Calculation of substructural analysis weights using a genetic algorithm

Abstract

This paper describes a genetic algorithm for the calculation of substructural analysis for use in ligand-based virtual screening. The algorithm is simple in concept and effective in operation, with simulated virtual screening experiments using the MDDR and WOMBAT datasets showing it to be superior to substructural analysis weights based on a naive Bayesian classifier