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Similarity Concepts and Database Mining

There are two pharmacophore similarity concepts in Moloc:
  1. 3-dimensional pharmacophores and full structures can be rigidly superimposed by optimally matching the pharmacophore elements (agons). The result is a similarity index with values between zero and one.
  2. Topological pharmacophores can be compared by matching like agons in all possible ways and by selecting the optimal pairing on criteria of agon similarity and similarity of inter-agon distance matrices.
Database Mining within Moloc utilizes the second method for computational speed reasons. It consists of the following steps: