SHREC’18 - Protein Shape Retrieval
Examples of Protein Shapes used in the SHREC2018 dataset Florent Langenfeld, Laboratoire GBA, CNAM

SHREC’18 - Protein Shape Retrieval

The article describing the performance of different shape similarity search methods on the protein shapes track of the SHREC2018 contest is available

Proteins are macromolecules central to biological processes that display a dynamic and complex surface. They display mul- tiple conformations differing by local (residue side-chain) or global (loop or domain) structural changes which can impact drastically their global and local shape. Since the structure of proteins is linked to their function and the disruption of their interactions can lead to a disease state, it is of major importance to characterize their shape. In the present work, we report the performance in enrichment of six shape-retrieval methods (3D-FusionNet, GSGW, HAPT, DEM, SIWKS and WKS) on a 2 267 protein structures dataset generated for this protein shape retrieval track of SHREC’18.

The SHREC paper describing the results of the participating teams has been presented by Matthieu Montes during the 3DOR workshop of the Eurographics 2018 conference on April 17th at Delft, Netherlands

It is available on the Zenodo platform