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Anti-inflammatory action of new hybrid N -acyl-[1,2]dithiolo-[3,4- c ]quinoline-1-thione.

S M MedvedevaPetrou AnthiMaria FesatidouA GavalasGeronikaki AthinaP I SavosinaD S DruzhilovskiyVladimir V PoroikovKhidmet S ShikhalievV G Kartsev
Published in: SAR and QSAR in environmental research (2024)
Most of pharmaceutical agents display a number of biological activities. It is obvious that testing even one compound for thousands of biological activities is not practically possible. A computer-aided prediction is therefore the method of choice in this case to select the most promising bioassays for particular compounds. Using the PASS Online software, we determined the probable anti-inflammatory action of the 12 new hybrid dithioloquinolinethiones derivatives. Chemical similarity search in the World-Wide Approved Drugs (WWAD) and DrugBank databases did not reveal close structural analogues with the anti-inflammatory action. Experimental testing of anti-inflammatory activity of the synthesized compounds in the carrageenan-induced inflammation mouse model confirmed the computational predictions. The anti-inflammatory activity of the studied compounds (2a, 3a-3k except for 3j) varied between 52.97% and 68.74%, being higher than the reference drug indomethacin (47%). The most active compounds appeared to be 3h (68.74%), 3k (66.91%) and 3b (63.74%) followed by 3e (61.50%). Thus, based on the in silico predictions a novel class of anti-inflammatory agents was discovered.
Keyphrases
  • anti inflammatory
  • molecular docking
  • mouse model
  • oxidative stress
  • drug induced
  • high glucose
  • genome wide
  • machine learning
  • diabetic rats
  • dna methylation
  • fatty acid
  • artificial intelligence
  • adverse drug