Quinoxalinones Based Aldose Reductase Inhibitors: 2D and 3D-QSAR Analysis

Mol Inform. 2019 Aug;38(8-9):e1800149. doi: 10.1002/minf.201800149. Epub 2019 May 27.

Abstract

In the present work, 2D- and 3D-quantitative structure-activity relationship (QSAR) analysis has been employed for a diverse set of eighty-nine quinoxalinones to identify the pharmacophoric features with significant correlation with the aldose reductase inhibitory activity. Using genetic algorithm (GA) as a variable selection method, multivariate linear regression (MLR) models were derived using a pool of molecular descriptors. All the six-descriptor based GA-MLR QSAR models are statistically robust with coefficient of determination (R2 )>0.80 and cross-validated R2 >0.77. The derived GA-MLR models were thoroughly validated using internal and external and Y-scrambling techniques. The CoMFA like model, which is based on a combination of steric and electrostatic effects and graphically inferred using contour plots, is highly robust with R2 >0.93 and cross-validated R2 >0.73. The established QSAR and CoMFA like models are proficient in identify key pharmacophoric features that govern the aldose reductase inhibitory activity of quinoxalinones.

Keywords: Aldose Reductase Activity; CoMFA like model; QSAR; Quinoxalinones.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aldehyde Reductase / antagonists & inhibitors*
  • Aldehyde Reductase / metabolism
  • Algorithms
  • Animals
  • Dose-Response Relationship, Drug
  • Drug Design
  • Enzyme Inhibitors / chemistry
  • Enzyme Inhibitors / pharmacology*
  • Linear Models
  • Models, Molecular
  • Molecular Structure
  • Multivariate Analysis
  • Quantitative Structure-Activity Relationship*
  • Quinoxalines / chemistry
  • Quinoxalines / pharmacology*

Substances

  • Enzyme Inhibitors
  • Quinoxalines
  • Aldehyde Reductase