Synthesis, computational study and cytotoxic activity of new 4-hydroxycoumarin derivatives
Abstract
Six new 4-hydroxycoumarin derivatives have been synthesized. They were characterized by UV-vis, IR, (1)H NMR, (13)C NMR, mass spectral data, elemental analysis, TLC and melting point determination. The new 4-hydroxycoumarin derivatives are studied by computational methods--DFT (B3LYP) and force field methods (MM2 and OPLS), in order to optimize their geometry and calculate quantum-chemical properties and conformational analysis. Five new 4-hydroxycoumarin derivatives were tested for cytotoxic activity in two tumor cell lines--HL-60 and EJ. The obtained results are compared with the utilized anticancer drug melphalan. Two of these compounds--ethyl 2-[(3,4-dihydroxyphenyl)(4-hydroxy-2-oxo-2H-chromen-3-yl)methyl]-3-oxobutanoate (SS-16) and ethyl 2-[(4-hydroxy-2-oxo-2H-chromen-3-yl)(3-nitrophenyl)methyl]-3-oxobutanoate (SS-21) show comparatively good cytotoxic properties. Their activity is weaker than melphalan. SS-16 seems to be more active than SS-21.
How strong is the evidence?
Evidence Hub reads this as a simulation / modelling, done in cell cultures (in vitro) and computer models (in silico), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
Read the paper
Related studies
- In silico toxicology protocols
- QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules
- Quantum Informed Machine-Learning Potentials for Molecular Dynamics Simulations of CO2's Chemisorption and Diffusion in Mg-MOF-74
- In-silico strategies in nano-drug design: Bridging nanomaterials and pharmacological applications
- mRNA codon optimization with quantum computers
- The computational power of the human brain
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.