Enhancing Zn (II) Recovery Efficiency: Bi-Divalent Nickel-Cobalt Ferrite Spinel NiXCo1-xFe2O4 as a Game-Changing Adsorbent—an Experimental and Computational Study

Chemosphere, Год журнала: 2024, Номер 362, С. 142702 - 142702

Опубликована: Июнь 25, 2024

Язык: Английский

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Exploring the mechanisms of diazinon adsorption onto alpha and beta cyclodextrins through molecular dynamics simulations: Insights into environmentally friendly pesticide remediation

Results in Engineering, Год журнала: 2024, Номер 21, С. 102020 - 102020

Опубликована: Март 1, 2024

This study investigated the adsorption of Diazinon on α and β-Cyclodextrins (CDs) through Molecular Dynamics Simulations. The entrance point variation in diazinon is analyzed, revealing distinct preferences for entry into β-CDs. center mass distance CDs investigated, highlighting dynamic behavior within β-CD. Interaction energies between diazinon, CD, water are explored, emphasizing significance van der Waals interactions adsorption. Hydrogen bonding analysis reveals preferential α-CD, attributed to number arrangement hydrogen bonds. Free energy calculations using Bennett acceptance ratio method indicate a stronger affinity supported by molecular electrostatic potential maps. also examines hydration capacity molecules' distribution, indicating differences Radial distribution function (RDF) illustrates process, molecule expulsion upon entry. Structural stability assessed root mean squared deviation, equilibrium attainment. Gibbs free suggest hydrophobic α-CD cavity. comprehensive contributes valuable insights MD diazinon-CDs interactions, shedding light their mechanisms applications wastewater treatment.

Язык: Английский

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Discovery of sugar-based natural framework as phytopathogenic virus capsid protein inhibitors using a state-of-the-art multiple screening strategy

International Journal of Biological Macromolecules, Год журнала: 2025, Номер 298, С. 140075 - 140075

Опубликована: Янв. 18, 2025

Язык: Английский

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Artificial intelligence in antidiabetic drug discovery: The advances in QSAR and the prediction of α-glucosidase inhibitors

Computational and Structural Biotechnology Journal, Год журнала: 2024, Номер 23, С. 2964 - 2977

Опубликована: Июль 6, 2024

Artificial Intelligence is transforming drug discovery, particularly in the hit identification phase of therapeutic compounds. One tool that has been instrumental this transformation Quantitative Structure-Activity Relationship (QSAR) analysis. This computer-aided design uses machine learning to predict biological activity new compounds based on numerical representation chemical structures against various targets. With diabetes mellitus becoming a significant health challenge recent times, there intense research interest modulating antidiabetic α-Glucosidase an target gained attention due its ability suppress postprandial hyperglycaemia, key contributor diabetic complications. review explored detailed approach developing QSAR models, focusing strategies for generating input variables (molecular descriptors) and computational approaches ranging from classical algorithms modern deep algorithms. We also highlighted studies have used these develop predictive models α-glucosidase inhibitors modulate critical target.

Язык: Английский

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Advanced AI Applications for Drug Discovery

Advances in medical technologies and clinical practice book series, Год журнала: 2024, Номер unknown, С. 42 - 86

Опубликована: Апрель 26, 2024

Addressing the critical challenge of lengthy and costly drug development, this chapter illuminates transformative role advanced artificial intelligence (AI) in discovery. It aims to dissect impact AI methodologies streamlining these traditionally complex processes. This begins by highlighting inefficiencies conventional discovery methods, emphasizing their resource-intensive nature. An in-depth discussion how technologies are revolutionizing identification novel targets, optimizing molecular structures candidates, accurately predicting efficacy toxicity is needed. exploration underscores AI's dual advantages: significantly reducing development timelines expenses while simultaneously enhancing precision predictions, leading safer more effective drugs. concludes with a vision future where AI-driven methods fully integrated personalized medicine genomics, signaling onset new era healthcare therapeutic innovation.

Язык: Английский

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DESIGN, SYNTHESIS, AND EVALUATION OF ANTIBACTERIAL POTENTIAL OF HYDRAZONE-TETHERED PYRAZOLE-THIAZOLE DERIVATIVES

Ankara Universitesi Eczacilik Fakultesi Dergisi, Год журнала: 2025, Номер 49(1), С. 4 - 4

Опубликована: Янв. 13, 2025

Objective: This study includes the investigation of antimicrobial potential a series compounds designed by hybridization thiazole, hydrazone and pyrazole systems identified as moieties in literature. The aim was to filter with drugability parameters, synthesize selected test their antibacterial silico vitro. Material Method: properties synthesized were determined online scanners effects on E. coli S. aureus strains disk diffusion method. Also, Autodock 4.2 software used determine inhibitory against dihydrofolate reductase (DHFR) enzyme. Result Discussion: In our study, among newly hydrazone-linked pyrazole-thiazole compounds, according parameters (17a-c) high efficiency. Among tested for activity, Compound 17c formed zone diameter 8 mm strain 9 at concentration 80 μg/ml. compound 7 40 Furthermore, ADMET profiles presented indicate that they may have suitable agents.

Язык: Английский

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Fragment optimized chalcone derivatives targeting OmpA protein as a therapeutic approach against multidrug resistant Acinetobacter baumannii

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 31, 2025

Язык: Английский

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Introduction to smart hospital

Elsevier eBooks, Год журнала: 2025, Номер unknown, С. 1 - 35

Опубликована: Янв. 1, 2025

Язык: Английский

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Computational studies for the development of extracellular vesicle-based biosensors

Biosensors and Bioelectronics, Год журнала: 2025, Номер 277, С. 117275 - 117275

Опубликована: Фев. 15, 2025

Язык: Английский

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Structural Reactivity of Diimine‐Dioxime Molecules in Anticancer Research: Quantum Chemical Insights, Molecular Modeling and ADMET Studies

ChemistrySelect, Год журнала: 2025, Номер 10(8)

Опубликована: Фев. 1, 2025

Abstract This study carried out quantum chemical calculations and molecular modeling studies of five diimine‐dioxime molecules (1–5). The optimized geometries, HOMOs–LUMOs electrostatic potential (MEP) diagrams the were calculated at DFT/B3LYP/6–311G(d,p) level theory. global reactivity parameters revealed that hardest most stable molecule is 1 ( η = 1.897 eV), while softest chemically reactive 2 S 1.621 eV −1 ). All compounds in silico ADMET drug‐likeness generally within acceptable limits all except 3 considered to have good oral bioavailability. Molecular docking also performed using VEGFR2 (PDB ID: 2XIR) EGFR 1M17) proteins predict anticancer properties molecules. binding energies obtained between −7.8 −9.7 kcal/mol. behavior 2–2XIR complex with best energy value kcal/mol under physiological conditions was by dynamics (MD) simulation for 100 ns. RMSD, RMSF, SASA, Rg, hydrogen bonding MD confirmed conformational stability complex. results indicated has contribute on discovering new agents.

Язык: Английский

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