General Protein Pretraining or Domain-Specific Designs? Benchmarking Protein Modeling on Realistic Applications

Understand

Recently, extensive deep learning architectures and pretraining strategies have been explored to support downstream protein applications.

• Additionally, domain-specific models incorporating biological knowledge have been developed to enhance performance in specialized tasks.
• In this work, we introduce $\textbf{Protap}$, a comprehensive benchmark that systematically compares backbone architectures, pretraining strategies, and domain-specific models across diverse and realistic downstream protein applications.
• Specifically, Protap covers five applications: three general tasks and two novel specialized tasks, i.e., enzyme-catalyzed protein cleavage site prediction and targeted protein degradation, which are industrially relevant yet missing from existing benchmarks.