Quantitative structure activity relationship studies of novel hydrazone derivatives as α-amylase inhibitors with index of ideality of correlation

Abstract

The present manuscript describes the synthesis, α-amylase inhibition, in silico studies and in-depth quantitative structure–activity relationship (QSAR) of a library of aroyl hydrazones based on benzothiazole skeleton. All the compounds of the developed library are characterized by various spectral techniques. α‐Amylase inhibitory potential of all compounds has been explored, where compound 7n exhibits remarkable α-amylase inhibition of 87.5% at 50 µg/mL. Robust QSAR models are made by using the balance of correlation method in CORAL software. The chemical structures at different concentration with optimal descriptors are represented by SMILES. A data set of 66 SMILES of 22 hydrazones at three distinct concentrations are prepared. The significance of the index of ideality of correlation (IIC) with applicability domain (AD) is also studied at depth. A QSAR model with best $R_{\mathit{validation}}^2$ = 0.8587 for split 1 is considered as a leading model. The outliers and promoters of increase and decrease of endpoint are also extracted. The binding modes of the most active compound, that is, 7n in the active site of Aspergillus oryzae α-amylase (PDB ID: 7TAA) are also explored by in silico molecular docking studies. Compound 7n displays high resemblance in binding mode and pose with the standard drug acarbose. Molecular dynamics simulations performed on protein–ligand complex for 100 ns, the protein gets stabilised after 20 ns and remained below 2 Å for the remaining simulation. Moreover, the deviation observed in RMSF during simulation for each amino acid residue with respect to Cα carbon atom is insignificant.

Graphical Abstract

Communicated by Ramaswamy H. Sarma

Keywords:

• Benzothiazole
• aroyl hydrazone
• α-amylase inhibition
• molecular docking
• QSAR
• IIC

Acknowledgements

The authors are thankful to Dr. Andrey A. Toropov and Dr. Alla P. Toropova for providing CORAL software. The authors are also thankful to their respective universities for providing the infrastructure. Financial support as senior research fellowship (SRF) to M. Duhan by Haryana State Council of Science and Technology is acknowledged for accomplishing this work.

Author contributions

Authors have done equivalent contributions to this work.

Disclosure statement

The authors reported no potential conflict of interest.

Additional information

Funding

Meenakshi Duhan thanks Haryana State Council of Science and Technology (HSCST) for the award of the research fellowship.