SHREC 2020 - Protein Shape Retrieval Contest

The article describing the performance of different shape similarity search methods on the protein shapes track of the SHREC2020 contest is available

This track aimed at retrieving protein evolutionary classification based on their surfaces meshes only. In the present work, we evaluated the performance of six shape comparison methods, among which three are based on machine learning, to distinguish between 588 multi-domain proteins and to recreate the evolutionary relationships at the protein and species levels of the SCOPe database. The six groups that participated in the challenge submitted a total of 15 sets of results. We observed that the performance of all the methods significantly decreases at the species level, suggesting that shape-only protein comparison is challenging for closely related proteins. Even if the dataset is limited in size (only 588 proteins are considered whereas more than 160,0 0 0 protein structures are experimentally solved), we think that this work provides useful insights into the current shape comparison methods performance, and highlights possible limitations to large-scale applications due to the computational cost.

The SHREC paper describing the results of the participating teams has been presented by Florent Langenfeld during the online 3DOR workshop of the Eurographics 2020 conference

It is available on the Zenodo platform