PharmID: pharmacophore identification using Gibbs sampling

The binding of a small molecule to a protein is inherently a 3D matching problem. As crystal structures are not available for most drug targets, there is a need to be able to infer from bioassay data the key binding features of small molecules and their disposition in space, the pharmacophore. Fingerprints of 3D features and a modification of Gibbs sampling to align a set of known flexible ligands, where all compounds are active, are used to discern possible pharmacophores. A clique detection method is used to map the features back onto the binding conformations. The complete algorithm is described in detail, and it is shown that the method can find common superimposition for several test data sets. The method reproduces answers very close to the crystal structure and literature pharmacophores in the examples presented. The basic algorithm is relatively fast and can easily deal with up to 100 compounds and tens of thousands of conformations. The algorithm is also able to handle multiple binding mode problems, which means it can superimpose molecules within the same data set according to two different sets of binding features. We demonstrate the successful use of this algorithm for multiple binding modes for a set of D2 and D4 ligands.