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NeurIPS 2023PosterAccept (Poster)

ProteinShake: Building datasets and benchmarks for deep learning on protein structures

Tim Kucera, Carlos Oliver, Dexiong Chen, Karsten Borgwardt

Max Planck Society and ETH Zurich · Max Planck Institute of Biochemistry & ETH Zürich · Max Planck Institute · Swiss Federal Institute of Technology

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摘要

We present ProteinShake, a Python software package that simplifies datasetcreation and model evaluation for deep learning on protein structures. Users cancreate custom datasets or load an extensive set of pre-processed datasets fromthe Protein Data Bank (PDB) and AlphaFoldDB. Each dataset is associated withprediction tasks and evaluation functions covering a broad array of biologicalchallenges. A benchmark on these tasks shows that pre-training almost alwaysimproves performance, the optimal data modality (graphs, voxel grids, or pointclouds) is task-dependent, and models struggle to generalize to new structures.ProteinShake makes protein structure data easily accessible and comparisonamong models straightforward, providing challenging benchmark settings withreal-world implications.ProteinShake is available at: https://proteinshake.ai