In this study, several imidazole derivatives in one pot multicomponent reaction from various aldehydes 1(a-z), 9,10-phenanthrenequinone, or benzyl (2), and ammonium acetate (3) were synthesized in the presence of acetic acid (AcOH) under reflux conditions at 120 °C. Also, the photochromic properties of synthesized compounds were investigated in AcOH as a solvent under laboratory conditions at a temperature of 120 °C. Moreover, the antibacterial activity of the synthesized compounds was investigated. The structure of the products was confirmed using FT-IR, UV-Vis, H-NMR, and CNMR spectroscopy. The antimicrobial activity of these compounds against gram-positive bacteria including Bacillus subtilis (B. subtilis) and gram-negative bacteria including Escherichia coli (E.coli) bacteria was evaluated by the Well diffusion (WD) method, and the compounds 4 o showed significant results for both antibacterial activity. To gain insight into how these compounds interact with two types of targets, i. e., human topoisomerase II alpha (5GWK) and acetylcholinesterase (7AIX), binding calculations have been used that provide significant results for both targets and show that most ligands can effectively bind to cleft nucleotides. Interfere in the first one or be well placed in them. Hydrophobic pocket in the dimension, which can ultimately lead to high scores achieved.
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http://dx.doi.org/10.1002/cbdv.202400325 | DOI Listing |
Dalton Trans
January 2025
Department of Chemistry, University of Victoria, P.O. Box 3065, Victoria, BC V8W 3 V6, Canada.
A charge-tagged N-heterocyclic carbene (NHC) has been synthesized and its utility in allowing the dynamic behaviour of metal complexes to be monitored in real time using electrospray ionization mass spectrometry demonstrated. This compound was used to prepare different metal-NHC complexes, and the kinetic behaviour of complex formation and ligand exchange was monitored in real time through the use of pressurized sample infusion electrospray mass spectrometry (PSI-ESI-MS).
View Article and Find Full Text PDFFood Sci Nutr
January 2025
Department of Plant Physiology, Institute for Biological Research "Siniša Stanković" - National Institute of Republic of Serbia University of Belgrade Belgrade Serbia.
(L.) Roxb. and (L.
View Article and Find Full Text PDFRSC Med Chem
October 2024
Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences 200241 Shanghai China
Bacterial infections pose a threat to human and animal health, and the formation of biofilm exacerbates the microbial threat. New antimicrobial agents to address this challenge are much needed. In this study, several new amphoteric compounds derived from the natural product coumarin were designed and synthesized by mimicking the structure and function of antimicrobial peptides.
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January 2025
Institute of Organic Chemistry, Justus Liebig University 35392 Giessen Germany https://www.uni-giessen.de/de/fbz/fb08/Inst/organische-chemie/AGGoettlich.
Parasites account for huge economic losses by infecting agriculturally important plants and animals. Furthermore, morbidity and death caused by parasites affect a large part of the world population, especially in economically weak regions. Anthelmintic drugs to tackle this challenge remain scarce and their efficiency becomes increasingly endangered by the advent of drug resistance development.
View Article and Find Full Text PDFiScience
January 2025
Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka 820-8502, Japan.
Drugs that interact with multiple therapeutic targets are potential high-value products in polypharmacology-based drug discovery, but the rational design remains a formidable challenge. Here, we present artificial intelligence (AI)-based methods to design the chemical structures of compounds that interact with multiple therapeutic target proteins. The molecular structure generation is performed by a fragment-based approach using a genetic algorithm with chemical substructures and a deep learning approach using reinforcement learning with stochastic policy gradients in the framework of generative adversarial networks.
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