Evaluating representation learning on the protein structure universe

arXiv:2406.13864v1 Announce Type: new
Abstract: We introduce ProteinWorkshop, a comprehensive benchmark suite for representation learning on protein structures with Geometric Graph Neural Networks. We consider large-scale pre-training and downstream tasks on both experimental and predicted structures to enable the systematic evaluation of the quality of the learned structural representation and their usefulness in capturing functional relationships for downstream tasks. We find that: (1) large-scale pretraining on AlphaFold structures and auxiliary tasks consistently improve the performance of both rotation-invariant and equivariant …

abstract arxiv benchmark cs.lg evaluation experimental graph graph neural networks networks neural networks pre-training protein protein structure protein structures q-bio.bm quality representation representation learning scale tasks training type universe