Shayma El-Atawneh, Amiram Goldblum*
*Corresponding author
Molecular Modeling and Drug Discovery Laboratory, The Institute for Drug Research, The Hebrew University of Jerusalem, Israel

Abstract

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.

INTRODUCTION

The need for methods enabling faster discovery of effective drug candidates is obvious, but also a result of the reduction in productivity in the number of new drug entities in the last decade (1). Towards that goal, virtual screening (VS) (2) and the production of “focused libraries” (3) expanded substantially. It is much more difficult to develop novel drugs as the ever-widening knowledge of possible side effects and risks, the understanding of interaction mechanisms and of human biochemical pathways impose much more testing at the preclinical phase. It is thus of major importance to develop highly useful in Silico methods of drug discovery as those could save more time and money.

ITERATIVE STOCHASTIC ELIMINATION

Since 2000, we developed the novel algorithm that was later called Iterative Stochastic Elimination (ISE) algorithm. ISE is a heuristic, which finds solutions to extremely complex combinatorial problems. Such problems can be presented as being composed of many variables, each variable having a large number of possible values, and there is a method for scoring each combination of ...