ProCare [1] is a package developed at the University of Strasbourg which is able to align and score the similarity of protein cavities. The aim is to find ligand binding sites between different proteins that are similar enough to bind the same ligand. The method used in ProCare is designed to look particularly at fragment (~⅓ size of a druglike ligand) binding sites. The aim is to predict potential fragment hits by comparing the cavities of the targets.

First, the fragment-binding site of the reference target is described as a point cloud annotated with pharmacophoric features of nearby protein atoms. This point cloud, created using VolSite [2] fills the protein cavity within a specific range of the fragment atoms. Volsite is also used to describe all possible cavity spaces of the query protein. The reference point cloud can then be ‘matched’ to a subsite within the query protein, using an iterative closest point algorithm. This alignment is based on the point cloud shape mainly, but the final scoring function takes into account the positions of the points and their annotations.

This ‘ProCare’ score is then combined with a interaction similarity score in which the interaction fingerprint of the reference protein-ligand complex is compared with the predicted interaction fingerprint of the ligand with the query protein. Polar interactions are more heavily weighted than non-polar interactions in this final score, which is used to rank potential hits and thus allow prioritization of compounds for screening. The method was tested by comparing the predicted hits of a query protein to substructures of experimentally determined drug-sized ligand binders.

References

1. A Computer Vision Approach to Align and Compare Protein Cavities: Application to Fragment-Based Drug Design, Merveille Eguida and Didier Rognan, Journal of Medicinal Chemistry 2020 63 (13), 7127-7142, doi:10.1021/acs.jmedchem.0c00422

2. Da Silva F, Desaphy J, Rognan D. IChem: A Versatile Toolkit for Detecting, Comparing, and Predicting Protein-Ligand Interactions. ChemMedChem. 2018 13(6), 507-510. doi:10.1002/cmdc.201700505