Pharmacophore and docking-based hierarchical virtual screening for the designing of aldose reductase inhibitors: Synthesis and biological evaluation

Bhawna Vyas, Manjinder Singh, Maninder Kaur, Om Silakari, Malkeet Singh Bahia, Baldev Singh

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

A set of 54 studied flavonoid inhibitors of aldose reductase (ALR2) enzyme has been utilized for pharmacophore modeling and 3D-QSAR analysis using "PHASE" program of Schrödinger software. The generated pharmacophore model (AADRR.1109) was challenged to screen "PHASE" database to identify new ALR2 inhibitors. The retrieved hits were employed for docking analysis and pharmacokinetic parameter calculation to obtain orally active molecules. To predict the activity of final retrieved hits, 3D-QSAR model was developed, and the best model was selected on the basis of various statistical parameters (Rtrain 2 0.719; Q test 2 0.647 and SD 0.663). Totally five screened molecules which showed better enhanced predicted activity were synthesized and evaluated for in vitro ALR2 inhibitory activity. All tested molecules showed ALR2 inhibitory activity (IC50) below 40 μM. Additionally, the free radical scavenging potential of synthesized molecules was also determined which played a useful role to control the progression of diabetic complications. All molecules showed good antioxidant potential, thus the designed molecules, in future, could be explored to ameliorate the development of diabetic complications.

Original languageEnglish
Pages (from-to)609-626
Number of pages18
JournalMedicinal Chemistry Research
Volume25
Issue number4
DOIs
StatePublished - 1 Apr 2016
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2016 Springer Science+Business Media.

Keywords

  • Aldose reductase (ALR2)
  • Diabetic complications
  • Docking analysis
  • Flavonoid derivatives
  • Pharmacophore mapping
  • Pharmacophore-based 3D-QSAR
  • Virtual screening

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