Iterative stochastic elimination for discovering hits and leads

Shayma El-Atawneh, Amiram Goldblum

Research output: Contribution to journalArticlepeer-review


Iterative Stochastic Elimination (ISE) is a novel algorithm that was originally developed in order to solve extremely complex problems in protein structure and interactions, and has recently been focusing on discovering bioactive molecules for treating disease. It is generic and therefore not limited to any type of problem. We discuss the basic ingredients of ISE and present a set of successful applications of discovering hits and leads for the innate immune system, for some types of cancer, for delivery by nano-liposomes, for treating alzheimer's disease and more. Currently involved in more than a dozen drug discovery programs, ISE has the potential to become a leading algorithm for discovering hits and leads in extremely short time and investment, and has already shown ability to discover multitargeted single molecules that are expected to have advantages compared to the current ``one target - one drug'' concept.
Original languageEnglish
Pages (from-to)41-46
Number of pages6
JournalChimica Oggi
Issue number5
StatePublished - 1 Sep 2017


  • Iterative stochastic elimination
  • algorithm
  • prediction
  • modeling
  • drug discovery
  • pharmaceutical chemistry


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