A Distance Function for Retrieval of Active Molecules from Complex Chemical Space Representations

Abstract

The concept of chemical space is of fundamental importance for chemoinformatics research. It is generally thought that high-dimensional space representations are too complex for the successful application of many compound classification or virtual screening methods. Here, we show that a simple "activity-centered" distance function is capable of accurately detecting molecular similarity relationships in "raw" chemical spaces of high dimensionality.