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CORAL: probing the structural requirements for α-amylase inhibition activity of 5-(3-arylallylidene)-2-(arylimino)thiazolidin-4-one derivatives based on QSAR with correlation intensity index, molecular docking, molecular dynamics, and ADMET studies.

Rahul SinghParvin KumarJayant SindhuAshwani KumarSohan Lal
Published in: Journal of biomolecular structure & dynamics (2023)
The present study aims to examine the structural requirements governing α-amylase inhibitory activity of 5-(3-arylallylidene)-2-(arylimino)thiazolidin-4-one derivatives and their precursors by employing a multifaceted approach combining in vitro and in silico studies. The in vitro assay findings revealed strong inhibitory effect of this class of compounds against α-amylase and compound 20 exhibited maximum percentage inhibition of 88.54 ± 0.69, 84.98 ± 0.40, 77.26 ± 0.75, 67.80 ± 0.54, and 62.93 ± 1.17 at 200, 100, 50, 25, and 12.5 µg mL -1 , respectively. Multiple CORAL QSAR models were developed from the randomly distributed eight splits by employing two target functions (TF 1 , TF 2 with W CII = 0.0 and = 0.3, respectively), and the quality of predictions by the produced models was validated with the help of various statistical parameters. The model M-4 ( R 2 Val = 0.8799 ) and model M-11 ( R 2 Val = 0.9064 ) were the leading models developed by using TF 1 and TF 2 . We designed five new congeneric inhibitors (D-1 to D-5) by incorporating SMILES features positively correlating with the activity. Molecular docking experiments were carried out to confirm the binding of these new inhibitors with the biological receptor α-amylase ( PDB ID: 7TAA ). Furthermore, molecular dynamic simulations provided a thorough knowledge of the binding process by shedding insight into the dynamic behavior and stability of the ligand-receptor complex over time. The results of this study highlight the key structural characteristics needed for improved α-amylase inhibitory efficacy and provide a rational basis for the development of more effective inhibitors.Communicated by Ramaswamy H. Sarma.
Keyphrases
  • molecular docking
  • molecular dynamics
  • molecular dynamics simulations
  • healthcare
  • binding protein
  • high throughput
  • single cell
  • case control
  • transcription factor
  • dna binding