Literature DB >> 33357037

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

Meenakshi Duhan1, Jayant Sindhu2, Parvin Kumar1, Meena Devi1, Rahul Singh1, Ramesh Kumar1, Sohan Lal1, Ashwani Kumar3, Sudhir Kumar4, Khalid Hussain5.   

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 Rvalidation2 = 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.

Entities:  

Keywords:  Benzothiazole; IIC; QSAR; aroyl hydrazone; molecular docking; α-amylase inhibition

Mesh:

Substances:

Year:  2020        PMID: 33357037     DOI: 10.1080/07391102.2020.1863861

Source DB:  PubMed          Journal:  J Biomol Struct Dyn        ISSN: 0739-1102            Impact factor:   5.235


  3 in total

1.  Ecotoxicological prediction of organic chemicals toward Pseudokirchneriella subcapitata by Monte Carlo approach.

Authors:  Shahram Lotfi; Shahin Ahmadi; Parvin Kumar
Journal:  RSC Adv       Date:  2022-09-01       Impact factor: 4.036

2.  Pyridine-N-Oxide Alkaloids from Allium stipitatum and Their Synthetic Disulfide Analogs as Potential Drug Candidates against Mycobacterium tuberculosis: A Molecular Docking, QSBAR, and ADMET Prediction Approach.

Authors:  Cedric Dzidzor Kodjo Amengor; Emmanuel Orman; Cynthia Amaning Danquah; Inemesit Okon Ben; Prince Danan Biniyam; Benjamin Kingsley Harley
Journal:  Biomed Res Int       Date:  2022-10-07       Impact factor: 3.246

3.  Identification of Cyclic Sulfonamides with an N-Arylacetamide Group as α-Glucosidase and α-Amylase Inhibitors: Biological Evaluation and Molecular Modeling.

Authors:  Furqan Ahmad Saddique; Matloob Ahmad; Usman Ali Ashfaq; Muhammad Muddassar; Sadia Sultan; Magdi E A Zaki
Journal:  Pharmaceuticals (Basel)       Date:  2022-01-17
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.