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Stigmata: an algorithm to determine structural commonalities in diverse datasets.

N E Shemetulskis·D Weininger·C J Blankley·J J Yang·C Humblet
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Abstract

An algorithm, Stigmata, is described, which extracts structural commonalities from chemical datasets. It is discussed using several illustrative examples and a pharmaceutically interesting set of dopamine D2 agonists. The commonalities are determined using two-dimensional topological 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 the information content of the modal fingerprint. The use of the modal fingerprint as a diversity assessment tool, as a database similarity query, and as a basis for color mapping the determined commonalities back onto the chemical structures is demonstrated.

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AlgorithmsDatabases, FactualDopamine AgonistsIndolesLigandsMolecular StructurePharmaceutical PreparationsPhenolsPiperazinePiperazinesJournal Article

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N E Shemetulskis, D Weininger, C J Blankley, J J Yang, C Humblet. Stigmata: an algorithm to determine structural commonalities in diverse datasets.. https://doi.org/10.1021/ci950169%2B

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