Florent Langenfeld, Laboratoire GBA, CNAM

SHREC’19 - Protein Shape Retrieval Contest

The article describing the performance of different shape similarity search methods on the protein shapes track of the SHREC2019 contest is available

This track aimed at retrieving protein evolutionary classification based on their surfaces meshes only. Given that proteins are dynamic, non-rigid objects and that evolution tends to conserve patterns related to their activity and function, this track offers a challenging issue using biologically relevant molecules. We evaluated the performance of 5 different algorithms and analyzed their ability, over a dataset of 5,298 objects, to retrieve various conformations of identical proteins and various conformations of ortholog proteins (proteins from different organisms and showing the same activity). All methods were able to retrieve a member of the same class as the query in at least 94% of the cases when considering the first match, but show more divergent when more matches were considered. Last, similarity metrics trained on databases dedicated to proteins improved the results.

The SHREC paper describing the results of the participating teams has been presented by Florent Langenfeld during the 3DOR workshop of the Eurographics 2019 conference on May 6th at Genova, Italy

It is available on the Zenodo platform