± 5.4702), and afatinib (− 36.4944 ± 5.4929) than the control, dasatinib (− 13.7785 ± 5.8058). Finally, toxicity analysis revealed orlistat and acarbose as the possible safer therapeutics by eliminating afatinib as it showed significant toxicity concerns. Our investigation supports the advance computational methods utilization in the field of drug discovery and suggest further experimental validation of proposed inhibitors of Src kinase for their safer use against inflammatory diseases. The ultimate aim of this study is to advance the development of effective treatments for inflammatory diseases, linked with Src overexpression.

Separation Process for Methanol–Methylal–Methyl Formate Multicomponent System in Polyformaldehyde Production Waste Liquid: Modeling and Techno-Economic Analysis

The vapor–liquid equilibrium (VLE) data of the ternary system methanol–methyl formate–methylal was measured at atmospheric pressure using a modified Rose equilibrium kettle with vapor–liquid double circulation method. The experiment data were correlated with the NRTL, UNIQUAC, and Wilson activity coefficient model equations. The results shown that the root mean square deviation (RMSD) between the calculated and simulated values of the three models followed the order: UNIQUAC ≈ NRTL &lt; Wilson, and except for the RMSD (T) in the range of 0.4–0.5, the others are less than 0.01. In addition, the NRTL model was selected to link with Aspen Plus software to simulate the separation process of polyformaldehyde (POM) waste liquid. The simulation results show that the methyl formate in POM waste stream can be purified by simple distillation, while the methylal separated from the POM waste liquid, which was affected by factors like the azeotropic behavior of binary components, necessitates a complex distillation process. Under optimal operating conditions, the recovery yield of methyl formate through direct distillation can reach 99.7%, with an economic benefit of 6960.1 CNY per ton of waste liquid. Although the economic benefit of the multi-component distillation reach 7281.2 CNY, the increase in the number of equipment and the complexity of the process have negative impacts.

Advancing siRNA Therapeutics targeting MCT-4: A Multifaceted approach integrating Arithmetical Designing, Screening, and molecular dynamics validation.

Monocarboxylate transporter 4 (MCT-4) is involved in various metabolic processes which are crucial in maintaining cellular pH and energy metabolism, and thus influence the tumor microenvironment. The study is aimed to rationally design effective Small interfering RNA (siRNA) that can silence MCT-4. We utilized a comprehensive workflow integrating multiple tools such as siDirect version 2.0, Oligowalk and i-score designer, to evaluate sequence features and predict target site accessibility, Guanine-Cytosine (GC) content and thermodynamic stability. Five (M1, M2, M3, M4 and M5) siRNAs sequences were retrived and subjected to further scrutiny on the account of off-target elimation, sequence conservation, secondary structure formation, and thermodynamic properties. The M1 demonstrated off targets and the M2 sequence showed secondry conformation and therefore M3, M4 and M5 were considered for further evaluation. Additionally, molecular docking and simulations (50ns) were conducted with human Argonaute 2 protein (h-Arg-2). The post- molecular dynamics (MD) analysis revealed M4 (5'UUGAAGAAGACACUGACGG3') as a most appropriate siRNA candidate agsint MCT-4 on the basis of Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), and H-Bond results. The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) analysis was also performed to further validate the selected siRNA candidates, which further affirmed M4 (5'UUGAAGAAGACACUGACGG3') as an potential candidate for future in-vitro and in-vivo evaluation.

Computational Analysis of CC2D1A Missense Mutations: Insight into Protein Structure and Interaction Dynamics.

CC2D1A is implicated in a range of conditions, including autism spectrum disorder, intellectual disability, seizures, autosomal recessive nonsyndromic intellectual disability, heterotaxy, and ciliary dysfunction. In order to understand the molecular mechanisms underlying these conditions, we focused on the structural and dynamic activity consequences of mutations within this gene. In this study, whole exome sequencing identified the c.1552G > A (GLU518LYS) missense mutation in the CC2D1A in an 18-year-old male, linking it to intellectual disability and autism. In addition to the GLU518LYS mutation, we conducted a comprehensive analysis of other predefined missense mutations (i.e., PRO192LEU, GLN506ARG, PRO532LEU, GLY781VAL, and GLY781GLU) found within the CC2D1A. Utilizing all-atom molecular dynamics (MD) simulations and neighborhood interaction analyses, we delve into the impact of these mutations on protein structure and function at an atomic level, aiming to shed light on their contribution to the pathogenesis of related diseases. The results suggest that GLU518LYS, GLY781VAL, and GLY781GLU mutations did not significantly alter overall global protein structure compared to the wild type, while PRO192LEU, GLN506ARG, and PRO532LEU exhibited slightly higher protein root-mean-square deviation (RMSD) values, which may indicate potential impacts on whole protein stability. Moreover, neighborhood interaction analysis indicated that ASP85 emerges as a unique interaction partner specifically associated with the GLU518LYS mutation, whereas LYS75, which interacts with the ASP85 in the mutated form, is absent in the wild type. This alteration signifies a crucial reconfiguration in the local interaction network at the site of the mutation.

VIRTUAL SCREENING OF THE ZIMBABWE NATURAL PRODUCT DATABASE FOR GLUCOKINASE ACTIVATORS

Objective: This study aimed to identify potential glucokinase activators within Zimbabwean natural products using virtual screening techniques. Methods: Twenty-one compounds filtered from ChEMBL ID 3820 (pEC50 ≥ 8) were used to generate a pharmacophore model, validated with DUD-E data. The model screened the 6220 compounds in the Zimbabwe Natural Products Database (ZiNaPoD) using LigandScout. Hit compounds were docked with glucokinase (protein ID 4NO7) using AutoDock Vina and AutoDock 4 in PyRx, followed by adsorption, distribution, metabolism, and excretion (ADME) screening by SwissADME. Molecular dynamics simulations were conducted on the resulting complexes using the CHARMM36m force field on GROMACS. Results: The validated pharmacophore model (80% accuracy, 95% sensitivity, 80% specificity) produced 149 hits, 16 of which had binding energies ≤ −8 kcal/mol after the two rounds of molecular docking. The ADME analysis narrowed the selection to four compounds, with binding energies ranging from −8.35 to −9.82 kcal/mol. All four demonstrated stability in molecular dynamic simulations, with average root mean square deviation (RMSD) values ranging from 1.491 to 3.835 Å. The Sphenostylisin I and Dihydroxymethyl dihydroxybenzyl chromanone (DMDBC) complexes exhibited the highest stability with average RMSD values of 1.491±2.794 Å and 2.875±1.452 Å, respectively. They also exhibited low-binding free energies of −30.30±0.38 and −30.20±0.49 kcal/mol, making them promising targets. Conclusion: Four potential glucokinase activators were identified, with Sphenostylisin I and DMDBC showing promise as candidates for developing new diabetes treatments due to their stability, favorable binding, and absence of liver-toxic groups.

Novel D-Ribofuranosyl Tetrazoles: Synthesis, Characterization, In Vitro Antimicrobial Activity, and Computational Studies.

The goal of this study was to synthesize and evaluate new antimicrobial compounds. We specifically focused on the development of 2,5-disubstituted tetrazole derivatives containing the O-methyl-2,3-O-isopropylidene-(D)-ribofuranoside groups through N-alkylation reactions. The synthesized compounds were characterized using 1H and 13C nuclear magnetic resonance (NMR) spectroscopy. Their antibacterial activity was tested against Pseudomonas aeruginosa, Escherichia coli, Streptococcus fasciens, and Staphylococcus aureus. Density functional theory (DFT) was applied to examine the electronic properties, including the highest occupied molecular orbital (HOMO)-least unoccupied molecular orbital (LUMO) gap, hardness, softness, density of states (DOS), and molecular electrostatic potential. Additionally, crystal structure modeling of protein 7AZ5 was performed to study the binding affinities through hydrophobic interactions and hydrogen bonding. Molecular dynamics simulations were carried out for 100 ns and OPLS_2005 force field re performed to investigate the stability of 3c and 5c into 7AZ5 binding site. Root-mean-square deviation (RMSD), root mean square fluctuation (RMSF), and intermolecular interactions analysis showed that these two compounds may gave relative stability into the 7AZ5 binding site. Several of the N-ribofuranosyl tetrazole derivatives synthesized displayed a strong antibacterial activity. Compounds 1c and 5c were particularly effective, with a minimum inhibitory concentration (MIC) of 15.06 μM and 13.37 μM, respectively, against E. coli and S. aureus both surpassing the efficacy of chloramphenicol (19.34 μM) and ampicillin (28.62 μM). These compounds also displayed the highest binding energies in protein modeling, indicating strong interactions with the DNA polymerase sliding clamp of E. coli. Compounds 1c and 5c show promise as potent antibacterial agents with notable chemical stability and favorable binding profiles. These findings suggest that these derivatives may serve as valuable leads for the development of new antimicrobial drugs.

Innovative engineering of superoxide dismutase for enhanced cardioprotective biocatalysis in myocardial ischemia-reperfusion injury

The present research compares the stability, catalytic activity, and cardioprotective benefits of the designed superoxide dismutase (SOD) variation SOD-M3 to those of the naturally occurring enzyme, along with additional alternatives. SOD-M3 exhibited a 51.5 % increase in expression yield, reaching 50 mg/L, compared to the wild-type's 33 mg/L. In structural biology, the average distance between atoms of stacked proteins or molecules is measured by RMSD. Testing the precision of protein-ligand docking models is a typical application. The projected structure closely resembles the reference or native structure when the RMSD is low. The enzyme's durability improved significantly, resulting in negligible aggregation in the Size Exclusion Chromatography (SEC) and root mean square deviation (RMSD) of 2.1 Å. SOD-M3 catalytically increased superoxide radical scavenging capability by 40 % and inhibited nitroblue tetrazolium (NBT) reduction by 90 % at 1 μg/mL concentration. The material exhibited increased stability, as seen by its decomposition temperature (Tm) of about 80 °C, as opposed to 65 °C in the wild-type strains. In cardiomyocyte protection experiments, SOD-M3 reduced lactate dehydrogenase (LDH) production by 55 % while decreasing reactive oxygen species (ROS) concentrations by 60 %. Since a 51.5 % increase in expression yield for SOD-M3 indicates improved production efficiency, which makes large-scale manufacturing more viable for clinical applications, it is therapeutically essential. Higher expression yields mean more cost-effective manufacture for enzyme-based therapy research and commercialization. In vivo, SOD-M3 decreased myocardial infarction diameter by 44 % while improving cardiac function, including increased ejection percentage and fractional contraction. The histopathological investigation revealed undamaged heart tissue and less necrotic areas. The results reported here demonstrate SOD-M3's superior activity of enzymes, cardioprotective perspective, and stability, making it a promising therapeutic alternative for illnesses related to cellular oxidation & ischemic cardiac diseases. An increase in enzyme concentrations can enhance the obtaining of reactive oxygen species (ROS), which build up during ischaemia episodes; therefore, this increase is essential. Improving the enzyme's solubility and stability by site-directed modifications makes SOD-M3 more stable and effective in physiological circumstances where its activity is crucial for therapeutic efficacy maximization. A further benefit of increased expression yield is that it can lower manufacturing costs, which will help get SOD-M3 into clinical settings. These modifications raise SOD-M3's cardioprotective potential, making it a strong contender for novel therapies against cardiac ischemia-reperfusion impacts.

Probing Pregnane‐3,20‐Dione, 17,21‐[(Methylborylene)Bis(Oxy)]‐, (5. Beta)‐ as an Antiviral Candidate Against White Spot Syndrome Virus (WSSV): Molecular Docking and Simulation Approach

White spot syndrome virus (WSSV) is a highly infectious virus that poses an imminent threat to global shrimp aquaculture and is responsible for significant mortality in shrimp farms. There is a lack of targeted drug therapy options for preventing or treating WSSV. Consequently, these envelope proteins have garnered attention as an alternative focus for drug development at the molecular level. In the current study, the binding efficiency of pregnane‐3,20‐dione, 17,21‐[(methylborylene)bis(oxy)]‐, (5. beta)‐, a compound identified from Turbianria ornata, was predicted. The target proteins were major envelope proteins VP28, VP24, and VP110 of WSSV. The ligand structure was generated using PubChem and the SMILES platform. Docking was performed using AutoDock 4.2, employing blind docking to identify the preferred binding sites autonomously. A 100‐nanosecond molecular dynamics (MD) simulation was conducted for each protein–ligand complex using Desmond software to evaluate the stability and dynamics of these interactions. The complexes exhibited minimum values for both docking scores and binding energies. The additional data on root mean square deviation (RMSD) and root mean square fluctuation (RMSF) further supported the stability of proteins and ligands. The compound’s strong and stable binding with multiple WSSV envelope proteins suggests its potential as a broad‐spectrum antiviral agent against WSSV. The study found that the compound pregnane‐3,20‐dione, 17,21‐[(methylborylene)bis(oxy)]‐, (5. beta)‐ demonstrated high binding affinity Turbinaria ornata and stability with the viral envelope proteins VP28, VP24, and VP110, indicating strong antiviral potential against WSSV.

Synthesis, Antileishmanial Activity, and in silico Study of 2-Hydroxy-3-(1,2,3-triazolyl)propyl Vanillin Derivatives

This study details the preparation, antileishmanial assay, and in silico analysis of twenty 2-hydroxy-3-(1,2,3-triazolyl)propyl vanillin derivatives. These compounds were synthesized in three steps and evaluated against Leishmania infantum, Leishmania amazonensis, and Leishmania braziliensis promastigotes. Compounds 3s and 3t were the most effective, showing good activity against all Leishmania species tested. Molecular docking indicated that all compounds bind favorably to the sterol 14α-demethylase (CYP51) enzyme from L. infantum. ADMET (absorption, distribution, metabolism, excretion and toxicity) analysis indicated good oral bioavailability, non-blood-brain barrier penetration, and high gastrointestinal absorption. Posaconazole and compounds 3e, 3s, and 3t remained stable in the CYP51 binding region during 100 ns molecular dynamics (MD) simulations. Root mean square deviation (RMSD) and root mean square fluctuations (RMSF) analyses from the MD trajectory revealed significant conformational fluctuations of the CYP51 N-terminal, suggesting occasional expulsion of 3e, potentially explaining its higher IC50 (half-maximal inhibitory concentration) values. Pairwise decomposition analyses from molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) calculations highlighted the importance of hydrophobic residues in interacting with the synthesized derivatives.