Surface-based protein domains retrieval methods from a SHREC2021 challenge

Proteins are essential to nearly all cellular mechanism and the effectors of the cells activities. As such, they often
interact through their surface with other proteins or other cellular ligands such as ions or organic molecules. The
evolution generates plenty of different proteins, with unique abilities, but also proteins with related functions
hence similar 3D surface properties (shape, physico-chemical properties, …). The protein surfaces are therefore
of primary importance for their activity. In the present work, we assess the ability of different methods to detect
such similarities based on the geometry of the protein surfaces (described as 3D meshes), using either their shape
only, or their shape and the electrostatic potential (a biologically relevant property of proteins surface). Five
different groups participated in this contest using the shape-only dataset, and one group extended its pre-existing
method to handle the electrostatic potential. Our comparative study reveals both the ability of the methods to
detect related proteins and their difficulties to distinguish between highly related proteins. Our study allows also
to analyze the putative influence of electrostatic information in addition to the one of protein shapes alone.