There are two pharmacophore similarity concepts in Moloc:
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.
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:
Conversion of the database to be searched to topological
pharmacophore format (once)
Conversion of lead structures or 3-d pharmacophores to
pharmacophore format
Similarity calculation between search pharmacophore and
Database pharmacophores
3-d structure extraction of top ranked database items
Matching hit structures onto 3-d lead or pharmacophore
Scanning of hit-library against background protein or target
structure or -pharmacophore
Filtering of hit library for various pharmacokinetic properties