The concept of chemical space is of fundamental importance for chemoinformatics research. It is generallythought that high-dimensional space representations are too complex for the successful application of manycompound classification or virtual screening methods. Here, we show that a simple “activity-centered” distancefunction is capable of accurately detecting molecular similarity relationships in “raw” chemical spaces ofhigh dimensionality.