Molecular shape analysis-guided virtual screening platform for adenosine kinase inhibitors

Savita Bhutoria, Ballari Das, Nanda Ghoshal

Research output: Contribution to journalArticlepeer-review

Abstract

We propose a new application of molecular shape descriptors in hierarchical selection during virtual screening (VS). Here, a structure-based pharmacophore and docking-guided VS protocol have been evolved to identify inhibitors against adenosine kinase (AK). The knowledge gained on the shape requirements has been extrapolated in classifying active and inactive molecules against this target. This classification enabled us to pick the appropri-ate ligand conformation in the binding site. We have suggested a set of hierarchical filters for VS, from a simple molecular shape analysis (MSA) descriptor-based recursive models to docking scores. This approach permits a systematic study to understand the importance of spatial requirements and limitations for inhibitors against AK. Finally, the guidelines on how to select compounds for AK to achieve success have been highlighted. The utility of this approach has been suggested by giving an example of database screening for plausible active compounds.

Original languageEnglish (US)
Pages (from-to)97-103
Number of pages7
JournalBioinformatics and Biology Insights
Volume10
DOIs
StatePublished - Jul 18 2016

Keywords

  • Adenosine kinase
  • Docking
  • Molecular shape analysis
  • Structure-based pharmacophore
  • Virtual screening

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Mathematics
  • Applied Mathematics

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