Proteo-R1: Reasoning AI for Protein Design
Proteo-R1 is a reasoning-guided protein design framework that decouples molecular understanding from geometric generation. It uses a multimodal large language model (MLLM) as an understanding expert to analyze sequences, structures, and textual context, identifying key functional residues for binding and specificity. These decisions are passed as hard constraints to a geometric generation module. The approach aims to improve interpretability, controllability, and systematic reuse of biochemical knowledge in de novo protein design, addressing limitations of existing non-deliberative models.
Key facts
- Proteo-R1 is a reasoning-guided protein design framework.
- It decouples molecular understanding from geometric generation.
- Uses a multimodal large language model (MLLM) as an understanding expert.
- Analyzes protein sequences, structures, and textual context.
- Identifies key functional residues governing binding and specificity.
- Residue-level decisions are passed as hard constraints.
- Aims to improve interpretability and controllability.
- Addresses limitations of non-deliberative models in de novo protein design.
Entities
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