Ensemble pharmacophore meets ensemble docking: A novel screening strategy for the identification of RIPK1 inhibitors

S. M. Fayaz, G. K. Rajanikant

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Programmed cell death has been a fascinating area of research since it throws new challenges and questions in spite of the tremendous ongoing research in this field. Recently, necroptosis, a programmed form of necrotic cell death, has been implicated in many diseases including neurological disorders. Receptor interacting serine/threonine protein kinase 1 (RIPK1) is an important regulatory protein involved in the necroptosis and inhibition of this protein is essential to stop necroptotic process and eventually cell death. Current structure-based virtual screening methods involve a wide range of strategies and recently, considering the multiple protein structures for pharmacophore extraction has been emphasized as a way to improve the outcome. However, using the pharmacophoric information completely during docking is very important. Further, in such methods, using the appropriate protein structures for docking is desirable. If not, potential compound hits, obtained through pharmacophore-based screening, may not have correct ranks and scores after docking. Therefore, a comprehensive integration of different ensemble methods is essential, which may provide better virtual screening results. In this study, dual ensemble screening, a novel computational strategy was used to identify diverse and potent inhibitors against RIPK1. All the pharmacophore features present in the binding site were captured using both the apo and holo protein structures and an ensemble pharmacophore was built by combining these features. This ensemble pharmacophore was employed in pharmacophore-based screening of ZINC database. The compound hits, thus obtained, were subjected to ensemble docking. The leads acquired through docking were further validated through feature evaluation and molecular dynamics simulation.

Original languageEnglish
Pages (from-to)779-794
Number of pages16
JournalJournal of Computer-Aided Molecular Design
Volume28
Issue number7
DOIs
Publication statusPublished - 01-01-2014

All Science Journal Classification (ASJC) codes

  • Drug Discovery
  • Physical and Theoretical Chemistry
  • Computer Science Applications
  • Medicine(all)

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