Pharmacophore Enhanced Shape Alignment "PheSA"
For a ligand molecule to inhibit a receptor or enzyme with high efficacy it must fit well into the protein's active site, which means that it must have a low energy conformer, whose shape fits nicely into the pocket and whose atoms are optimally positioned to establish attractive polar and apolar interactions with the protein atoms. If the binding conformer of an efficacious ligand structure is known, then a typical virtual screening strategy is to assess the shape and pharmacophoric feature similarity of multiple conformers of the candidate molecules.
Typical task: Binding conformer of CSF1R inhibitor & query structure
The PheSA algorithm was designed for this purpose. It first aligns two rigid 3D-molecules such that both, their shape and their pharmacophore feature overlap is maximized. In this regard PheSA is similar to OpenEye's ROCS technology. The optimized alignment of both molecules is then quantitatively described by the PheSA similarity, a value ranging from 0.0 to 1.0 that is composed of equal contributions of both, shape and pharmacophore similarity.
Best matching query conformer aligned to known binding CSF1R inhibitor
Typical applications of PheSA are the alignment of chemical structures for visual inspection or binding-mode hypotheses, as well as for virtual screening to identify molecules that have 3D-similarity to a known query.
If you know or believe to know the binding conformer of a small molecule that is active
as inhibitor or antagonist against a protein target, then you may use the PheSA
algorithm from within DataWarrior for these purposes:
The PheSA algorithm was engineered by Joel Wahl and is described in https://pubs.acs.org/doi/10.1021/acs.jcim.4c00516