10.1016/j.cag.2020.07.013
https://zenodo.org/records/4522073
oai:zenodo.org:4522073
Langenfeld
Langenfeld
Florent
Peng
Peng
Yuxu
Lai
Lai
Yu-Kun
Rosin
Rosin
Paul
Aderinwale
Aderinwale
Tunde
Terashi
Terashi
Genki
Christoffer
Christoffer
Charles
Kihara
Kihara
Daisuke
Benhabiles
Benhabiles
Halim
Hammoudi
Hammoudi
Karim
Cabani
Cabani
Adnane
Windal
Windal
Feryal
Melkemi
Melkemi
Mahmoud
Giachetti
Giachetti
Andrea
Mylonas
Mylonas
Stelios
Axenopoulos
Axenopoulos
Apostolos
Daras
Daras
Petros
Otu
Otu
Ekpo
Zwiggelaar
Zwiggelaar
Reyer
Hunter
Hunter
David
Liu
Liu
Yonghuai
Montes
Montes
Matthieu
SHREC 2020: Multi-domain protein shape retrieval challenge
Zenodo
2020
3D Shape analysis
3D Shape descriptor
3D Shape Retrieval
3D Shape Matching
Protein Shape
SHREC
2020-07-15
eng
https://zenodo.org/communities/eu
Creative Commons Attribution 4.0 International
Proteins are natural modular objects usually composed of several domains, each domain bearing a spe- cific function that is mediated through its surface, which is accessible to vicinal molecules. This draws attention to an understudied characteristic of protein structures: surface, that is mostly unexploited by protein structure comparison methods. 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.
European Commission
10.13039/501100000780
640283
2D Conformal mapping of protein surfaces: applications to VIsualization and DOCKing software