STIGMATA - AN ALGORITHM TO DETERMINE STRUCTURAL COMMONALITIES IN DIVERSE DATASETS

An algorithm, Stigmata, is described, which extracts structural common alities from chemical datasets. It is discussed using several illustra tive examples and a pharmaceutically interesting set of dopamine D-2 a gonists. The commonalities are determined using two-dimensional topolo gical chemical descriptions and are incorporated into the key feature of the algorithm, the modal fingerprint. Flexibility is built into the algorithm by means of a user-defined threshold value, which affects t he information content of the modal fingerprint. The use of the modal fingerprint as a diversity assessment tool, as a database similarity q uery, and as a basis for color mapping the determined commonalities ba ck onto the chemical structures is demonstrated.